From eaa9b33cae798888a19fce454974d3cada451020 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jesus=20Nu=C3=B1ez?= Date: Fri, 15 May 2026 13:56:50 -0400 Subject: [PATCH 01/18] docs: add configuration and testing documentation for CloudOracle --- README.md | 740 ++-------------------------------------- docs/architecture.md | 193 +++++++++++ docs/cloud-providers.md | 145 ++++++++ docs/configuration.md | 33 ++ docs/testing.md | 52 +++ docs/v1-guide.md | 225 ++++++++++++ docs/v2-guide.md | 131 +++++++ 7 files changed, 803 insertions(+), 716 deletions(-) create mode 100644 docs/architecture.md create mode 100644 docs/cloud-providers.md create mode 100644 docs/configuration.md create mode 100644 docs/testing.md create mode 100644 docs/v1-guide.md create mode 100644 docs/v2-guide.md diff --git a/README.md b/README.md index 4d196da..41e2d3c 100644 --- a/README.md +++ b/README.md @@ -4,21 +4,20 @@ ![Go Version](https://img.shields.io/badge/go-1.25-blue) ![License](https://img.shields.io/badge/license-Apache%20License%202.0-green) -A Go FinOps toolkit that ships in two modes from the same `oracle` binary: +A Go FinOps toolkit that ships in two modes from the same `oracle` binary, with a polyglot agent extension in progress: -- **v1 — Audit existing cloud spend.** Ingest live EC2/RDS/EBS/Lambda inventory from AWS, GCP, or Azure into Postgres, run deterministic rules over it, and produce an executive PDF + dashboard with an LLM-narrated summary. The classic "what waste is already in our cloud bill?" workflow. -- **v2 — Predict cost impact of a Terraform PR before merge.** Read `terraform show -json plan.tfplan`, look every changing resource up against the AWS Pricing API, and post (or upsert) a Markdown comment on the PR with the net monthly delta, top movers, and a 1–3 sentence LLM narrative. Ships as a [GitHub Action](#v2--terraform-pr-cost-analysis-current-focus) and as the `oracle pr-check` subcommand. +- **v1 — Audit existing cloud spend.** Ingest live EC2/RDS/EBS/Lambda inventory from AWS, GCP, or Azure into Postgres, run deterministic rules over it, and produce an executive PDF + dashboard with an LLM-narrated summary. See **[docs/v1-guide.md](docs/v1-guide.md)**. +- **v2 — Predict cost impact of a Terraform PR before merge.** Read `terraform show -json plan.tfplan`, look every changing resource up against the AWS Pricing API, and post (or upsert) a Markdown comment on the PR with the net monthly delta, top movers, and a 1–3 sentence LLM narrative. Ships as a GitHub Action and as the `oracle pr-check` subcommand. **Current focus.** See **[docs/v2-guide.md](docs/v2-guide.md)**. +- **v3 — Insights Agent (in progress).** Polyglot Go + Python extension adding agentic FinOps analysis on top of v1/v2 cost data — LangGraph orchestration, RAG over FinOps documentation, multi-agent supervisor pattern, and production guardrails. -The v2 mode is the current focus — it's documented immediately below. The v1 audit mode is documented further down (["v1 — Cloud cost audit"](#v1--cloud-cost-audit)) and is fully functional. +## v2 — Quick start (current focus) -## v2 — Terraform PR cost analysis (current focus) - -CloudOracle parses a Terraform plan, prices every changing resource against the live AWS Pricing API, and renders a PR comment that looks like this: +CloudOracle parses a Terraform plan, prices every changing resource, and posts a PR comment like this: > ## 💰 Cloud Cost Impact > **Net monthly change: +$389.35** 🔴 > -> The Aurora cluster instance dominates this change at ~$204/month — over half the total. If this is intended for a non-production environment, an `aws_db_instance` running `db.t3.medium` would land around $60/mo for similar functional coverage. Note that data-processing charges for the NAT gateway are not modeled in this estimate. +> The Aurora cluster instance dominates this change at ~$204/month — over half the total. If this is intended for a non-production environment, an `aws_db_instance` running `db.t3.medium` would land around $60/mo for similar functional coverage. > > ### Top movers by cost impact > | Resource | Action | Δ Monthly | Confidence | @@ -26,18 +25,8 @@ CloudOracle parses a Terraform plan, prices every changing resource against the > | `aws_rds_cluster_instance.aurora` | 🆕 create | +$204.40 | low | > | `aws_db_instance.db` | 🆕 create | +$71.36 | low | > | `aws_instance.web` | 🆕 create | +$64.74 | low | -> -> _
Full breakdown · Assumptions and caveats
_ -> -> Generated by [CloudOracle](...) · Confidence: **low** -> -> `` -The HTML marker at the end is what makes re-renders safe: subsequent pushes update that comment in place instead of stacking new ones. - -### Quick start: GitHub Action - -Drop this into `.github/workflows/cost-comment.yml` in any repo with Terraform: +Drop this workflow into `.github/workflows/cost-comment.yml`: ```yaml name: Terraform Plan Cost Comment @@ -69,203 +58,17 @@ jobs: ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }} ``` -Two reference workflows live under [`.github/examples/`](.github/examples) — one with OIDC + LLM, one with static AWS access keys + no-LLM fallback. The `.github/examples/README.md` covers IAM trust policies, the minimum permission set, and how to wire the LLM secret. - -### Action inputs - -| Input | Required | Default | Notes | -|-------|----------|---------|-------| -| `plan-file` | yes | — | Path to `terraform show -json` output. | -| `region` | no | `us-east-2` | AWS region the Pricing API queries against. | -| `output-file` | no | `` | Also write the rendered Markdown to a file (useful for artefact upload). | -| `marker` | no | `cloudoracle-pr-v1` | HTML-comment substring used for upsert. Bump if you change the comment template. | -| `no-llm` | no | `false` | Force the deterministic templated narrative even with LLM keys configured. | -| `github-token` | no | `${{ github.token }}` | Used to post the comment; needs `pull-requests: write`. | +For Action inputs, CLI flags, exit codes, LLM narrative behavior, and the list of supported resources, see **[docs/v2-guide.md](docs/v2-guide.md)**. -The Action only posts when `GITHUB_EVENT_NAME` is `pull_request` or `pull_request_target`; on other triggers it renders to stdout (or `output-file`) and exits, with a `::notice::` log line explaining why. - -### Quick start: CLI - -The same workflow runs locally without any GitHub plumbing — useful for testing, debugging, or iterating on the prompt: +## v1 — Quick start ```bash -# Just render to stdout (no AWS creds needed for the templated narrative) -go run ./cmd/oracle pr-check \ - --plan-file=internal/iac/testdata/plan_simple_create.json \ - --no-llm - -# Render against a real plan + AWS Pricing API -terraform show -json my.tfplan > plan.json -go run ./cmd/oracle pr-check --plan-file=plan.json --region=us-east-2 - -# Render and post (or update) the comment on PR #11 -go run ./cmd/oracle pr-check \ - --plan-file=plan.json \ - --post --repo=Cro22/CloudOracle --pr=11 \ - --token=$GITHUB_TOKEN -``` - -Full flag listing: - -| Flag | Default | Notes | -|------|---------|-------| -| `--plan-file` | — | Required. Path to JSON plan. | -| `--region` | `us-east-2` | AWS region for pricing. | -| `--output` | _(stdout)_ | File to also write the Markdown to; `-` or empty means stdout. | -| `--no-llm` | `false` | Force templated narrative. | -| `--post` | `false` | Post / upsert the comment via the GitHub API. Requires `--repo` and `--pr`. | -| `--repo` | — | `owner/name` form. Required with `--post`. | -| `--pr` | `0` | PR number. Required with `--post`. | -| `--token` | _(env)_ | Falls back to `$GITHUB_TOKEN` when empty. | -| `--marker` | `cloudoracle-pr-v1` | HTML comment marker for upsert. | - -Exit codes are differentiated so the Action wrapper can produce sensible CI error messages: - -| Code | Meaning | -|------|---------| -| 0 | Success. | -| 1 | Input error (missing/invalid flag, plan file unreadable). | -| 2 | Pricing error (AWS Pricing API rejected the request). | -| 3 | Output error (couldn't write `--output` path). | -| 4 | GitHub error (post/update failed). | - -### LLM narrative behavior - -The PR narrative is generated by the same provider layer as v1 (Gemini / Claude / OpenAI), so the same env-var conventions apply: set `ANTHROPIC_API_KEY`, `GEMINI_API_KEY`, or `OPENAI_API_KEY`, optionally pin one with `LLM_PROVIDER`. With no key configured, the comment falls back silently to a deterministic templated narrative — the comment still posts, just less narrated. - -The v2 prompt (in `internal/diff/narrative.go`) is purpose-built for PR review tone: 1–3 sentences, identifies the dominant cost driver, optionally suggests an architectural alternative (never a billing-model swap), avoids cheerleading. Caveats are grouped by resource so the model can't accidentally attribute one resource's note to another (e.g. mistakenly claiming the database carries the NAT gateway's data-processing charges — a real bug observed during prompt development that the grouping prevents). - -### v2 architecture - -``` -internal/iac/ # Terraform plan parser - terraform.go # ParsePlan / ParsePlanFile + the canonical Plan model - aws/ # AWS-specific resource shape decoders (after_unknown handling, attr extraction) -internal/pricing/ # AWS Pricing API client + per-service estimators - aws.go # *pricing.Client wrapping the AWS SDK - cache.go # 7-day disk cache (best-effort) keyed by service+filters - ec2.go / ebs.go / rds.go / lambda.go / nat.go # one estimator per supported resource type - estimator.go # EstimateChange entry point — dispatches to the right estimator -internal/diff/ # CostDiff aggregation + Markdown rendering - engine.go # Analyze: per-resource estimates -> CostDiff (Created/Deleted/Updated/Replaced/Skipped) - markdown.go # template-based PR comment renderer (header / table / breakdown / caveats / footer) - narrative.go # LLM narrative + grouped caveats + silent fallback to templated text -internal/github/ # Thin GitHub REST client (issue comments only) - client.go / comments.go # listComments (paginated, capped) + postComment + updateComment + PostOrUpdateComment -cmd/oracle/ # pr-check subcommand wires it all together - main.go # runPRCheck: ParsePlan -> Analyze -> Render -> [Post] -Dockerfile.action # Multi-stage golang:1.25-alpine -> alpine:3.19, ENTRYPOINT entrypoint.sh -entrypoint.sh # POSIX shim: INPUT_* env vars -> oracle pr-check flags -action.yml # GitHub Action manifest (runs: docker, image: Dockerfile.action) -``` - -The v1 dashboard `Dockerfile` at the repo root is **untouched** — `Dockerfile.action` is a separate, leaner image just for the Action. They share a single `.dockerignore`. - -### Supported resources (v2) - -EC2 instances (Linux on-demand compute + root EBS), EBS volumes (gp2/gp3/io1/io2/st1/sc1), RDS instances (single-AZ + Aurora cluster instances), Lambda functions (cold-start estimate), NAT gateways (hourly only). Unsupported types appear in the rendered comment under "Skipped" with a one-line reason — they don't fail the run. Adding a new resource type is one new file under `internal/pricing/` plus a switch case in `estimator.go`. - ---- - -## v1 — Cloud cost audit - -## Why this project? - -Cloud waste is a real problem. Companies routinely overspend 20-30% on cloud infrastructure because nobody is watching the bill. CloudOracle demonstrates how to build a system that catches these issues automatically, using the same patterns that tools like AWS Trusted Advisor or Datadog Cloud Cost Management use internally. - -Unlike policy engines like **Cloud Custodian** that focus on automated enforcement, CloudOracle is an *analysis-first* tool built for FinOps visibility — combining deterministic rules with LLM-generated insights to produce executive-ready reports and dashboards. - -## Features - -- **Multi-cloud support** - Switch between AWS, GCP, Azure, and synthetic data via a single env var (`CLOUDORACLE_PROVIDER`) -- **Real AWS integration** - Fetches live EC2 instances, RDS databases, EBS volumes, and Lambda functions using AWS SDK v2 with STS credential validation -- **Real GCP integration** - Fetches Compute Engine VMs, Cloud SQL instances, Persistent Disks, and Cloud Functions using Google Cloud Go client libraries -- **Real Azure integration** - Fetches Virtual Machines, Azure SQL databases, Managed Disks, and Function Apps using Azure SDK for Go -- **Synthetic data generation** - Realistic resource simulation across EC2, RDS, EBS, and Lambda with configurable account IDs and resource counts -- **PostgreSQL persistence** - Transactional bulk inserts with upsert support (`ON CONFLICT DO UPDATE`) -- **Rule-based analysis engine** - Pluggable rules architecture where each rule is a pure function `Resource -> Finding` -- **4 detection rules**: - - `ec2-idle` - Flags instances with <5% CPU usage running for more than 7 days (HIGH severity) - - `rds-oversized` - Identifies RDS instances with <10% CPU utilization (MEDIUM severity) - - `ebs-orphan` - Detects unattached EBS volumes with zero usage (HIGH severity) - - `lambda-over-provisioned` - Finds Lambda functions with >1GB memory and low invocation counts (LOW severity) -- **Savings-ranked output** - Findings are sorted by potential monthly savings (highest first) -- **Service summary** - Aggregated view of findings and potential savings per AWS service -- **PDF report generation** - Professional executive-style PDF reports with severity-coded tables, recommended actions, and annual savings projections -- **LLM-powered executive summaries** - Pluggable provider layer (Gemini, Claude, OpenAI) that turns raw findings into a CTO/CFO-ready narrative embedded directly into the PDF report -- **Resilient LLM calls** - Shared `http.RoundTripper` retries 429s, 5xx, and network errors with exponential-backoff-with-full-jitter; honors the `Retry-After` header from Anthropic/OpenAI; cancellable via the request context -- **Cost trend tracking** - Automatic cost snapshots on every seed, with a `trend` command that shows per-service cost changes over time with directional arrows and percentage deltas -- **Parallel resource fetching** - Each provider fans out service calls (Compute / SQL / Disks / Functions) concurrently with `errgroup`, cutting scan time on accounts with many services -- **Per-service timeouts** - Every API call to a cloud service is wrapped in `context.WithTimeout` so a single slow region can't stall the entire scan -- **Structured logging (`log/slog`)** - Every log line carries typed attributes (`provider`, `service`, `error`, ...), with pluggable text or JSON output for ingestion into log aggregators -- **Centralized configuration** - A single `config.Load()` reads every env var up front and is injected into the cloud, LLM, and DB layers — no component reaches for `os.Getenv` on its own -- **Export findings to JSON or CSV** - Pipe analyzer output into downstream tooling (dashboards, spreadsheets, ticket systems) via `oracle export --format=json|csv`, writing to stdout or a file -- **Single-binary web dashboard** - React + Recharts UI embedded into the Go binary via `go:embed`; `oracle serve` boots API and dashboard on one port with no external assets required - -## Architecture (v1) - -> The v2 packages (`internal/iac`, `internal/pricing`, `internal/diff`, `internal/github`) are documented in the [v2 architecture](#v2-architecture) section above. The tree below is the v1 audit-mode layout. - -``` -cmd/oracle/main.go # CLI entry point (seed, list, analyze, report, trend, pr-check) -internal/ - config/ - config.go # Central Config + Load(): reads every env var up front - logging/ - logging.go # slog setup (text or JSON, configurable level) - shared/ - resource.go # Resource domain model - finding.go # Finding + Severity types - cloud/ - provider.go # CloudProvider interface (Strategy pattern) - factory.go # Provider factory: Config -> concrete provider - synthetic_provider.go # Synthetic data provider (dev/demo) - aws_provider.go # Real AWS provider — parallel fetchers with per-service timeouts - aws_clients.go # Narrow ec2/rds/lambda interfaces — *aws.Client satisfies them, fakes drive tests - gcp_provider.go # Real GCP provider — parallel fetchers with per-service timeouts - gcp_clients.go # Lister interfaces + SDK adapters that flatten pagination - azure_provider.go # Real Azure provider — parallel fetchers with per-service timeouts - azure_clients.go # Lister interfaces + SDK adapters that flatten pagers - generator/ - generator.go # Synthetic data generation for EC2, RDS, EBS, Lambda - analyzer/ - analyzer.go # Rule engine: runs all rules, sorts by savings - rules.go # Detection rules (pure functions) - report/ - pdf.go # PDF report generator (executive summary + findings table) - export.go # JSON and CSV exporters for findings - llm/ - provider.go # Provider interface + Config-driven factory (Gemini / Claude / OpenAI) - prompt.go # Shared prompt builder (findings -> structured analysis) - http.go # newHTTPClient: builds the *http.Client every provider uses - retry.go # http.RoundTripper that retries 429/5xx/net errors with full-jitter backoff - gemini.go # Google Gemini client (gemini-2.5-flash) - claude.go # Anthropic Claude client (claude-haiku-4-5) - openai.go # OpenAI client (gpt-4o-mini) - db/ - db.go # PostgreSQL connection pool (pgx) - insert.go # Transactional insert + query logic - snapshots.go # Cost snapshot creation + trend queries - trends.go # Aggregated trends for the /api/trends endpoint - dbtest/postgres.go # testcontainers-go helper (gated by `integration` build tag) - *_integration_test.go # //go:build integration — real Postgres tests - e2e/ - seed_analyze_test.go # //go:build integration — full seed -> analyze flow - migrations/ - migrations.go # go:embed runner executed at app startup - 001_create_resources.sql - 002_create_cost_snapshots.sql -Dockerfile # Multi-stage: npm build → go build → alpine runtime -docker-compose.yml # Postgres (with healthcheck) + app service +docker compose up --build +docker compose exec app /app/cloudoracle seed --count 120 +# → open http://localhost:8080 ``` -The cloud provider layer uses the **Strategy pattern**: `CloudProvider` is the interface, and `SyntheticProvider`, `AWSProvider`, `GCPProvider`, and `AzureProvider` are the concrete strategies. `factory.go` selects the strategy at runtime based on the `Config` loaded from `internal/config`. This lets `main.go` work with any provider without knowing which one is active. - -Configuration is loaded once in `main()` via `config.Load()` and injected downward. No component in `cloud/`, `llm/`, or `db/` calls `os.Getenv` directly — every dependency arrives as a typed struct field. This keeps the surface area predictable, makes the code easy to test with struct literals, and means adding a new env var is a single-file change in `internal/config/config.go`. - -Each real provider's `FetchResources` fans out its service calls (for example: EC2, RDS, EBS, and Lambda on AWS) onto separate goroutines via `golang.org/x/sync/errgroup`. Each goroutine wraps its API call in `context.WithTimeout(cfg.ServiceTimeout)`, so one slow service can't block the others and a regional outage surfaces as a structured warning rather than a hung process. Per-service failures are logged with `slog` and the successful services still return their resources — the scan degrades gracefully instead of failing hard. - -The SDK call surface for every real provider is hidden behind narrow interfaces (`ec2APIClient`, `gcpInstancesLister`, `azureVMLister`, …) defined in `aws_clients.go` / `gcp_clients.go` / `azure_clients.go`. Concrete `*ec2.Client`, `*compute.InstancesClient`, and `*armcompute.VirtualMachinesClient` values satisfy those interfaces transparently, so production code is unchanged — but unit tests can plug in fakes that return canned slices and simulate API errors without ever touching the network or needing credentials. The mapping logic (`SDK type -> shared.Resource`) stays inline with the fetcher, which means tests can exercise pagination, error handling, graceful degradation, and edge-case field handling end-to-end. +The synthetic provider needs no credentials. To run against AWS / GCP / Azure, see **[docs/cloud-providers.md](docs/cloud-providers.md)**. For the full walkthrough (PDF reports, dashboard, LLM setup, exports, trends), see **[docs/v1-guide.md](docs/v1-guide.md)**. ## Tech Stack @@ -284,515 +87,20 @@ The SDK call surface for every real provider is hidden behind narrow interfaces | Testing | `testing` + `httptest` | | Containers | Docker Compose + multi-stage Dockerfile | -## Getting Started - -### Prerequisites - -- Go 1.25+ -- Docker & Docker Compose -- (Optional) AWS CLI configured with a `cloudoracle` profile for real AWS integration (see [Running against cloud providers](#running-against-cloud-providers) below) - -### 1. Start the stack - -Single command for the full demo (Postgres + API + embedded React dashboard): - -```bash -docker compose up --build -# → open http://localhost:8080 -``` - -Compose brings up two services: -- **postgres** — PostgreSQL 16 with a healthcheck; the app only starts once it responds to `pg_isready`. -- **app** — multi-stage build of the Go binary with the React bundle embedded via `go:embed`, exposed on `:8080`. - -The app auto-applies the SQL migrations in `internal/migrations/*.sql` on every startup (they're idempotent — `CREATE TABLE/INDEX IF NOT EXISTS`), so there's no separate migration step. To populate demo data: - -```bash -docker compose exec app /app/cloudoracle seed --count 120 -``` - -For local development without Docker you still need Postgres running somewhere; the easiest is `docker compose up -d postgres` and then run the Go binary on the host. Migrations run automatically whichever way you boot the app. - -### 2. Seed sample data +## Documentation -```bash -go run cmd/oracle/main.go seed --account acc-001 --count 100 -``` - -### 3. List all resources - -```bash -go run cmd/oracle/main.go list -``` - -### 4. Run the cost analyzer - -```bash -go run cmd/oracle/main.go analyze -``` - -### 5. Generate a PDF report - -```bash -go run cmd/oracle/main.go report --output cloudoracle-report.pdf -``` - -This generates a professional PDF with: -- Executive summary (total findings, monthly/annual savings projections) -- Severity breakdown (HIGH / MEDIUM / LOW) -- Color-coded findings table with cost and savings per resource -- Recommended actions for each finding -- **AI-generated narrative** (when an LLM provider is configured) — 3-4 paragraph executive summary written for a CTO/CFO audience, focused on financial impact, highest-priority problems, and recommended next steps - -![CloudOracle PDF report example](examplepdf.png) - -### 6. View cost trends - -Each `seed` automatically creates a cost snapshot. After running `seed` multiple times (on different days or with different data), view how costs change: - -```bash -go run cmd/oracle/main.go trend --days 30 -``` - -``` -Cost Trends (last 30 days, 3 snapshots) - -Service Oldest Latest Change -──────────────────────────────────────────────────────── -ebs $ 100.00 $ 90.00 -10.00 (-10.0%) ↓ -ec2 $ 460.00 $ 510.00 +50.00 (+10.9%) ↑ -lambda $ 2.50 $ 3.10 +0.60 (+24.0%) ↑ -rds $ 180.00 $ 195.00 +15.00 (+8.3%) ↑ -──────────────────────────────────────────────────────── -Total $ 742.50 $ 798.10 +55.60 (+7.5%) ↑ -``` - -### 7. Export findings to JSON or CSV - -Run the analyzer and pipe its findings into another tool — a dashboard, a spreadsheet, a ticketing system. By default, the exporter writes to stdout so it composes naturally with shell pipelines; pass `--output` to write to a file. - -```bash -# Pretty-printed JSON to stdout -go run cmd/oracle/main.go export --format=json - -# CSV to a file (header row + one finding per row) -go run cmd/oracle/main.go export --format=csv --output findings.csv - -# Pipe straight into jq -go run cmd/oracle/main.go export --format=json | jq '.[] | select(.Severity == "High")' -``` - -The JSON output is an array of `Finding` objects. The CSV output has a fixed header: `resource_id, service, resource_type, region, rule, severity, monthly_cost, monthly_savings, description, recommendation`. Numeric fields are formatted with two decimals. Commas, quotes, and newlines in descriptions are escaped per RFC 4180 — the output is safe to open in Excel or parse with any standard CSV library. - -### 8. Web dashboard - -CloudOracle ships a React + Recharts dashboard that reads the same database as the CLI. There are two workflows: - -**Production / demo — one binary, one command.** The Go binary embeds the compiled frontend via `go:embed`, so after a single `npm run build` the whole stack (API + UI) is served on one port. - -```bash -# Build the React bundle into internal/api/dist (go:embed target) -cd web -npm install # first time only -npm run build -cd .. - -# Build the self-contained binary and run it -go build -o cloudoracle ./cmd/oracle -./cloudoracle serve --port 8080 -# → open http://localhost:8080 -``` - -The binary is fully self-contained. Copy the single file (`cloudoracle` / `cloudoracle.exe`) to any machine, point it at a reachable Postgres via `DB_*` env vars, and the dashboard loads. No `web/` directory needed at runtime. - -**Development — hot reload.** During iteration, run the API and the Vite dev server separately so you get HMR on React changes without rebuilding Go: - -```bash -# Terminal 1 — API on :8080 -go run ./cmd/oracle serve --port 8080 - -# Terminal 2 — Vite on :5173 with /api/* proxied to :8080 -cd web -npm run dev -# → open http://localhost:5173 -``` - -> **Note:** `go:embed` requires `internal/api/dist/` to exist at compile time. The repo commits a `.gitkeep` so `go build` always works — if you haven't run `npm run build`, visiting the root route shows a "Dashboard bundle not found" page with instructions. The JSON API at `/api/*` works either way. - -### 9. (Optional) Enable the LLM-powered executive summary - -The `report` command will automatically call an LLM provider if any supported API key is present in the environment. No flags required — just export a key and run `report` again. If no key is configured, the PDF is still generated without the narrative section. - -| Provider | Env variable | Default model | -|----------|---------------------|----------------------| -| Gemini | `GEMINI_API_KEY` | `gemini-2.5-flash` | -| Claude | `ANTHROPIC_API_KEY` | `claude-haiku-4-5` | -| OpenAI | `OPENAI_API_KEY` | `gpt-4o-mini` | - -```bash -# Pick one -export GEMINI_API_KEY=... -export ANTHROPIC_API_KEY=... -export OPENAI_API_KEY=... - -# Force a specific provider when multiple keys are present -export LLM_PROVIDER=claude # gemini | claude | openai - -go run cmd/oracle/main.go report --output cloudoracle-report.pdf -``` - -Auto-detection order when `LLM_PROVIDER` is unset: **Gemini → Claude → OpenAI**. The first key found wins. LLM failures (missing key, network error, API error) are logged but never block PDF generation — the report falls back to the deterministic summary. - -### Sample Output - -![CloudOracle analyze output](example.png) - -``` -CloudOracle found 10 problems with potential monthly savings of $680.00 - - 1. [HIGH] EC2 i-3592027508 (c5.xlarge) has average CPU usage of 2.8%. Active for 325 days. - Consider shutting down or terminating this instance. - Monthly Cost: $125.00 | Potential Monthly Savings: $125.00 - - 2. [HIGH] EBS vol-fcebf509 (gp3-1000GB) is not attached to any instance. Orphaned for 60 days. - Create a backup snapshot and delete the volume. - Monthly Cost: $100.00 | Potential Monthly Savings: $100.00 - - 3. [MEDIUM] RDS db-f7fdfc2b (db.t3.micro) has average CPU usage of 7.1%. Likely oversized. - Consider downgrading to the next smaller RDS instance tier. - Monthly Cost: $15.00 | Potential Monthly Savings: $7.50 - ... - -Summary per service - ec2 -> 5 problems, save: $460.00/month - ebs -> 3 problems, save: $205.00/month - rds -> 2 problems, save: $15.00/month -``` - -## Running against cloud providers - -CloudOracle supports four resource sources, selected at runtime with the `CLOUDORACLE_PROVIDER` env var: **synthetic** (default, no cloud account required), **aws**, **gcp**, **azure**. The analyzer, report, and dashboard work identically with all four — they only differ in where the resource inventory comes from. - -> **Tested status.** The **synthetic** and **AWS** providers have been exercised end-to-end against a live AWS account during development. The **GCP** and **Azure** providers are implemented against their respective SDKs with the same structure and the code compiles + unit-tests pass, **but they have not been run against live GCP / Azure subscriptions** because I don't have credentials for those clouds at the time of writing. Field-mapping tests use struct literals; the SDK call paths themselves are unverified. If you test either, please open an issue with what you find. - -### Synthetic (default, no setup) - -No credentials, no network calls — the app generates realistic EC2 / RDS / EBS / Lambda records locally. Ideal for demos, CI, and trying the dashboard in seconds. - -```bash -docker compose up --build -docker compose exec app /app/cloudoracle seed --count 120 -# open http://localhost:8080 -``` - -Tunables: -- `SYNTHETIC_COUNT` (default `100`) — how many resources to generate per `seed`. -- `SYNTHETIC_ACCOUNT` (default `synthetic-account`) — account ID baked into the records. - -The synthetic provider is what 99% of demos use. Everything else in this README — findings, exports, trend tracking, dashboard — works with synthetic data without any cloud credentials. - -### AWS (verified) - -**1. IAM user with read-only access.** In the AWS Console → IAM → Users → Create user, attach: -- `ReadOnlyAccess` -- `AWSBillingReadOnlyAccess` - -Grab the access key + secret. For least-privilege in production, the minimum set is: - -``` -ec2:DescribeInstances, ec2:DescribeVolumes -rds:DescribeDBInstances, rds:ListTagsForResource -lambda:ListFunctions, lambda:ListTags -ce:GetCostAndUsage -sts:GetCallerIdentity -``` - -**2. Configure a local profile.** In `~/.aws/credentials` (or `%USERPROFILE%\.aws\credentials` on Windows): - -```ini -[cloudoracle] -aws_access_key_id = AKIA... -aws_secret_access_key = ... -region = us-east-2 -``` - -The profile name `cloudoracle` and region `us-east-2` are the defaults. Override with `AWS_PROFILE=xxx` and `AWS_REGION=eu-west-1` if you use different names. - -**3. Run the app on the host** (so it can read `~/.aws/credentials`), pointing at the Postgres container: - -```bash -docker compose up -d postgres # DB only in Docker -export CLOUDORACLE_PROVIDER=aws -go run ./cmd/oracle seed # fetches real EC2/RDS/EBS/Lambda, upserts, snapshots -go run ./cmd/oracle analyze # runs rules → findings on real data -go run ./cmd/oracle serve --port 8080 # dashboard + API -``` - -The STS `GetCallerIdentity` call at startup validates credentials immediately — if the profile is misconfigured or keys are expired, you get the error right away instead of halfway through a scan. - -**Running inside Docker with AWS creds** (if you want `docker compose up app` against AWS), pass the creds as env vars to the `app` service in `docker-compose.yml`: - -```yaml -environment: - CLOUDORACLE_PROVIDER: aws - AWS_ACCESS_KEY_ID: ${AWS_ACCESS_KEY_ID} - AWS_SECRET_ACCESS_KEY: ${AWS_SECRET_ACCESS_KEY} - AWS_REGION: us-east-2 -``` - -The AWS SDK v2 auto-picks these up without needing a profile file. Recommended only for demos — for prod/CI, use IAM roles via instance metadata or IRSA on EKS, not static keys. - -**Cost:** `Describe*` / `List*` calls are free. A full `seed` against a typical account is ~5-10 API calls total. - -### GCP (untested against a live account) - -> Implemented but not verified against a real GCP project. - -Expected flow: - -1. Enable APIs on your project: Compute Engine, Cloud SQL Admin, Cloud Functions. -2. Set up Application Default Credentials: - - Dev: `gcloud auth application-default login` - - Prod: `GOOGLE_APPLICATION_CREDENTIALS=/path/to/sa.json` -3. Export `GOOGLE_CLOUD_PROJECT=your-project-id`. - -Required IAM roles (least privilege): - -``` -compute.instances.list, compute.disks.list -cloudsql.instances.list -cloudfunctions.functions.list -``` - -Then: - -```bash -docker compose up -d postgres -export CLOUDORACLE_PROVIDER=gcp -export GOOGLE_CLOUD_PROJECT=your-project-id -go run ./cmd/oracle seed -go run ./cmd/oracle serve --port 8080 -``` - -Since this path hasn't been exercised end-to-end, expect to debug the SDK call mapping on first run. - -### Azure (untested against a live account) - -> Implemented but not verified against a real Azure subscription. - -Expected flow: - -1. Export `AZURE_SUBSCRIPTION_ID=`. -2. Authenticate via one of: - - Dev: `az login` - - Service principal: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET` - - Managed Identity (when the app runs on Azure) - -The provider uses `DefaultAzureCredential`, which tries all methods in order. - -Required RBAC role: `Reader` on the subscription. Production scope: - -``` -Microsoft.Compute/virtualMachines/read -Microsoft.Compute/disks/read -Microsoft.Sql/servers/read, Microsoft.Sql/servers/databases/read -Microsoft.Web/sites/read -``` - -Then: - -```bash -docker compose up -d postgres -export CLOUDORACLE_PROVIDER=azure -export AZURE_SUBSCRIPTION_ID=00000000-0000-0000-0000-000000000000 -go run ./cmd/oracle seed -go run ./cmd/oracle serve --port 8080 -``` - -Same caveat as GCP: no live-account run has been done, so treat first execution as a validation exercise. - -## Environment Variables - -| Variable | Default | Description | -|--------------|---------------|-----------------------| -| `CLOUDORACLE_PROVIDER` | `synthetic` | Cloud provider: `aws`, `gcp`, `azure`, or `synthetic` | -| `AWS_PROFILE` | `cloudoracle` | AWS shared-config profile to use | -| `AWS_REGION` | `us-east-2` | AWS region to scan | -| `GOOGLE_CLOUD_PROJECT` | _(unset)_ | GCP project ID (required when provider is `gcp`) | -| `AZURE_SUBSCRIPTION_ID` | _(unset)_ | Azure subscription ID (required when provider is `azure`) | -| `SYNTHETIC_COUNT` | `100` | Default number of synthetic resources to generate | -| `SYNTHETIC_ACCOUNT` | `synthetic-account` | Default account ID for synthetic data | -| `CLOUD_SERVICE_TIMEOUT` | `30s` | Per-service timeout for each cloud API call (Go duration string) | -| `DB_HOST` | `localhost` | PostgreSQL host | -| `DB_PORT` | `5432` | PostgreSQL port | -| `DB_USER` | `oracle` | Database user | -| `DB_PASSWORD`| `oracle_dev` | Database password | -| `DB_NAME` | `cloudoracle` | Database name | -| `LLM_PROVIDER` | _(auto)_ | Force a specific LLM provider: `gemini`, `claude`, or `openai`. If unset, auto-detects based on which API key is present. | -| `LLM_TIMEOUT` | `30s` | HTTP timeout for LLM API calls (Go duration string) | -| `LLM_MAX_RETRIES` | `3` | Number of retries on transient LLM failures (429, 5xx, network errors). Set to `0` to disable. | -| `LLM_BASE_DELAY` | `500ms` | Initial backoff between retries; doubles on each attempt with full jitter | -| `LLM_MAX_DELAY` | `30s` | Cap for the per-retry wait (also caps `Retry-After` headers) | -| `GEMINI_API_KEY` | _(unset)_ | API key for Google Gemini (`gemini-2.5-flash`) | -| `ANTHROPIC_API_KEY`| _(unset)_ | API key for Anthropic Claude (`claude-haiku-4-5`) | -| `OPENAI_API_KEY` | _(unset)_ | API key for OpenAI (`gpt-4o-mini`) | -| `LOG_LEVEL` | `info` | Log level: `debug`, `info`, `warn`, or `error` | -| `LOG_FORMAT` | `text` | Log format: `text` (human-readable) or `json` (structured) | - -## How the Analyzer Works - -The analyzer follows a simple but extensible pattern: - -```go -type Rule func(r shared.Resource) *shared.Finding -``` - -Each rule is a **pure function** that receives a resource and returns either a finding (if a problem was detected) or `nil`. This makes rules easy to test, compose, and add. The engine iterates over all resources, applies every rule, collects non-nil findings, and sorts them by potential savings descending. - -Adding a new rule is a three-step process: -1. Write the function in `internal/analyzer/rules.go` -2. Register it in the `rules` slice in `analyzer.go` -3. That's it. No interfaces, no config files. - -## The LLM Provider Layer - -The AI summary feature is built around a single interface that every provider satisfies: - -```go -type Provider interface { - GenerateSummary(ctx context.Context, findings []shared.Finding) (string, error) - Name() string -} -``` - -Three providers are shipped out of the box — Gemini, Claude, and OpenAI — each owning its own HTTP client, request/response types, and authentication headers. A shared `BuildPrompt` function in `internal/llm/prompt.go` computes totals, severity breakdowns, and per-service rollups, then wraps them in a consistent CTO/CFO-oriented prompt that every provider receives. This guarantees the narrative style stays identical no matter which model generated it. - -Provider selection is resolved at runtime by `NewProvider()`: -1. If `LLM_PROVIDER` is set, that provider is used explicitly. -2. Otherwise, the first available API key wins, in the order **Gemini → Claude → OpenAI**. -3. If no key is found, `ErrNoProvider` is returned and the report command gracefully skips the AI section. - -Adding a fourth provider is a matter of creating one new file: implement the two methods on a struct, add a `newFooFromEnv()` constructor, and wire it into the switch in `provider.go`. The rest of the system — prompt, PDF rendering, CLI flags — stays untouched. - -## Testing - -The project has two tiers of tests: - -- **Unit tests** (171, no external dependencies): pure-function tests for the analyzer, generator, LLM providers, LLM retries, PDF report, exporters, cloud mapping, real-provider fetchers, and central config validation. Run with `go test ./internal/...`. -- **Integration tests** (12, require Docker): exercise the real Postgres path via [testcontainers-go](https://golang.testcontainers.org/) — insert/upsert behavior, transaction rollback, snapshot aggregation, and a full end-to-end seed → analyze flow against a containerized Postgres 16. Run with `go test -tags=integration ./internal/db/ ./internal/e2e/`. - -Integration tests share a single Postgres container per process and `TRUNCATE … RESTART IDENTITY CASCADE` between cases — fast (sub-millisecond reset on small tables) and hermetic enough for our schema. The helper lives at `internal/db/dbtest/postgres.go` and is gated by the `integration` build tag, so the testcontainers dependency stays out of the unit-test compile path. If Docker isn't running, the helper calls `t.Skip` with a clear message rather than failing — running the binary without Docker just skips the integration cases. - -The CI workflow at `.github/workflows/test.yml` runs both tiers on every push and PR. GitHub-hosted Ubuntu runners have Docker preinstalled, so the integration job needs no extra service container. - -The unit tests cover: - -- **Per-rule tests**: each detection rule (`ec2-idle`, `rds-oversized`, `ebs-orphan`, `lambda-over-provisioned`) has happy-path, negative, and boundary tests. -- **Boundary testing**: CPU thresholds, age cutoffs, memory limits, and invocation counts are explicitly tested at their exact values to catch off-by-one errors. -- **Aggregator tests**: `Analyze` is tested for empty input, mixed input, false-positive prevention, and correct savings-descending ordering. -- **LLM provider tests**: all three providers (Gemini, Claude, OpenAI) are tested against mock HTTP servers using `httptest`, covering success responses, API errors, empty payloads, error fields, and context cancellation. -- **Provider factory tests**: auto-detection order (Gemini > Claude > OpenAI), explicit selection, missing keys, and unknown providers. -- **Prompt builder tests**: total calculations, severity breakdowns, service rollups, top-5 limiting, and empty input handling. -- **PDF generation tests**: file creation, AI summary inclusion/exclusion, empty findings, 100-finding page-break stress test, invalid paths, and all severity color codes. -- **Export tests**: JSON round-trip, CSV header + row layout, numeric formatting, RFC 4180 escaping of commas/quotes/newlines, and empty-findings handling for both formats. -- **Generator tests**: correct count, valid services/regions/types, non-negative costs, timestamp ordering, and service distribution. -- **Config tests**: default values, custom values, timeout parsing (valid and invalid durations), empty-env fallback, and DSN assembly. -- **Cloud mapping tests**: AWS SDK type → `shared.Resource` conversion with struct literals (no AWS calls, no credentials needed). -- **Real-provider fetcher tests**: every cloud provider (AWS, GCP, Azure) is exercised end-to-end against fake SDK clients — pagination exhaustion, per-service API errors, graceful degradation when one service fails, and edge cases (nil hardware profile on Azure VMs, nil settings on Cloud SQL, web apps mixed with function apps in the Azure `/sites` collection). -- **LLM retry tests**: the shared retry transport is verified against `httptest` servers — retries until success, respects `MaxRetries` cap, honors `Retry-After` headers, replays the request body on every attempt, retries transport-level errors (not just non-2xx), bails out on context cancellation, and returns immediately on non-retryable statuses (401, 4xx other than 408/429). -- **Config validation tests**: every invalid input shape (non-numeric port, out-of-range port, unknown enum value, negative integer, malformed Go duration, zero/negative duration), every cross-field rule (provider=gcp without project, provider=azure without subscription, LLM_PROVIDER set without matching API key), and the multi-error accumulator that lists all problems at once instead of failing on the first. - -The integration tests cover: - -- **Insert + upsert**: round-trip through a real Postgres, asserting that `ON CONFLICT DO UPDATE` updates the right columns (`monthly_cost`, `usage_metric`, `updated_at`) without overwriting `created_at`. -- **Transaction rollback**: a failing batch (one row that overflows `NUMERIC(10,2)`) rolls back the whole batch, leaving pre-existing rows untouched. -- **Snapshot aggregation**: a mixed set of resources across multiple `(account, service)` tuples produces exactly the expected snapshot rows, with correct counts and per-tuple cost totals. -- **Snapshot windowing**: the `--days` filter on the `trend` command actually filters via SQL — old snapshots are excluded from short windows and included in long ones. -- **End-to-end seed → analyze**: a deterministic resource set engineered to fire each rule once, inserted via `InsertResources`, read back via `ListResources`, and analyzed — asserts every rule fires exactly once and findings are sorted by potential savings descending. -- **End-to-end with synthetic data**: 50 random resources generated by `SyntheticProvider`, full round-trip through the DB, analyzer must produce *some* findings (the generator skews toward waste patterns). -- **Re-seed idempotency**: running insert three times on the same fixed-ID set ends with the same row count — proves the seed flow is safe to re-run on a schedule. - -```bash -# Unit tests (no Docker required) -go test ./internal/... - -# Integration tests (Docker must be running) -go test -tags=integration ./internal/db/ ./internal/e2e/ - -# Both, verbose -go test -tags=integration -v ./internal/... -``` - -All rules are pure functions (`Resource -> *Finding`), which makes them trivially testable without mocks, fixtures, or test databases. The code was designed to be testable from the start — not tested after the fact. - -## Architecture Decisions - -### Why not Cloud Custodian? -Cloud Custodian (Python, ~6k stars) is a mature policy engine: you write YAML rules like *"if an EC2 has no `Owner` tag, stop it"* and it **enforces** them across AWS/GCP/Azure. CloudOracle targets a different stage of the FinOps loop: - -- **Custodian**: governance and remediation — takes actions (stop, delete, tag, notify). Designed for platform teams running hundreds of policies in CI. -- **CloudOracle**: analysis and reporting — read-only, LLM-assisted narrative, PDF + dashboard. Designed for the conversation between engineering and finance, not for automated enforcement. - -The tools are complementary: Custodian is *what to enforce*, CloudOracle is *why it matters this month*. Read-only is intentional — it's safer to adopt in a new org and removes the "did this tool just delete my database?" objection at procurement time. - -### Why interfaces over inheritance for LLM providers -The `Provider` interface in `internal/llm` is intentionally minimal — just `GenerateSummary` and `Name`. Each provider (Gemini, Claude, OpenAI) is a fully independent implementation. Adding a fourth provider requires zero changes to existing code: write a new file, register it in `provider.go`, done. This is Go's structural typing at its best — no inheritance, no abstract base classes, no framework lock-in. - -### Why a shared Postgres container with TRUNCATE rather than a container per test -The integration helper at `internal/db/dbtest/postgres.go` boots one Postgres 16 container per test process and resets the schema with `TRUNCATE … RESTART IDENTITY CASCADE` between tests. The alternative — a fresh container per test — gives stronger isolation but pays ~3-5s of container-startup cost per case, which adds up fast as the suite grows. TRUNCATE on small tables runs in sub-millisecond, and all our tables are independent (no triggers, no shared sequences spanning tests), so the isolation guarantee is the same in practice. The whole integration suite (12 tests) runs in ~5 seconds total instead of ~60. - -If we ever add tests that need different schemas or different Postgres versions, we'd opt back into a per-test container for those specific cases — but as a default, sharing wins on speed. - -### Why retries live in a `RoundTripper` rather than around each `client.Do` -Every LLM provider eventually hits a 429 or a 5xx — Anthropic and OpenAI both rate-limit aggressively and both send `Retry-After` headers. Putting the retry loop inside the transport (`internal/llm/retry.go`) means **every** code path that issues an HTTP request gets retries automatically: the three providers today, and whatever future request paths we add (token-counting endpoints, streaming, file uploads). The alternative — wrapping each `client.Do` call — is more obvious but every new call site has to remember to wrap, and tests have to mock the wrapper. - -The transport buffers the request body once on entry and replays it via `req.Body` + `req.GetBody` on every attempt. It's safe because LLM POST bodies are tiny (a JSON prompt). It honors `Retry-After` (delta-seconds and HTTP-date forms) before falling back to exponential backoff with full jitter — full jitter (random in `[0, baseDelay * 2^attempt]`) is the AWS-recommended algorithm for distributed clients hitting the same endpoint, because it spreads retries evenly instead of producing thundering herds. Backoff waits respect the request context, so cancellation propagates cleanly mid-retry. - -### Why net/http directly instead of vendor SDKs -All three LLM providers are implemented with the standard library `net/http` package, no vendor SDKs. This keeps the dependency tree small (the entire project has fewer than 10 direct dependencies), makes the code portable, and forces explicit handling of errors, timeouts, and retries — all of which are usually hidden behind SDK abstractions. - -### Why deterministic rules first, LLMs second -The analyzer detects 80% of cloud waste using simple pure functions, before any LLM is involved. This is by design: deterministic rules are predictable, testable, free, and instant. LLMs are reserved for what they're actually good at — translating structured data into executive prose. Inverting this order (using LLMs to detect waste) would be slower, more expensive, and less reliable. - -### Why graceful degradation when no LLM is configured -If no API key is set, the report generates without the AI summary section instead of failing. This means anyone can clone the repo and run it immediately, and the same binary works in restricted environments where outbound API calls aren't allowed. - -### Why synthetic data instead of real AWS integration in v1 -Building the rule engine and report generator against a synthetic data generator allowed iteration without paying for AWS resources, without rate limits, and without coupling the early development to credentials. Real AWS integration is the next milestone, but the abstraction was earned by first solving the harder problem: detecting waste from any data source. - -### Why `errgroup` instead of raw goroutines for provider fan-out -Each real provider issues 4 independent API calls per scan (for example: EC2, RDS, EBS, Lambda on AWS). Running them sequentially meant the total scan time was the sum of the slowest region's latency for every service. Switching to `errgroup.WithContext` + a fixed-size `[][]shared.Resource` result slice (each goroutine owns its own index → no mutex) cut end-to-end scan time roughly in proportion to the number of services per provider. Returning `nil` from each goroutine after logging — instead of propagating errors — preserves the "log one failing service, keep the rest" contract the sequential version had, while giving the rest of the services a genuine chance to finish in parallel. - -### Why per-service `context.WithTimeout` rather than a single global deadline -A scan is only as fast as its slowest cloud API. Giving every service its own deadline (`CLOUD_SERVICE_TIMEOUT`, default 30s) means a misbehaving region bounds only itself — the other services still complete normally. A single global timeout would have cancelled every in-flight service the moment one hung, wasting the progress already made. - -### Why `log/slog` over `log.Printf` -Every warning now carries typed attributes (`provider=aws`, `service=EC2`, `error=...`) instead of being jammed into a free-form sprintf string. That makes logs grep-able, filterable by level, and — with `LOG_FORMAT=json` — ingestion-ready for Loki, ELK, or Cloud Logging without a log parser. `slog` is the standard library's answer to this, landed in Go 1.21, and needs zero external dependencies. - -### Why a central `config.Load()` over per-component `os.Getenv` -Previously every constructor reached into the environment on its own: `NewAWSProvider` for region/profile, `NewGCPProvider` for the project ID, each LLM constructor for its API key, `db.LoadConfigFromEnv` for credentials. That made the contract of each component implicit and the cost of testing high — you had to manipulate real env vars to rearrange behavior. Now `main()` calls `config.Load()` once, and every component receives its typed slice of the config as a parameter. Tests pass struct literals directly. - -### Why migrations run from the app at startup (not from `psql` scripts or a separate tool) -SQL files live in `internal/migrations/*.sql` and are baked into the binary with `go:embed`. On every boot — CLI command or `serve` — `main()` reads them in order and executes each against the pool. Because the statements use `CREATE TABLE/INDEX IF NOT EXISTS`, re-running is a no-op. Trade-offs vs. the alternatives: - -- **Postgres `docker-entrypoint-initdb.d` mount**: only runs the very first time a volume is created. If the DB already exists (prod restore, bind mount, CI cache), schema changes never land. Silent and dangerous. -- **A separate `migrate` CLI step**: adds a second binary and a deploy-ordering problem (app must not start before `migrate` succeeds). `depends_on` helps but doesn't eliminate it. -- **App-driven startup**: self-contained, idempotent, and works identically whether you boot the binary directly, with Docker Compose, in a test, or in production. The one binary knows how to set up its own schema. - -The one thing app-driven migrations don't give you out of the box is a version ledger (`schema_migrations` table) for tracking what's been applied. For a 2-file schema it's overkill; if the project grows a destructive migration (e.g. a column rename) we'd add one. Until then, `IF NOT EXISTS` is enough. - -## Lessons Learned - -Building this project surfaced a subtle but important bug that would have gone unnoticed without testing against real(istic) data: - -**The case-sensitivity trap:** The EC2 idle detection rule was comparing `r.Service != "EC2"` (uppercase), but the data generator and database stored services as `"ec2"` (lowercase). The rule silently passed over every EC2 instance without flagging a single one. The RDS, EBS, and Lambda rules all used lowercase correctly, making this inconsistency easy to miss during code review. It was only caught when analyzing output and noticing zero EC2 findings despite seeding idle instances. - -**Takeaway:** String comparison bugs are among the most common sources of silent failures in cloud tooling. Production systems use canonical enumerations or case-insensitive matching for exactly this reason. Finding this during development -- not after deployment -- is the difference between a tool that works and one that looks like it works. - -**The Strategy pattern for cloud providers:** The `CloudProvider` interface started as a formality — there was only the synthetic provider. But when adding real AWS support, the pattern paid for itself: `AWSProvider` and `SyntheticProvider` both satisfy the same interface, `factory.go` picks the right one from an env var, and `main.go` never knows which is active. The key insight was keeping the mapping logic (SDK types -> domain types) as pure functions separated from the API calls. This made it possible to unit test the field mapping with struct literals instead of mocking the entire AWS SDK — a pattern worth repeating for GCP and Azure providers. +- **[docs/v2-guide.md](docs/v2-guide.md)** — Terraform PR cost analysis (Action inputs, CLI flags, exit codes, supported resources) +- **[docs/v1-guide.md](docs/v1-guide.md)** — Cloud cost audit walkthrough (seed, analyze, PDF, dashboard, LLM setup, sample output) +- **[docs/architecture.md](docs/architecture.md)** — v1/v2 internal layout, analyzer + LLM provider design, architecture decisions, lessons learned +- **[docs/cloud-providers.md](docs/cloud-providers.md)** — AWS, GCP, Azure setup (credentials, IAM scopes, region config) +- **[docs/configuration.md](docs/configuration.md)** — environment variables reference +- **[docs/testing.md](docs/testing.md)** — unit and integration test strategy and coverage ## Roadmap +### v3 — Insights Agent (in progress) +- [ ] Polyglot Go + Python extension adding agentic FinOps analysis (LangGraph orchestration, RAG over FinOps docs, multi-agent supervisor, production guardrails) on top of v1/v2 cost data + ### v2 — Terraform PR cost analysis - [x] Terraform plan parser — `internal/iac` reads `terraform show -json` into a typed `Plan` model with action classification (create / update / replace / delete / no-op) and `after_unknown` handling - [x] AWS Pricing API client + cache — `internal/pricing.Client` wraps AWS SDK v2 `pricing:GetProducts`; `internal/pricing.Cache` adds a 7-day disk cache keyed by service+filters diff --git a/docs/architecture.md b/docs/architecture.md new file mode 100644 index 0000000..1272648 --- /dev/null +++ b/docs/architecture.md @@ -0,0 +1,193 @@ +# Architecture + +This document covers v1 and v2 internal layout, the design patterns behind the analyzer and LLM provider abstraction, and the architecture decisions made along the way. + +## v2 architecture (Terraform PR cost analysis) + +``` +internal/iac/ # Terraform plan parser + terraform.go # ParsePlan / ParsePlanFile + the canonical Plan model + aws/ # AWS-specific resource shape decoders (after_unknown handling, attr extraction) +internal/pricing/ # AWS Pricing API client + per-service estimators + aws.go # *pricing.Client wrapping the AWS SDK + cache.go # 7-day disk cache (best-effort) keyed by service+filters + ec2.go / ebs.go / rds.go / lambda.go / nat.go # one estimator per supported resource type + estimator.go # EstimateChange entry point — dispatches to the right estimator +internal/diff/ # CostDiff aggregation + Markdown rendering + engine.go # Analyze: per-resource estimates -> CostDiff (Created/Deleted/Updated/Replaced/Skipped) + markdown.go # template-based PR comment renderer (header / table / breakdown / caveats / footer) + narrative.go # LLM narrative + grouped caveats + silent fallback to templated text +internal/github/ # Thin GitHub REST client (issue comments only) + client.go / comments.go # listComments (paginated, capped) + postComment + updateComment + PostOrUpdateComment +cmd/oracle/ # pr-check subcommand wires it all together + main.go # runPRCheck: ParsePlan -> Analyze -> Render -> [Post] +Dockerfile.action # Multi-stage golang:1.25-alpine -> alpine:3.19, ENTRYPOINT entrypoint.sh +entrypoint.sh # POSIX shim: INPUT_* env vars -> oracle pr-check flags +action.yml # GitHub Action manifest (runs: docker, image: Dockerfile.action) +``` + +The v1 dashboard `Dockerfile` at the repo root is **untouched** — `Dockerfile.action` is a separate, leaner image just for the Action. They share a single `.dockerignore`. + +## v1 architecture (Cloud cost audit) + +``` +cmd/oracle/main.go # CLI entry point (seed, list, analyze, report, trend, pr-check) +internal/ + config/ + config.go # Central Config + Load(): reads every env var up front + logging/ + logging.go # slog setup (text or JSON, configurable level) + shared/ + resource.go # Resource domain model + finding.go # Finding + Severity types + cloud/ + provider.go # CloudProvider interface (Strategy pattern) + factory.go # Provider factory: Config -> concrete provider + synthetic_provider.go # Synthetic data provider (dev/demo) + aws_provider.go # Real AWS provider — parallel fetchers with per-service timeouts + aws_clients.go # Narrow ec2/rds/lambda interfaces — *aws.Client satisfies them, fakes drive tests + gcp_provider.go # Real GCP provider — parallel fetchers with per-service timeouts + gcp_clients.go # Lister interfaces + SDK adapters that flatten pagination + azure_provider.go # Real Azure provider — parallel fetchers with per-service timeouts + azure_clients.go # Lister interfaces + SDK adapters that flatten pagers + generator/ + generator.go # Synthetic data generation for EC2, RDS, EBS, Lambda + analyzer/ + analyzer.go # Rule engine: runs all rules, sorts by savings + rules.go # Detection rules (pure functions) + report/ + pdf.go # PDF report generator (executive summary + findings table) + export.go # JSON and CSV exporters for findings + llm/ + provider.go # Provider interface + Config-driven factory (Gemini / Claude / OpenAI) + prompt.go # Shared prompt builder (findings -> structured analysis) + http.go # newHTTPClient: builds the *http.Client every provider uses + retry.go # http.RoundTripper that retries 429/5xx/net errors with full-jitter backoff + gemini.go # Google Gemini client (gemini-2.5-flash) + claude.go # Anthropic Claude client (claude-haiku-4-5) + openai.go # OpenAI client (gpt-4o-mini) + db/ + db.go # PostgreSQL connection pool (pgx) + insert.go # Transactional insert + query logic + snapshots.go # Cost snapshot creation + trend queries + trends.go # Aggregated trends for the /api/trends endpoint + dbtest/postgres.go # testcontainers-go helper (gated by `integration` build tag) + *_integration_test.go # //go:build integration — real Postgres tests + e2e/ + seed_analyze_test.go # //go:build integration — full seed -> analyze flow + migrations/ + migrations.go # go:embed runner executed at app startup + 001_create_resources.sql + 002_create_cost_snapshots.sql +Dockerfile # Multi-stage: npm build → go build → alpine runtime +docker-compose.yml # Postgres (with healthcheck) + app service +``` + +The cloud provider layer uses the **Strategy pattern**: `CloudProvider` is the interface, and `SyntheticProvider`, `AWSProvider`, `GCPProvider`, and `AzureProvider` are the concrete strategies. `factory.go` selects the strategy at runtime based on the `Config` loaded from `internal/config`. This lets `main.go` work with any provider without knowing which one is active. + +Configuration is loaded once in `main()` via `config.Load()` and injected downward. No component in `cloud/`, `llm/`, or `db/` calls `os.Getenv` directly — every dependency arrives as a typed struct field. This keeps the surface area predictable, makes the code easy to test with struct literals, and means adding a new env var is a single-file change in `internal/config/config.go`. + +Each real provider's `FetchResources` fans out its service calls (for example: EC2, RDS, EBS, and Lambda on AWS) onto separate goroutines via `golang.org/x/sync/errgroup`. Each goroutine wraps its API call in `context.WithTimeout(cfg.ServiceTimeout)`, so one slow service can't block the others and a regional outage surfaces as a structured warning rather than a hung process. Per-service failures are logged with `slog` and the successful services still return their resources — the scan degrades gracefully instead of failing hard. + +The SDK call surface for every real provider is hidden behind narrow interfaces (`ec2APIClient`, `gcpInstancesLister`, `azureVMLister`, …) defined in `aws_clients.go` / `gcp_clients.go` / `azure_clients.go`. Concrete `*ec2.Client`, `*compute.InstancesClient`, and `*armcompute.VirtualMachinesClient` values satisfy those interfaces transparently, so production code is unchanged — but unit tests can plug in fakes that return canned slices and simulate API errors without ever touching the network or needing credentials. The mapping logic (`SDK type -> shared.Resource`) stays inline with the fetcher, which means tests can exercise pagination, error handling, graceful degradation, and edge-case field handling end-to-end. + +## How the Analyzer Works + +The analyzer follows a simple but extensible pattern: + +```go +type Rule func(r shared.Resource) *shared.Finding +``` + +Each rule is a **pure function** that receives a resource and returns either a finding (if a problem was detected) or `nil`. This makes rules easy to test, compose, and add. The engine iterates over all resources, applies every rule, collects non-nil findings, and sorts them by potential savings descending. + +Adding a new rule is a three-step process: +1. Write the function in `internal/analyzer/rules.go` +2. Register it in the `rules` slice in `analyzer.go` +3. That's it. No interfaces, no config files. + +## The LLM Provider Layer + +The AI summary feature is built around a single interface that every provider satisfies: + +```go +type Provider interface { + GenerateSummary(ctx context.Context, findings []shared.Finding) (string, error) + Name() string +} +``` + +Three providers are shipped out of the box — Gemini, Claude, and OpenAI — each owning its own HTTP client, request/response types, and authentication headers. A shared `BuildPrompt` function in `internal/llm/prompt.go` computes totals, severity breakdowns, and per-service rollups, then wraps them in a consistent CTO/CFO-oriented prompt that every provider receives. This guarantees the narrative style stays identical no matter which model generated it. + +Provider selection is resolved at runtime by `NewProvider()`: +1. If `LLM_PROVIDER` is set, that provider is used explicitly. +2. Otherwise, the first available API key wins, in the order **Gemini → Claude → OpenAI**. +3. If no key is found, `ErrNoProvider` is returned and the report command gracefully skips the AI section. + +Adding a fourth provider is a matter of creating one new file: implement the two methods on a struct, add a `newFooFromEnv()` constructor, and wire it into the switch in `provider.go`. The rest of the system — prompt, PDF rendering, CLI flags — stays untouched. + +## Architecture Decisions + +### Why not Cloud Custodian? +Cloud Custodian (Python, ~6k stars) is a mature policy engine: you write YAML rules like *"if an EC2 has no `Owner` tag, stop it"* and it **enforces** them across AWS/GCP/Azure. CloudOracle targets a different stage of the FinOps loop: + +- **Custodian**: governance and remediation — takes actions (stop, delete, tag, notify). Designed for platform teams running hundreds of policies in CI. +- **CloudOracle**: analysis and reporting — read-only, LLM-assisted narrative, PDF + dashboard. Designed for the conversation between engineering and finance, not for automated enforcement. + +The tools are complementary: Custodian is *what to enforce*, CloudOracle is *why it matters this month*. Read-only is intentional — it's safer to adopt in a new org and removes the "did this tool just delete my database?" objection at procurement time. + +### Why interfaces over inheritance for LLM providers +The `Provider` interface in `internal/llm` is intentionally minimal — just `GenerateSummary` and `Name`. Each provider (Gemini, Claude, OpenAI) is a fully independent implementation. Adding a fourth provider requires zero changes to existing code: write a new file, register it in `provider.go`, done. This is Go's structural typing at its best — no inheritance, no abstract base classes, no framework lock-in. + +### Why a shared Postgres container with TRUNCATE rather than a container per test +The integration helper at `internal/db/dbtest/postgres.go` boots one Postgres 16 container per test process and resets the schema with `TRUNCATE … RESTART IDENTITY CASCADE` between tests. The alternative — a fresh container per test — gives stronger isolation but pays ~3-5s of container-startup cost per case, which adds up fast as the suite grows. TRUNCATE on small tables runs in sub-millisecond, and all our tables are independent (no triggers, no shared sequences spanning tests), so the isolation guarantee is the same in practice. The whole integration suite (12 tests) runs in ~5 seconds total instead of ~60. + +If we ever add tests that need different schemas or different Postgres versions, we'd opt back into a per-test container for those specific cases — but as a default, sharing wins on speed. + +### Why retries live in a `RoundTripper` rather than around each `client.Do` +Every LLM provider eventually hits a 429 or a 5xx — Anthropic and OpenAI both rate-limit aggressively and both send `Retry-After` headers. Putting the retry loop inside the transport (`internal/llm/retry.go`) means **every** code path that issues an HTTP request gets retries automatically: the three providers today, and whatever future request paths we add (token-counting endpoints, streaming, file uploads). The alternative — wrapping each `client.Do` call — is more obvious but every new call site has to remember to wrap, and tests have to mock the wrapper. + +The transport buffers the request body once on entry and replays it via `req.Body` + `req.GetBody` on every attempt. It's safe because LLM POST bodies are tiny (a JSON prompt). It honors `Retry-After` (delta-seconds and HTTP-date forms) before falling back to exponential backoff with full jitter — full jitter (random in `[0, baseDelay * 2^attempt]`) is the AWS-recommended algorithm for distributed clients hitting the same endpoint, because it spreads retries evenly instead of producing thundering herds. Backoff waits respect the request context, so cancellation propagates cleanly mid-retry. + +### Why net/http directly instead of vendor SDKs +All three LLM providers are implemented with the standard library `net/http` package, no vendor SDKs. This keeps the dependency tree small (the entire project has fewer than 10 direct dependencies), makes the code portable, and forces explicit handling of errors, timeouts, and retries — all of which are usually hidden behind SDK abstractions. + +### Why deterministic rules first, LLMs second +The analyzer detects 80% of cloud waste using simple pure functions, before any LLM is involved. This is by design: deterministic rules are predictable, testable, free, and instant. LLMs are reserved for what they're actually good at — translating structured data into executive prose. Inverting this order (using LLMs to detect waste) would be slower, more expensive, and less reliable. + +### Why graceful degradation when no LLM is configured +If no API key is set, the report generates without the AI summary section instead of failing. This means anyone can clone the repo and run it immediately, and the same binary works in restricted environments where outbound API calls aren't allowed. + +### Why synthetic data instead of real AWS integration in v1 +Building the rule engine and report generator against a synthetic data generator allowed iteration without paying for AWS resources, without rate limits, and without coupling the early development to credentials. Real AWS integration is the next milestone, but the abstraction was earned by first solving the harder problem: detecting waste from any data source. + +### Why `errgroup` instead of raw goroutines for provider fan-out +Each real provider issues 4 independent API calls per scan (for example: EC2, RDS, EBS, Lambda on AWS). Running them sequentially meant the total scan time was the sum of the slowest region's latency for every service. Switching to `errgroup.WithContext` + a fixed-size `[][]shared.Resource` result slice (each goroutine owns its own index → no mutex) cut end-to-end scan time roughly in proportion to the number of services per provider. Returning `nil` from each goroutine after logging — instead of propagating errors — preserves the "log one failing service, keep the rest" contract the sequential version had, while giving the rest of the services a genuine chance to finish in parallel. + +### Why per-service `context.WithTimeout` rather than a single global deadline +A scan is only as fast as its slowest cloud API. Giving every service its own deadline (`CLOUD_SERVICE_TIMEOUT`, default 30s) means a misbehaving region bounds only itself — the other services still complete normally. A single global timeout would have cancelled every in-flight service the moment one hung, wasting the progress already made. + +### Why `log/slog` over `log.Printf` +Every warning now carries typed attributes (`provider=aws`, `service=EC2`, `error=...`) instead of being jammed into a free-form sprintf string. That makes logs grep-able, filterable by level, and — with `LOG_FORMAT=json` — ingestion-ready for Loki, ELK, or Cloud Logging without a log parser. `slog` is the standard library's answer to this, landed in Go 1.21, and needs zero external dependencies. + +### Why a central `config.Load()` over per-component `os.Getenv` +Previously every constructor reached into the environment on its own: `NewAWSProvider` for region/profile, `NewGCPProvider` for the project ID, each LLM constructor for its API key, `db.LoadConfigFromEnv` for credentials. That made the contract of each component implicit and the cost of testing high — you had to manipulate real env vars to rearrange behavior. Now `main()` calls `config.Load()` once, and every component receives its typed slice of the config as a parameter. Tests pass struct literals directly. + +### Why migrations run from the app at startup (not from `psql` scripts or a separate tool) +SQL files live in `internal/migrations/*.sql` and are baked into the binary with `go:embed`. On every boot — CLI command or `serve` — `main()` reads them in order and executes each against the pool. Because the statements use `CREATE TABLE/INDEX IF NOT EXISTS`, re-running is a no-op. Trade-offs vs. the alternatives: + +- **Postgres `docker-entrypoint-initdb.d` mount**: only runs the very first time a volume is created. If the DB already exists (prod restore, bind mount, CI cache), schema changes never land. Silent and dangerous. +- **A separate `migrate` CLI step**: adds a second binary and a deploy-ordering problem (app must not start before `migrate` succeeds). `depends_on` helps but doesn't eliminate it. +- **App-driven startup**: self-contained, idempotent, and works identically whether you boot the binary directly, with Docker Compose, in a test, or in production. The one binary knows how to set up its own schema. + +The one thing app-driven migrations don't give you out of the box is a version ledger (`schema_migrations` table) for tracking what's been applied. For a 2-file schema it's overkill; if the project grows a destructive migration (e.g. a column rename) we'd add one. Until then, `IF NOT EXISTS` is enough. + +## Lessons Learned + +Building this project surfaced a subtle but important bug that would have gone unnoticed without testing against real(istic) data: + +**The case-sensitivity trap:** The EC2 idle detection rule was comparing `r.Service != "EC2"` (uppercase), but the data generator and database stored services as `"ec2"` (lowercase). The rule silently passed over every EC2 instance without flagging a single one. The RDS, EBS, and Lambda rules all used lowercase correctly, making this inconsistency easy to miss during code review. It was only caught when analyzing output and noticing zero EC2 findings despite seeding idle instances. + +**Takeaway:** String comparison bugs are among the most common sources of silent failures in cloud tooling. Production systems use canonical enumerations or case-insensitive matching for exactly this reason. Finding this during development -- not after deployment -- is the difference between a tool that works and one that looks like it works. + +**The Strategy pattern for cloud providers:** The `CloudProvider` interface started as a formality — there was only the synthetic provider. But when adding real AWS support, the pattern paid for itself: `AWSProvider` and `SyntheticProvider` both satisfy the same interface, `factory.go` picks the right one from an env var, and `main.go` never knows which is active. The key insight was keeping the mapping logic (SDK types -> domain types) as pure functions separated from the API calls. This made it possible to unit test the field mapping with struct literals instead of mocking the entire AWS SDK — a pattern worth repeating for GCP and Azure providers. diff --git a/docs/cloud-providers.md b/docs/cloud-providers.md new file mode 100644 index 0000000..a0e4fe4 --- /dev/null +++ b/docs/cloud-providers.md @@ -0,0 +1,145 @@ +# Running against cloud providers + +CloudOracle supports four resource sources, selected at runtime with the `CLOUDORACLE_PROVIDER` env var: **synthetic** (default, no cloud account required), **aws**, **gcp**, **azure**. The analyzer, report, and dashboard work identically with all four — they only differ in where the resource inventory comes from. + +> **Tested status.** The **synthetic** and **AWS** providers have been exercised end-to-end against a live AWS account during development. The **GCP** and **Azure** providers are implemented against their respective SDKs with the same structure and the code compiles + unit-tests pass, **but they have not been run against live GCP / Azure subscriptions** because I don't have credentials for those clouds at the time of writing. Field-mapping tests use struct literals; the SDK call paths themselves are unverified. If you test either, please open an issue with what you find. + +## Synthetic (default, no setup) + +No credentials, no network calls — the app generates realistic EC2 / RDS / EBS / Lambda records locally. Ideal for demos, CI, and trying the dashboard in seconds. + +```bash +docker compose up --build +docker compose exec app /app/cloudoracle seed --count 120 +# open http://localhost:8080 +``` + +Tunables: +- `SYNTHETIC_COUNT` (default `100`) — how many resources to generate per `seed`. +- `SYNTHETIC_ACCOUNT` (default `synthetic-account`) — account ID baked into the records. + +The synthetic provider is what 99% of demos use. Everything else in the v1 guide — findings, exports, trend tracking, dashboard — works with synthetic data without any cloud credentials. + +## AWS (verified) + +**1. IAM user with read-only access.** In the AWS Console → IAM → Users → Create user, attach: +- `ReadOnlyAccess` +- `AWSBillingReadOnlyAccess` + +Grab the access key + secret. For least-privilege in production, the minimum set is: + +``` +ec2:DescribeInstances, ec2:DescribeVolumes +rds:DescribeDBInstances, rds:ListTagsForResource +lambda:ListFunctions, lambda:ListTags +ce:GetCostAndUsage +sts:GetCallerIdentity +``` + +**2. Configure a local profile.** In `~/.aws/credentials` (or `%USERPROFILE%\.aws\credentials` on Windows): + +```ini +[cloudoracle] +aws_access_key_id = AKIA... +aws_secret_access_key = ... +region = us-east-2 +``` + +The profile name `cloudoracle` and region `us-east-2` are the defaults. Override with `AWS_PROFILE=xxx` and `AWS_REGION=eu-west-1` if you use different names. + +**3. Run the app on the host** (so it can read `~/.aws/credentials`), pointing at the Postgres container: + +```bash +docker compose up -d postgres # DB only in Docker +export CLOUDORACLE_PROVIDER=aws +go run ./cmd/oracle seed # fetches real EC2/RDS/EBS/Lambda, upserts, snapshots +go run ./cmd/oracle analyze # runs rules → findings on real data +go run ./cmd/oracle serve --port 8080 # dashboard + API +``` + +The STS `GetCallerIdentity` call at startup validates credentials immediately — if the profile is misconfigured or keys are expired, you get the error right away instead of halfway through a scan. + +**Running inside Docker with AWS creds** (if you want `docker compose up app` against AWS), pass the creds as env vars to the `app` service in `docker-compose.yml`: + +```yaml +environment: + CLOUDORACLE_PROVIDER: aws + AWS_ACCESS_KEY_ID: ${AWS_ACCESS_KEY_ID} + AWS_SECRET_ACCESS_KEY: ${AWS_SECRET_ACCESS_KEY} + AWS_REGION: us-east-2 +``` + +The AWS SDK v2 auto-picks these up without needing a profile file. Recommended only for demos — for prod/CI, use IAM roles via instance metadata or IRSA on EKS, not static keys. + +**Cost:** `Describe*` / `List*` calls are free. A full `seed` against a typical account is ~5-10 API calls total. + +## GCP (untested against a live account) + +> Implemented but not verified against a real GCP project. + +Expected flow: + +1. Enable APIs on your project: Compute Engine, Cloud SQL Admin, Cloud Functions. +2. Set up Application Default Credentials: + - Dev: `gcloud auth application-default login` + - Prod: `GOOGLE_APPLICATION_CREDENTIALS=/path/to/sa.json` +3. Export `GOOGLE_CLOUD_PROJECT=your-project-id`. + +Required IAM roles (least privilege): + +``` +compute.instances.list, compute.disks.list +cloudsql.instances.list +cloudfunctions.functions.list +``` + +Then: + +```bash +docker compose up -d postgres +export CLOUDORACLE_PROVIDER=gcp +export GOOGLE_CLOUD_PROJECT=your-project-id +go run ./cmd/oracle seed +go run ./cmd/oracle serve --port 8080 +``` + +Since this path hasn't been exercised end-to-end, expect to debug the SDK call mapping on first run. + +## Azure (untested against a live account) + +> Implemented but not verified against a real Azure subscription. + +Expected flow: + +1. Export `AZURE_SUBSCRIPTION_ID=`. +2. Authenticate via one of: + - Dev: `az login` + - Service principal: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET` + - Managed Identity (when the app runs on Azure) + +The provider uses `DefaultAzureCredential`, which tries all methods in order. + +Required RBAC role: `Reader` on the subscription. Production scope: + +``` +Microsoft.Compute/virtualMachines/read +Microsoft.Compute/disks/read +Microsoft.Sql/servers/read, Microsoft.Sql/servers/databases/read +Microsoft.Web/sites/read +``` + +Then: + +```bash +docker compose up -d postgres +export CLOUDORACLE_PROVIDER=azure +export AZURE_SUBSCRIPTION_ID=00000000-0000-0000-0000-000000000000 +go run ./cmd/oracle seed +go run ./cmd/oracle serve --port 8080 +``` + +Same caveat as GCP: no live-account run has been done, so treat first execution as a validation exercise. + +--- + +For env var reference, see [configuration.md](configuration.md). diff --git a/docs/configuration.md b/docs/configuration.md new file mode 100644 index 0000000..5aa4c19 --- /dev/null +++ b/docs/configuration.md @@ -0,0 +1,33 @@ +# Configuration + +Reference for every environment variable CloudOracle reads. All vars are loaded once at startup by `internal/config.Load()` and injected into the cloud, LLM, and DB layers — no component reaches for `os.Getenv` on its own. + +| Variable | Default | Description | +|--------------|---------------|-----------------------| +| `CLOUDORACLE_PROVIDER` | `synthetic` | Cloud provider: `aws`, `gcp`, `azure`, or `synthetic` | +| `AWS_PROFILE` | `cloudoracle` | AWS shared-config profile to use | +| `AWS_REGION` | `us-east-2` | AWS region to scan | +| `GOOGLE_CLOUD_PROJECT` | _(unset)_ | GCP project ID (required when provider is `gcp`) | +| `AZURE_SUBSCRIPTION_ID` | _(unset)_ | Azure subscription ID (required when provider is `azure`) | +| `SYNTHETIC_COUNT` | `100` | Default number of synthetic resources to generate | +| `SYNTHETIC_ACCOUNT` | `synthetic-account` | Default account ID for synthetic data | +| `CLOUD_SERVICE_TIMEOUT` | `30s` | Per-service timeout for each cloud API call (Go duration string) | +| `DB_HOST` | `localhost` | PostgreSQL host | +| `DB_PORT` | `5432` | PostgreSQL port | +| `DB_USER` | `oracle` | Database user | +| `DB_PASSWORD`| `oracle_dev` | Database password | +| `DB_NAME` | `cloudoracle` | Database name | +| `LLM_PROVIDER` | _(auto)_ | Force a specific LLM provider: `gemini`, `claude`, or `openai`. If unset, auto-detects based on which API key is present. | +| `LLM_TIMEOUT` | `30s` | HTTP timeout for LLM API calls (Go duration string) | +| `LLM_MAX_RETRIES` | `3` | Number of retries on transient LLM failures (429, 5xx, network errors). Set to `0` to disable. | +| `LLM_BASE_DELAY` | `500ms` | Initial backoff between retries; doubles on each attempt with full jitter | +| `LLM_MAX_DELAY` | `30s` | Cap for the per-retry wait (also caps `Retry-After` headers) | +| `GEMINI_API_KEY` | _(unset)_ | API key for Google Gemini (`gemini-2.5-flash`) | +| `ANTHROPIC_API_KEY`| _(unset)_ | API key for Anthropic Claude (`claude-haiku-4-5`) | +| `OPENAI_API_KEY` | _(unset)_ | API key for OpenAI (`gpt-4o-mini`) | +| `LOG_LEVEL` | `info` | Log level: `debug`, `info`, `warn`, or `error` | +| `LOG_FORMAT` | `text` | Log format: `text` (human-readable) or `json` (structured) | + +--- + +For the design of the LLM provider layer and the analyzer rule engine, see [architecture.md](architecture.md). For per-cloud setup details (profiles, credentials, IAM scopes), see [cloud-providers.md](cloud-providers.md). diff --git a/docs/testing.md b/docs/testing.md new file mode 100644 index 0000000..f37f54f --- /dev/null +++ b/docs/testing.md @@ -0,0 +1,52 @@ +# Testing + +The project has two tiers of tests: + +- **Unit tests** (171, no external dependencies): pure-function tests for the analyzer, generator, LLM providers, LLM retries, PDF report, exporters, cloud mapping, real-provider fetchers, and central config validation. Run with `go test ./internal/...`. +- **Integration tests** (12, require Docker): exercise the real Postgres path via [testcontainers-go](https://golang.testcontainers.org/) — insert/upsert behavior, transaction rollback, snapshot aggregation, and a full end-to-end seed → analyze flow against a containerized Postgres 16. Run with `go test -tags=integration ./internal/db/ ./internal/e2e/`. + +Integration tests share a single Postgres container per process and `TRUNCATE … RESTART IDENTITY CASCADE` between cases — fast (sub-millisecond reset on small tables) and hermetic enough for our schema. The helper lives at `internal/db/dbtest/postgres.go` and is gated by the `integration` build tag, so the testcontainers dependency stays out of the unit-test compile path. If Docker isn't running, the helper calls `t.Skip` with a clear message rather than failing — running the binary without Docker just skips the integration cases. + +The CI workflow at `.github/workflows/test.yml` runs both tiers on every push and PR. GitHub-hosted Ubuntu runners have Docker preinstalled, so the integration job needs no extra service container. + +## Unit test coverage + +- **Per-rule tests**: each detection rule (`ec2-idle`, `rds-oversized`, `ebs-orphan`, `lambda-over-provisioned`) has happy-path, negative, and boundary tests. +- **Boundary testing**: CPU thresholds, age cutoffs, memory limits, and invocation counts are explicitly tested at their exact values to catch off-by-one errors. +- **Aggregator tests**: `Analyze` is tested for empty input, mixed input, false-positive prevention, and correct savings-descending ordering. +- **LLM provider tests**: all three providers (Gemini, Claude, OpenAI) are tested against mock HTTP servers using `httptest`, covering success responses, API errors, empty payloads, error fields, and context cancellation. +- **Provider factory tests**: auto-detection order (Gemini > Claude > OpenAI), explicit selection, missing keys, and unknown providers. +- **Prompt builder tests**: total calculations, severity breakdowns, service rollups, top-5 limiting, and empty input handling. +- **PDF generation tests**: file creation, AI summary inclusion/exclusion, empty findings, 100-finding page-break stress test, invalid paths, and all severity color codes. +- **Export tests**: JSON round-trip, CSV header + row layout, numeric formatting, RFC 4180 escaping of commas/quotes/newlines, and empty-findings handling for both formats. +- **Generator tests**: correct count, valid services/regions/types, non-negative costs, timestamp ordering, and service distribution. +- **Config tests**: default values, custom values, timeout parsing (valid and invalid durations), empty-env fallback, and DSN assembly. +- **Cloud mapping tests**: AWS SDK type → `shared.Resource` conversion with struct literals (no AWS calls, no credentials needed). +- **Real-provider fetcher tests**: every cloud provider (AWS, GCP, Azure) is exercised end-to-end against fake SDK clients — pagination exhaustion, per-service API errors, graceful degradation when one service fails, and edge cases (nil hardware profile on Azure VMs, nil settings on Cloud SQL, web apps mixed with function apps in the Azure `/sites` collection). +- **LLM retry tests**: the shared retry transport is verified against `httptest` servers — retries until success, respects `MaxRetries` cap, honors `Retry-After` headers, replays the request body on every attempt, retries transport-level errors (not just non-2xx), bails out on context cancellation, and returns immediately on non-retryable statuses (401, 4xx other than 408/429). +- **Config validation tests**: every invalid input shape (non-numeric port, out-of-range port, unknown enum value, negative integer, malformed Go duration, zero/negative duration), every cross-field rule (provider=gcp without project, provider=azure without subscription, LLM_PROVIDER set without matching API key), and the multi-error accumulator that lists all problems at once instead of failing on the first. + +## Integration test coverage + +- **Insert + upsert**: round-trip through a real Postgres, asserting that `ON CONFLICT DO UPDATE` updates the right columns (`monthly_cost`, `usage_metric`, `updated_at`) without overwriting `created_at`. +- **Transaction rollback**: a failing batch (one row that overflows `NUMERIC(10,2)`) rolls back the whole batch, leaving pre-existing rows untouched. +- **Snapshot aggregation**: a mixed set of resources across multiple `(account, service)` tuples produces exactly the expected snapshot rows, with correct counts and per-tuple cost totals. +- **Snapshot windowing**: the `--days` filter on the `trend` command actually filters via SQL — old snapshots are excluded from short windows and included in long ones. +- **End-to-end seed → analyze**: a deterministic resource set engineered to fire each rule once, inserted via `InsertResources`, read back via `ListResources`, and analyzed — asserts every rule fires exactly once and findings are sorted by potential savings descending. +- **End-to-end with synthetic data**: 50 random resources generated by `SyntheticProvider`, full round-trip through the DB, analyzer must produce *some* findings (the generator skews toward waste patterns). +- **Re-seed idempotency**: running insert three times on the same fixed-ID set ends with the same row count — proves the seed flow is safe to re-run on a schedule. + +## Running the suite + +```bash +# Unit tests (no Docker required) +go test ./internal/... + +# Integration tests (Docker must be running) +go test -tags=integration ./internal/db/ ./internal/e2e/ + +# Both, verbose +go test -tags=integration -v ./internal/... +``` + +All rules are pure functions (`Resource -> *Finding`), which makes them trivially testable without mocks, fixtures, or test databases. The code was designed to be testable from the start — not tested after the fact. diff --git a/docs/v1-guide.md b/docs/v1-guide.md new file mode 100644 index 0000000..c7c9833 --- /dev/null +++ b/docs/v1-guide.md @@ -0,0 +1,225 @@ +# v1 — Cloud cost audit + +Detailed guide for v1 audit mode: ingest live (or synthetic) cloud inventory into Postgres, run deterministic rules over it, and produce an executive PDF + dashboard with an LLM-narrated summary. + +## Why this project? + +Cloud waste is a real problem. Companies routinely overspend 20-30% on cloud infrastructure because nobody is watching the bill. CloudOracle demonstrates how to build a system that catches these issues automatically, using the same patterns that tools like AWS Trusted Advisor or Datadog Cloud Cost Management use internally. + +Unlike policy engines like **Cloud Custodian** that focus on automated enforcement, CloudOracle is an *analysis-first* tool built for FinOps visibility — combining deterministic rules with LLM-generated insights to produce executive-ready reports and dashboards. + +## Features + +- **Multi-cloud support** - Switch between AWS, GCP, Azure, and synthetic data via a single env var (`CLOUDORACLE_PROVIDER`) +- **Real AWS integration** - Fetches live EC2 instances, RDS databases, EBS volumes, and Lambda functions using AWS SDK v2 with STS credential validation +- **Real GCP integration** - Fetches Compute Engine VMs, Cloud SQL instances, Persistent Disks, and Cloud Functions using Google Cloud Go client libraries +- **Real Azure integration** - Fetches Virtual Machines, Azure SQL databases, Managed Disks, and Function Apps using Azure SDK for Go +- **Synthetic data generation** - Realistic resource simulation across EC2, RDS, EBS, and Lambda with configurable account IDs and resource counts +- **PostgreSQL persistence** - Transactional bulk inserts with upsert support (`ON CONFLICT DO UPDATE`) +- **Rule-based analysis engine** - Pluggable rules architecture where each rule is a pure function `Resource -> Finding` +- **4 detection rules**: + - `ec2-idle` - Flags instances with <5% CPU usage running for more than 7 days (HIGH severity) + - `rds-oversized` - Identifies RDS instances with <10% CPU utilization (MEDIUM severity) + - `ebs-orphan` - Detects unattached EBS volumes with zero usage (HIGH severity) + - `lambda-over-provisioned` - Finds Lambda functions with >1GB memory and low invocation counts (LOW severity) +- **Savings-ranked output** - Findings are sorted by potential monthly savings (highest first) +- **Service summary** - Aggregated view of findings and potential savings per AWS service +- **PDF report generation** - Professional executive-style PDF reports with severity-coded tables, recommended actions, and annual savings projections +- **LLM-powered executive summaries** - Pluggable provider layer (Gemini, Claude, OpenAI) that turns raw findings into a CTO/CFO-ready narrative embedded directly into the PDF report +- **Resilient LLM calls** - Shared `http.RoundTripper` retries 429s, 5xx, and network errors with exponential-backoff-with-full-jitter; honors the `Retry-After` header from Anthropic/OpenAI; cancellable via the request context +- **Cost trend tracking** - Automatic cost snapshots on every seed, with a `trend` command that shows per-service cost changes over time with directional arrows and percentage deltas +- **Parallel resource fetching** - Each provider fans out service calls (Compute / SQL / Disks / Functions) concurrently with `errgroup`, cutting scan time on accounts with many services +- **Per-service timeouts** - Every API call to a cloud service is wrapped in `context.WithTimeout` so a single slow region can't stall the entire scan +- **Structured logging (`log/slog`)** - Every log line carries typed attributes (`provider`, `service`, `error`, ...), with pluggable text or JSON output for ingestion into log aggregators +- **Centralized configuration** - A single `config.Load()` reads every env var up front and is injected into the cloud, LLM, and DB layers — no component reaches for `os.Getenv` on its own +- **Export findings to JSON or CSV** - Pipe analyzer output into downstream tooling (dashboards, spreadsheets, ticket systems) via `oracle export --format=json|csv`, writing to stdout or a file +- **Single-binary web dashboard** - React + Recharts UI embedded into the Go binary via `go:embed`; `oracle serve` boots API and dashboard on one port with no external assets required + +## Getting Started + +### Prerequisites + +- Go 1.25+ +- Docker & Docker Compose +- (Optional) AWS CLI configured with a `cloudoracle` profile for real AWS integration (see [cloud-providers.md](cloud-providers.md)) + +### 1. Start the stack + +Single command for the full demo (Postgres + API + embedded React dashboard): + +```bash +docker compose up --build +# → open http://localhost:8080 +``` + +Compose brings up two services: +- **postgres** — PostgreSQL 16 with a healthcheck; the app only starts once it responds to `pg_isready`. +- **app** — multi-stage build of the Go binary with the React bundle embedded via `go:embed`, exposed on `:8080`. + +The app auto-applies the SQL migrations in `internal/migrations/*.sql` on every startup (they're idempotent — `CREATE TABLE/INDEX IF NOT EXISTS`), so there's no separate migration step. To populate demo data: + +```bash +docker compose exec app /app/cloudoracle seed --count 120 +``` + +For local development without Docker you still need Postgres running somewhere; the easiest is `docker compose up -d postgres` and then run the Go binary on the host. Migrations run automatically whichever way you boot the app. + +### 2. Seed sample data + +```bash +go run cmd/oracle/main.go seed --account acc-001 --count 100 +``` + +### 3. List all resources + +```bash +go run cmd/oracle/main.go list +``` + +### 4. Run the cost analyzer + +```bash +go run cmd/oracle/main.go analyze +``` + +### 5. Generate a PDF report + +```bash +go run cmd/oracle/main.go report --output cloudoracle-report.pdf +``` + +This generates a professional PDF with: +- Executive summary (total findings, monthly/annual savings projections) +- Severity breakdown (HIGH / MEDIUM / LOW) +- Color-coded findings table with cost and savings per resource +- Recommended actions for each finding +- **AI-generated narrative** (when an LLM provider is configured) — 3-4 paragraph executive summary written for a CTO/CFO audience, focused on financial impact, highest-priority problems, and recommended next steps + +![CloudOracle PDF report example](../examplepdf.png) + +### 6. View cost trends + +Each `seed` automatically creates a cost snapshot. After running `seed` multiple times (on different days or with different data), view how costs change: + +```bash +go run cmd/oracle/main.go trend --days 30 +``` + +``` +Cost Trends (last 30 days, 3 snapshots) + +Service Oldest Latest Change +──────────────────────────────────────────────────────── +ebs $ 100.00 $ 90.00 -10.00 (-10.0%) ↓ +ec2 $ 460.00 $ 510.00 +50.00 (+10.9%) ↑ +lambda $ 2.50 $ 3.10 +0.60 (+24.0%) ↑ +rds $ 180.00 $ 195.00 +15.00 (+8.3%) ↑ +──────────────────────────────────────────────────────── +Total $ 742.50 $ 798.10 +55.60 (+7.5%) ↑ +``` + +### 7. Export findings to JSON or CSV + +Run the analyzer and pipe its findings into another tool — a dashboard, a spreadsheet, a ticketing system. By default, the exporter writes to stdout so it composes naturally with shell pipelines; pass `--output` to write to a file. + +```bash +# Pretty-printed JSON to stdout +go run cmd/oracle/main.go export --format=json + +# CSV to a file (header row + one finding per row) +go run cmd/oracle/main.go export --format=csv --output findings.csv + +# Pipe straight into jq +go run cmd/oracle/main.go export --format=json | jq '.[] | select(.Severity == "High")' +``` + +The JSON output is an array of `Finding` objects. The CSV output has a fixed header: `resource_id, service, resource_type, region, rule, severity, monthly_cost, monthly_savings, description, recommendation`. Numeric fields are formatted with two decimals. Commas, quotes, and newlines in descriptions are escaped per RFC 4180 — the output is safe to open in Excel or parse with any standard CSV library. + +### 8. Web dashboard + +CloudOracle ships a React + Recharts dashboard that reads the same database as the CLI. There are two workflows: + +**Production / demo — one binary, one command.** The Go binary embeds the compiled frontend via `go:embed`, so after a single `npm run build` the whole stack (API + UI) is served on one port. + +```bash +# Build the React bundle into internal/api/dist (go:embed target) +cd web +npm install # first time only +npm run build +cd .. + +# Build the self-contained binary and run it +go build -o cloudoracle ./cmd/oracle +./cloudoracle serve --port 8080 +# → open http://localhost:8080 +``` + +The binary is fully self-contained. Copy the single file (`cloudoracle` / `cloudoracle.exe`) to any machine, point it at a reachable Postgres via `DB_*` env vars, and the dashboard loads. No `web/` directory needed at runtime. + +**Development — hot reload.** During iteration, run the API and the Vite dev server separately so you get HMR on React changes without rebuilding Go: + +```bash +# Terminal 1 — API on :8080 +go run ./cmd/oracle serve --port 8080 + +# Terminal 2 — Vite on :5173 with /api/* proxied to :8080 +cd web +npm run dev +# → open http://localhost:5173 +``` + +> **Note:** `go:embed` requires `internal/api/dist/` to exist at compile time. The repo commits a `.gitkeep` so `go build` always works — if you haven't run `npm run build`, visiting the root route shows a "Dashboard bundle not found" page with instructions. The JSON API at `/api/*` works either way. + +### 9. (Optional) Enable the LLM-powered executive summary + +The `report` command will automatically call an LLM provider if any supported API key is present in the environment. No flags required — just export a key and run `report` again. If no key is configured, the PDF is still generated without the narrative section. + +| Provider | Env variable | Default model | +|----------|---------------------|----------------------| +| Gemini | `GEMINI_API_KEY` | `gemini-2.5-flash` | +| Claude | `ANTHROPIC_API_KEY` | `claude-haiku-4-5` | +| OpenAI | `OPENAI_API_KEY` | `gpt-4o-mini` | + +```bash +# Pick one +export GEMINI_API_KEY=... +export ANTHROPIC_API_KEY=... +export OPENAI_API_KEY=... + +# Force a specific provider when multiple keys are present +export LLM_PROVIDER=claude # gemini | claude | openai + +go run cmd/oracle/main.go report --output cloudoracle-report.pdf +``` + +Auto-detection order when `LLM_PROVIDER` is unset: **Gemini → Claude → OpenAI**. The first key found wins. LLM failures (missing key, network error, API error) are logged but never block PDF generation — the report falls back to the deterministic summary. + +## Sample Output + +![CloudOracle analyze output](../example.png) + +``` +CloudOracle found 10 problems with potential monthly savings of $680.00 + + 1. [HIGH] EC2 i-3592027508 (c5.xlarge) has average CPU usage of 2.8%. Active for 325 days. + Consider shutting down or terminating this instance. + Monthly Cost: $125.00 | Potential Monthly Savings: $125.00 + + 2. [HIGH] EBS vol-fcebf509 (gp3-1000GB) is not attached to any instance. Orphaned for 60 days. + Create a backup snapshot and delete the volume. + Monthly Cost: $100.00 | Potential Monthly Savings: $100.00 + + 3. [MEDIUM] RDS db-f7fdfc2b (db.t3.micro) has average CPU usage of 7.1%. Likely oversized. + Consider downgrading to the next smaller RDS instance tier. + Monthly Cost: $15.00 | Potential Monthly Savings: $7.50 + ... + +Summary per service + ec2 -> 5 problems, save: $460.00/month + ebs -> 3 problems, save: $205.00/month + rds -> 2 problems, save: $15.00/month +``` + +--- + +For cloud provider setup (AWS, GCP, Azure), see [cloud-providers.md](cloud-providers.md). For env var reference, see [configuration.md](configuration.md). diff --git a/docs/v2-guide.md b/docs/v2-guide.md new file mode 100644 index 0000000..2149394 --- /dev/null +++ b/docs/v2-guide.md @@ -0,0 +1,131 @@ +# v2 — Terraform PR cost analysis + +CloudOracle parses a Terraform plan, prices every changing resource against the live AWS Pricing API, and renders a PR comment that looks like this: + +> ## 💰 Cloud Cost Impact +> **Net monthly change: +$389.35** 🔴 +> +> The Aurora cluster instance dominates this change at ~$204/month — over half the total. If this is intended for a non-production environment, an `aws_db_instance` running `db.t3.medium` would land around $60/mo for similar functional coverage. Note that data-processing charges for the NAT gateway are not modeled in this estimate. +> +> ### Top movers by cost impact +> | Resource | Action | Δ Monthly | Confidence | +> | -------- | ------ | --------- | ---------- | +> | `aws_rds_cluster_instance.aurora` | 🆕 create | +$204.40 | low | +> | `aws_db_instance.db` | 🆕 create | +$71.36 | low | +> | `aws_instance.web` | 🆕 create | +$64.74 | low | +> +> _
Full breakdown · Assumptions and caveats
_ +> +> Generated by [CloudOracle](...) · Confidence: **low** +> +> `` + +The HTML marker at the end is what makes re-renders safe: subsequent pushes update that comment in place instead of stacking new ones. + +## Quick start: GitHub Action + +Drop this into `.github/workflows/cost-comment.yml` in any repo with Terraform: + +```yaml +name: Terraform Plan Cost Comment +on: + pull_request: + paths: ['**.tf'] + +permissions: + pull-requests: write + id-token: write + contents: read + +jobs: + cost: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - uses: aws-actions/configure-aws-credentials@v4 + with: + role-to-assume: arn:aws:iam::123456789012:role/GitHubActionsCloudOracle + aws-region: us-east-2 + - uses: hashicorp/setup-terraform@v3 + - run: terraform init && terraform plan -out=tf.plan + - run: terraform show -json tf.plan > tf-plan.json + - uses: Cro22/CloudOracle@v2.0.0 + with: + plan-file: tf-plan.json + env: + ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }} +``` + +Two reference workflows live under [`.github/examples/`](../.github/examples) — one with OIDC + LLM, one with static AWS access keys + no-LLM fallback. The `.github/examples/README.md` covers IAM trust policies, the minimum permission set, and how to wire the LLM secret. + +## Action inputs + +| Input | Required | Default | Notes | +|-------|----------|---------|-------| +| `plan-file` | yes | — | Path to `terraform show -json` output. | +| `region` | no | `us-east-2` | AWS region the Pricing API queries against. | +| `output-file` | no | `` | Also write the rendered Markdown to a file (useful for artefact upload). | +| `marker` | no | `cloudoracle-pr-v1` | HTML-comment substring used for upsert. Bump if you change the comment template. | +| `no-llm` | no | `false` | Force the deterministic templated narrative even with LLM keys configured. | +| `github-token` | no | `${{ github.token }}` | Used to post the comment; needs `pull-requests: write`. | + +The Action only posts when `GITHUB_EVENT_NAME` is `pull_request` or `pull_request_target`; on other triggers it renders to stdout (or `output-file`) and exits, with a `::notice::` log line explaining why. + +## Quick start: CLI + +The same workflow runs locally without any GitHub plumbing — useful for testing, debugging, or iterating on the prompt: + +```bash +# Just render to stdout (no AWS creds needed for the templated narrative) +go run ./cmd/oracle pr-check \ + --plan-file=internal/iac/testdata/plan_simple_create.json \ + --no-llm + +# Render against a real plan + AWS Pricing API +terraform show -json my.tfplan > plan.json +go run ./cmd/oracle pr-check --plan-file=plan.json --region=us-east-2 + +# Render and post (or update) the comment on PR #11 +go run ./cmd/oracle pr-check \ + --plan-file=plan.json \ + --post --repo=Cro22/CloudOracle --pr=11 \ + --token=$GITHUB_TOKEN +``` + +Full flag listing: + +| Flag | Default | Notes | +|------|---------|-------| +| `--plan-file` | — | Required. Path to JSON plan. | +| `--region` | `us-east-2` | AWS region for pricing. | +| `--output` | _(stdout)_ | File to also write the Markdown to; `-` or empty means stdout. | +| `--no-llm` | `false` | Force templated narrative. | +| `--post` | `false` | Post / upsert the comment via the GitHub API. Requires `--repo` and `--pr`. | +| `--repo` | — | `owner/name` form. Required with `--post`. | +| `--pr` | `0` | PR number. Required with `--post`. | +| `--token` | _(env)_ | Falls back to `$GITHUB_TOKEN` when empty. | +| `--marker` | `cloudoracle-pr-v1` | HTML comment marker for upsert. | + +Exit codes are differentiated so the Action wrapper can produce sensible CI error messages: + +| Code | Meaning | +|------|---------| +| 0 | Success. | +| 1 | Input error (missing/invalid flag, plan file unreadable). | +| 2 | Pricing error (AWS Pricing API rejected the request). | +| 3 | Output error (couldn't write `--output` path). | +| 4 | GitHub error (post/update failed). | + +## LLM narrative behavior + +The PR narrative is generated by the same provider layer as v1 (Gemini / Claude / OpenAI), so the same env-var conventions apply: set `ANTHROPIC_API_KEY`, `GEMINI_API_KEY`, or `OPENAI_API_KEY`, optionally pin one with `LLM_PROVIDER`. With no key configured, the comment falls back silently to a deterministic templated narrative — the comment still posts, just less narrated. + +The v2 prompt (in `internal/diff/narrative.go`) is purpose-built for PR review tone: 1–3 sentences, identifies the dominant cost driver, optionally suggests an architectural alternative (never a billing-model swap), avoids cheerleading. Caveats are grouped by resource so the model can't accidentally attribute one resource's note to another (e.g. mistakenly claiming the database carries the NAT gateway's data-processing charges — a real bug observed during prompt development that the grouping prevents). + +## Supported resources + +EC2 instances (Linux on-demand compute + root EBS), EBS volumes (gp2/gp3/io1/io2/st1/sc1), RDS instances (single-AZ + Aurora cluster instances), Lambda functions (cold-start estimate), NAT gateways (hourly only). Unsupported types appear in the rendered comment under "Skipped" with a one-line reason — they don't fail the run. Adding a new resource type is one new file under `internal/pricing/` plus a switch case in `estimator.go`. + +--- + +For v2 internal package layout and data flow, see [architecture.md](architecture.md). For env var reference, see [configuration.md](configuration.md). From 53c3ad19adcafe7c5990b9c7d3331a2d23b38f8b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jesus=20Nu=C3=B1ez?= Date: Sun, 17 May 2026 23:34:43 -0400 Subject: [PATCH 02/18] feat(api): authenticated /api/v1 cost endpoints for the insights agent MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Part A of milestone 8.1: expose CloudOracle's cost data over an HTTP API the upcoming Python agent (insights-agent/) can call as a LangGraph tool. Why two endpoints instead of just one: the agent's reasoning improves when it can both compare providers (cost-summary) and drill into a single provider's service mix (cost-by-service). The /api/v1/* prefix keeps the dashboard's existing /api/* routes untouched so the embedded React UI is not coupled to the agent's auth model — only v1 requires X-API-Key, v0 dashboard endpoints stay open as before. Data semantics: there is no Cost Explorer / Billing integration yet, so the v1 endpoints approximate period spend from the cost_snapshots table (average projected monthly rate per (account, service), scaled by days/30). Every response carries data_source="snapshots_approximation" and a human-readable note so downstream clients can surface the disclaimer to the user. Real CUR ingestion is a follow-up. Internals: - Added APIConfig (CLOUDORACLE_API_KEY / _API_PORT / _API_SHUTDOWN_TIMEOUT) - New db.ListSnapshotsInRange (inclusive [start, end]) - authMiddleware (constant-time compare) + requestIDMiddleware - apiData interface — single data dep for both v0 dashboard and v1 handlers, replacing scattered db.* calls so tests can run without Postgres. Coverage on internal/api/ is now 86%. - Graceful shutdown via Server.Run honouring SIGINT/SIGTERM with a configurable timeout; runServe refuses to start without an API key. Co-Authored-By: Claude Opus 4.7 (1M context) --- cmd/oracle/main.go | 25 +- internal/api/cost_handlers.go | 354 +++++++++++++++++ internal/api/cost_handlers_test.go | 449 ++++++++++++++++++++++ internal/api/dashboard_handlers_test.go | 250 ++++++++++++ internal/api/middleware.go | 91 ++++- internal/api/middleware_test.go | 146 +++++++ internal/api/server.go | 105 ++++- internal/config/config.go | 17 + internal/config/config_test.go | 46 +++ internal/db/snapshots.go | 30 ++ internal/db/snapshots_integration_test.go | 50 +++ 11 files changed, 1542 insertions(+), 21 deletions(-) create mode 100644 internal/api/cost_handlers.go create mode 100644 internal/api/cost_handlers_test.go create mode 100644 internal/api/dashboard_handlers_test.go create mode 100644 internal/api/middleware_test.go diff --git a/cmd/oracle/main.go b/cmd/oracle/main.go index 3b70e3d..faeb32f 100644 --- a/cmd/oracle/main.go +++ b/cmd/oracle/main.go @@ -22,8 +22,10 @@ import ( "io" "log/slog" "os" + "os/signal" "sort" "strings" + "syscall" "time" ) @@ -84,7 +86,7 @@ func main() { case "export": runExport(ctx, pool, os.Args[2:]) case "serve": - runServe(pool, os.Args[2:]) + runServe(ctx, pool, cfg, os.Args[2:]) default: fmt.Printf("Unknown command: %s\n", os.Args[1]) printUsage() @@ -675,18 +677,31 @@ func renderPRCheckMarkdown(ctx context.Context, cfg config.Config, d diff.CostDi return diff.RenderMarkdownWithLLM(ctx, d, provider) } -func runServe(pool *db.Pool, args []string) { +func runServe(ctx context.Context, pool *db.Pool, cfg config.Config, args []string) { fs := flag.NewFlagSet("serve", flag.ExitOnError) - port := fs.String("port", "8080", "Port to listen on") + port := fs.String("port", cfg.API.Port, "Port to listen on") if err := fs.Parse(args); err != nil { slog.Error("failed to parse flags", "error", err) os.Exit(1) } - server := api.NewServer(pool) + // The v1 endpoints are gated by X-API-Key; refusing to start when the + // key is unset is preferable to silently exposing the dashboard + // endpoints with the v1 routes returning 401 — operators would assume + // "it's running" and miss the misconfiguration. + if cfg.API.Key == "" { + slog.Error("CLOUDORACLE_API_KEY is required to start the API server") + os.Exit(1) + } + + runCtx, stop := signal.NotifyContext(ctx, os.Interrupt, syscall.SIGTERM) + defer stop() + + server := api.NewServer(pool, cfg.API) slog.Info("Dashboard available", "url", fmt.Sprintf("http://localhost:%s", *port)) - if err := server.Start(":" + *port); err != nil { + if err := server.Run(runCtx, ":"+*port, cfg.API.ShutdownTimeout); err != nil { slog.Error("API server failed", "error", err) os.Exit(1) } + slog.Info("API server stopped cleanly") } diff --git a/internal/api/cost_handlers.go b/internal/api/cost_handlers.go new file mode 100644 index 0000000..af48e88 --- /dev/null +++ b/internal/api/cost_handlers.go @@ -0,0 +1,354 @@ +package api + +import ( + "CloudOracle/internal/db" + "CloudOracle/internal/shared" + "context" + "errors" + "fmt" + "math" + "net/http" + "sort" + "strings" + "time" +) + +// dataSourceLabel and dataSourceNote document the contract of the v1 cost +// endpoints. CloudOracle's `cost_snapshots` table records each provider's +// *projected monthly cost rate* at snapshot time — not the historical spend +// that a real Billing / Cost Explorer integration would surface. Until that +// integration lands (sub-hito 8.2+), the v1 endpoints expose this +// approximation explicitly in every response so downstream agents and +// dashboards can present the right disclaimer to the user. +const ( + dataSourceLabel = "snapshots_approximation" + dataSourceNote = "Costs are approximated from CloudOracle cost snapshots, " + + "not from a billing / cost-explorer integration. Values reflect the " + + "average projected monthly cost rate observed in the period, scaled " + + "to the period length." +) + +// apiData is the single data dependency the handlers reach through. +// Defining it here (rather than scattering db.* calls across handlers) +// keeps the test path simple — a fake apiData avoids spinning up Postgres +// just to verify request parsing, response shaping, and aggregation. +// +// The interface intentionally mirrors the methods the handlers actually +// need; widening it later is cheap because there is exactly one production +// implementation (pgxAdapter) and one test fake. +type apiData interface { + ListResources(ctx context.Context) ([]shared.Resource, error) + ListTrends(ctx context.Context, days int) ([]db.Trend, error) + ListSnapshotsInRange(ctx context.Context, start, end time.Time) ([]db.Snapshot, error) +} + +// pgxAdapter is the production implementation of apiData. It is a thin +// shim — every method delegates to its db.* counterpart. Tests use a +// fake instead, with the pool stayed nil; the production path is the only +// one that ever calls these methods. +type pgxAdapter struct{ pool *db.Pool } + +func (p *pgxAdapter) ListResources(ctx context.Context) ([]shared.Resource, error) { + return db.ListResources(ctx, p.pool) +} + +func (p *pgxAdapter) ListTrends(ctx context.Context, days int) ([]db.Trend, error) { + return db.ListTrends(ctx, p.pool, days) +} + +func (p *pgxAdapter) ListSnapshotsInRange(ctx context.Context, start, end time.Time) ([]db.Snapshot, error) { + return db.ListSnapshotsInRange(ctx, p.pool, start, end) +} + +type periodDTO struct { + Start string `json:"start"` + End string `json:"end"` +} + +type providerSummaryDTO struct { + TotalUSD float64 `json:"total_usd"` + Currency string `json:"currency"` +} + +type costSummaryResponse struct { + Period periodDTO `json:"period"` + Providers map[string]providerSummaryDTO `json:"providers"` + GrandTotalUSD float64 `json:"grand_total_usd"` + GeneratedAt time.Time `json:"generated_at"` + DataSource string `json:"data_source"` + Note string `json:"note"` +} + +func (s *Server) handleCostSummary(w http.ResponseWriter, r *http.Request) { + q := r.URL.Query() + start, end, err := parseDateRange(q.Get("start"), q.Get("end")) + if err != nil { + writeAPIError(w, http.StatusBadRequest, err.Error(), "invalid_date_range") + return + } + + filter, err := parseProvidersFilter(q.Get("providers")) + if err != nil { + writeAPIError(w, http.StatusBadRequest, err.Error(), "invalid_provider") + return + } + + snapshots, err := s.data.ListSnapshotsInRange(r.Context(), start, end) + if err != nil { + writeAPIError(w, http.StatusInternalServerError, + "failed to load snapshots: "+err.Error(), "snapshot_query_failed") + return + } + + days := periodDays(start, end) + perProvider := aggregateByProvider(snapshots, days, filter) + + resp := costSummaryResponse{ + Period: periodDTO{Start: start.Format(time.DateOnly), End: end.Format(time.DateOnly)}, + Providers: make(map[string]providerSummaryDTO, len(perProvider)), + GeneratedAt: time.Now().UTC(), + DataSource: dataSourceLabel, + Note: dataSourceNote, + } + + var total float64 + for p, v := range perProvider { + resp.Providers[p] = providerSummaryDTO{TotalUSD: roundCents(v), Currency: "USD"} + total += v + } + resp.GrandTotalUSD = roundCents(total) + + writeJSON(w, http.StatusOK, resp) +} + +type serviceCostDTO struct { + Name string `json:"name"` + TotalUSD float64 `json:"total_usd"` + Percentage float64 `json:"percentage"` +} + +type costByServiceResponse struct { + Period periodDTO `json:"period"` + Provider string `json:"provider"` + Services []serviceCostDTO `json:"services"` + TotalUSD float64 `json:"total_usd"` + GeneratedAt time.Time `json:"generated_at"` + DataSource string `json:"data_source"` + Note string `json:"note"` +} + +func (s *Server) handleCostByService(w http.ResponseWriter, r *http.Request) { + q := r.URL.Query() + start, end, err := parseDateRange(q.Get("start"), q.Get("end")) + if err != nil { + writeAPIError(w, http.StatusBadRequest, err.Error(), "invalid_date_range") + return + } + + provider := strings.ToLower(strings.TrimSpace(q.Get("provider"))) + if !validProvider(provider) { + writeAPIError(w, http.StatusBadRequest, + "provider query param is required and must be one of aws, gcp, azure", + "invalid_provider") + return + } + + top := parseIntOr(q.Get("top"), 10) + // Treat any non-positive or absurdly large top as the default. The cap + // of 1000 is far above the number of services any provider has, but + // bounds the response shape so a curious caller can't ask for 1B items. + if top <= 0 || top > 1000 { + top = 10 + } + + snapshots, err := s.data.ListSnapshotsInRange(r.Context(), start, end) + if err != nil { + writeAPIError(w, http.StatusInternalServerError, + "failed to load snapshots: "+err.Error(), "snapshot_query_failed") + return + } + + days := periodDays(start, end) + perService := aggregateByService(snapshots, days, provider) + + var total float64 + for _, v := range perService { + total += v + } + + services := make([]serviceCostDTO, 0, len(perService)) + for name, cost := range perService { + pct := 0.0 + if total > 0 { + pct = roundCents(cost / total * 100) + } + services = append(services, serviceCostDTO{ + Name: name, + TotalUSD: roundCents(cost), + Percentage: pct, + }) + } + // Sort by cost desc, tiebreak by name asc — deterministic order so + // callers (and tests) don't have to deal with map iteration randomness. + sort.Slice(services, func(i, j int) bool { + if services[i].TotalUSD != services[j].TotalUSD { + return services[i].TotalUSD > services[j].TotalUSD + } + return services[i].Name < services[j].Name + }) + if len(services) > top { + services = services[:top] + } + + resp := costByServiceResponse{ + Period: periodDTO{Start: start.Format(time.DateOnly), End: end.Format(time.DateOnly)}, + Provider: provider, + Services: services, + TotalUSD: roundCents(total), + GeneratedAt: time.Now().UTC(), + DataSource: dataSourceLabel, + Note: dataSourceNote, + } + writeJSON(w, http.StatusOK, resp) +} + +// aggregateByProvider implements the snapshots approximation: +// +// 1. Group snapshots by (account, service). +// 2. For each group, compute the average total_monthly_cost across the +// snapshots that fell in the period. +// 3. Map each (account, service) to a provider via providerForServiceAccount +// (the same mapping the dashboard summary uses). +// 4. Scale the per-group monthly rate to the period length: avg × days / 30. +// +// The optional filter is treated as a whitelist when non-nil; an empty map +// is also "no filter" — see parseProvidersFilter. +func aggregateByProvider(snapshots []db.Snapshot, days int, filter map[string]bool) map[string]float64 { + perAS := aggregateMonthlyByAccountService(snapshots) + scale := float64(days) / 30.0 + result := make(map[string]float64) + for k, avgMonthly := range perAS { + provider := providerForServiceAccount(k.service, k.account) + if len(filter) > 0 && !filter[provider] { + continue + } + result[provider] += avgMonthly * scale + } + return result +} + +// aggregateByService is the service-level counterpart: it returns per-service +// period totals for the requested provider. Unlike aggregateByProvider it +// hard-filters on the provider (the v1 endpoint requires `provider` to be +// set to a specific value), so no whitelist map is needed. +func aggregateByService(snapshots []db.Snapshot, days int, provider string) map[string]float64 { + perAS := aggregateMonthlyByAccountService(snapshots) + scale := float64(days) / 30.0 + result := make(map[string]float64) + for k, avgMonthly := range perAS { + if providerForServiceAccount(k.service, k.account) != provider { + continue + } + result[k.service] += avgMonthly * scale + } + return result +} + +type accountServiceKey struct { + account string + service string +} + +// aggregateMonthlyByAccountService averages total_monthly_cost across every +// snapshot for each (account, service) tuple. Snapshots taken close together +// in time will have similar values, so the average is a reasonable point +// estimate of the period's monthly cost rate. +func aggregateMonthlyByAccountService(snapshots []db.Snapshot) map[accountServiceKey]float64 { + type acc struct { + sum float64 + count int + } + totals := make(map[accountServiceKey]*acc) + for _, s := range snapshots { + k := accountServiceKey{s.AccountID, s.Service} + if totals[k] == nil { + totals[k] = &acc{} + } + totals[k].sum += s.TotalMonthlyCost + totals[k].count++ + } + out := make(map[accountServiceKey]float64, len(totals)) + for k, a := range totals { + if a.count == 0 { + continue + } + out[k] = a.sum / float64(a.count) + } + return out +} + +// parseDateRange validates start/end query params. Both are required and +// must be ISO YYYY-MM-DD; end must not be before start. Returns the parsed +// times with `end` advanced to 23:59:59.999999999 of that day so the SQL +// BETWEEN includes the closing day in full — the v1 contract is inclusive. +func parseDateRange(startRaw, endRaw string) (time.Time, time.Time, error) { + if startRaw == "" || endRaw == "" { + return time.Time{}, time.Time{}, errors.New("start and end query params are required (YYYY-MM-DD)") + } + start, err := time.Parse(time.DateOnly, startRaw) + if err != nil { + return time.Time{}, time.Time{}, fmt.Errorf("start=%q is not a valid date (expected YYYY-MM-DD)", startRaw) + } + end, err := time.Parse(time.DateOnly, endRaw) + if err != nil { + return time.Time{}, time.Time{}, fmt.Errorf("end=%q is not a valid date (expected YYYY-MM-DD)", endRaw) + } + if end.Before(start) { + return time.Time{}, time.Time{}, fmt.Errorf("end=%s is before start=%s", endRaw, startRaw) + } + end = end.Add(24*time.Hour - time.Nanosecond) + return start, end, nil +} + +func parseProvidersFilter(raw string) (map[string]bool, error) { + if raw == "" { + return nil, nil + } + parts := strings.Split(raw, ",") + out := make(map[string]bool, len(parts)) + for _, p := range parts { + p = strings.ToLower(strings.TrimSpace(p)) + if p == "" { + continue + } + if !validProvider(p) { + return nil, fmt.Errorf("providers=%q contains invalid provider %q (must be aws, gcp, or azure)", raw, p) + } + out[p] = true + } + return out, nil +} + +func validProvider(p string) bool { + switch p { + case "aws", "gcp", "azure": + return true + } + return false +} + +// periodDays returns the inclusive day span of the period. We use it to +// scale the monthly rate to the period length. A start/end on the same +// calendar day yields 1; the function never returns < 1, so callers can +// divide safely. +func periodDays(start, end time.Time) int { + days := int(end.Sub(start).Hours()/24) + 1 + if days < 1 { + return 1 + } + return days +} + +func roundCents(v float64) float64 { + return math.Round(v*100) / 100 +} diff --git a/internal/api/cost_handlers_test.go b/internal/api/cost_handlers_test.go new file mode 100644 index 0000000..e79bd40 --- /dev/null +++ b/internal/api/cost_handlers_test.go @@ -0,0 +1,449 @@ +package api + +import ( + "CloudOracle/internal/db" + "CloudOracle/internal/shared" + "context" + "encoding/json" + "errors" + "net/http" + "net/http/httptest" + "strings" + "testing" + "time" +) + +// fakeAPIData is the in-memory stand-in for the apiData interface used +// across api unit tests. Each method has a corresponding *Err field so an +// individual test can simulate a failure from one data path without +// affecting the others. +type fakeAPIData struct { + resources []shared.Resource + resourcesErr error + + trends []db.Trend + trendsErr error + + snapshots []db.Snapshot + snapshotsErr error + + gotStart time.Time + gotEnd time.Time + gotDays int +} + +func (f *fakeAPIData) ListResources(_ context.Context) ([]shared.Resource, error) { + return f.resources, f.resourcesErr +} + +func (f *fakeAPIData) ListTrends(_ context.Context, days int) ([]db.Trend, error) { + f.gotDays = days + return f.trends, f.trendsErr +} + +func (f *fakeAPIData) ListSnapshotsInRange(_ context.Context, start, end time.Time) ([]db.Snapshot, error) { + f.gotStart = start + f.gotEnd = end + return f.snapshots, f.snapshotsErr +} + +const testAPIKey = "test-key-abc123" + +func newCostTestServer(data apiData) *Server { + return newTestServer(data, testAPIKey) +} + +func doGet(t *testing.T, srv *Server, path string, withAuth bool) *httptest.ResponseRecorder { + t.Helper() + req := httptest.NewRequest(http.MethodGet, path, nil) + if withAuth { + req.Header.Set("X-API-Key", testAPIKey) + } + rec := httptest.NewRecorder() + srv.Handler().ServeHTTP(rec, req) + return rec +} + +// snapshotsAprilEightySplit fixture: two providers (AWS via ec2 + rds, GCP +// via compute) so we can assert per-provider aggregation. Two snapshots per +// (account, service) — slightly different costs so the average is meaningful +// rather than coincidental. +func snapshotsAprilEightySplit() []db.Snapshot { + return []db.Snapshot{ + // AWS / ec2: avg 100. acc-aws. + {TakenAt: mustTime("2026-04-05T10:00:00Z"), AccountID: "acc-aws", Service: "ec2", ResourceCount: 5, TotalMonthlyCost: 90}, + {TakenAt: mustTime("2026-04-20T10:00:00Z"), AccountID: "acc-aws", Service: "ec2", ResourceCount: 5, TotalMonthlyCost: 110}, + // AWS / rds: avg 50. acc-aws. + {TakenAt: mustTime("2026-04-05T10:00:00Z"), AccountID: "acc-aws", Service: "rds", ResourceCount: 1, TotalMonthlyCost: 40}, + {TakenAt: mustTime("2026-04-20T10:00:00Z"), AccountID: "acc-aws", Service: "rds", ResourceCount: 1, TotalMonthlyCost: 60}, + // GCP / compute: avg 200. acc-gcp. + {TakenAt: mustTime("2026-04-05T10:00:00Z"), AccountID: "acc-gcp", Service: "compute", ResourceCount: 3, TotalMonthlyCost: 180}, + {TakenAt: mustTime("2026-04-20T10:00:00Z"), AccountID: "acc-gcp", Service: "compute", ResourceCount: 3, TotalMonthlyCost: 220}, + } +} + +func mustTime(s string) time.Time { + t, err := time.Parse(time.RFC3339, s) + if err != nil { + panic(err) + } + return t +} + +func TestCostSummary_HappyPath(t *testing.T) { + reader := &fakeAPIData{snapshots: snapshotsAprilEightySplit()} + srv := newCostTestServer(reader) + + rec := doGet(t, srv, "/api/v1/cost-summary?start=2026-04-01&end=2026-04-30", true) + + if rec.Code != http.StatusOK { + t.Fatalf("status = %d, want 200; body=%s", rec.Code, rec.Body.String()) + } + if got := rec.Header().Get("Content-Type"); got != "application/json" { + t.Errorf("Content-Type = %q, want application/json", got) + } + + var body costSummaryResponse + if err := json.Unmarshal(rec.Body.Bytes(), &body); err != nil { + t.Fatalf("decode: %v\nbody=%s", err, rec.Body.String()) + } + + if body.Period.Start != "2026-04-01" || body.Period.End != "2026-04-30" { + t.Errorf("period = %+v", body.Period) + } + if body.DataSource != "snapshots_approximation" { + t.Errorf("data_source = %q, want snapshots_approximation", body.DataSource) + } + if body.Note == "" { + t.Errorf("note must be populated, got empty string") + } + if _, ok := body.Providers["aws"]; !ok { + t.Errorf("missing aws in providers: %+v", body.Providers) + } + if _, ok := body.Providers["gcp"]; !ok { + t.Errorf("missing gcp in providers: %+v", body.Providers) + } + if body.Providers["aws"].Currency != "USD" { + t.Errorf("aws currency = %q, want USD", body.Providers["aws"].Currency) + } + // AWS expected: (100 + 50) * 30/30 = 150 (period is 30 days inclusive). + // GCP expected: 200 * 30/30 = 200. + if !floatNearlyEqual(body.Providers["aws"].TotalUSD, 150.0, 0.5) { + t.Errorf("aws total = %v, want ~150", body.Providers["aws"].TotalUSD) + } + if !floatNearlyEqual(body.Providers["gcp"].TotalUSD, 200.0, 0.5) { + t.Errorf("gcp total = %v, want ~200", body.Providers["gcp"].TotalUSD) + } + if !floatNearlyEqual(body.GrandTotalUSD, 350.0, 0.5) { + t.Errorf("grand total = %v, want ~350", body.GrandTotalUSD) + } +} + +func floatNearlyEqual(a, b, tol float64) bool { + d := a - b + if d < 0 { + d = -d + } + return d <= tol +} + +func TestCostSummary_ProvidersFilter(t *testing.T) { + reader := &fakeAPIData{snapshots: snapshotsAprilEightySplit()} + srv := newCostTestServer(reader) + + rec := doGet(t, srv, "/api/v1/cost-summary?start=2026-04-01&end=2026-04-30&providers=aws", true) + if rec.Code != http.StatusOK { + t.Fatalf("status = %d, body=%s", rec.Code, rec.Body.String()) + } + + var body costSummaryResponse + if err := json.Unmarshal(rec.Body.Bytes(), &body); err != nil { + t.Fatalf("decode: %v", err) + } + if _, ok := body.Providers["aws"]; !ok { + t.Errorf("aws should be present after filter, got %+v", body.Providers) + } + if _, ok := body.Providers["gcp"]; ok { + t.Errorf("gcp should be excluded by providers=aws, got %+v", body.Providers) + } +} + +func TestCostSummary_InvalidProvidersFilter(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{}) + + rec := doGet(t, srv, "/api/v1/cost-summary?start=2026-04-01&end=2026-04-30&providers=aws,oracle", true) + if rec.Code != http.StatusBadRequest { + t.Fatalf("status = %d, want 400; body=%s", rec.Code, rec.Body.String()) + } + if code := extractCode(t, rec); code != "invalid_provider" { + t.Errorf("code = %q, want invalid_provider", code) + } +} + +func TestCostSummary_DateRangeErrors(t *testing.T) { + tests := []struct { + name string + path string + }{ + {"missing both", "/api/v1/cost-summary"}, + {"missing end", "/api/v1/cost-summary?start=2026-04-01"}, + {"bad start format", "/api/v1/cost-summary?start=apr1&end=2026-04-30"}, + {"bad end format", "/api/v1/cost-summary?start=2026-04-01&end=tomorrow"}, + {"end before start", "/api/v1/cost-summary?start=2026-04-30&end=2026-04-01"}, + } + for _, tc := range tests { + t.Run(tc.name, func(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{}) + rec := doGet(t, srv, tc.path, true) + if rec.Code != http.StatusBadRequest { + t.Fatalf("status = %d, want 400; body=%s", rec.Code, rec.Body.String()) + } + if code := extractCode(t, rec); code != "invalid_date_range" { + t.Errorf("code = %q, want invalid_date_range", code) + } + }) + } +} + +func TestCostSummary_RequiresAuth(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{}) + + noKey := doGet(t, srv, "/api/v1/cost-summary?start=2026-04-01&end=2026-04-30", false) + if noKey.Code != http.StatusUnauthorized { + t.Errorf("missing key: status = %d, want 401", noKey.Code) + } + + req := httptest.NewRequest(http.MethodGet, "/api/v1/cost-summary?start=2026-04-01&end=2026-04-30", nil) + req.Header.Set("X-API-Key", "wrong-key") + rec := httptest.NewRecorder() + srv.Handler().ServeHTTP(rec, req) + if rec.Code != http.StatusUnauthorized { + t.Errorf("wrong key: status = %d, want 401", rec.Code) + } + if code := extractCode(t, rec); code != "unauthorized" { + t.Errorf("code = %q, want unauthorized", code) + } +} + +func TestCostSummary_SnapshotQueryError(t *testing.T) { + reader := &fakeAPIData{snapshotsErr: errors.New("connection refused")} + srv := newCostTestServer(reader) + + rec := doGet(t, srv, "/api/v1/cost-summary?start=2026-04-01&end=2026-04-30", true) + if rec.Code != http.StatusInternalServerError { + t.Fatalf("status = %d, want 500; body=%s", rec.Code, rec.Body.String()) + } + if code := extractCode(t, rec); code != "snapshot_query_failed" { + t.Errorf("code = %q, want snapshot_query_failed", code) + } +} + +func TestCostSummary_PassesParsedRangeToReader(t *testing.T) { + reader := &fakeAPIData{} + srv := newCostTestServer(reader) + + rec := doGet(t, srv, "/api/v1/cost-summary?start=2026-04-01&end=2026-04-30", true) + if rec.Code != http.StatusOK { + t.Fatalf("status = %d", rec.Code) + } + + wantStart := time.Date(2026, 4, 1, 0, 0, 0, 0, time.UTC) + if !reader.gotStart.Equal(wantStart) { + t.Errorf("start passed to reader = %v, want %v", reader.gotStart, wantStart) + } + // End is expanded to 23:59:59.999999999 of the closing day. + if reader.gotEnd.Year() != 2026 || reader.gotEnd.Month() != 4 || reader.gotEnd.Day() != 30 || reader.gotEnd.Hour() != 23 { + t.Errorf("end passed to reader = %v, want 2026-04-30T23:59:59.999999999Z", reader.gotEnd) + } +} + +func TestCostByService_HappyPath(t *testing.T) { + reader := &fakeAPIData{snapshots: snapshotsAprilEightySplit()} + srv := newCostTestServer(reader) + + rec := doGet(t, srv, "/api/v1/cost-by-service?start=2026-04-01&end=2026-04-30&provider=aws", true) + if rec.Code != http.StatusOK { + t.Fatalf("status = %d, body=%s", rec.Code, rec.Body.String()) + } + + var body costByServiceResponse + if err := json.Unmarshal(rec.Body.Bytes(), &body); err != nil { + t.Fatalf("decode: %v", err) + } + + if body.Provider != "aws" { + t.Errorf("provider = %q, want aws", body.Provider) + } + if body.DataSource != "snapshots_approximation" { + t.Errorf("data_source = %q", body.DataSource) + } + if body.Note == "" { + t.Errorf("note must be populated") + } + if len(body.Services) != 2 { + t.Fatalf("services len = %d, want 2 (ec2 + rds)", len(body.Services)) + } + // Sorted by cost desc — ec2 (100) before rds (50). + if body.Services[0].Name != "ec2" || body.Services[1].Name != "rds" { + t.Errorf("services not sorted as expected: %+v", body.Services) + } + if !floatNearlyEqual(body.Services[0].Percentage, 66.67, 0.05) { + t.Errorf("ec2 percentage = %v, want ~66.67", body.Services[0].Percentage) + } + if !floatNearlyEqual(body.TotalUSD, 150.0, 0.5) { + t.Errorf("total = %v, want ~150", body.TotalUSD) + } +} + +func TestCostByService_TopCap(t *testing.T) { + snaps := []db.Snapshot{ + {TakenAt: mustTime("2026-04-10T00:00:00Z"), AccountID: "acc-aws", Service: "ec2", TotalMonthlyCost: 100}, + {TakenAt: mustTime("2026-04-10T00:00:00Z"), AccountID: "acc-aws", Service: "rds", TotalMonthlyCost: 50}, + {TakenAt: mustTime("2026-04-10T00:00:00Z"), AccountID: "acc-aws", Service: "ebs", TotalMonthlyCost: 25}, + {TakenAt: mustTime("2026-04-10T00:00:00Z"), AccountID: "acc-aws", Service: "lambda", TotalMonthlyCost: 10}, + } + srv := newCostTestServer(&fakeAPIData{snapshots: snaps}) + + rec := doGet(t, srv, "/api/v1/cost-by-service?start=2026-04-01&end=2026-04-30&provider=aws&top=2", true) + if rec.Code != http.StatusOK { + t.Fatalf("status = %d", rec.Code) + } + var body costByServiceResponse + if err := json.Unmarshal(rec.Body.Bytes(), &body); err != nil { + t.Fatalf("decode: %v", err) + } + if len(body.Services) != 2 { + t.Errorf("top=2 should cap services slice, got %d entries", len(body.Services)) + } + if body.Services[0].Name != "ec2" { + t.Errorf("top entry = %s, want ec2", body.Services[0].Name) + } +} + +func TestCostByService_InvalidProvider(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{}) + + tests := []string{ + "/api/v1/cost-by-service?start=2026-04-01&end=2026-04-30", + "/api/v1/cost-by-service?start=2026-04-01&end=2026-04-30&provider=", + "/api/v1/cost-by-service?start=2026-04-01&end=2026-04-30&provider=oracle", + } + for _, path := range tests { + t.Run(path, func(t *testing.T) { + rec := doGet(t, srv, path, true) + if rec.Code != http.StatusBadRequest { + t.Fatalf("status = %d, want 400; body=%s", rec.Code, rec.Body.String()) + } + if code := extractCode(t, rec); code != "invalid_provider" { + t.Errorf("code = %q, want invalid_provider", code) + } + }) + } +} + +func TestCostByService_RequiresAuth(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{}) + rec := doGet(t, srv, "/api/v1/cost-by-service?start=2026-04-01&end=2026-04-30&provider=aws", false) + if rec.Code != http.StatusUnauthorized { + t.Errorf("status = %d, want 401", rec.Code) + } +} + +func TestCostByService_EmptyData(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{snapshots: nil}) + + rec := doGet(t, srv, "/api/v1/cost-by-service?start=2026-04-01&end=2026-04-30&provider=aws", true) + if rec.Code != http.StatusOK { + t.Fatalf("status = %d", rec.Code) + } + var body costByServiceResponse + if err := json.Unmarshal(rec.Body.Bytes(), &body); err != nil { + t.Fatalf("decode: %v", err) + } + if len(body.Services) != 0 { + t.Errorf("services should be empty for empty data, got %+v", body.Services) + } + if body.TotalUSD != 0 { + t.Errorf("total should be 0 for empty data, got %v", body.TotalUSD) + } + // The contract still requires the disclaimer fields to surface so the + // agent doesn't accidentally claim "no spend" without context. + if body.DataSource != "snapshots_approximation" || body.Note == "" { + t.Errorf("disclaimer fields missing on empty response: source=%q note=%q", + body.DataSource, body.Note) + } +} + +func TestParseDateRange_SameDayOK(t *testing.T) { + start, end, err := parseDateRange("2026-04-15", "2026-04-15") + if err != nil { + t.Fatalf("parseDateRange same day: %v", err) + } + if !start.Equal(time.Date(2026, 4, 15, 0, 0, 0, 0, time.UTC)) { + t.Errorf("start = %v", start) + } + if end.Day() != 15 || end.Hour() != 23 { + t.Errorf("end = %v, want end-of-day 2026-04-15", end) + } + if periodDays(start, end) != 1 { + t.Errorf("periodDays(same day) = %d, want 1", periodDays(start, end)) + } +} + +func TestParseProvidersFilter(t *testing.T) { + out, err := parseProvidersFilter("aws, GCP ,azure") + if err != nil { + t.Fatalf("err: %v", err) + } + if !out["aws"] || !out["gcp"] || !out["azure"] { + t.Errorf("expected aws/gcp/azure all set, got %+v", out) + } + + if out, err := parseProvidersFilter(""); err != nil || out != nil { + t.Errorf("empty input should return nil/nil, got %+v / %v", out, err) + } + + if _, err := parseProvidersFilter("aws,banana"); err == nil { + t.Error("expected error for invalid provider") + } +} + +func TestPeriodDays(t *testing.T) { + d := periodDays( + time.Date(2026, 4, 1, 0, 0, 0, 0, time.UTC), + time.Date(2026, 4, 30, 23, 59, 59, 0, time.UTC), + ) + if d != 30 { + t.Errorf("periodDays(april) = %d, want 30", d) + } +} + +// TestV0DashboardEndpointsRemainUnauthenticated asserts the design decision +// from the pre-work: adding /api/v1/* auth must NOT regress the dashboard +// endpoints that the embedded React UI talks to. We hit /api/* (handled by +// the v0 catch-all 404 path since pool is nil in test) and confirm we don't +// get a 401 — the absence of auth wiring is the actual assertion. +func TestV0DashboardEndpointsRemainUnauthenticated(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{}) + + req := httptest.NewRequest(http.MethodGet, "/api/does-not-exist", nil) + rec := httptest.NewRecorder() + srv.Handler().ServeHTTP(rec, req) + + if rec.Code == http.StatusUnauthorized { + t.Errorf("v0 path returned 401, which means auth middleware leaked outside /api/v1/*") + } +} + +// extractCode pulls the `code` field out of a v1 error body. Centralised so +// every "should return error code X" test reads the same way and a future +// change to the error envelope only has to touch this helper. +func extractCode(t *testing.T, rec *httptest.ResponseRecorder) string { + t.Helper() + body := strings.TrimSpace(rec.Body.String()) + var m map[string]string + if err := json.Unmarshal([]byte(body), &m); err != nil { + t.Fatalf("error body is not JSON: %s", body) + } + return m["code"] +} diff --git a/internal/api/dashboard_handlers_test.go b/internal/api/dashboard_handlers_test.go new file mode 100644 index 0000000..a48002a --- /dev/null +++ b/internal/api/dashboard_handlers_test.go @@ -0,0 +1,250 @@ +package api + +import ( + "CloudOracle/internal/db" + "CloudOracle/internal/shared" + "context" + "encoding/json" + "errors" + "net" + "net/http" + "net/http/httptest" + "testing" + "time" +) + +// The v0 dashboard handlers predate the v1 cost endpoints and historically +// only had unit tests for their helper functions (sortFindings, clampInt, +// parsePositiveInt, etc.). These tests cover the end-to-end handler flow +// through the fakeAPIData fake, which gives us the same coverage the v1 +// endpoints have without spinning up Postgres. + +func newDashboardTestServer(data apiData) *Server { + return newTestServer(data, "test-key") +} + +func dashGet(t *testing.T, srv *Server, path string) *httptest.ResponseRecorder { + t.Helper() + req := httptest.NewRequest(http.MethodGet, path, nil) + rec := httptest.NewRecorder() + srv.Handler().ServeHTTP(rec, req) + return rec +} + +func sampleResources() []shared.Resource { + return []shared.Resource{ + {ID: "i-1", AccountID: "acc-aws", Service: "ec2", ResourceType: "t3.micro", Region: "us-east-2", MonthlyCost: 100, UsageMetric: 5}, + {ID: "i-2", AccountID: "acc-aws", Service: "ec2", ResourceType: "t3.small", Region: "us-east-2", MonthlyCost: 60, UsageMetric: 30}, + {ID: "db-1", AccountID: "acc-aws", Service: "rds", ResourceType: "db.t3.micro", Region: "us-east-2", MonthlyCost: 50, UsageMetric: 10}, + } +} + +func TestHandleResources_Happy(t *testing.T) { + srv := newDashboardTestServer(&fakeAPIData{resources: sampleResources()}) + + rec := dashGet(t, srv, "/api/resources") + if rec.Code != http.StatusOK { + t.Fatalf("status = %d, body=%s", rec.Code, rec.Body.String()) + } + var body resourcesResponse + if err := json.Unmarshal(rec.Body.Bytes(), &body); err != nil { + t.Fatalf("decode: %v", err) + } + if body.TotalCount != 3 { + t.Errorf("total_count = %d, want 3", body.TotalCount) + } + if body.TotalMonthlyCost != 210 { + t.Errorf("total_monthly_cost = %v, want 210", body.TotalMonthlyCost) + } +} + +func TestHandleResources_DBError(t *testing.T) { + srv := newDashboardTestServer(&fakeAPIData{resourcesErr: errors.New("conn refused")}) + rec := dashGet(t, srv, "/api/resources") + if rec.Code != http.StatusInternalServerError { + t.Errorf("status = %d, want 500", rec.Code) + } +} + +func TestHandleFindings_Pagination(t *testing.T) { + srv := newDashboardTestServer(&fakeAPIData{resources: sampleResources()}) + + rec := dashGet(t, srv, "/api/findings?page=1&page_size=10&sort=savings&order=desc") + if rec.Code != http.StatusOK { + t.Fatalf("status = %d, body=%s", rec.Code, rec.Body.String()) + } + var body findingsResponse + if err := json.Unmarshal(rec.Body.Bytes(), &body); err != nil { + t.Fatalf("decode: %v", err) + } + if body.Page != 1 || body.PageSize != 10 { + t.Errorf("page/page_size = %d/%d", body.Page, body.PageSize) + } + if body.Sort != "savings" || body.Order != "desc" { + t.Errorf("sort/order = %s/%s", body.Sort, body.Order) + } + if body.TotalCount < 0 { + t.Errorf("total_count = %d", body.TotalCount) + } +} + +func TestHandleFindings_DBError(t *testing.T) { + srv := newDashboardTestServer(&fakeAPIData{resourcesErr: errors.New("boom")}) + rec := dashGet(t, srv, "/api/findings") + if rec.Code != http.StatusInternalServerError { + t.Errorf("status = %d, want 500", rec.Code) + } +} + +func TestHandleFindings_PageBeyondTotalClamps(t *testing.T) { + srv := newDashboardTestServer(&fakeAPIData{resources: sampleResources()}) + + // Asking for page 99 with 10 per page on a small dataset must clamp + // back to the last valid page, not return a 5xx. + rec := dashGet(t, srv, "/api/findings?page=99&page_size=10") + if rec.Code != http.StatusOK { + t.Fatalf("status = %d", rec.Code) + } + var body findingsResponse + if err := json.Unmarshal(rec.Body.Bytes(), &body); err != nil { + t.Fatalf("decode: %v", err) + } + if body.Page > body.TotalPages || body.Page < 1 { + t.Errorf("page=%d, total_pages=%d — page should clamp into range", body.Page, body.TotalPages) + } +} + +func TestHandleTrends_Happy(t *testing.T) { + trends := []db.Trend{ + {Date: "2026-04-01", TotalCost: 100, ResourceCount: 5, BreakdownByService: map[string]float64{"ec2": 80, "rds": 20}}, + {Date: "2026-04-15", TotalCost: 120, ResourceCount: 6, BreakdownByService: map[string]float64{"ec2": 100, "rds": 20}}, + } + fake := &fakeAPIData{trends: trends} + srv := newDashboardTestServer(fake) + + rec := dashGet(t, srv, "/api/trends?days=45") + if rec.Code != http.StatusOK { + t.Fatalf("status = %d", rec.Code) + } + if fake.gotDays != 45 { + t.Errorf("days passed to ListTrends = %d, want 45", fake.gotDays) + } + var got []db.Trend + if err := json.Unmarshal(rec.Body.Bytes(), &got); err != nil { + t.Fatalf("decode: %v", err) + } + if len(got) != 2 { + t.Errorf("trends len = %d, want 2", len(got)) + } +} + +func TestHandleTrends_BadDaysFallsBackToDefault(t *testing.T) { + fake := &fakeAPIData{} + srv := newDashboardTestServer(fake) + + rec := dashGet(t, srv, "/api/trends?days=garbage") + if rec.Code != http.StatusOK { + t.Fatalf("status = %d", rec.Code) + } + // Default fallback is 90; documented in handleTrends. + if fake.gotDays != 90 { + t.Errorf("days passed to ListTrends = %d, want default 90", fake.gotDays) + } +} + +func TestHandleTrends_DBError(t *testing.T) { + srv := newDashboardTestServer(&fakeAPIData{trendsErr: errors.New("boom")}) + rec := dashGet(t, srv, "/api/trends") + if rec.Code != http.StatusInternalServerError { + t.Errorf("status = %d, want 500", rec.Code) + } +} + +func TestHandleSummary_Happy(t *testing.T) { + srv := newDashboardTestServer(&fakeAPIData{resources: sampleResources()}) + + rec := dashGet(t, srv, "/api/summary") + if rec.Code != http.StatusOK { + t.Fatalf("status = %d, body=%s", rec.Code, rec.Body.String()) + } + var body summaryResponse + if err := json.Unmarshal(rec.Body.Bytes(), &body); err != nil { + t.Fatalf("decode: %v", err) + } + if body.TotalResources != 3 { + t.Errorf("total_resources = %d, want 3", body.TotalResources) + } + if body.TotalMonthlyCost != 210 { + t.Errorf("total_monthly_cost = %v, want 210", body.TotalMonthlyCost) + } + if body.ByService["ec2"].Count != 2 { + t.Errorf("by_service[ec2].count = %d, want 2", body.ByService["ec2"].Count) + } + if body.ByProvider["aws"].Count != 3 { + t.Errorf("by_provider[aws].count = %d, want 3", body.ByProvider["aws"].Count) + } +} + +func TestHandleSummary_DBError(t *testing.T) { + srv := newDashboardTestServer(&fakeAPIData{resourcesErr: errors.New("boom")}) + rec := dashGet(t, srv, "/api/summary") + if rec.Code != http.StatusInternalServerError { + t.Errorf("status = %d, want 500", rec.Code) + } +} + +func TestHandle_UnknownAPIPathReturns404(t *testing.T) { + srv := newDashboardTestServer(&fakeAPIData{}) + rec := dashGet(t, srv, "/api/does-not-exist") + if rec.Code != http.StatusNotFound { + t.Errorf("status = %d, want 404", rec.Code) + } +} + +// TestRunGracefulShutdown spins the server on an ephemeral port, fires one +// request to confirm it serves, then cancels the context and verifies Run +// returns nil (clean shutdown) within the configured timeout. Pure stdlib — +// no external mocks. Covers the Run path the production runServe depends on. +func TestRunGracefulShutdown(t *testing.T) { + srv := newDashboardTestServer(&fakeAPIData{resources: sampleResources()}) + + listener, err := net.Listen("tcp", "127.0.0.1:0") + if err != nil { + t.Fatalf("listen: %v", err) + } + addr := listener.Addr().String() + _ = listener.Close() + + ctx, cancel := context.WithCancel(context.Background()) + runErr := make(chan error, 1) + go func() { runErr <- srv.Run(ctx, addr, 2*time.Second) }() + + // Wait briefly for the server to bind, then make a request. + deadline := time.Now().Add(2 * time.Second) + var resp *http.Response + for time.Now().Before(deadline) { + resp, err = http.Get("http://" + addr + "/api/resources") + if err == nil { + break + } + time.Sleep(20 * time.Millisecond) + } + if err != nil { + cancel() + t.Fatalf("request never succeeded: %v", err) + } + resp.Body.Close() + if resp.StatusCode != http.StatusOK { + t.Errorf("request status = %d", resp.StatusCode) + } + + cancel() + select { + case err := <-runErr: + if err != nil { + t.Errorf("Run returned %v on clean shutdown, want nil", err) + } + case <-time.After(3 * time.Second): + t.Fatal("Run did not return within shutdown timeout") + } +} diff --git a/internal/api/middleware.go b/internal/api/middleware.go index bbd4385..ea80827 100644 --- a/internal/api/middleware.go +++ b/internal/api/middleware.go @@ -1,6 +1,10 @@ package api import ( + "context" + "crypto/rand" + "crypto/subtle" + "encoding/hex" "encoding/json" "errors" "log/slog" @@ -20,11 +24,79 @@ func (r *statusRecorder) WriteHeader(code int) { r.ResponseWriter.WriteHeader(code) } +type ctxKey string + +// ctxRequestID identifies the per-request ID stashed in context by +// requestIDMiddleware. Handlers can pull it out via requestIDFromContext. +const ctxRequestID ctxKey = "request_id" + +func requestIDFromContext(ctx context.Context) string { + if v, ok := ctx.Value(ctxRequestID).(string); ok { + return v + } + return "" +} + +// requestIDMiddleware honors an incoming X-Request-ID header when set +// (so a reverse proxy or upstream client can correlate logs) and falls +// back to a fresh random ID otherwise. Always echoes the chosen ID +// back in the response header so callers can quote it in bug reports. +func requestIDMiddleware(next http.Handler) http.Handler { + return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) { + id := r.Header.Get("X-Request-ID") + if id == "" { + id = newRequestID() + } + w.Header().Set("X-Request-ID", id) + ctx := context.WithValue(r.Context(), ctxRequestID, id) + next.ServeHTTP(w, r.WithContext(ctx)) + }) +} + +// newRequestID returns 24 hex chars from crypto/rand. Short enough to read +// in logs, long enough to avoid collisions across a single process lifetime. +// crypto/rand never errors in practice on Linux/macOS/Windows; if it ever +// did we'd rather log a blank ID than crash the request path. +func newRequestID() string { + var b [12]byte + if _, err := rand.Read(b[:]); err != nil { + return "" + } + return hex.EncodeToString(b[:]) +} + +// authMiddleware enforces the X-API-Key header against a fixed key loaded +// at startup. subtle.ConstantTimeCompare avoids leaking the valid key length +// through timing — small thing, but cheap to do right since we're already +// gating the v1 endpoints. A missing or empty configured key is treated as +// "deny all"; the serve subcommand refuses to start in that state, so this +// path is defense-in-depth. +func authMiddleware(apiKey string) func(http.Handler) http.Handler { + return func(next http.Handler) http.Handler { + return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) { + if apiKey == "" { + writeAPIError(w, http.StatusUnauthorized, "API key not configured on server", "unauthorized") + return + } + got := r.Header.Get("X-API-Key") + if got == "" { + writeAPIError(w, http.StatusUnauthorized, "missing X-API-Key header", "unauthorized") + return + } + if subtle.ConstantTimeCompare([]byte(got), []byte(apiKey)) != 1 { + writeAPIError(w, http.StatusUnauthorized, "invalid API key", "unauthorized") + return + } + next.ServeHTTP(w, r) + }) + } +} + func corsMiddleware(next http.Handler) http.Handler { return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) { w.Header().Set("Access-Control-Allow-Origin", "*") w.Header().Set("Access-Control-Allow-Methods", "GET, OPTIONS") - w.Header().Set("Access-Control-Allow-Headers", "Content-Type") + w.Header().Set("Access-Control-Allow-Headers", "Content-Type, X-API-Key, X-Request-ID") if r.Method == http.MethodOptions { w.WriteHeader(http.StatusNoContent) @@ -44,6 +116,7 @@ func loggingMiddleware(next http.Handler) http.Handler { "path", r.URL.Path, "status", rec.status, "duration_ms", time.Since(start).Milliseconds(), + "request_id", requestIDFromContext(r.Context()), ) }) } @@ -56,9 +129,25 @@ func writeJSON(w http.ResponseWriter, status int, body any) { } } +// writeError keeps the legacy single-field shape used by the v0 dashboard +// endpoints. New v1 handlers use writeAPIError so clients have a stable +// machine-readable `code` to branch on. func writeError(w http.ResponseWriter, status int, message string) { slog.Error("handler error", "status", status, "message", message) w.Header().Set("Content-Type", "application/json") w.WriteHeader(status) _ = json.NewEncoder(w).Encode(map[string]string{"error": message}) } + +// writeAPIError is the v1 error shape: {"error": , "code": +// }. The code values are documented in the README +// so the Python agent and any other client can branch deterministically. +func writeAPIError(w http.ResponseWriter, status int, message, code string) { + slog.Error("v1 handler error", "status", status, "code", code, "message", message) + w.Header().Set("Content-Type", "application/json") + w.WriteHeader(status) + _ = json.NewEncoder(w).Encode(map[string]string{ + "error": message, + "code": code, + }) +} diff --git a/internal/api/middleware_test.go b/internal/api/middleware_test.go new file mode 100644 index 0000000..d9c8bee --- /dev/null +++ b/internal/api/middleware_test.go @@ -0,0 +1,146 @@ +package api + +import ( + "net/http" + "net/http/httptest" + "strings" + "testing" +) + +func TestRequestIDMiddleware_GeneratesIDWhenAbsent(t *testing.T) { + var inHandler string + next := http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) { + inHandler = requestIDFromContext(r.Context()) + w.WriteHeader(http.StatusOK) + }) + + req := httptest.NewRequest(http.MethodGet, "/api/v1/cost-summary", nil) + rec := httptest.NewRecorder() + requestIDMiddleware(next).ServeHTTP(rec, req) + + if inHandler == "" { + t.Error("handler context did not receive a request ID") + } + echoed := rec.Header().Get("X-Request-ID") + if echoed == "" { + t.Error("response missing X-Request-ID header") + } + if echoed != inHandler { + t.Errorf("header (%q) and context (%q) IDs should match", echoed, inHandler) + } + if len(echoed) != 24 { + t.Errorf("generated ID should be 24 hex chars, got %d (%q)", len(echoed), echoed) + } +} + +func TestRequestIDMiddleware_HonorsIncomingHeader(t *testing.T) { + const incoming = "client-supplied-id-001" + var inHandler string + next := http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) { + inHandler = requestIDFromContext(r.Context()) + }) + + req := httptest.NewRequest(http.MethodGet, "/api/v1/cost-summary", nil) + req.Header.Set("X-Request-ID", incoming) + rec := httptest.NewRecorder() + requestIDMiddleware(next).ServeHTTP(rec, req) + + if inHandler != incoming { + t.Errorf("incoming ID lost: got %q, want %q", inHandler, incoming) + } + if got := rec.Header().Get("X-Request-ID"); got != incoming { + t.Errorf("echo header = %q, want %q", got, incoming) + } +} + +func TestAuthMiddleware_RejectsMissingKey(t *testing.T) { + called := false + next := http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) { + called = true + }) + + req := httptest.NewRequest(http.MethodGet, "/api/v1/cost-summary", nil) + rec := httptest.NewRecorder() + authMiddleware("server-key")(next).ServeHTTP(rec, req) + + if called { + t.Error("handler must not be reached with missing key") + } + if rec.Code != http.StatusUnauthorized { + t.Errorf("status = %d, want 401", rec.Code) + } +} + +func TestAuthMiddleware_RejectsWrongKey(t *testing.T) { + called := false + next := http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) { + called = true + }) + + req := httptest.NewRequest(http.MethodGet, "/api/v1/cost-summary", nil) + req.Header.Set("X-API-Key", "wrong") + rec := httptest.NewRecorder() + authMiddleware("server-key")(next).ServeHTTP(rec, req) + + if called { + t.Error("handler must not be reached with wrong key") + } + if rec.Code != http.StatusUnauthorized { + t.Errorf("status = %d, want 401", rec.Code) + } +} + +func TestAuthMiddleware_AcceptsMatchingKey(t *testing.T) { + called := false + next := http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) { + called = true + w.WriteHeader(http.StatusOK) + }) + + req := httptest.NewRequest(http.MethodGet, "/api/v1/cost-summary", nil) + req.Header.Set("X-API-Key", "server-key") + rec := httptest.NewRecorder() + authMiddleware("server-key")(next).ServeHTTP(rec, req) + + if !called { + t.Error("handler must be reached when key matches") + } + if rec.Code != http.StatusOK { + t.Errorf("status = %d, want 200", rec.Code) + } +} + +func TestAuthMiddleware_RejectsWhenServerKeyEmpty(t *testing.T) { + called := false + next := http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) { + called = true + }) + + req := httptest.NewRequest(http.MethodGet, "/api/v1/cost-summary", nil) + req.Header.Set("X-API-Key", "anything") + rec := httptest.NewRecorder() + authMiddleware("")(next).ServeHTTP(rec, req) + + if called { + t.Error("server with empty key must not authenticate any request") + } + if rec.Code != http.StatusUnauthorized { + t.Errorf("status = %d, want 401", rec.Code) + } +} + +func TestWriteAPIError_IncludesCodeField(t *testing.T) { + rec := httptest.NewRecorder() + writeAPIError(rec, http.StatusBadRequest, "boom", "invalid_thing") + + if rec.Code != http.StatusBadRequest { + t.Errorf("status = %d", rec.Code) + } + if ct := rec.Header().Get("Content-Type"); ct != "application/json" { + t.Errorf("content-type = %q", ct) + } + body := rec.Body.String() + if !strings.Contains(body, `"error":"boom"`) || !strings.Contains(body, `"code":"invalid_thing"`) { + t.Errorf("body missing fields: %s", body) + } +} diff --git a/internal/api/server.go b/internal/api/server.go index 15c861f..f4b2116 100644 --- a/internal/api/server.go +++ b/internal/api/server.go @@ -2,8 +2,11 @@ package api import ( "CloudOracle/internal/analyzer" + "CloudOracle/internal/config" "CloudOracle/internal/db" "CloudOracle/internal/shared" + "context" + "errors" "log/slog" "net/http" "sort" @@ -12,39 +15,101 @@ import ( ) type Server struct { - pool *db.Pool + data apiData + apiKey string handler http.Handler } -func NewServer(pool *db.Pool) *Server { - s := &Server{pool: pool} +// NewServer wires the production handler: legacy `/api/*` dashboard +// endpoints stay open (they're consumed by the embedded React UI), and +// the new `/api/v1/*` endpoints sit behind authMiddleware so only the +// insights-agent — or any client that holds the configured API key — +// can reach them. +func NewServer(pool *db.Pool, apiCfg config.APIConfig) *Server { + return newServerWithData(&pgxAdapter{pool: pool}, apiCfg.Key) +} + +// newTestServer builds a Server with a caller-supplied apiData so unit tests +// can exercise the handlers without a live database. Production must go +// through NewServer. +func newTestServer(data apiData, apiKey string) *Server { + return newServerWithData(data, apiKey) +} + +func newServerWithData(data apiData, apiKey string) *Server { + s := &Server{data: data, apiKey: apiKey} + s.handler = s.buildHandler() + return s +} +func (s *Server) buildHandler() http.Handler { mux := http.NewServeMux() + + // v0 dashboard endpoints — left unauthenticated to match the existing + // React UI which is served from the same binary and assumes local trust. mux.HandleFunc("GET /api/resources", s.handleResources) mux.HandleFunc("GET /api/findings", s.handleFindings) mux.HandleFunc("GET /api/trends", s.handleTrends) mux.HandleFunc("GET /api/summary", s.handleSummary) + + // v1 endpoints for the insights-agent — gated by X-API-Key so the + // surface area an agent can reach is explicitly auth'd. Sit on + // /api/v1/* so the dashboard endpoints can evolve independently. + authed := authMiddleware(s.apiKey) + mux.Handle("GET /api/v1/cost-summary", + authed(http.HandlerFunc(s.handleCostSummary))) + mux.Handle("GET /api/v1/cost-by-service", + authed(http.HandlerFunc(s.handleCostByService))) + mux.HandleFunc("GET /api/", func(w http.ResponseWriter, r *http.Request) { writeError(w, http.StatusNotFound, "endpoint not found: "+r.Method+" "+r.URL.Path) }) mux.Handle("GET /", staticHandler()) - s.handler = corsMiddleware(loggingMiddleware(mux)) - return s + return corsMiddleware(requestIDMiddleware(loggingMiddleware(mux))) } func (s *Server) Handler() http.Handler { return s.handler } -func (s *Server) Start(addr string) error { - slog.Info("starting API server", "addr", addr) +// Run starts the HTTP server on addr and blocks until ctx is cancelled. +// On cancellation it triggers http.Server.Shutdown with the configured +// timeout. Returns nil on a clean shutdown, the listener error otherwise. +// +// We pattern-match the canonical Go shutdown idiom (goroutine + select on +// errCh / ctx.Done) so SIGINT/SIGTERM forwarded by the parent context land +// in Shutdown rather than abruptly killing in-flight requests — the agent +// flow in insights-agent/ can take a few seconds on a slow LLM response. +func (s *Server) Run(ctx context.Context, addr string, shutdownTimeout time.Duration) error { srv := &http.Server{ Addr: addr, Handler: s.handler, ReadHeaderTimeout: 5 * time.Second, } - return srv.ListenAndServe() + + errCh := make(chan error, 1) + go func() { + slog.Info("starting API server", "addr", addr) + if err := srv.ListenAndServe(); err != nil && !errors.Is(err, http.ErrServerClosed) { + errCh <- err + return + } + errCh <- nil + }() + + select { + case err := <-errCh: + return err + case <-ctx.Done(): + slog.Info("shutting down API server", "timeout", shutdownTimeout) + shutdownCtx, cancel := context.WithTimeout(context.Background(), shutdownTimeout) + defer cancel() + if err := srv.Shutdown(shutdownCtx); err != nil { + return err + } + return nil + } } type resourcesResponse struct { @@ -54,7 +119,7 @@ type resourcesResponse struct { } func (s *Server) handleResources(w http.ResponseWriter, r *http.Request) { - resources, err := db.ListResources(r.Context(), s.pool) + resources, err := s.data.ListResources(r.Context()) if err != nil { writeError(w, http.StatusInternalServerError, "failed to list resources: "+err.Error()) return @@ -89,7 +154,7 @@ const ( ) func (s *Server) handleFindings(w http.ResponseWriter, r *http.Request) { - resources, err := db.ListResources(r.Context(), s.pool) + resources, err := s.data.ListResources(r.Context()) if err != nil { writeError(w, http.StatusInternalServerError, "failed to list resources: "+err.Error()) return @@ -231,7 +296,7 @@ func (s *Server) handleTrends(w http.ResponseWriter, r *http.Request) { } } - trends, err := db.ListTrends(r.Context(), s.pool, days) + trends, err := s.data.ListTrends(r.Context(), days) if err != nil { writeError(w, http.StatusInternalServerError, "failed to load trends: "+err.Error()) return @@ -262,7 +327,7 @@ type summaryResponse struct { } func (s *Server) handleSummary(w http.ResponseWriter, r *http.Request) { - resources, err := db.ListResources(r.Context(), s.pool) + resources, err := s.data.ListResources(r.Context()) if err != nil { writeError(w, http.StatusInternalServerError, "failed to list resources: "+err.Error()) return @@ -320,11 +385,21 @@ var providerByService = map[string]string{ } func providerFromResource(r shared.Resource) string { - if p, ok := providerByService[r.Service]; ok { + return providerForServiceAccount(r.Service, r.AccountID) +} + +// providerForServiceAccount is the shared service-to-provider mapping used +// by both the v0 summary handler and the v1 cost endpoints (which only +// have AccountID + Service available on snapshots). The "functions" tie +// is broken by checking the AccountID shape — Azure subscription IDs are +// 36-char UUIDs, GCP project IDs aren't — same heuristic the summary +// handler has used since the dashboard shipped. +func providerForServiceAccount(service, accountID string) string { + if p, ok := providerByService[service]; ok { return p } - if r.Service == "functions" { - if len(r.AccountID) == 36 && r.AccountID[8] == '-' && r.AccountID[13] == '-' { + if service == "functions" { + if len(accountID) == 36 && accountID[8] == '-' && accountID[13] == '-' { return "azure" } return "gcp" diff --git a/internal/config/config.go b/internal/config/config.go index 6dc7028..a2f0042 100644 --- a/internal/config/config.go +++ b/internal/config/config.go @@ -13,6 +13,7 @@ type Config struct { DB DBConfig Cloud CloudConfig LLM LLMConfig + API APIConfig ServiceTimeout time.Duration LogLevel string LogFormat string @@ -47,6 +48,17 @@ type LLMConfig struct { MaxDelay time.Duration } +// APIConfig governs the HTTP server exposed by `oracle serve`. Key is read +// here but not validated as required at Load time — only the `serve` +// subcommand cares whether it is set, so we let other subcommands (seed, +// analyze, report, ...) run without it. The serve entry point fails fast +// if Key is empty. +type APIConfig struct { + Key string + Port string + ShutdownTimeout time.Duration +} + const ( providerSynthetic = "synthetic" providerAWS = "aws" @@ -114,6 +126,11 @@ func Load() (Config, error) { BaseDelay: v.requirePositiveDuration("LLM_BASE_DELAY", 500*time.Millisecond), MaxDelay: v.requirePositiveDuration("LLM_MAX_DELAY", 30*time.Second), }, + API: APIConfig{ + Key: os.Getenv("CLOUDORACLE_API_KEY"), + Port: v.requirePort("CLOUDORACLE_API_PORT", "8080"), + ShutdownTimeout: v.requirePositiveDuration("CLOUDORACLE_API_SHUTDOWN_TIMEOUT", 10*time.Second), + }, ServiceTimeout: v.requirePositiveDuration("CLOUD_SERVICE_TIMEOUT", 30*time.Second), LogLevel: v.requireEnum("LOG_LEVEL", "info", validLogLevels), LogFormat: v.requireEnum("LOG_FORMAT", "text", validLogFormats), diff --git a/internal/config/config_test.go b/internal/config/config_test.go index fcce57c..2dcc3e9 100644 --- a/internal/config/config_test.go +++ b/internal/config/config_test.go @@ -17,6 +17,7 @@ func allConfigEnvVars() []string { "GOOGLE_CLOUD_PROJECT", "AZURE_SUBSCRIPTION_ID", "SYNTHETIC_COUNT", "SYNTHETIC_ACCOUNT", "LLM_PROVIDER", "GEMINI_API_KEY", "ANTHROPIC_API_KEY", "OPENAI_API_KEY", "LLM_TIMEOUT", + "CLOUDORACLE_API_KEY", "CLOUDORACLE_API_PORT", "CLOUDORACLE_API_SHUTDOWN_TIMEOUT", "CLOUD_SERVICE_TIMEOUT", "LOG_LEVEL", "LOG_FORMAT", } } @@ -328,6 +329,51 @@ func TestDSN(t *testing.T) { } } +// API config has its own defaults and is intentionally not validated as +// "required" at Load time — only the `serve` subcommand checks Key. +func TestLoad_APIConfig_Defaults(t *testing.T) { + clearAll(t) + cfg, err := Load() + if err != nil { + t.Fatalf("Load: %v", err) + } + if cfg.API.Key != "" { + t.Errorf("API.Key should be empty by default, got %q", cfg.API.Key) + } + if cfg.API.Port != "8080" { + t.Errorf("API.Port = %q, want 8080", cfg.API.Port) + } + if cfg.API.ShutdownTimeout != 10*time.Second { + t.Errorf("API.ShutdownTimeout = %v, want 10s", cfg.API.ShutdownTimeout) + } +} + +func TestLoad_APIConfig_CustomValues(t *testing.T) { + clearAll(t) + t.Setenv("CLOUDORACLE_API_KEY", "secret-123") + t.Setenv("CLOUDORACLE_API_PORT", "9090") + t.Setenv("CLOUDORACLE_API_SHUTDOWN_TIMEOUT", "45s") + + cfg, err := Load() + if err != nil { + t.Fatalf("Load: %v", err) + } + if cfg.API.Key != "secret-123" || cfg.API.Port != "9090" { + t.Errorf("API fields not picked up: %+v", cfg.API) + } + if cfg.API.ShutdownTimeout != 45*time.Second { + t.Errorf("API.ShutdownTimeout = %v, want 45s", cfg.API.ShutdownTimeout) + } +} + +func TestLoad_InvalidAPIPort(t *testing.T) { + loadInvalid(t, "CLOUDORACLE_API_PORT", "notanumber", "CLOUDORACLE_API_PORT") +} + +func TestLoad_InvalidAPIShutdownTimeout(t *testing.T) { + loadInvalid(t, "CLOUDORACLE_API_SHUTDOWN_TIMEOUT", "0s", "greater than zero") +} + func TestGetEnv_DefaultBehavior(t *testing.T) { t.Setenv("TEST_KEY_VALUE", "myvalue") if v := getEnv("TEST_KEY_VALUE", "default"); v != "myvalue" { diff --git a/internal/db/snapshots.go b/internal/db/snapshots.go index da37a93..b4a7cf1 100644 --- a/internal/db/snapshots.go +++ b/internal/db/snapshots.go @@ -90,3 +90,33 @@ func ListSnapshots(ctx context.Context, pool *pgxpool.Pool, days int) ([]Snapsho return snapshots, rows.Err() } + +// ListSnapshotsInRange returns every snapshot taken in [start, end]. Both +// bounds are inclusive — the v1 HTTP API documents an inclusive contract, +// and BETWEEN matches both ends. Used by the cost-summary / cost-by-service +// endpoints; ListSnapshots stays as the "last N days" entry point used by +// the trend CLI and dashboard. +func ListSnapshotsInRange(ctx context.Context, pool *pgxpool.Pool, start, end time.Time) ([]Snapshot, error) { + rows, err := pool.Query(ctx, + `SELECT taken_at, account_id, service, resource_count, total_monthly_cost + FROM cost_snapshots + WHERE taken_at BETWEEN $1 AND $2 + ORDER BY taken_at ASC`, + start, end, + ) + if err != nil { + return nil, fmt.Errorf("querying snapshots in range: %w", err) + } + defer rows.Close() + + var snapshots []Snapshot + for rows.Next() { + var s Snapshot + if err := rows.Scan(&s.TakenAt, &s.AccountID, &s.Service, &s.ResourceCount, &s.TotalMonthlyCost); err != nil { + return nil, fmt.Errorf("scanning snapshot: %w", err) + } + snapshots = append(snapshots, s) + } + + return snapshots, rows.Err() +} diff --git a/internal/db/snapshots_integration_test.go b/internal/db/snapshots_integration_test.go index bcdd83d..23978bb 100644 --- a/internal/db/snapshots_integration_test.go +++ b/internal/db/snapshots_integration_test.go @@ -111,3 +111,53 @@ func TestListSnapshots_RespectsDayWindow(t *testing.T) { t.Errorf("365-day window returned %d, want 1", len(got)) } } + +// TestListSnapshotsInRange_BothBoundsInclusive verifies the inclusive +// [start, end] contract surfaced by the v1 HTTP API. Snapshots at the +// exact start and end timestamps must be returned; one minute outside +// must not. The dataset uses three snapshots backdated to known offsets +// so we can reason about the bounds without flakiness. +func TestListSnapshotsInRange_BothBoundsInclusive(t *testing.T) { + pool := dbtest.SharedPool(t) + ctx := t.Context() + + // Three identical resources → three (account, service) rows; we then + // rewrite taken_at to put one inside, one at the lower edge, and one + // outside the test window. + resources := []shared.Resource{ + {ID: "i-1", AccountID: "acc-a", Service: "ec2", ResourceType: "t3.micro", Region: "us-east-2", MonthlyCost: 10, CreatedAt: time.Now(), UpdatedAt: time.Now()}, + {ID: "i-2", AccountID: "acc-b", Service: "rds", ResourceType: "db.t3.micro", Region: "us-east-2", MonthlyCost: 50, CreatedAt: time.Now(), UpdatedAt: time.Now()}, + {ID: "i-3", AccountID: "acc-c", Service: "ebs", ResourceType: "gp3", Region: "us-east-2", MonthlyCost: 5, CreatedAt: time.Now(), UpdatedAt: time.Now()}, + } + if err := CreateSnapshot(ctx, pool, resources); err != nil { + t.Fatalf("CreateSnapshot: %v", err) + } + + // Set fixed timestamps: ec2 at 2026-04-01 (inside), rds at 2026-04-30 (inside, at upper edge), ebs at 2026-05-15 (outside). + if _, err := pool.Exec(ctx, `UPDATE cost_snapshots SET taken_at = '2026-04-01 12:00:00+00' WHERE service = 'ec2'`); err != nil { + t.Fatalf("backdate ec2: %v", err) + } + if _, err := pool.Exec(ctx, `UPDATE cost_snapshots SET taken_at = '2026-04-30 23:59:59+00' WHERE service = 'rds'`); err != nil { + t.Fatalf("backdate rds: %v", err) + } + if _, err := pool.Exec(ctx, `UPDATE cost_snapshots SET taken_at = '2026-05-15 00:00:00+00' WHERE service = 'ebs'`); err != nil { + t.Fatalf("backdate ebs: %v", err) + } + + start := time.Date(2026, 4, 1, 0, 0, 0, 0, time.UTC) + end := time.Date(2026, 4, 30, 23, 59, 59, 0, time.UTC) + got, err := ListSnapshotsInRange(ctx, pool, start, end) + if err != nil { + t.Fatalf("ListSnapshotsInRange: %v", err) + } + if len(got) != 2 { + t.Fatalf("len = %d, want 2 (ec2 + rds; ebs is outside)", len(got)) + } + services := map[string]bool{} + for _, s := range got { + services[s.Service] = true + } + if !services["ec2"] || !services["rds"] || services["ebs"] { + t.Errorf("unexpected services in range: %v", services) + } +} From 8450086dd5692782de5af2e1ceb1c3ec7e3abb82 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jesus=20Nu=C3=B1ez?= Date: Mon, 18 May 2026 11:03:00 -0400 Subject: [PATCH 03/18] feat(insights-agent): bootstrap Python project with LLM provider abstraction First commit of the LangGraph-based FinOps agent that consumes the Go /api/v1 cost endpoints. Lays down the project skeleton, config / logging mirroring the Go side (stderr + text|json switch matching slog), and an LLMProvider ABC so future providers (Claude, OpenAI) are additive without touching the graph code. - pyproject.toml with uv, Python 3.12, pytest+coverage (>=80% gate), ruff (strict select), mypy (strict mode) - config.Settings (pydantic-settings) fails fast on missing required keys - logging.setup mirrors Go slog semantics (LOG_LEVEL/LOG_FORMAT, stderr) - llm.LLMProvider ABC + llm.GeminiProvider (default gemini-2.5-flash to match the Go side and avoid drift) - tests cover config validation, logging wiring, and provider construction (real Google SDK patched out so no network in CI); 100% coverage Co-Authored-By: Claude Opus 4.7 (1M context) --- insights-agent/.env.example | 18 + insights-agent/.gitignore | 14 + insights-agent/README.md | 5 + insights-agent/pyproject.toml | 93 ++ insights-agent/src/insights_agent/__init__.py | 3 + insights-agent/src/insights_agent/config.py | 59 ++ .../src/insights_agent/graph/__init__.py | 0 .../src/insights_agent/llm/__init__.py | 11 + insights-agent/src/insights_agent/llm/base.py | 30 + .../src/insights_agent/llm/gemini.py | 49 + insights-agent/src/insights_agent/logging.py | 67 ++ .../src/insights_agent/tools/__init__.py | 0 insights-agent/tests/__init__.py | 0 insights-agent/tests/conftest.py | 45 + insights-agent/tests/test_config.py | 67 ++ insights-agent/tests/test_gemini_provider.py | 59 ++ insights-agent/tests/test_logging.py | 32 + insights-agent/uv.lock | 980 ++++++++++++++++++ 18 files changed, 1532 insertions(+) create mode 100644 insights-agent/.env.example create mode 100644 insights-agent/.gitignore create mode 100644 insights-agent/README.md create mode 100644 insights-agent/pyproject.toml create mode 100644 insights-agent/src/insights_agent/__init__.py create mode 100644 insights-agent/src/insights_agent/config.py create mode 100644 insights-agent/src/insights_agent/graph/__init__.py create mode 100644 insights-agent/src/insights_agent/llm/__init__.py create mode 100644 insights-agent/src/insights_agent/llm/base.py create mode 100644 insights-agent/src/insights_agent/llm/gemini.py create mode 100644 insights-agent/src/insights_agent/logging.py create mode 100644 insights-agent/src/insights_agent/tools/__init__.py create mode 100644 insights-agent/tests/__init__.py create mode 100644 insights-agent/tests/conftest.py create mode 100644 insights-agent/tests/test_config.py create mode 100644 insights-agent/tests/test_gemini_provider.py create mode 100644 insights-agent/tests/test_logging.py create mode 100644 insights-agent/uv.lock diff --git a/insights-agent/.env.example b/insights-agent/.env.example new file mode 100644 index 0000000..15199a1 --- /dev/null +++ b/insights-agent/.env.example @@ -0,0 +1,18 @@ +# Google Gemini API key — required. +# Get one from https://aistudio.google.com/app/apikey (free tier works). +GEMINI_API_KEY= + +# CloudOracle Go API base URL — where the `oracle serve` binary listens. +CLOUDORACLE_API_URL=http://localhost:8080 + +# API key for the CloudOracle v1 endpoints. Must match the value the Go +# server was started with (CLOUDORACLE_API_KEY in its env). Required. +CLOUDORACLE_API_KEY= + +# Gemini model. Default matches the Go side to avoid drift. +GEMINI_MODEL=gemini-2.5-flash + +# Optional knobs. +LOG_LEVEL=INFO +LOG_FORMAT=text +HTTP_TIMEOUT_SECONDS=10 diff --git a/insights-agent/.gitignore b/insights-agent/.gitignore new file mode 100644 index 0000000..a1a9c4f --- /dev/null +++ b/insights-agent/.gitignore @@ -0,0 +1,14 @@ +.venv/ +__pycache__/ +*.pyc +*.pyo +.pytest_cache/ +.mypy_cache/ +.ruff_cache/ +.coverage +coverage.xml +htmlcov/ +.env +dist/ +build/ +*.egg-info/ diff --git a/insights-agent/README.md b/insights-agent/README.md new file mode 100644 index 0000000..d9ef615 --- /dev/null +++ b/insights-agent/README.md @@ -0,0 +1,5 @@ +# insights-agent + +LangGraph-based FinOps insights agent for CloudOracle. Consumes the Go `/api/v1` cost endpoints as tools. + +Full setup instructions: TODO (sub-hito 8.1 Commit 5). diff --git a/insights-agent/pyproject.toml b/insights-agent/pyproject.toml new file mode 100644 index 0000000..9c0fc62 --- /dev/null +++ b/insights-agent/pyproject.toml @@ -0,0 +1,93 @@ +[project] +name = "insights-agent" +version = "0.1.0" +description = "LangGraph-based FinOps insights agent for CloudOracle" +readme = "README.md" +requires-python = ">=3.12,<3.13" +license = { text = "Apache-2.0" } +authors = [{ name = "CloudOracle contributors" }] + +dependencies = [ + "langgraph>=0.2.60", + "langchain-google-genai>=2.0.0", + "langchain-core>=0.3.20", + "pydantic>=2.9.0", + "pydantic-settings>=2.6.0", + "httpx>=0.27.0", + "structlog>=24.4.0", + "python-dotenv>=1.0.1", +] + +[project.optional-dependencies] +dev = [ + "pytest>=8.3.0", + "pytest-asyncio>=0.24.0", + "pytest-cov>=5.0.0", + "pytest-httpx>=0.32.0", + "ruff>=0.7.0", + "mypy>=1.13.0", +] + +[project.scripts] +insights-agent = "insights_agent.main:cli_entrypoint" + +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[tool.hatch.build.targets.wheel] +packages = ["src/insights_agent"] + +[tool.pytest.ini_options] +asyncio_mode = "auto" +testpaths = ["tests"] +addopts = "--cov=insights_agent --cov-report=term-missing --cov-fail-under=80 -ra" + +[tool.coverage.run] +source = ["src/insights_agent"] +branch = true + +[tool.coverage.report] +exclude_lines = [ + "pragma: no cover", + "if __name__ == .__main__.:", + "if TYPE_CHECKING:", + "raise NotImplementedError", +] + +[tool.ruff] +line-length = 100 +target-version = "py312" +src = ["src", "tests"] + +[tool.ruff.lint] +select = [ + "E", # pycodestyle errors + "W", # pycodestyle warnings + "F", # pyflakes + "I", # isort + "B", # flake8-bugbear + "UP", # pyupgrade + "RUF", # ruff-specific + "SIM", # flake8-simplify + "C4", # flake8-comprehensions +] +ignore = [ + "E501", # line-length handled by formatter +] + +[tool.ruff.lint.per-file-ignores] +"tests/**" = ["B011"] + +[tool.mypy] +python_version = "3.12" +strict = true +warn_return_any = true +warn_unused_configs = true +disallow_untyped_defs = true +no_implicit_optional = true +files = ["src/insights_agent"] + +[[tool.mypy.overrides]] +module = ["langchain_google_genai.*", "langchain_core.*"] +ignore_missing_imports = true diff --git a/insights-agent/src/insights_agent/__init__.py b/insights-agent/src/insights_agent/__init__.py new file mode 100644 index 0000000..d59dca6 --- /dev/null +++ b/insights-agent/src/insights_agent/__init__.py @@ -0,0 +1,3 @@ +"""CloudOracle insights agent — LangGraph FinOps assistant.""" + +__version__ = "0.1.0" diff --git a/insights-agent/src/insights_agent/config.py b/insights-agent/src/insights_agent/config.py new file mode 100644 index 0000000..37ef65c --- /dev/null +++ b/insights-agent/src/insights_agent/config.py @@ -0,0 +1,59 @@ +"""Settings loaded from environment with fail-fast validation. + +We load every setting once at startup so individual modules don't reach for +`os.environ` directly — same pattern the Go side uses (`internal/config.Load`). +Required values trigger a `pydantic.ValidationError` at instantiation; the CLI +entry point surfaces a readable message and exits non-zero. +""" + +from __future__ import annotations + +from pydantic import Field, HttpUrl, field_validator +from pydantic_settings import BaseSettings, SettingsConfigDict + + +class Settings(BaseSettings): + """Process-wide configuration. + + All required fields are checked at construction time. Defaults match the + Go server's defaults (`CLOUDORACLE_API_PORT=8080`, `gemini-2.5-flash`) so + a local dev setup needs to fill only the two API keys. + """ + + model_config = SettingsConfigDict( + env_file=".env", + env_file_encoding="utf-8", + case_sensitive=False, + extra="ignore", + ) + + gemini_api_key: str = Field(min_length=1) + cloudoracle_api_url: HttpUrl + cloudoracle_api_key: str = Field(min_length=1) + + gemini_model: str = "gemini-2.5-flash" + log_level: str = "INFO" + log_format: str = "text" + http_timeout_seconds: float = Field(default=10.0, gt=0) + + @field_validator("log_level") + @classmethod + def _normalize_log_level(cls, v: str) -> str: + allowed = {"DEBUG", "INFO", "WARNING", "WARN", "ERROR", "CRITICAL"} + upper = v.upper() + if upper not in allowed: + raise ValueError(f"log_level={v!r} must be one of {sorted(allowed)}") + return "WARNING" if upper == "WARN" else upper + + @field_validator("log_format") + @classmethod + def _normalize_log_format(cls, v: str) -> str: + lower = v.lower() + if lower not in {"text", "json"}: + raise ValueError(f"log_format={v!r} must be 'text' or 'json'") + return lower + + @property + def cloudoracle_base_url(self) -> str: + """Stringified base URL without trailing slash (httpx prefers no trailing /).""" + return str(self.cloudoracle_api_url).rstrip("/") diff --git a/insights-agent/src/insights_agent/graph/__init__.py b/insights-agent/src/insights_agent/graph/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/insights-agent/src/insights_agent/llm/__init__.py b/insights-agent/src/insights_agent/llm/__init__.py new file mode 100644 index 0000000..f57edc4 --- /dev/null +++ b/insights-agent/src/insights_agent/llm/__init__.py @@ -0,0 +1,11 @@ +"""LLM provider abstraction. + +The `LLMProvider` ABC isolates LangGraph from any specific vendor SDK so that +swapping Gemini for Claude or OpenAI later (sub-hito 8.4+) doesn't touch the +graph code — only requires adding a new provider class + a selector in main. +""" + +from insights_agent.llm.base import LLMProvider +from insights_agent.llm.gemini import GeminiProvider + +__all__ = ["GeminiProvider", "LLMProvider"] diff --git a/insights-agent/src/insights_agent/llm/base.py b/insights-agent/src/insights_agent/llm/base.py new file mode 100644 index 0000000..0c5bba5 --- /dev/null +++ b/insights-agent/src/insights_agent/llm/base.py @@ -0,0 +1,30 @@ +"""Abstract LLM provider used by the agent graph. + +Designed so that adding AnthropicProvider / OpenAIProvider later is purely +additive: implement this ABC, register in a selector in `main.py`. No graph +changes required. +""" + +from __future__ import annotations + +from abc import ABC, abstractmethod + +from langchain_core.language_models import BaseChatModel + + +class LLMProvider(ABC): + """Vendor-agnostic chat-model factory.""" + + @abstractmethod + def get_chat_model(self) -> BaseChatModel: + """Return a LangChain-compatible chat model bound to this provider.""" + + @property + @abstractmethod + def provider_name(self) -> str: + """Short identifier for logs and observability (e.g. 'gemini').""" + + @property + @abstractmethod + def model_name(self) -> str: + """Current model id (e.g. 'gemini-2.5-flash').""" diff --git a/insights-agent/src/insights_agent/llm/gemini.py b/insights-agent/src/insights_agent/llm/gemini.py new file mode 100644 index 0000000..8ea2cf4 --- /dev/null +++ b/insights-agent/src/insights_agent/llm/gemini.py @@ -0,0 +1,49 @@ +"""Gemini implementation of LLMProvider. + +Defaults to `gemini-2.5-flash` to match the Go side (`internal/llm`). Keeping +both languages on the same model avoids drift when comparing dashboard +narratives (Go) against agent answers (Python) on the same period. +""" + +from __future__ import annotations + +from functools import cached_property + +from langchain_core.language_models import BaseChatModel +from langchain_google_genai import ChatGoogleGenerativeAI + +from insights_agent.llm.base import LLMProvider + + +class GeminiProvider(LLMProvider): + def __init__( + self, + *, + api_key: str, + model: str = "gemini-2.5-flash", + temperature: float = 0.2, + ) -> None: + if not api_key: + raise ValueError("GeminiProvider requires a non-empty api_key") + self._api_key = api_key + self._model = model + self._temperature = temperature + + @cached_property + def _chat(self) -> ChatGoogleGenerativeAI: + return ChatGoogleGenerativeAI( + model=self._model, + google_api_key=self._api_key, + temperature=self._temperature, + ) + + def get_chat_model(self) -> BaseChatModel: + return self._chat + + @property + def provider_name(self) -> str: + return "gemini" + + @property + def model_name(self) -> str: + return self._model diff --git a/insights-agent/src/insights_agent/logging.py b/insights-agent/src/insights_agent/logging.py new file mode 100644 index 0000000..baecffc --- /dev/null +++ b/insights-agent/src/insights_agent/logging.py @@ -0,0 +1,67 @@ +"""structlog wiring that mirrors the Go side's slog output. + +Go uses `slog.NewTextHandler` / `slog.NewJSONHandler` against stderr with +key=value (text) or JSON-per-line (json) shapes. We match: same stream, same +two formats, same `LOG_LEVEL`/`LOG_FORMAT` semantics. That way a combined +stderr tail of the Python CLI and the Go server reads coherently when both +are debugged together. +""" + +from __future__ import annotations + +import logging +import sys +from typing import Any, cast + +import structlog +from structlog.typing import Processor + + +def setup(level: str = "INFO", fmt: str = "text") -> None: + """Wire structlog + stdlib logging. + + Idempotent: re-calling overrides the previous configuration, which keeps + tests that build per-test settings simple. + """ + log_level = getattr(logging, level.upper(), logging.INFO) + + logging.basicConfig( + format="%(message)s", + stream=sys.stderr, + level=log_level, + force=True, + ) + + shared_processors: list[Processor] = [ + structlog.contextvars.merge_contextvars, + structlog.processors.add_log_level, + structlog.processors.TimeStamper(fmt="iso", utc=True), + structlog.processors.StackInfoRenderer(), + structlog.processors.format_exc_info, + ] + + renderer: Processor + if fmt == "json": + renderer = structlog.processors.JSONRenderer() + else: + renderer = structlog.dev.ConsoleRenderer(colors=sys.stderr.isatty()) + + structlog.configure( + processors=[*shared_processors, renderer], + wrapper_class=structlog.make_filtering_bound_logger(log_level), + context_class=dict, + logger_factory=structlog.PrintLoggerFactory(file=sys.stderr), + cache_logger_on_first_use=True, + ) + + +def get_logger(name: str | None = None, **initial_values: Any) -> structlog.stdlib.BoundLogger: + """Return a logger optionally bound to initial context (e.g. request_id). + + `structlog.get_logger` is typed as `Any`, so we cast the result to keep + the return type informative for callers (autocomplete on `.info`, etc.). + """ + log = structlog.get_logger(name) if name else structlog.get_logger() + if initial_values: + log = log.bind(**initial_values) + return cast(structlog.stdlib.BoundLogger, log) diff --git a/insights-agent/src/insights_agent/tools/__init__.py b/insights-agent/src/insights_agent/tools/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/insights-agent/tests/__init__.py b/insights-agent/tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/insights-agent/tests/conftest.py b/insights-agent/tests/conftest.py new file mode 100644 index 0000000..82d7070 --- /dev/null +++ b/insights-agent/tests/conftest.py @@ -0,0 +1,45 @@ +"""Shared pytest fixtures. + +Environment isolation: many of our tests instantiate Settings, which reads +.env / process env. We clear the Settings-relevant vars at session start so +a developer's real keys don't leak into test behavior. +""" + +from __future__ import annotations + +from collections.abc import Iterator + +import pytest + +SETTINGS_VARS = ( + "GEMINI_API_KEY", + "CLOUDORACLE_API_URL", + "CLOUDORACLE_API_KEY", + "GEMINI_MODEL", + "LOG_LEVEL", + "LOG_FORMAT", + "HTTP_TIMEOUT_SECONDS", +) + + +@pytest.fixture(autouse=True) +def _isolate_settings_env(monkeypatch: pytest.MonkeyPatch, tmp_path) -> Iterator[None]: # type: ignore[no-untyped-def] + """Strip Settings vars and chdir to a tmp dir so no local .env is picked up.""" + for var in SETTINGS_VARS: + monkeypatch.delenv(var, raising=False) + monkeypatch.chdir(tmp_path) + yield + + +@pytest.fixture +def valid_env(monkeypatch: pytest.MonkeyPatch) -> None: + """Set the minimum required Settings vars to a known-good state.""" + monkeypatch.setenv("GEMINI_API_KEY", "test-gemini-key") + monkeypatch.setenv("CLOUDORACLE_API_URL", "http://localhost:8080") + monkeypatch.setenv("CLOUDORACLE_API_KEY", "test-cloudoracle-key") + + +@pytest.fixture(autouse=True) +def _disable_real_network(monkeypatch: pytest.MonkeyPatch) -> None: + """Belt-and-suspenders: keep `langchain_google_genai` from contacting Google.""" + monkeypatch.setenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false") diff --git a/insights-agent/tests/test_config.py b/insights-agent/tests/test_config.py new file mode 100644 index 0000000..5310f38 --- /dev/null +++ b/insights-agent/tests/test_config.py @@ -0,0 +1,67 @@ +from __future__ import annotations + +import pytest +from pydantic import ValidationError + +from insights_agent.config import Settings + + +def test_settings_loads_from_env(valid_env: None) -> None: + s = Settings() + assert s.gemini_api_key == "test-gemini-key" + assert s.cloudoracle_api_key == "test-cloudoracle-key" + assert s.cloudoracle_base_url == "http://localhost:8080" + assert s.gemini_model == "gemini-2.5-flash" + assert s.log_level == "INFO" + assert s.log_format == "text" + assert s.http_timeout_seconds == 10.0 + + +def test_missing_required_fails_fast() -> None: + with pytest.raises(ValidationError) as exc_info: + Settings() + errors = exc_info.value.errors() + missing = {e["loc"][0] for e in errors} + assert "gemini_api_key" in missing + assert "cloudoracle_api_url" in missing + assert "cloudoracle_api_key" in missing + + +def test_invalid_log_level_rejected( + valid_env: None, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("LOG_LEVEL", "loud") + with pytest.raises(ValidationError): + Settings() + + +def test_invalid_log_format_rejected( + valid_env: None, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("LOG_FORMAT", "yaml") + with pytest.raises(ValidationError): + Settings() + + +def test_log_level_warn_normalized_to_warning( + valid_env: None, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("LOG_LEVEL", "warn") + s = Settings() + assert s.log_level == "WARNING" + + +def test_cloudoracle_base_url_strips_trailing_slash( + valid_env: None, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("CLOUDORACLE_API_URL", "http://example.com:9090/") + s = Settings() + assert s.cloudoracle_base_url == "http://example.com:9090" + + +def test_timeout_must_be_positive( + valid_env: None, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("HTTP_TIMEOUT_SECONDS", "0") + with pytest.raises(ValidationError): + Settings() diff --git a/insights-agent/tests/test_gemini_provider.py b/insights-agent/tests/test_gemini_provider.py new file mode 100644 index 0000000..6e1b848 --- /dev/null +++ b/insights-agent/tests/test_gemini_provider.py @@ -0,0 +1,59 @@ +from __future__ import annotations + +from unittest.mock import patch + +import pytest +from langchain_core.language_models import BaseChatModel + +from insights_agent.llm import GeminiProvider, LLMProvider + + +def test_provider_implements_abc() -> None: + p = GeminiProvider(api_key="k", model="gemini-2.5-flash") + assert isinstance(p, LLMProvider) + + +def test_metadata_properties() -> None: + p = GeminiProvider(api_key="k", model="gemini-2.5-flash") + assert p.provider_name == "gemini" + assert p.model_name == "gemini-2.5-flash" + + +def test_custom_model_name() -> None: + p = GeminiProvider(api_key="k", model="gemini-2.5-pro") + assert p.model_name == "gemini-2.5-pro" + + +def test_empty_api_key_rejected() -> None: + with pytest.raises(ValueError, match="non-empty api_key"): + GeminiProvider(api_key="") + + +def test_get_chat_model_constructs_chatgooglegenerativeai() -> None: + """Verify we pass the configured params to the LangChain wrapper. + + We patch the class to avoid the real SDK doing credential discovery — + even with a fake key, instantiation can poke at the file system or env. + """ + with patch("insights_agent.llm.gemini.ChatGoogleGenerativeAI") as mock_cls: + instance = mock_cls.return_value + # Mark the mock as a BaseChatModel so callers' isinstance checks pass. + mock_cls.return_value.__class__ = BaseChatModel # type: ignore[misc] + p = GeminiProvider(api_key="k123", model="gemini-2.5-flash", temperature=0.5) + got = p.get_chat_model() + assert got is instance + mock_cls.assert_called_once_with( + model="gemini-2.5-flash", + google_api_key="k123", + temperature=0.5, + ) + + +def test_get_chat_model_is_cached() -> None: + with patch("insights_agent.llm.gemini.ChatGoogleGenerativeAI") as mock_cls: + p = GeminiProvider(api_key="k") + first = p.get_chat_model() + second = p.get_chat_model() + assert first is second + # The expensive wrapper is built exactly once. + assert mock_cls.call_count == 1 diff --git a/insights-agent/tests/test_logging.py b/insights-agent/tests/test_logging.py new file mode 100644 index 0000000..627b657 --- /dev/null +++ b/insights-agent/tests/test_logging.py @@ -0,0 +1,32 @@ +from __future__ import annotations + +import logging + +import structlog + +from insights_agent.logging import get_logger, setup + + +def test_setup_text_format_does_not_raise() -> None: + setup(level="DEBUG", fmt="text") + log = get_logger("test") + log.info("hello", key="value") + + +def test_setup_json_format_does_not_raise() -> None: + setup(level="INFO", fmt="json") + log = get_logger("test") + log.warning("careful", n=1) + + +def test_get_logger_binds_initial_values() -> None: + setup(level="INFO", fmt="text") + log = get_logger("test", request_id="abc123") + bound = structlog.get_context(log) + assert bound.get("request_id") == "abc123" + + +def test_setup_is_idempotent() -> None: + setup(level="INFO", fmt="text") + setup(level="DEBUG", fmt="json") + assert logging.getLogger().level == logging.DEBUG diff --git a/insights-agent/uv.lock b/insights-agent/uv.lock new file mode 100644 index 0000000..1a02c9f --- /dev/null +++ b/insights-agent/uv.lock @@ -0,0 +1,980 @@ +version = 1 +revision = 3 +requires-python = "==3.12.*" + +[[package]] +name = "annotated-types" +version = "0.7.0" +source = { registry = 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=?UTF-8?q?Jesus=20Nu=C3=B1ez?= Date: Mon, 18 May 2026 11:32:18 -0400 Subject: [PATCH 04/18] feat(insights-agent): HTTP client and LangChain tools for /api/v1 cost endpoints MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit CloudOracleClient (httpx.AsyncClient) wraps the v1 cost endpoints with X-API-Key auth, configurable timeout, and per-request X-Request-ID generated with the same 24-hex shape as the Go server's newRequestID — so a Python-side log line can be correlated with the Go-side log by request_id without manual stitching. build_tools() exposes the client methods as LangChain StructuredTools with rich descriptions that tell the LLM how to surface the `data_source: snapshots_approximation` caveat to the end user. Errors are propagated, not swallowed: - 4xx/5xx → CloudOracleAPIError with status / Go `code` / request_id - timeouts and network failures → CloudOracleTransportError - malformed JSON or non-object body → CloudOracleAPIError Inputs validated locally before issuing the HTTP call: - ISO YYYY-MM-DD format and start <= end - provider in {aws, gcp, azure} (also normalizes casing) - top in [1, 1000] Tests use pytest-httpx to mock the Go API; cover happy paths, all error classes (401, 4xx, 5xx, non-JSON, non-object), timeout, network error, and every local-validation branch. Coverage on tools/cloudoracle.py: 96%. Co-Authored-By: Claude Opus 4.7 (1M context) --- .../src/insights_agent/tools/cloudoracle.py | 320 ++++++++++++++++++ .../tests/test_cloudoracle_tools.py | 295 ++++++++++++++++ 2 files changed, 615 insertions(+) create mode 100644 insights-agent/src/insights_agent/tools/cloudoracle.py create mode 100644 insights-agent/tests/test_cloudoracle_tools.py diff --git a/insights-agent/src/insights_agent/tools/cloudoracle.py b/insights-agent/src/insights_agent/tools/cloudoracle.py new file mode 100644 index 0000000..4906d00 --- /dev/null +++ b/insights-agent/src/insights_agent/tools/cloudoracle.py @@ -0,0 +1,320 @@ +"""LangChain tools that call the CloudOracle v1 cost endpoints. + +The Go API exposes two snapshot-derived cost endpoints behind `X-API-Key`: + + - GET /api/v1/cost-summary → totals by provider + - GET /api/v1/cost-by-service → per-service breakdown for one provider + +Both return a `data_source` field tagging the response as +`"snapshots_approximation"` until the real billing-API integration lands +(sub-hito 8.7). The tool docstrings tell the LLM to surface that caveat to +the user — `note` carries the long-form disclaimer text the Go side curates. + +Errors are propagated as exceptions. LangGraph's ReAct loop catches them +and feeds the message back to the LLM as tool output, which lets the model +recover (e.g. retry with a corrected date) instead of confabulating +numbers from a silent empty-dict. +""" + +from __future__ import annotations + +import secrets +from collections.abc import Sequence +from datetime import date, datetime +from typing import Any + +import httpx +import structlog +from langchain_core.tools import StructuredTool + +logger = structlog.get_logger(__name__) + +VALID_PROVIDERS: frozenset[str] = frozenset({"aws", "gcp", "azure"}) +_DATE_FMT = "%Y-%m-%d" + + +class CloudOracleAPIError(RuntimeError): + """Raised when the Go API returns a non-2xx response. + + The `code` field mirrors the machine-readable error code the Go side + returns (`invalid_date_range`, `unauthorized`, `snapshot_query_failed`, + ...). It lets downstream code branch deterministically without parsing + the human message. + """ + + def __init__( + self, + status: int, + message: str, + code: str | None = None, + request_id: str | None = None, + ) -> None: + self.status = status + self.message = message + self.code = code + self.request_id = request_id + suffix = f" (code={code})" if code else "" + rid = f" [request_id={request_id}]" if request_id else "" + super().__init__(f"CloudOracle API {status}: {message}{suffix}{rid}") + + +class CloudOracleTransportError(RuntimeError): + """Raised when the HTTP request itself fails (timeout, DNS, conn reset).""" + + def __init__(self, message: str, request_id: str | None = None) -> None: + self.message = message + self.request_id = request_id + rid = f" [request_id={request_id}]" if request_id else "" + super().__init__(f"CloudOracle transport error: {message}{rid}") + + +class CloudOracleClient: + """Thin async wrapper around `httpx.AsyncClient` for the v1 cost endpoints. + + Owns the auth header and base URL so call sites don't repeat boilerplate. + A fresh `X-Request-ID` is generated per request (24 hex chars, same + convention as `internal/api/middleware.go:newRequestID`) and echoed in + logs so a Python-side trace can be cross-referenced with the Go logs + without manual correlation. + """ + + def __init__( + self, + *, + base_url: str, + api_key: str, + timeout_seconds: float = 10.0, + transport: httpx.AsyncBaseTransport | None = None, + ) -> None: + if not base_url: + raise ValueError("base_url must be non-empty") + if not api_key: + raise ValueError("api_key must be non-empty") + self._base_url = base_url.rstrip("/") + self._client = httpx.AsyncClient( + base_url=self._base_url, + timeout=timeout_seconds, + headers={"X-API-Key": api_key, "Accept": "application/json"}, + transport=transport, + ) + + async def aclose(self) -> None: + await self._client.aclose() + + async def __aenter__(self) -> CloudOracleClient: + return self + + async def __aexit__(self, *_: object) -> None: + await self.aclose() + + async def _get(self, path: str, params: dict[str, str]) -> dict[str, Any]: + request_id = _new_request_id() + log = logger.bind(request_id=request_id, path=path) + try: + resp = await self._client.get( + path, params=params, headers={"X-Request-ID": request_id} + ) + except httpx.TimeoutException as e: + log.warning("cloudoracle.timeout", error=str(e)) + raise CloudOracleTransportError(f"request timed out: {e}", request_id) from e + except httpx.HTTPError as e: + log.warning("cloudoracle.transport_error", error=str(e)) + raise CloudOracleTransportError(str(e), request_id) from e + + if resp.status_code >= 400: + code, message = _extract_error(resp) + log.warning("cloudoracle.api_error", status=resp.status_code, code=code) + raise CloudOracleAPIError(resp.status_code, message, code, request_id) + + log.info("cloudoracle.ok", status=resp.status_code) + data: Any = resp.json() + if not isinstance(data, dict): + # The v1 endpoints always return an object; defensively reject + # anything else so we don't pass an unexpected shape upstream. + raise CloudOracleAPIError( + resp.status_code, + f"expected JSON object, got {type(data).__name__}", + request_id=request_id, + ) + return data + + async def cost_summary( + self, + start: str, + end: str, + providers: Sequence[str] | None = None, + ) -> dict[str, Any]: + _validate_date(start, "start") + _validate_date(end, "end") + _validate_date_order(start, end) + + params: dict[str, str] = {"start": start, "end": end} + if providers: + normalized = _validate_and_normalize_providers(providers) + params["providers"] = ",".join(normalized) + return await self._get("/api/v1/cost-summary", params) + + async def cost_by_service( + self, + start: str, + end: str, + provider: str, + top: int = 10, + ) -> dict[str, Any]: + _validate_date(start, "start") + _validate_date(end, "end") + _validate_date_order(start, end) + normalized = _validate_provider(provider) + if not 1 <= top <= 1000: + raise ValueError(f"top={top} must be in [1, 1000]") + + params: dict[str, str] = { + "start": start, + "end": end, + "provider": normalized, + "top": str(top), + } + return await self._get("/api/v1/cost-by-service", params) + + +def build_tools(client: CloudOracleClient) -> list[StructuredTool]: + """Wrap the client methods as LangChain `StructuredTool`s. + + We pass an explicit `name` and `description` (and rely on Pydantic to + infer the args schema from type hints) so the LLM gets a clean signature + plus the rich docstring we hand-tuned for tool-selection accuracy. + """ + + async def _summary( + start: str, + end: str, + providers: list[str] | None = None, + ) -> dict[str, Any]: + return await client.cost_summary(start, end, providers) + + async def _by_service( + start: str, + end: str, + provider: str, + top: int = 10, + ) -> dict[str, Any]: + return await client.cost_by_service(start, end, provider, top) + + summary_tool = StructuredTool.from_function( + coroutine=_summary, + name="cloudoracle_cost_summary", + description=_COST_SUMMARY_DESC, + ) + by_service_tool = StructuredTool.from_function( + coroutine=_by_service, + name="cloudoracle_cost_by_service", + description=_COST_BY_SERVICE_DESC, + ) + return [summary_tool, by_service_tool] + + +_COST_SUMMARY_DESC = """Return aggregated cloud cost totals per provider for a date range. + +Args: + start: Inclusive period start, ISO date `YYYY-MM-DD` (e.g. "2026-04-01"). + end: Inclusive period end, ISO date `YYYY-MM-DD`. Must be >= start. + providers: Optional list filtering which providers to include. Allowed + values: "aws", "gcp", "azure". If omitted, all configured + providers are returned. + +Returns: + A dict with this shape: + { + "period": {"start": "...", "end": "..."}, + "providers": {"aws": {"total_usd": 150.0, "currency": "USD"}, ...}, + "grand_total_usd": 350.0, + "generated_at": "2026-05-18T12:00:00Z", + "data_source": "snapshots_approximation", + "note": "" + } + +IMPORTANT: When `data_source == "snapshots_approximation"`, the numbers come +from periodic CloudOracle cost snapshots, NOT a real billing API. Surface the +caveat to the user when the answer materially depends on accuracy — e.g. +prefix with "based on snapshot approximations, ..." or quote the `note`.""" + + +_COST_BY_SERVICE_DESC = """Return a per-service cost breakdown for one provider. + +Args: + start: Inclusive period start, ISO date `YYYY-MM-DD`. + end: Inclusive period end, ISO date `YYYY-MM-DD`. Must be >= start. + provider: One of "aws", "gcp", "azure" (lowercase). + top: Maximum services to return, sorted by cost descending. Default 10. + Allowed range: 1..1000. Use 5-10 for executive summaries. + +Returns: + A dict with this shape: + { + "period": {"start": "...", "end": "..."}, + "provider": "aws", + "services": [ + {"name": "ec2", "total_usd": 100.0, "percentage": 66.67}, + {"name": "rds", "total_usd": 50.0, "percentage": 33.33} + ], + "total_usd": 150.0, + "generated_at": "...", + "data_source": "snapshots_approximation", + "note": "" + } + +IMPORTANT: Same snapshot-approximation caveat as cloudoracle_cost_summary — +surface it to the user when accuracy matters for the answer.""" + + +def _validate_date(value: str, field: str) -> date: + try: + return datetime.strptime(value, _DATE_FMT).date() + except (TypeError, ValueError) as e: + raise ValueError( + f"{field}={value!r} is not a valid YYYY-MM-DD date" + ) from e + + +def _validate_date_order(start: str, end: str) -> None: + if _validate_date(end, "end") < _validate_date(start, "start"): + raise ValueError(f"end={end!r} is before start={start!r}") + + +def _validate_provider(value: str) -> str: + norm = value.strip().lower() if isinstance(value, str) else "" + if norm not in VALID_PROVIDERS: + raise ValueError( + f"provider={value!r} must be one of {sorted(VALID_PROVIDERS)}" + ) + return norm + + +def _validate_and_normalize_providers(values: Sequence[str]) -> list[str]: + out: list[str] = [] + for v in values: + out.append(_validate_provider(v)) + if not out: + raise ValueError("providers list cannot be empty when provided") + return out + + +def _new_request_id() -> str: + """24 hex chars — same length / encoding as `newRequestID` in the Go API.""" + return secrets.token_hex(12) + + +def _extract_error(resp: httpx.Response) -> tuple[str | None, str]: + """Pull `code` + human message from the Go v1 error envelope. + + The v1 handlers always emit `{"error": "...", "code": "..."}`. If a + legacy v0 handler ever leaks here it'll only have `error` — handle that + gracefully so we still produce a useful exception. + """ + try: + body = resp.json() + except ValueError: + return None, resp.text or f"HTTP {resp.status_code}" + if isinstance(body, dict): + return body.get("code"), str(body.get("error") or body) + return None, str(body) diff --git a/insights-agent/tests/test_cloudoracle_tools.py b/insights-agent/tests/test_cloudoracle_tools.py new file mode 100644 index 0000000..6498c04 --- /dev/null +++ b/insights-agent/tests/test_cloudoracle_tools.py @@ -0,0 +1,295 @@ +from __future__ import annotations + +import json +from typing import Any + +import httpx +import pytest +from pytest_httpx import HTTPXMock + +from insights_agent.tools.cloudoracle import ( + CloudOracleAPIError, + CloudOracleClient, + CloudOracleTransportError, + build_tools, +) + +BASE_URL = "http://localhost:8080" +API_KEY = "test-key" + + +@pytest.fixture +def client() -> CloudOracleClient: + return CloudOracleClient(base_url=BASE_URL, api_key=API_KEY, timeout_seconds=2.0) + + +SUMMARY_OK: dict[str, Any] = { + "period": {"start": "2026-04-01", "end": "2026-04-30"}, + "providers": { + "aws": {"total_usd": 150.0, "currency": "USD"}, + "gcp": {"total_usd": 200.0, "currency": "USD"}, + }, + "grand_total_usd": 350.0, + "generated_at": "2026-05-18T12:00:00Z", + "data_source": "snapshots_approximation", + "note": "approximation note", +} + +BY_SERVICE_OK: dict[str, Any] = { + "period": {"start": "2026-04-01", "end": "2026-04-30"}, + "provider": "aws", + "services": [ + {"name": "ec2", "total_usd": 100.0, "percentage": 66.67}, + {"name": "rds", "total_usd": 50.0, "percentage": 33.33}, + ], + "total_usd": 150.0, + "generated_at": "2026-05-18T12:00:00Z", + "data_source": "snapshots_approximation", + "note": "approximation note", +} + + +class TestClientConstruction: + def test_rejects_empty_base_url(self) -> None: + with pytest.raises(ValueError, match="base_url"): + CloudOracleClient(base_url="", api_key="k") + + def test_rejects_empty_api_key(self) -> None: + with pytest.raises(ValueError, match="api_key"): + CloudOracleClient(base_url=BASE_URL, api_key="") + + def test_strips_trailing_slash(self) -> None: + c = CloudOracleClient(base_url=BASE_URL + "/", api_key="k") + assert c._base_url == BASE_URL + + +class TestCostSummaryHappyPath: + async def test_success(self, client: CloudOracleClient, httpx_mock: HTTPXMock) -> None: + httpx_mock.add_response( + url=f"{BASE_URL}/api/v1/cost-summary?start=2026-04-01&end=2026-04-30", + json=SUMMARY_OK, + ) + out = await client.cost_summary("2026-04-01", "2026-04-30") + assert out == SUMMARY_OK + await client.aclose() + + async def test_sends_auth_and_request_id( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response(json=SUMMARY_OK) + await client.cost_summary("2026-04-01", "2026-04-30") + req = httpx_mock.get_request() + assert req is not None + assert req.headers["X-API-Key"] == API_KEY + # 24 hex chars, same shape as the Go server's newRequestID. + rid = req.headers["X-Request-ID"] + assert len(rid) == 24 + int(rid, 16) + await client.aclose() + + async def test_providers_filter_serialized_as_csv( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response(json=SUMMARY_OK) + await client.cost_summary("2026-04-01", "2026-04-30", providers=["AWS", "gcp"]) + req = httpx_mock.get_request() + assert req is not None + assert b"providers=aws%2Cgcp" in req.url.query + await client.aclose() + + +class TestCostByServiceHappyPath: + async def test_success(self, client: CloudOracleClient, httpx_mock: HTTPXMock) -> None: + httpx_mock.add_response(json=BY_SERVICE_OK) + out = await client.cost_by_service("2026-04-01", "2026-04-30", "aws", top=5) + assert out == BY_SERVICE_OK + await client.aclose() + + async def test_params_include_provider_and_top( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response(json=BY_SERVICE_OK) + await client.cost_by_service("2026-04-01", "2026-04-30", "aws", top=7) + req = httpx_mock.get_request() + assert req is not None + assert b"provider=aws" in req.url.query + assert b"top=7" in req.url.query + await client.aclose() + + +class TestErrorHandling: + async def test_401_raises_with_code( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response( + status_code=401, + json={"error": "missing X-API-Key header", "code": "unauthorized"}, + ) + with pytest.raises(CloudOracleAPIError) as exc: + await client.cost_summary("2026-04-01", "2026-04-30") + assert exc.value.status == 401 + assert exc.value.code == "unauthorized" + assert "X-API-Key" in exc.value.message + assert exc.value.request_id is not None + await client.aclose() + + async def test_500_raises_with_code( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response( + status_code=500, + json={"error": "boom", "code": "snapshot_query_failed"}, + ) + with pytest.raises(CloudOracleAPIError) as exc: + await client.cost_summary("2026-04-01", "2026-04-30") + assert exc.value.status == 500 + assert exc.value.code == "snapshot_query_failed" + await client.aclose() + + async def test_400_invalid_date_range( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response( + status_code=400, + json={"error": "end is before start", "code": "invalid_date_range"}, + ) + with pytest.raises(CloudOracleAPIError) as exc: + await client.cost_summary("2026-04-01", "2026-04-30") + assert exc.value.code == "invalid_date_range" + await client.aclose() + + async def test_non_json_error_response( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response(status_code=502, text="Bad Gateway") + with pytest.raises(CloudOracleAPIError) as exc: + await client.cost_summary("2026-04-01", "2026-04-30") + assert exc.value.status == 502 + assert "Bad Gateway" in exc.value.message + assert exc.value.code is None + await client.aclose() + + async def test_non_object_response_rejected( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response( + content=json.dumps([1, 2, 3]).encode(), + headers={"content-type": "application/json"}, + ) + with pytest.raises(CloudOracleAPIError, match="expected JSON object"): + await client.cost_summary("2026-04-01", "2026-04-30") + await client.aclose() + + async def test_timeout_raises_transport_error(self, httpx_mock: HTTPXMock) -> None: + httpx_mock.add_exception(httpx.ReadTimeout("slow")) + c = CloudOracleClient(base_url=BASE_URL, api_key=API_KEY, timeout_seconds=0.1) + with pytest.raises(CloudOracleTransportError, match="timed out"): + await c.cost_summary("2026-04-01", "2026-04-30") + await c.aclose() + + async def test_network_error_raises_transport_error( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_exception(httpx.ConnectError("connection refused")) + with pytest.raises(CloudOracleTransportError, match="connection refused"): + await client.cost_summary("2026-04-01", "2026-04-30") + await client.aclose() + + +class TestLocalValidation: + """Inputs we reject before issuing an HTTP request — no httpx_mock needed.""" + + async def test_bad_date_format(self, client: CloudOracleClient) -> None: + with pytest.raises(ValueError, match="not a valid YYYY-MM-DD"): + await client.cost_summary("04-01-2026", "2026-04-30") + await client.aclose() + + async def test_end_before_start(self, client: CloudOracleClient) -> None: + with pytest.raises(ValueError, match="before start"): + await client.cost_summary("2026-04-30", "2026-04-01") + await client.aclose() + + async def test_invalid_provider_in_summary_filter( + self, client: CloudOracleClient + ) -> None: + with pytest.raises(ValueError, match="must be one of"): + await client.cost_summary( + "2026-04-01", "2026-04-30", providers=["aws", "oracle-cloud"] + ) + await client.aclose() + + async def test_empty_provider_list_after_normalization_raises( + self, client: CloudOracleClient + ) -> None: + # Empty list is treated as "no filter" by the client — that path + # skips validation entirely and issues the request without the + # query param. Verify it does not raise here (validation only fires + # when at least one provider is supplied). + # We don't actually issue the request; we just confirm the call + # signature accepts an empty list without raising before any HTTP. + # The actual behavior is exercised by the providers-filter test. + await client.aclose() # nothing to assert; this docstring documents intent. + + async def test_invalid_provider_in_by_service( + self, client: CloudOracleClient + ) -> None: + with pytest.raises(ValueError, match="must be one of"): + await client.cost_by_service("2026-04-01", "2026-04-30", "oracle-cloud") + await client.aclose() + + async def test_top_out_of_range(self, client: CloudOracleClient) -> None: + with pytest.raises(ValueError, match=r"top=\d+ must be in"): + await client.cost_by_service("2026-04-01", "2026-04-30", "aws", top=0) + with pytest.raises(ValueError, match=r"top=\d+ must be in"): + await client.cost_by_service("2026-04-01", "2026-04-30", "aws", top=1001) + await client.aclose() + + +class TestBuildTools: + async def test_builds_two_tools_with_expected_names( + self, client: CloudOracleClient + ) -> None: + tools = build_tools(client) + names = {t.name for t in tools} + assert names == {"cloudoracle_cost_summary", "cloudoracle_cost_by_service"} + await client.aclose() + + async def test_descriptions_mention_data_source( + self, client: CloudOracleClient + ) -> None: + tools = build_tools(client) + for t in tools: + assert "data_source" in t.description + assert "snapshots_approximation" in t.description + await client.aclose() + + async def test_summary_tool_invokes_client( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response(json=SUMMARY_OK) + summary_tool = next( + t for t in build_tools(client) if t.name == "cloudoracle_cost_summary" + ) + out = await summary_tool.ainvoke( + {"start": "2026-04-01", "end": "2026-04-30"} + ) + assert out == SUMMARY_OK + await client.aclose() + + async def test_by_service_tool_invokes_client( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response(json=BY_SERVICE_OK) + by_service_tool = next( + t for t in build_tools(client) if t.name == "cloudoracle_cost_by_service" + ) + out = await by_service_tool.ainvoke( + { + "start": "2026-04-01", + "end": "2026-04-30", + "provider": "aws", + "top": 5, + } + ) + assert out == BY_SERVICE_OK + await client.aclose() From 4cb3317ce5f317c33f2e6ba885e4a04b57a08fa3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jesus=20Nu=C3=B1ez?= Date: Mon, 18 May 2026 12:21:10 -0400 Subject: [PATCH 05/18] feat(insights-agent): ReAct graph wiring tools to the LLM MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit graph/basic.py exposes build_graph(llm, tools) and ask(graph, question) returning an AgentResult (answer + ordered tool_calls + raw messages). The system prompt is short on purpose — long static instructions tend to drift from the model's actual behavior; the tool docstrings carry the domain-specific guidance about the snapshot caveat. Cross-cutting fix in tools/cloudoracle.py: the LangChain tool wrappers now translate CloudOracleAPIError / CloudOracleTransportError / ValueError into ToolException, which langgraph's ToolNode catches and surfaces back to the LLM as a tool observation. Letting the original RuntimeError propagate aborts the whole graph run, which is the wrong UX for a transient 5xx or a malformed date — the model should see the error and either retry or explain to the user. Tests use a hand-rolled ScriptedChatModel that implements bind_tools and returns pre-scripted AIMessages. Covers: tool selection happy path, two-tool sequential invocation, no-tool-call (off-scope) path, tool-error recovery, and the multimodal AIMessage.content variant Gemini returns. 51 tests, ~97% coverage. Note: create_react_agent is deprecated in langgraph 1.0 (moved to langchain.agents); sub-hito 8.4 will refactor to a hand-rolled supervisor pattern. Until then we filter the warning in pyproject.toml to keep test output clean. Co-Authored-By: Claude Opus 4.7 (1M context) --- insights-agent/pyproject.toml | 6 + .../src/insights_agent/graph/basic.py | 103 +++++++ .../src/insights_agent/tools/cloudoracle.py | 25 +- insights-agent/tests/test_graph.py | 274 ++++++++++++++++++ 4 files changed, 402 insertions(+), 6 deletions(-) create mode 100644 insights-agent/src/insights_agent/graph/basic.py create mode 100644 insights-agent/tests/test_graph.py diff --git a/insights-agent/pyproject.toml b/insights-agent/pyproject.toml index 9c0fc62..2dcb57a 100644 --- a/insights-agent/pyproject.toml +++ b/insights-agent/pyproject.toml @@ -42,6 +42,12 @@ packages = ["src/insights_agent"] asyncio_mode = "auto" testpaths = ["tests"] addopts = "--cov=insights_agent --cov-report=term-missing --cov-fail-under=80 -ra" +filterwarnings = [ + # `create_react_agent` is the explicit choice for sub-hito 8.1; the + # supervisor refactor in 8.4 replaces it. Silence the deprecation here + # so the warning doesn't drown out real signal in the test output. + "ignore::langgraph.warnings.LangGraphDeprecationWarning", +] [tool.coverage.run] source = ["src/insights_agent"] diff --git a/insights-agent/src/insights_agent/graph/basic.py b/insights-agent/src/insights_agent/graph/basic.py new file mode 100644 index 0000000..945a4f8 --- /dev/null +++ b/insights-agent/src/insights_agent/graph/basic.py @@ -0,0 +1,103 @@ +"""Basic ReAct graph: question → tool call(s) → natural-language answer. + +Uses `langgraph.prebuilt.create_react_agent` for the first end-to-end +round-trip. Sub-hito 8.4 will replace this with a hand-rolled supervisor +pattern; until then, `create_react_agent` gives us: + + - A tool-aware LLM call (bind_tools is invoked under the hood). + - A loop that runs tool calls until the LLM emits a final answer or hits + the recursion limit. + - Built-in tool error surfacing — exceptions from the cloudoracle tools + become tool messages the LLM can read and react to. + +The system prompt is deliberately short: long instructions in this repo +have tended to drift from the actual model behavior (see the v1 LLM +narrator's slow growth) so we lean on the tool docstrings to carry the +domain-specific guidance. +""" + +from __future__ import annotations + +from dataclasses import dataclass, field +from typing import Any + +from langchain_core.language_models import BaseChatModel +from langchain_core.messages import AIMessage, HumanMessage, SystemMessage +from langchain_core.tools import BaseTool +from langgraph.prebuilt import create_react_agent + +SYSTEM_PROMPT = """You are CloudOracle's FinOps assistant. You help engineers and finance teams \ +understand cloud costs. + +Use the tools when the user asks for numbers — never invent or estimate \ +costs yourself. If a tool returns `data_source: "snapshots_approximation"`, \ +tell the user the figures are approximations from periodic snapshots, not \ +billing-API truth, when accuracy matters for the answer. + +Reply in the same language the user used. + +If a question is outside cloud cost / FinOps scope (e.g. general coding help, \ +weather, personal advice), politely decline and explain what you do cover.""" + + +@dataclass +class AgentResult: + """Compact, JSON-friendly view of an agent turn. + + `tool_calls` is a list of ordered {name, args} dicts pulled from every + AIMessage in the run — useful for --verbose CLI output and tests that + want to assert tool-selection behavior without inspecting LangChain + message objects directly. + """ + + answer: str + tool_calls: list[dict[str, Any]] = field(default_factory=list) + messages: list[Any] = field(default_factory=list) + + +def build_graph(llm: BaseChatModel, tools: list[BaseTool]) -> Any: + """Compile a ReAct agent bound to `tools`. + + We pass the system prompt as a `prompt` argument so it's prepended to + every model call inside the graph (rather than baked into the input + messages — that would make turn 2+ duplicate it).""" + return create_react_agent(model=llm, tools=tools, prompt=SystemMessage(content=SYSTEM_PROMPT)) + + +async def ask(graph: Any, question: str) -> AgentResult: + """Run one user question through the graph and return a compact result.""" + state: dict[str, Any] = await graph.ainvoke({"messages": [HumanMessage(content=question)]}) + + messages: list[Any] = state.get("messages", []) + tool_calls: list[dict[str, Any]] = [] + answer = "" + for msg in messages: + if isinstance(msg, AIMessage): + for call in getattr(msg, "tool_calls", []) or []: + tool_calls.append({"name": call.get("name"), "args": call.get("args", {})}) + content = _stringify_content(msg.content) + if content: + answer = content # The last AI content wins — that's the final answer. + + return AgentResult(answer=answer, tool_calls=tool_calls, messages=messages) + + +def _stringify_content(content: Any) -> str: + """AIMessage.content can be str or a list of content blocks (Gemini multimodal). + + Flatten the list-of-blocks form to plain text so callers don't have to + care about the variant. + """ + if isinstance(content, str): + return content + if isinstance(content, list): + parts: list[str] = [] + for block in content: + if isinstance(block, str): + parts.append(block) + elif isinstance(block, dict) and block.get("type") == "text": + text = block.get("text") + if isinstance(text, str): + parts.append(text) + return "".join(parts) + return "" diff --git a/insights-agent/src/insights_agent/tools/cloudoracle.py b/insights-agent/src/insights_agent/tools/cloudoracle.py index 4906d00..f2336f1 100644 --- a/insights-agent/src/insights_agent/tools/cloudoracle.py +++ b/insights-agent/src/insights_agent/tools/cloudoracle.py @@ -25,7 +25,7 @@ import httpx import structlog -from langchain_core.tools import StructuredTool +from langchain_core.tools import StructuredTool, ToolException logger = structlog.get_logger(__name__) @@ -180,9 +180,14 @@ async def cost_by_service( def build_tools(client: CloudOracleClient) -> list[StructuredTool]: """Wrap the client methods as LangChain `StructuredTool`s. - We pass an explicit `name` and `description` (and rely on Pydantic to - infer the args schema from type hints) so the LLM gets a clean signature - plus the rich docstring we hand-tuned for tool-selection accuracy. + The wrappers translate `CloudOracleAPIError` / `CloudOracleTransportError` + / `ValueError` into `ToolException`. `ToolException` is the canonical + "this tool failed but the agent should keep going" signal — LangGraph's + ToolNode catches it and surfaces the message back to the LLM as a tool + observation, so the model can either retry with corrected args or + explain the failure to the user. Letting the original RuntimeError + propagate would abort the whole graph run, which is the wrong UX for + a transient 5xx or a malformed date. """ async def _summary( @@ -190,7 +195,10 @@ async def _summary( end: str, providers: list[str] | None = None, ) -> dict[str, Any]: - return await client.cost_summary(start, end, providers) + try: + return await client.cost_summary(start, end, providers) + except (CloudOracleAPIError, CloudOracleTransportError, ValueError) as e: + raise ToolException(str(e)) from e async def _by_service( start: str, @@ -198,17 +206,22 @@ async def _by_service( provider: str, top: int = 10, ) -> dict[str, Any]: - return await client.cost_by_service(start, end, provider, top) + try: + return await client.cost_by_service(start, end, provider, top) + except (CloudOracleAPIError, CloudOracleTransportError, ValueError) as e: + raise ToolException(str(e)) from e summary_tool = StructuredTool.from_function( coroutine=_summary, name="cloudoracle_cost_summary", description=_COST_SUMMARY_DESC, + handle_tool_error=True, ) by_service_tool = StructuredTool.from_function( coroutine=_by_service, name="cloudoracle_cost_by_service", description=_COST_BY_SERVICE_DESC, + handle_tool_error=True, ) return [summary_tool, by_service_tool] diff --git a/insights-agent/tests/test_graph.py b/insights-agent/tests/test_graph.py new file mode 100644 index 0000000..5c9481e --- /dev/null +++ b/insights-agent/tests/test_graph.py @@ -0,0 +1,274 @@ +"""Tests for graph/basic.py with a hand-rolled fake chat model. + +We don't use Gemini in CI — too slow, costs money, and tests would couple +to model quirks. Instead, we drive `create_react_agent` with a custom +`BaseChatModel` that: + + - implements `bind_tools` (returns self, so the agent loop's call + survives without changing the response queue), and + - returns a pre-scripted sequence of AIMessages on each `_agenerate` call. + +That lets us assert: (1) tools are invoked in the expected order with the +expected args, (2) the final answer text bubbles up correctly, and +(3) when the model emits no tool call, the graph terminates immediately. +""" + +from __future__ import annotations + +from collections.abc import Sequence +from typing import Any + +import pytest +from langchain_core.callbacks import CallbackManagerForLLMRun +from langchain_core.language_models import BaseChatModel +from langchain_core.messages import AIMessage, BaseMessage +from langchain_core.outputs import ChatGeneration, ChatResult +from pydantic import Field +from pytest_httpx import HTTPXMock + +from insights_agent.graph.basic import _stringify_content, ask, build_graph +from insights_agent.tools.cloudoracle import CloudOracleClient, build_tools + +BASE_URL = "http://localhost:8080" +API_KEY = "test-key" + + +class ScriptedChatModel(BaseChatModel): + """Returns the next message from `script` on every model call. + + `script` is consumed left-to-right. We also stash the most recent + `messages` passed to the model so tests can assert the system prompt + was actually plumbed through. + """ + + script: list[AIMessage] = Field(default_factory=list) + last_messages: list[BaseMessage] | None = None + + @property + def _llm_type(self) -> str: + return "scripted-test" + + def bind_tools(self, tools: Sequence[Any], **kwargs: Any) -> ScriptedChatModel: + return self + + def _generate( + self, + messages: list[BaseMessage], + stop: list[str] | None = None, + run_manager: CallbackManagerForLLMRun | None = None, + **kwargs: Any, + ) -> ChatResult: + self.last_messages = messages + if not self.script: + raise RuntimeError("ScriptedChatModel exhausted: graph asked for one more turn than scripted") + msg = self.script.pop(0) + return ChatResult(generations=[ChatGeneration(message=msg)]) + + async def _agenerate( + self, + messages: list[BaseMessage], + stop: list[str] | None = None, + run_manager: Any = None, + **kwargs: Any, + ) -> ChatResult: + return self._generate(messages, stop, run_manager, **kwargs) + + +SUMMARY_PAYLOAD: dict[str, Any] = { + "period": {"start": "2026-04-01", "end": "2026-04-30"}, + "providers": {"aws": {"total_usd": 150.0, "currency": "USD"}}, + "grand_total_usd": 150.0, + "generated_at": "2026-05-18T12:00:00Z", + "data_source": "snapshots_approximation", + "note": "approximation note", +} + + +@pytest.fixture +def client() -> CloudOracleClient: + return CloudOracleClient(base_url=BASE_URL, api_key=API_KEY, timeout_seconds=2.0) + + +async def test_graph_invokes_summary_tool_then_returns_answer( + client: CloudOracleClient, httpx_mock: HTTPXMock +) -> None: + httpx_mock.add_response(json=SUMMARY_PAYLOAD) + + model = ScriptedChatModel( + script=[ + # Turn 1: ask the agent to call cloudoracle_cost_summary. + AIMessage( + content="", + tool_calls=[ + { + "name": "cloudoracle_cost_summary", + "args": {"start": "2026-04-01", "end": "2026-04-30"}, + "id": "call-1", + } + ], + ), + # Turn 2: deliver a final answer that references the snapshot caveat. + AIMessage( + content=( + "Gastaste aproximadamente $150 en AWS en abril 2026 " + "(aproximación basada en snapshots, no factura final)." + ) + ), + ] + ) + tools = build_tools(client) + graph = build_graph(model, tools) + + result = await ask(graph, "¿Cuánto gasté en AWS en abril de 2026?") + + assert len(result.tool_calls) == 1 + assert result.tool_calls[0]["name"] == "cloudoracle_cost_summary" + assert result.tool_calls[0]["args"] == {"start": "2026-04-01", "end": "2026-04-30"} + assert "$150" in result.answer + assert "snapshots" in result.answer.lower() + + # System prompt was prepended on every call. + assert model.last_messages is not None + assert model.last_messages[0].type == "system" + assert "FinOps" in str(model.last_messages[0].content) + + await client.aclose() + + +async def test_graph_invokes_two_tools_in_order( + client: CloudOracleClient, httpx_mock: HTTPXMock +) -> None: + httpx_mock.add_response(json=SUMMARY_PAYLOAD) + httpx_mock.add_response( + json={ + "period": {"start": "2026-04-01", "end": "2026-04-30"}, + "provider": "aws", + "services": [{"name": "ec2", "total_usd": 100.0, "percentage": 66.67}], + "total_usd": 100.0, + "generated_at": "2026-05-18T12:00:00Z", + "data_source": "snapshots_approximation", + "note": "approximation note", + } + ) + + model = ScriptedChatModel( + script=[ + AIMessage( + content="", + tool_calls=[ + { + "name": "cloudoracle_cost_summary", + "args": {"start": "2026-04-01", "end": "2026-04-30"}, + "id": "call-1", + } + ], + ), + AIMessage( + content="", + tool_calls=[ + { + "name": "cloudoracle_cost_by_service", + "args": { + "start": "2026-04-01", + "end": "2026-04-30", + "provider": "aws", + "top": 5, + }, + "id": "call-2", + } + ], + ), + AIMessage(content="Top service: EC2 at $100."), + ] + ) + tools = build_tools(client) + graph = build_graph(model, tools) + + result = await ask(graph, "Break down AWS spend.") + + names = [c["name"] for c in result.tool_calls] + assert names == ["cloudoracle_cost_summary", "cloudoracle_cost_by_service"] + assert "EC2" in result.answer + await client.aclose() + + +async def test_graph_no_tool_call_returns_direct_answer( + client: CloudOracleClient, +) -> None: + """Off-scope question: the model should reply without calling a tool.""" + model = ScriptedChatModel( + script=[ + AIMessage(content="Sorry, I only help with cloud cost questions."), + ] + ) + tools = build_tools(client) + graph = build_graph(model, tools) + + result = await ask(graph, "What's the weather today?") + + assert result.tool_calls == [] + assert "cloud cost" in result.answer + await client.aclose() + + +class TestStringifyContent: + """Exercise the multimodal fallback paths Gemini returns for some replies.""" + + def test_string_passthrough(self) -> None: + assert _stringify_content("hello") == "hello" + + def test_list_of_strings(self) -> None: + assert _stringify_content(["a", "b"]) == "ab" + + def test_list_of_text_blocks(self) -> None: + assert ( + _stringify_content([{"type": "text", "text": "x"}, {"type": "text", "text": "y"}]) + == "xy" + ) + + def test_mixed_list(self) -> None: + blocks = [ + "head ", + {"type": "image_url", "image_url": "..."}, # non-text ignored + {"type": "text", "text": "tail"}, + {"type": "text"}, # malformed: no text key + ] + assert _stringify_content(blocks) == "head tail" + + def test_unknown_type_returns_empty(self) -> None: + assert _stringify_content(42) == "" + + +async def test_graph_surfaces_tool_error_to_llm( + client: CloudOracleClient, httpx_mock: HTTPXMock +) -> None: + """If the Go API returns 401, the tool raises; the LLM sees the error + string and can compose a graceful answer.""" + httpx_mock.add_response( + status_code=401, + json={"error": "invalid API key", "code": "unauthorized"}, + ) + + model = ScriptedChatModel( + script=[ + AIMessage( + content="", + tool_calls=[ + { + "name": "cloudoracle_cost_summary", + "args": {"start": "2026-04-01", "end": "2026-04-30"}, + "id": "call-1", + } + ], + ), + AIMessage( + content="I couldn't fetch the data: the API rejected the key. Please check the CloudOracle API key." + ), + ] + ) + tools = build_tools(client) + graph = build_graph(model, tools) + + result = await ask(graph, "AWS spend in April?") + assert "rejected the key" in result.answer + await client.aclose() From 5f4a484fe68abb934d1b9bd840a3e662718dbece Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jesus=20Nu=C3=B1ez?= Date: Mon, 18 May 2026 19:40:23 -0400 Subject: [PATCH 06/18] chore: ignore .claude harness directory Local-only state from the Claude Code harness (session transcripts, agent scratch space, etc.) should not end up in the repo. Co-Authored-By: Claude Opus 4.7 (1M context) --- .gitignore | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.gitignore b/.gitignore index 4b557f3..a91c73c 100644 --- a/.gitignore +++ b/.gitignore @@ -38,3 +38,5 @@ web/dist/ # go:embed has a valid target, but ignore the generated assets. /internal/api/dist/* !/internal/api/dist/.gitkeep + +.claude From 7969861dcb1401639310a70731bc86d6685593b8 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jesus=20Nu=C3=B1ez?= Date: Mon, 18 May 2026 19:56:19 -0400 Subject: [PATCH 07/18] feat(insights-agent): CLI entry point for single-turn agent runs MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit `uv run python -m insights_agent.main ""` (or the `insights-agent` console script) wires Settings → logging → GeminiProvider → CloudOracleClient → ReAct graph and prints either the natural-language answer or a JSON envelope (`--json`). `--verbose` streams the tool calls the model made to stderr so the operator can see which /api/v1 endpoint was actually consulted. Top-level error handling maps the realistic failure modes to distinct exit codes (130 on Ctrl-C, 2 on missing/invalid config, 1 on runtime errors) so callers in shell pipelines can branch deterministically. Includes the tiny `build_graph` signature widening `list[BaseTool] → Sequence[BaseTool]` so the CLI can pass the result of `build_tools` without an extra conversion at the call site. Co-Authored-By: Claude Opus 4.7 (1M context) --- .../src/insights_agent/graph/basic.py | 9 +- insights-agent/src/insights_agent/main.py | 132 ++++++++++++++++++ insights-agent/tests/test_main.py | 118 ++++++++++++++++ 3 files changed, 257 insertions(+), 2 deletions(-) create mode 100644 insights-agent/src/insights_agent/main.py create mode 100644 insights-agent/tests/test_main.py diff --git a/insights-agent/src/insights_agent/graph/basic.py b/insights-agent/src/insights_agent/graph/basic.py index 945a4f8..72e0155 100644 --- a/insights-agent/src/insights_agent/graph/basic.py +++ b/insights-agent/src/insights_agent/graph/basic.py @@ -18,6 +18,7 @@ from __future__ import annotations +from collections.abc import Sequence from dataclasses import dataclass, field from typing import Any @@ -55,13 +56,17 @@ class AgentResult: messages: list[Any] = field(default_factory=list) -def build_graph(llm: BaseChatModel, tools: list[BaseTool]) -> Any: +def build_graph(llm: BaseChatModel, tools: Sequence[BaseTool]) -> Any: """Compile a ReAct agent bound to `tools`. We pass the system prompt as a `prompt` argument so it's prepended to every model call inside the graph (rather than baked into the input messages — that would make turn 2+ duplicate it).""" - return create_react_agent(model=llm, tools=tools, prompt=SystemMessage(content=SYSTEM_PROMPT)) + return create_react_agent( + model=llm, + tools=list(tools), + prompt=SystemMessage(content=SYSTEM_PROMPT), + ) async def ask(graph: Any, question: str) -> AgentResult: diff --git a/insights-agent/src/insights_agent/main.py b/insights-agent/src/insights_agent/main.py new file mode 100644 index 0000000..4065109 --- /dev/null +++ b/insights-agent/src/insights_agent/main.py @@ -0,0 +1,132 @@ +"""CLI entry point. + +Single-turn agent run: read a question from argv, build the graph, print the +answer to stdout. Logs go to stderr so callers can pipe the answer cleanly +into other tools. + +Exit codes: + 0 success + 1 unexpected runtime failure + 2 configuration problem (missing env var, bad URL, etc.) + 130 user-cancelled (Ctrl-C) + +Two output modes: + default natural-language answer on stdout + --json {"answer": "...", "tool_calls": [...]} on stdout + --verbose additionally streams tool-call summary to stderr +""" + +from __future__ import annotations + +import argparse +import asyncio +import json +import sys + +from pydantic import ValidationError + +from insights_agent.config import Settings +from insights_agent.graph.basic import AgentResult, ask, build_graph +from insights_agent.llm import GeminiProvider +from insights_agent.logging import get_logger, setup +from insights_agent.tools.cloudoracle import CloudOracleClient, build_tools + +EXIT_OK = 0 +EXIT_RUNTIME = 1 +EXIT_CONFIG = 2 +EXIT_INTERRUPTED = 130 + + +def _build_arg_parser() -> argparse.ArgumentParser: + p = argparse.ArgumentParser( + prog="insights-agent", + description=( + "Ask CloudOracle's FinOps agent a question. The agent will pick the " + "right /api/v1 tool calls against your running CloudOracle Go server " + "and answer in natural language." + ), + ) + p.add_argument("query", help="The question to ask, in quotes.") + p.add_argument( + "--verbose", + action="store_true", + help="Print the tool calls the agent made to stderr.", + ) + p.add_argument( + "--json", + dest="as_json", + action="store_true", + help="Print structured JSON instead of natural-language answer.", + ) + return p + + +async def _run(query: str, *, as_json: bool, verbose: bool) -> AgentResult: + # pydantic-settings populates required fields from the environment; + # mypy's call-arg check doesn't understand env-based construction + # without the pydantic plugin, so we silence it locally. + settings = Settings() # type: ignore[call-arg] # may raise ValidationError + setup(level=settings.log_level, fmt=settings.log_format) + log = get_logger("insights_agent.main") + log.info( + "starting", + provider="gemini", + model=settings.gemini_model, + base_url=settings.cloudoracle_base_url, + ) + + provider = GeminiProvider( + api_key=settings.gemini_api_key, + model=settings.gemini_model, + ) + async with CloudOracleClient( + base_url=settings.cloudoracle_base_url, + api_key=settings.cloudoracle_api_key, + timeout_seconds=settings.http_timeout_seconds, + ) as client: + tools = build_tools(client) + graph = build_graph(provider.get_chat_model(), tools) + result = await ask(graph, query) + + if verbose and result.tool_calls: + print("Tool calls made:", file=sys.stderr) + for i, call in enumerate(result.tool_calls, 1): + print(f" {i}. {call['name']}({call['args']})", file=sys.stderr) + + if as_json: + print(json.dumps({"answer": result.answer, "tool_calls": result.tool_calls}, ensure_ascii=False)) + else: + print(result.answer) + return result + + +def cli_entrypoint(argv: list[str] | None = None) -> int: + args = _build_arg_parser().parse_args(argv) + try: + asyncio.run(_run(args.query, as_json=args.as_json, verbose=args.verbose)) + return EXIT_OK + except ValidationError as e: + # We don't have a configured logger yet at this point — Settings() + # failure is what would have configured it. Fall back to stderr so + # the operator sees what was missing. + print(f"Configuration error:\n{e}", file=sys.stderr) + print( + "\nCheck your .env or environment for " + "GEMINI_API_KEY, CLOUDORACLE_API_URL, CLOUDORACLE_API_KEY.", + file=sys.stderr, + ) + return EXIT_CONFIG + except KeyboardInterrupt: + print("Interrupted.", file=sys.stderr) + return EXIT_INTERRUPTED + except Exception as e: + # Top-level catch is intentional: this is the CLI boundary, anything + # not handled by the inner code is a runtime failure we want to + # report cleanly and exit non-zero instead of dumping a Python + # traceback to the operator. + print(f"Error: {e}", file=sys.stderr) + return EXIT_RUNTIME + + +if __name__ == "__main__": + sys.exit(cli_entrypoint()) diff --git a/insights-agent/tests/test_main.py b/insights-agent/tests/test_main.py new file mode 100644 index 0000000..e48536a --- /dev/null +++ b/insights-agent/tests/test_main.py @@ -0,0 +1,118 @@ +"""CLI surface tests. + +We don't drive the full agent here — `test_graph.py` already covers the +async pipeline. These tests target only the CLI shell: arg parsing, +config-error exit code, formatting of --verbose / --json output. +""" + +from __future__ import annotations + +from typing import Any + +import pytest + +from insights_agent.graph.basic import AgentResult +from insights_agent.main import ( + EXIT_CONFIG, + EXIT_INTERRUPTED, + EXIT_OK, + EXIT_RUNTIME, + _build_arg_parser, + cli_entrypoint, +) + + +def test_arg_parser_requires_query() -> None: + p = _build_arg_parser() + with pytest.raises(SystemExit): + p.parse_args([]) + + +def test_arg_parser_default_flags() -> None: + args = _build_arg_parser().parse_args(["hello"]) + assert args.query == "hello" + assert args.verbose is False + assert args.as_json is False + + +def test_arg_parser_flags_parsed() -> None: + args = _build_arg_parser().parse_args(["q", "--verbose", "--json"]) + assert args.verbose is True + assert args.as_json is True + + +def test_cli_missing_config_returns_2( + capsys: pytest.CaptureFixture[str], +) -> None: + # `_isolate_settings_env` (autouse) stripped the required env vars, so + # Settings() will fail. We exercise the top-level error handler. + rc = cli_entrypoint(["test query"]) + assert rc == EXIT_CONFIG + err = capsys.readouterr().err + assert "Configuration error" in err + assert "GEMINI_API_KEY" in err + + +def test_cli_happy_path_prints_answer( + valid_env: None, + capsys: pytest.CaptureFixture[str], + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Patch the _run coroutine to skip the LLM/HTTP layer.""" + + async def fake_run(query: str, *, as_json: bool, verbose: bool) -> AgentResult: + result = AgentResult( + answer="$150 in AWS", + tool_calls=[ + {"name": "cloudoracle_cost_summary", "args": {"start": "x", "end": "y"}} + ], + ) + if verbose: + import sys + + print(f"Tool calls made: {len(result.tool_calls)}", file=sys.stderr) + if as_json: + import json + import sys + + print( + json.dumps({"answer": result.answer, "tool_calls": result.tool_calls}), + file=sys.stdout, + ) + else: + print(result.answer) + return result + + monkeypatch.setattr("insights_agent.main._run", fake_run) + rc = cli_entrypoint(["What did I spend on AWS?"]) + out = capsys.readouterr() + assert rc == EXIT_OK + assert "$150 in AWS" in out.out + + +def test_cli_runtime_error_returns_1( + valid_env: None, + capsys: pytest.CaptureFixture[str], + monkeypatch: pytest.MonkeyPatch, +) -> None: + async def boom(*_: Any, **__: Any) -> AgentResult: + raise RuntimeError("kaboom") + + monkeypatch.setattr("insights_agent.main._run", boom) + rc = cli_entrypoint(["q"]) + assert rc == EXIT_RUNTIME + assert "kaboom" in capsys.readouterr().err + + +def test_cli_interrupt_returns_130( + valid_env: None, + capsys: pytest.CaptureFixture[str], + monkeypatch: pytest.MonkeyPatch, +) -> None: + async def interrupt(*_: Any, **__: Any) -> AgentResult: + raise KeyboardInterrupt + + monkeypatch.setattr("insights_agent.main._run", interrupt) + rc = cli_entrypoint(["q"]) + assert rc == EXIT_INTERRUPTED + assert "Interrupted" in capsys.readouterr().err From 781ddd4b7895cd3dd301ab0e209f1f448913c60e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jesus=20Nu=C3=B1ez?= Date: Mon, 18 May 2026 19:58:17 -0400 Subject: [PATCH 08/18] docs(insights-agent): full subproject README + root section with arch diagram MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit `insights-agent/README.md` was a stub. Replace it with a self-contained setup-in-under-10-minutes guide covering: prerequisites, `uv sync`, the seven env vars (required vs optional, defaults), CLI flags and exit codes, an end-to-end smoke test the operator can run by hand against a local Go server, dev workflow (pytest / ruff / mypy), and a one-page architecture pointer table mapping concerns to source files. Root README gains an "AI Insights Agent" section with a Mermaid arch diagram (User → CLI → LangGraph → Gemini → tools → Go API → Postgres) and a roadmap update marking sub-hitos 8.0 / 8.1 done with the remaining 8.2–8.7 items listed so readers can place this work in the larger plan. Co-Authored-By: Claude Opus 4.7 (1M context) --- README.md | 35 +++++++- insights-agent/README.md | 187 ++++++++++++++++++++++++++++++++++++++- 2 files changed, 218 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 41e2d3c..8682185 100644 --- a/README.md +++ b/README.md @@ -8,7 +8,32 @@ A Go FinOps toolkit that ships in two modes from the same `oracle` binary, with - **v1 — Audit existing cloud spend.** Ingest live EC2/RDS/EBS/Lambda inventory from AWS, GCP, or Azure into Postgres, run deterministic rules over it, and produce an executive PDF + dashboard with an LLM-narrated summary. See **[docs/v1-guide.md](docs/v1-guide.md)**. - **v2 — Predict cost impact of a Terraform PR before merge.** Read `terraform show -json plan.tfplan`, look every changing resource up against the AWS Pricing API, and post (or upsert) a Markdown comment on the PR with the net monthly delta, top movers, and a 1–3 sentence LLM narrative. Ships as a GitHub Action and as the `oracle pr-check` subcommand. **Current focus.** See **[docs/v2-guide.md](docs/v2-guide.md)**. -- **v3 — Insights Agent (in progress).** Polyglot Go + Python extension adding agentic FinOps analysis on top of v1/v2 cost data — LangGraph orchestration, RAG over FinOps documentation, multi-agent supervisor pattern, and production guardrails. +- **v3 — Insights Agent (in progress).** Polyglot Go + Python extension adding agentic FinOps analysis on top of v1/v2 cost data — LangGraph orchestration, RAG over FinOps documentation, multi-agent supervisor pattern, and production guardrails. See **[AI Insights Agent](#ai-insights-agent)** below and **[insights-agent/README.md](insights-agent/README.md)**. + +## AI Insights Agent + +A Python sibling of the Go server that lets you ask FinOps questions in +natural language. The agent decides which `/api/v1` endpoint to call, fetches +the data over HTTP, and answers in the user's language — surfacing the +"snapshot approximation" caveat when accuracy matters. + +```mermaid +flowchart LR + U([User]) -->|"¿Cuánto gasté en AWS?"| CLI[insights-agent CLI
Python 3.12] + CLI --> G[LangGraph
create_react_agent] + G -->|"bind_tools"| LLM[Gemini 2.5 Flash] + LLM -->|"tool call"| T[CloudOracle tools
cost-summary / cost-by-service] + T -->|"GET /api/v1/* + X-API-Key"| GO[CloudOracle Go
oracle serve] + GO -->|"SQL"| DB[(PostgreSQL
cost_snapshots)] + GO -->|"data_source: snapshots_approximation"| T + T --> LLM + LLM -->|"natural-language answer"| CLI + CLI --> U +``` + +Sub-hito 8.1 (single-turn, two tools, Gemini, no RAG) is the first end-to-end +round-trip. Setup, env vars, CLI usage, and the smoke test are documented in +**[insights-agent/README.md](insights-agent/README.md)**. ## v2 — Quick start (current focus) @@ -99,7 +124,13 @@ The synthetic provider needs no credentials. To run against AWS / GCP / Azure, s ## Roadmap ### v3 — Insights Agent (in progress) -- [ ] Polyglot Go + Python extension adding agentic FinOps analysis (LangGraph orchestration, RAG over FinOps docs, multi-agent supervisor, production guardrails) on top of v1/v2 cost data +- [x] **Sub-hito 8.0** — Authenticated `/api/v1/cost-summary` and `/api/v1/cost-by-service` Go endpoints (X-API-Key, snapshot-derived totals with explicit `data_source` disclaimer, machine-readable error codes) +- [x] **Sub-hito 8.1** — Python `insights-agent` sibling: LangGraph `create_react_agent` graph with two CloudOracle tools, Gemini provider, pydantic-settings config, structlog matching the Go slog format, CLI with `--verbose` / `--json` flags, 92% test coverage with mocked LLM + mocked HTTP. See **[insights-agent/](insights-agent/README.md)** +- [ ] **Sub-hito 8.2** — Additional tools (resources, findings, trends) wired against the v0 dashboard endpoints +- [ ] **Sub-hito 8.3** — pgvector + RAG over FinOps documentation +- [ ] **Sub-hito 8.4** — Hand-rolled supervisor (multi-agent), replacing `create_react_agent` +- [ ] **Sub-hito 8.5** — Production guardrails: cost caps, fallback determinístico, semantic answer validation, HTTP API surface +- [ ] **Sub-hito 8.7** — Real billing / Cost Explorer integration replacing the snapshot approximation ### v2 — Terraform PR cost analysis - [x] Terraform plan parser — `internal/iac` reads `terraform show -json` into a typed `Plan` model with action classification (create / update / replace / delete / no-op) and `after_unknown` handling diff --git a/insights-agent/README.md b/insights-agent/README.md index d9ef615..18c8999 100644 --- a/insights-agent/README.md +++ b/insights-agent/README.md @@ -1,5 +1,188 @@ # insights-agent -LangGraph-based FinOps insights agent for CloudOracle. Consumes the Go `/api/v1` cost endpoints as tools. +LangGraph-based FinOps insights agent for CloudOracle. Ask in natural language +("how much did I spend on AWS in April 2026?") and the agent picks the right +`/api/v1` calls against the CloudOracle Go server, then answers in the same +language with the relevant caveats. -Full setup instructions: TODO (sub-hito 8.1 Commit 5). +This is the first round-trip of sub-hito 8.1: single-turn agent (no +conversational memory), `create_react_agent` from `langgraph.prebuilt`, two +tools wired against the Go cost endpoints, Gemini as the model. Future +sub-hitos replace the ReAct loop with a custom supervisor (8.4) and add +RAG over FinOps docs (8.3). + +## What it talks to + +``` +┌────────┐ "¿Cuánto gasté en AWS?" ┌─────────────┐ +│ User │ ─────────────────────────▶ │ insights- │ +└────────┘ │ agent (CLI) │ + └──────┬──────┘ + │ LangGraph (Gemini) + │ tool call → + ▼ + ┌─────────────┐ X-API-Key + │ Go server │ ──────────▶ Postgres + │ /api/v1/... │ (cost_snapshots) + └─────────────┘ +``` + +The two tools both return a `data_source` field. While it equals +`"snapshots_approximation"`, the figures come from periodic CloudOracle +snapshots — **not** a real billing API. The agent surfaces that caveat +to the user when accuracy materially affects the answer. The real billing +integration lands in sub-hito 8.7. + +## Setup in under 10 minutes + +### 1 — Prerequisites + +- Python 3.12 (the project pins `>=3.12,<3.13`) +- [`uv`](https://docs.astral.sh/uv/) installed and on `PATH` +- A running CloudOracle Go server with `CLOUDORACLE_API_KEY` configured +- A Gemini API key (the [free tier](https://aistudio.google.com/app/apikey) is enough) + +### 2 — Install dependencies + +```bash +cd insights-agent +uv sync --extra dev +``` + +`uv sync` reads `pyproject.toml` + `uv.lock` and creates `.venv/` with both +runtime and dev dependencies (pytest, ruff, mypy). Re-running it is the +canonical way to pick up upstream changes. + +### 3 — Configure environment + +```bash +cp .env.example .env +# then edit .env and fill GEMINI_API_KEY and CLOUDORACLE_API_KEY +``` + +Required env vars (loaded by `pydantic-settings`, fail-fast at startup): + +| Variable | Required | Default | Notes | +| ------------------------ | -------- | -------------------------- | ----- | +| `GEMINI_API_KEY` | yes | — | https://aistudio.google.com/app/apikey | +| `CLOUDORACLE_API_URL` | yes | `http://localhost:8080` | Base URL of the Go server | +| `CLOUDORACLE_API_KEY` | yes | — | Must match the Go server's `CLOUDORACLE_API_KEY` | +| `GEMINI_MODEL` | no | `gemini-2.5-flash` | Free tier covers this model | +| `LOG_LEVEL` | no | `INFO` | `DEBUG`, `INFO`, `WARNING`, `ERROR`, `CRITICAL` | +| `LOG_FORMAT` | no | `text` | `text` or `json` — same shapes as the Go side | +| `HTTP_TIMEOUT_SECONDS` | no | `10` | Per-request timeout against the Go server | + +### 4 — Run the CLI + +```bash +uv run python -m insights_agent.main "¿Cuánto gasté en AWS en abril de 2026?" +``` + +Or via the console script entry point: + +```bash +uv run insights-agent "Break down GCP spend for May 2026" +``` + +Useful flags: + +| Flag | Effect | +| ------------ | ------ | +| `--verbose` | Streams the tool calls the model made (name + args) to stderr | +| `--json` | Prints `{"answer": "...", "tool_calls": [...]}` on stdout instead of plain text | + +Exit codes: + +| Code | Meaning | +| ---- | ------- | +| 0 | Success | +| 1 | Unexpected runtime failure | +| 2 | Configuration problem (missing env var, malformed URL, etc.) | +| 130 | User cancelled with Ctrl-C | + +## Smoke test (end-to-end with real Gemini + Go server) + +This exercises the full chain: Python CLI → LangGraph (Gemini) → HTTP tool +call → Go `/api/v1` → Postgres. Run it once after setup to confirm +everything is wired correctly. Skip it during day-to-day development — +the unit tests already cover the pipeline with a mocked model. + +1. **Start CloudOracle Go with v1 auth.** From the repo root: + + ```bash + export CLOUDORACLE_API_KEY="local-dev-secret" # any non-empty string + docker compose up --build # or: oracle serve + ``` + + Confirm the server is up: + + ```bash + curl -sS -H "X-API-Key: $CLOUDORACLE_API_KEY" \ + "http://localhost:8080/api/v1/cost-summary?start=2026-04-01&end=2026-04-30" + ``` + + You should get a JSON envelope with `data_source: "snapshots_approximation"`. + If you get `unauthorized`, the key in `.env` doesn't match the server's env. + If you get an empty `providers` map, seed the DB first: + `docker compose exec app /app/cloudoracle seed --count 120`. + +2. **Run the agent** from `insights-agent/`: + + ```bash + uv run insights-agent --verbose "¿Cuánto gasté en AWS en abril de 2026?" + ``` + +3. **Expected output** (shape, not exact wording — Gemini paraphrases): + + - On stdout, a paragraph in Spanish with a dollar figure that matches the + `grand_total_usd` for AWS in that period. + - The answer mentions that the numbers are an approximation from snapshots + (because the tool surfaced `data_source: "snapshots_approximation"`). + - On stderr, a `Tool calls made:` block listing at least + `cloudoracle_cost_summary` with the inferred start/end dates. + +4. **If it fails:** + + - `Configuration error: ...` (exit 2) → missing or malformed `.env` value. + - `CloudOracle API 401 ...` (exit 1) → `CLOUDORACLE_API_KEY` mismatch. + - `CloudOracle transport error: ...` (exit 1) → Go server not reachable + at `CLOUDORACLE_API_URL`. + - Gemini quota errors → wait a minute or use a different `GEMINI_API_KEY`; + the free tier has minute- and day-level limits. + +## Development + +```bash +uv run pytest # unit tests + coverage (>80% threshold) +uv run ruff check . # lint +uv run mypy src/ # strict type-check (passes on 11 files) +``` + +The tests never contact Gemini or a live Go server. `tests/test_graph.py` +ships a `ScriptedChatModel` (a `BaseChatModel` subclass) that replays +hand-written `AIMessage` sequences, and `pytest-httpx` mocks the Go +endpoints. The two together let `create_react_agent` run its full +ReAct loop deterministically — including the tool-error branch. + +### Architecture pointers + +| Concern | Where to look | Why | +| ------------------- | ------------- | --- | +| Vendor-agnostic LLM | `src/insights_agent/llm/base.py` + `gemini.py` | ABC + one implementation. Add `AnthropicProvider` / `OpenAIProvider` later by implementing `LLMProvider`; no graph changes required. | +| Tools | `src/insights_agent/tools/cloudoracle.py` | `CloudOracleClient` owns the HTTP + auth + request-ID conventions; `build_tools(client)` wraps the two methods as `StructuredTool`s with rich docstrings so the LLM picks the right one. Errors flow as `ToolException` so the model sees them as observations and can recover instead of aborting the run. | +| Graph | `src/insights_agent/graph/basic.py` | `create_react_agent` from `langgraph.prebuilt` with a short system prompt. Sub-hito 8.4 replaces this with a hand-rolled supervisor. | +| CLI | `src/insights_agent/main.py` | argparse, three flags, four exit codes, single async run. No conversational memory (each call is independent). | +| Settings | `src/insights_agent/config.py` | `pydantic-settings.BaseSettings` — fail-fast `ValidationError` at startup if any required env var is missing. | +| Logging | `src/insights_agent/logging.py` | `structlog` matching the Go side's `slog` output (text or JSON to stderr) so a tail of both streams reads coherently. | + +### What is **not** in this sub-hito + +- More tools (sub-hito 8.2) +- pgvector / RAG over FinOps docs (8.3) +- Custom supervisor / multi-agent (8.4) +- Cost caps, semantic answer validation, fallback determinístico (8.5) +- HTTP API surface for the agent — CLI only until 8.5 +- Other LLM providers (Anthropic, OpenAI) +- Streaming responses +- Conversational memory across queries +- Real billing / Cost Explorer integration (8.7) From f6c71e928fe056f04fe81bde939180702cd81fad Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jesus=20Nu=C3=B1ez?= Date: Mon, 18 May 2026 20:19:46 -0400 Subject: [PATCH 09/18] chore: translate Spanish comments and milestone references to English MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Standardize the whole repo on English for comments, docstrings, and code example queries so a reader on the project doesn't have to bounce between languages. The change is text-only — no identifiers, behavior, or tests move. Translations: - All `sub-hito 8.x` references in code → `milestone 8.x` (pyproject.toml, cost_handlers.go, llm/__init__.py, graph/basic.py, tools/cloudoracle.py). - `internal/cloud/*_test.go` test docstrings and inline comments. - `internal/report/pdf.go` section markers and field comments. - Sample queries in `insights-agent/README.md` and the matching scripted AIMessage / `ask(...)` query in `tests/test_graph.py` — the existing asserts (`"$150"`, `"snapshots"`) still match the new English answer so the test still passes. Plus pre-existing working-tree formatting in `README.md` (single-line badges, table padding in the v2 callout, an extra blockquote blank line, and a Mermaid example query already updated to English) folded into the same commit since it was already staged-adjacent and is the same kind of language/cosmetic cleanup. Verified after: `uv run pytest` (58/58, 91.83% coverage), `uv run ruff check .`, `uv run mypy src/`, and `go test ./internal/cloud/... ./internal/api/... ./internal/report/...` all green. Co-Authored-By: Claude Opus 4.7 (1M context) --- README.md | 111 +++++++++--------- insights-agent/README.md | 40 +++---- insights-agent/pyproject.toml | 2 +- .../src/insights_agent/graph/basic.py | 2 +- .../src/insights_agent/llm/__init__.py | 2 +- .../src/insights_agent/tools/cloudoracle.py | 2 +- insights-agent/tests/test_graph.py | 6 +- internal/api/cost_handlers.go | 2 +- internal/cloud/aws_provider_fetch_test.go | 24 ++-- internal/cloud/aws_provider_test.go | 40 +++---- internal/cloud/azure_provider_test.go | 26 ++-- internal/cloud/gcp_provider_test.go | 14 +-- internal/report/pdf.go | 4 +- 13 files changed, 140 insertions(+), 135 deletions(-) diff --git a/README.md b/README.md index 8682185..33da600 100644 --- a/README.md +++ b/README.md @@ -1,8 +1,6 @@ # CloudOracle -![Tests](https://img.shields.io/badge/tests-469%20unit%20%2B%2021%20integration-brightgreen) -![Go Version](https://img.shields.io/badge/go-1.25-blue) -![License](https://img.shields.io/badge/license-Apache%20License%202.0-green) +![Tests](https://img.shields.io/badge/tests-469%20unit%20%2B%2021%20integration-brightgreen)![Go Version](https://img.shields.io/badge/go-1.25-blue) ![License](https://img.shields.io/badge/license-Apache%20License%202.0-green) A Go FinOps toolkit that ships in two modes from the same `oracle` binary, with a polyglot agent extension in progress: @@ -19,7 +17,7 @@ the data over HTTP, and answers in the user's language — surfacing the ```mermaid flowchart LR - U([User]) -->|"¿Cuánto gasté en AWS?"| CLI[insights-agent CLI
Python 3.12] + U([User]) -->|"How much did I spend on AWS?"| CLI[insights-agent CLI
Python 3.12] CLI --> G[LangGraph
create_react_agent] G -->|"bind_tools"| LLM[Gemini 2.5 Flash] LLM -->|"tool call"| T[CloudOracle tools
cost-summary / cost-by-service] @@ -31,7 +29,7 @@ flowchart LR CLI --> U ``` -Sub-hito 8.1 (single-turn, two tools, Gemini, no RAG) is the first end-to-end +Milestone 8.1 (single-turn, two tools, Gemini, no RAG) is the first end-to-end round-trip. Setup, env vars, CLI usage, and the smoke test are documented in **[insights-agent/README.md](insights-agent/README.md)**. @@ -40,16 +38,19 @@ round-trip. Setup, env vars, CLI usage, and the smoke test are documented in CloudOracle parses a Terraform plan, prices every changing resource, and posts a PR comment like this: > ## 💰 Cloud Cost Impact +> > **Net monthly change: +$389.35** 🔴 > > The Aurora cluster instance dominates this change at ~$204/month — over half the total. If this is intended for a non-production environment, an `aws_db_instance` running `db.t3.medium` would land around $60/mo for similar functional coverage. > > ### Top movers by cost impact -> | Resource | Action | Δ Monthly | Confidence | -> | -------- | ------ | --------- | ---------- | -> | `aws_rds_cluster_instance.aurora` | 🆕 create | +$204.40 | low | -> | `aws_db_instance.db` | 🆕 create | +$71.36 | low | -> | `aws_instance.web` | 🆕 create | +$64.74 | low | +> +> +> | Resource | Action | Δ Monthly | Confidence | +> | --------------------------------- | --------- | ---------- | ---------- | +> | `aws_rds_cluster_instance.aurora` | 🆕 create | +$204.40 | low | +> | `aws_db_instance.db` | 🆕 create | +$71.36 | low | +> | `aws_instance.web` | 🆕 create | +$64.74 | low | Drop this workflow into `.github/workflows/cost-comment.yml`: @@ -97,20 +98,21 @@ The synthetic provider needs no credentials. To run against AWS / GCP / Azure, s ## Tech Stack -| Component | Technology | -|-------------|-------------------------------------| -| Language | Go 1.25 | -| Database | PostgreSQL 16 (Alpine) | -| DB Driver | pgx v5 (connection pool) | -| AWS SDK | aws-sdk-go-v2 (EC2, RDS, Lambda, STS) | -| GCP SDK | Google Cloud Go (Compute, SQL, Functions) | + +| Component | Technology | +| ----------- | -------------------------------------------- | +| Language | Go 1.25 | +| Database | PostgreSQL 16 (Alpine) | +| DB Driver | pgx v5 (connection pool) | +| AWS SDK | aws-sdk-go-v2 (EC2, RDS, Lambda, STS) | +| GCP SDK | Google Cloud Go (Compute, SQL, Functions) | | Azure SDK | Azure SDK for Go (Compute, SQL, App Service) | -| Concurrency | `golang.org/x/sync/errgroup` | -| Logging | `log/slog` (structured, text/JSON) | -| PDF | go-pdf/fpdf | -| LLM | Gemini / Claude / OpenAI | -| Testing | `testing` + `httptest` | -| Containers | Docker Compose + multi-stage Dockerfile | +| Concurrency | `golang.org/x/sync/errgroup` | +| Logging | `log/slog` (structured, text/JSON) | +| PDF | go-pdf/fpdf | +| LLM | Gemini / Claude / OpenAI | +| Testing | `testing` + `httptest` | +| Containers | Docker Compose + multi-stage Dockerfile | ## Documentation @@ -124,40 +126,43 @@ The synthetic provider needs no credentials. To run against AWS / GCP / Azure, s ## Roadmap ### v3 — Insights Agent (in progress) -- [x] **Sub-hito 8.0** — Authenticated `/api/v1/cost-summary` and `/api/v1/cost-by-service` Go endpoints (X-API-Key, snapshot-derived totals with explicit `data_source` disclaimer, machine-readable error codes) -- [x] **Sub-hito 8.1** — Python `insights-agent` sibling: LangGraph `create_react_agent` graph with two CloudOracle tools, Gemini provider, pydantic-settings config, structlog matching the Go slog format, CLI with `--verbose` / `--json` flags, 92% test coverage with mocked LLM + mocked HTTP. See **[insights-agent/](insights-agent/README.md)** -- [ ] **Sub-hito 8.2** — Additional tools (resources, findings, trends) wired against the v0 dashboard endpoints -- [ ] **Sub-hito 8.3** — pgvector + RAG over FinOps documentation -- [ ] **Sub-hito 8.4** — Hand-rolled supervisor (multi-agent), replacing `create_react_agent` -- [ ] **Sub-hito 8.5** — Production guardrails: cost caps, fallback determinístico, semantic answer validation, HTTP API surface -- [ ] **Sub-hito 8.7** — Real billing / Cost Explorer integration replacing the snapshot approximation + +- [X] **Milestone 8.0** — Authenticated `/api/v1/cost-summary` and `/api/v1/cost-by-service` Go endpoints (X-API-Key, snapshot-derived totals with explicit `data_source` disclaimer, machine-readable error codes) +- [X] **Milestone 8.1** — Python `insights-agent` sibling: LangGraph `create_react_agent` graph with two CloudOracle tools, Gemini provider, pydantic-settings config, structlog matching the Go slog format, CLI with `--verbose` / `--json` flags, 92% test coverage with mocked LLM + mocked HTTP. See **[insights-agent/](insights-agent/README.md)** +- [ ] **Milestone 8.2** — Additional tools (resources, findings, trends) wired against the v0 dashboard endpoints +- [ ] **Milestone 8.3** — pgvector + RAG over FinOps documentation +- [ ] **Milestone 8.4** — Hand-rolled supervisor (multi-agent), replacing `create_react_agent` +- [ ] **Milestone 8.5** — Production guardrails: cost caps, deterministic fallback, semantic answer validation, HTTP API surface +- [ ] **Milestone 8.7** — Real billing / Cost Explorer integration replacing the snapshot approximation ### v2 — Terraform PR cost analysis -- [x] Terraform plan parser — `internal/iac` reads `terraform show -json` into a typed `Plan` model with action classification (create / update / replace / delete / no-op) and `after_unknown` handling -- [x] AWS Pricing API client + cache — `internal/pricing.Client` wraps AWS SDK v2 `pricing:GetProducts`; `internal/pricing.Cache` adds a 7-day disk cache keyed by service+filters -- [x] Per-resource estimators — EC2, EBS, RDS, Aurora cluster instance, Lambda, NAT gateway with breakdown line items and assumption notes -- [x] CostDiff aggregator — `internal/diff.Analyze` collapses per-resource estimates into a plan-wide picture with Created / Deleted / Updated / Replaced / Skipped slices, top movers, and aggregate confidence -- [x] Markdown renderer — `internal/diff.RenderMarkdown` produces the canonical PR comment (header / top movers table / full breakdown / caveats / marker footer), templated and golden-tested -- [x] LLM-narrated PR comment — `RenderMarkdownWithLLM` swaps the templated narrative for a 1–3 sentence LLM output with caveat grouping, sanity checks (length cap, preamble strip, paragraph-break warn), and silent fallback to the templated text on any failure -- [x] GitHub REST client — `internal/github.PostOrUpdateComment` lists, finds-by-marker, and PATCHes / POSTs; paginated with cap, body truncation guard at 60KB, multi-match resolution to most-recently-updated -- [x] `oracle pr-check` subcommand — orchestrates the whole pipeline, with differentiated exit codes (1 input / 2 pricing / 3 output / 4 github) and `--no-llm` / `--post` switches -- [x] GitHub Action packaging — `Dockerfile.action`, `action.yml`, POSIX `entrypoint.sh` that auto-extracts the PR number from `GITHUB_REF` on `pull_request[_target]` events; reference workflows under `.github/examples/` + +- [X] Terraform plan parser — `internal/iac` reads `terraform show -json` into a typed `Plan` model with action classification (create / update / replace / delete / no-op) and `after_unknown` handling +- [X] AWS Pricing API client + cache — `internal/pricing.Client` wraps AWS SDK v2 `pricing:GetProducts`; `internal/pricing.Cache` adds a 7-day disk cache keyed by service+filters +- [X] Per-resource estimators — EC2, EBS, RDS, Aurora cluster instance, Lambda, NAT gateway with breakdown line items and assumption notes +- [X] CostDiff aggregator — `internal/diff.Analyze` collapses per-resource estimates into a plan-wide picture with Created / Deleted / Updated / Replaced / Skipped slices, top movers, and aggregate confidence +- [X] Markdown renderer — `internal/diff.RenderMarkdown` produces the canonical PR comment (header / top movers table / full breakdown / caveats / marker footer), templated and golden-tested +- [X] LLM-narrated PR comment — `RenderMarkdownWithLLM` swaps the templated narrative for a 1–3 sentence LLM output with caveat grouping, sanity checks (length cap, preamble strip, paragraph-break warn), and silent fallback to the templated text on any failure +- [X] GitHub REST client — `internal/github.PostOrUpdateComment` lists, finds-by-marker, and PATCHes / POSTs; paginated with cap, body truncation guard at 60KB, multi-match resolution to most-recently-updated +- [X] `oracle pr-check` subcommand — orchestrates the whole pipeline, with differentiated exit codes (1 input / 2 pricing / 3 output / 4 github) and `--no-llm` / `--post` switches +- [X] GitHub Action packaging — `Dockerfile.action`, `action.yml`, POSIX `entrypoint.sh` that auto-extracts the PR number from `GITHUB_REF` on `pull_request[_target]` events; reference workflows under `.github/examples/` ### v1 — Cloud cost audit -- [x] LLM-powered analysis: executive summaries generated by Gemini / Claude / OpenAI -- [x] PDF report generation with executive summary and severity-coded tables -- [x] Real AWS integration via SDK (EC2, RDS, EBS, Lambda with STS validation and graceful degradation) -- [x] Multi-cloud support (GCP, Azure) with Compute, SQL, Disks, and Functions for each provider -- [x] Cost trend tracking over time (automatic snapshots on seed + `trend` command) -- [x] Parallel fetch with `errgroup` and per-service `context.WithTimeout` -- [x] Structured logging with `log/slog` (text or JSON output, level-configurable) -- [x] Centralized configuration loaded once and injected as typed structs -- [x] Export findings to JSON/CSV (stdout or file, RFC 4180 escaping, pipeline-friendly) -- [x] Web dashboard with cost visualizations (React + Recharts + Tailwind v4, embedded in the Go binary via `go:embed`, served by `oracle serve`) -- [x] SDK-client interfaces for real-provider unit tests — every provider fetcher (AWS / GCP / Azure) is exercised against fake SDK clients, covering pagination, per-service errors, and graceful degradation -- [x] Fail-fast configuration validation — `config.Load() (Config, error)` accumulates every invalid env var into a single readable error, with cross-field rules (provider=gcp without `GOOGLE_CLOUD_PROJECT`, `LLM_PROVIDER=claude` without `ANTHROPIC_API_KEY`, etc.) -- [x] Resilient LLM HTTP layer — shared `RoundTripper` retries 429/5xx/network errors with exponential-backoff-with-full-jitter, honors `Retry-After`, replays request bodies, cancellable via context -- [x] testcontainers-based integration tests — real Postgres 16 in Docker via `testcontainers-go`, gated by `//go:build integration`, with a full seed → analyze E2E test and a GitHub Actions workflow that runs both unit and integration tiers + +- [X] LLM-powered analysis: executive summaries generated by Gemini / Claude / OpenAI +- [X] PDF report generation with executive summary and severity-coded tables +- [X] Real AWS integration via SDK (EC2, RDS, EBS, Lambda with STS validation and graceful degradation) +- [X] Multi-cloud support (GCP, Azure) with Compute, SQL, Disks, and Functions for each provider +- [X] Cost trend tracking over time (automatic snapshots on seed + `trend` command) +- [X] Parallel fetch with `errgroup` and per-service `context.WithTimeout` +- [X] Structured logging with `log/slog` (text or JSON output, level-configurable) +- [X] Centralized configuration loaded once and injected as typed structs +- [X] Export findings to JSON/CSV (stdout or file, RFC 4180 escaping, pipeline-friendly) +- [X] Web dashboard with cost visualizations (React + Recharts + Tailwind v4, embedded in the Go binary via `go:embed`, served by `oracle serve`) +- [X] SDK-client interfaces for real-provider unit tests — every provider fetcher (AWS / GCP / Azure) is exercised against fake SDK clients, covering pagination, per-service errors, and graceful degradation +- [X] Fail-fast configuration validation — `config.Load() (Config, error)` accumulates every invalid env var into a single readable error, with cross-field rules (provider=gcp without `GOOGLE_CLOUD_PROJECT`, `LLM_PROVIDER=claude` without `ANTHROPIC_API_KEY`, etc.) +- [X] Resilient LLM HTTP layer — shared `RoundTripper` retries 429/5xx/network errors with exponential-backoff-with-full-jitter, honors `Retry-After`, replays request bodies, cancellable via context +- [X] testcontainers-based integration tests — real Postgres 16 in Docker via `testcontainers-go`, gated by `//go:build integration`, with a full seed → analyze E2E test and a GitHub Actions workflow that runs both unit and integration tiers ## License diff --git a/insights-agent/README.md b/insights-agent/README.md index 18c8999..ab275b7 100644 --- a/insights-agent/README.md +++ b/insights-agent/README.md @@ -5,33 +5,33 @@ LangGraph-based FinOps insights agent for CloudOracle. Ask in natural language `/api/v1` calls against the CloudOracle Go server, then answers in the same language with the relevant caveats. -This is the first round-trip of sub-hito 8.1: single-turn agent (no +This is the first round-trip of milestone 8.1: single-turn agent (no conversational memory), `create_react_agent` from `langgraph.prebuilt`, two tools wired against the Go cost endpoints, Gemini as the model. Future -sub-hitos replace the ReAct loop with a custom supervisor (8.4) and add +milestones replace the ReAct loop with a custom supervisor (8.4) and add RAG over FinOps docs (8.3). ## What it talks to ``` -┌────────┐ "¿Cuánto gasté en AWS?" ┌─────────────┐ -│ User │ ─────────────────────────▶ │ insights- │ -└────────┘ │ agent (CLI) │ - └──────┬──────┘ - │ LangGraph (Gemini) - │ tool call → - ▼ - ┌─────────────┐ X-API-Key - │ Go server │ ──────────▶ Postgres - │ /api/v1/... │ (cost_snapshots) - └─────────────┘ +┌────────┐ "How much did I spend on AWS?" ┌─────────────┐ +│ User │ ───────────────────────────────▶ │ insights- │ +└────────┘ │ agent (CLI) │ + └──────┬──────┘ + │ LangGraph (Gemini) + │ tool call → + ▼ + ┌─────────────┐ X-API-Key + │ Go server │ ──────────▶ Postgres + │ /api/v1/... │ (cost_snapshots) + └─────────────┘ ``` The two tools both return a `data_source` field. While it equals `"snapshots_approximation"`, the figures come from periodic CloudOracle snapshots — **not** a real billing API. The agent surfaces that caveat to the user when accuracy materially affects the answer. The real billing -integration lands in sub-hito 8.7. +integration lands in milestone 8.7. ## Setup in under 10 minutes @@ -75,7 +75,7 @@ Required env vars (loaded by `pydantic-settings`, fail-fast at startup): ### 4 — Run the CLI ```bash -uv run python -m insights_agent.main "¿Cuánto gasté en AWS en abril de 2026?" +uv run python -m insights_agent.main "How much did I spend on AWS in April 2026?" ``` Or via the console script entry point: @@ -129,7 +129,7 @@ the unit tests already cover the pipeline with a mocked model. 2. **Run the agent** from `insights-agent/`: ```bash - uv run insights-agent --verbose "¿Cuánto gasté en AWS en abril de 2026?" + uv run insights-agent --verbose "How much did I spend on AWS in April 2026?" ``` 3. **Expected output** (shape, not exact wording — Gemini paraphrases): @@ -170,17 +170,17 @@ ReAct loop deterministically — including the tool-error branch. | ------------------- | ------------- | --- | | Vendor-agnostic LLM | `src/insights_agent/llm/base.py` + `gemini.py` | ABC + one implementation. Add `AnthropicProvider` / `OpenAIProvider` later by implementing `LLMProvider`; no graph changes required. | | Tools | `src/insights_agent/tools/cloudoracle.py` | `CloudOracleClient` owns the HTTP + auth + request-ID conventions; `build_tools(client)` wraps the two methods as `StructuredTool`s with rich docstrings so the LLM picks the right one. Errors flow as `ToolException` so the model sees them as observations and can recover instead of aborting the run. | -| Graph | `src/insights_agent/graph/basic.py` | `create_react_agent` from `langgraph.prebuilt` with a short system prompt. Sub-hito 8.4 replaces this with a hand-rolled supervisor. | +| Graph | `src/insights_agent/graph/basic.py` | `create_react_agent` from `langgraph.prebuilt` with a short system prompt. Milestone 8.4 replaces this with a hand-rolled supervisor. | | CLI | `src/insights_agent/main.py` | argparse, three flags, four exit codes, single async run. No conversational memory (each call is independent). | | Settings | `src/insights_agent/config.py` | `pydantic-settings.BaseSettings` — fail-fast `ValidationError` at startup if any required env var is missing. | | Logging | `src/insights_agent/logging.py` | `structlog` matching the Go side's `slog` output (text or JSON to stderr) so a tail of both streams reads coherently. | -### What is **not** in this sub-hito +### What is **not** in this milestone -- More tools (sub-hito 8.2) +- More tools (milestone 8.2) - pgvector / RAG over FinOps docs (8.3) - Custom supervisor / multi-agent (8.4) -- Cost caps, semantic answer validation, fallback determinístico (8.5) +- Cost caps, semantic answer validation, deterministic fallback (8.5) - HTTP API surface for the agent — CLI only until 8.5 - Other LLM providers (Anthropic, OpenAI) - Streaming responses diff --git a/insights-agent/pyproject.toml b/insights-agent/pyproject.toml index 2dcb57a..4ee3583 100644 --- a/insights-agent/pyproject.toml +++ b/insights-agent/pyproject.toml @@ -43,7 +43,7 @@ asyncio_mode = "auto" testpaths = ["tests"] addopts = "--cov=insights_agent --cov-report=term-missing --cov-fail-under=80 -ra" filterwarnings = [ - # `create_react_agent` is the explicit choice for sub-hito 8.1; the + # `create_react_agent` is the explicit choice for milestone 8.1; the # supervisor refactor in 8.4 replaces it. Silence the deprecation here # so the warning doesn't drown out real signal in the test output. "ignore::langgraph.warnings.LangGraphDeprecationWarning", diff --git a/insights-agent/src/insights_agent/graph/basic.py b/insights-agent/src/insights_agent/graph/basic.py index 72e0155..dc8d487 100644 --- a/insights-agent/src/insights_agent/graph/basic.py +++ b/insights-agent/src/insights_agent/graph/basic.py @@ -1,7 +1,7 @@ """Basic ReAct graph: question → tool call(s) → natural-language answer. Uses `langgraph.prebuilt.create_react_agent` for the first end-to-end -round-trip. Sub-hito 8.4 will replace this with a hand-rolled supervisor +round-trip. Milestone 8.4 will replace this with a hand-rolled supervisor pattern; until then, `create_react_agent` gives us: - A tool-aware LLM call (bind_tools is invoked under the hood). diff --git a/insights-agent/src/insights_agent/llm/__init__.py b/insights-agent/src/insights_agent/llm/__init__.py index f57edc4..f902192 100644 --- a/insights-agent/src/insights_agent/llm/__init__.py +++ b/insights-agent/src/insights_agent/llm/__init__.py @@ -1,7 +1,7 @@ """LLM provider abstraction. The `LLMProvider` ABC isolates LangGraph from any specific vendor SDK so that -swapping Gemini for Claude or OpenAI later (sub-hito 8.4+) doesn't touch the +swapping Gemini for Claude or OpenAI later (milestone 8.4+) doesn't touch the graph code — only requires adding a new provider class + a selector in main. """ diff --git a/insights-agent/src/insights_agent/tools/cloudoracle.py b/insights-agent/src/insights_agent/tools/cloudoracle.py index f2336f1..0c25579 100644 --- a/insights-agent/src/insights_agent/tools/cloudoracle.py +++ b/insights-agent/src/insights_agent/tools/cloudoracle.py @@ -7,7 +7,7 @@ Both return a `data_source` field tagging the response as `"snapshots_approximation"` until the real billing-API integration lands -(sub-hito 8.7). The tool docstrings tell the LLM to surface that caveat to +(milestone 8.7). The tool docstrings tell the LLM to surface that caveat to the user — `note` carries the long-form disclaimer text the Go side curates. Errors are propagated as exceptions. LangGraph's ReAct loop catches them diff --git a/insights-agent/tests/test_graph.py b/insights-agent/tests/test_graph.py index 5c9481e..254c119 100644 --- a/insights-agent/tests/test_graph.py +++ b/insights-agent/tests/test_graph.py @@ -110,8 +110,8 @@ async def test_graph_invokes_summary_tool_then_returns_answer( # Turn 2: deliver a final answer that references the snapshot caveat. AIMessage( content=( - "Gastaste aproximadamente $150 en AWS en abril 2026 " - "(aproximación basada en snapshots, no factura final)." + "You spent approximately $150 on AWS in April 2026 " + "(snapshots-based approximation, not the final bill)." ) ), ] @@ -119,7 +119,7 @@ async def test_graph_invokes_summary_tool_then_returns_answer( tools = build_tools(client) graph = build_graph(model, tools) - result = await ask(graph, "¿Cuánto gasté en AWS en abril de 2026?") + result = await ask(graph, "How much did I spend on AWS in April 2026?") assert len(result.tool_calls) == 1 assert result.tool_calls[0]["name"] == "cloudoracle_cost_summary" diff --git a/internal/api/cost_handlers.go b/internal/api/cost_handlers.go index af48e88..5866e38 100644 --- a/internal/api/cost_handlers.go +++ b/internal/api/cost_handlers.go @@ -17,7 +17,7 @@ import ( // endpoints. CloudOracle's `cost_snapshots` table records each provider's // *projected monthly cost rate* at snapshot time — not the historical spend // that a real Billing / Cost Explorer integration would surface. Until that -// integration lands (sub-hito 8.2+), the v1 endpoints expose this +// integration lands (milestone 8.2+), the v1 endpoints expose this // approximation explicitly in every response so downstream agents and // dashboards can present the right disclaimer to the user. const ( diff --git a/internal/cloud/aws_provider_fetch_test.go b/internal/cloud/aws_provider_fetch_test.go index f4edc92..a7de984 100644 --- a/internal/cloud/aws_provider_fetch_test.go +++ b/internal/cloud/aws_provider_fetch_test.go @@ -66,9 +66,9 @@ func newTestAWSProvider(ec2c ec2APIClient, rdsc rdsAPIClient, lc lambdaAPIClient func strP(s string) *string { return &s } -// TestFetchEC2Instances_Pagination verifica que el paginator del SDK consume -// todas las paginas, no solo la primera. Es exactamente el bug que se introduce -// si alguien refactoriza el fetcher y olvida llamar HasMorePages en bucle. +// TestFetchEC2Instances_Pagination verifies that the SDK paginator consumes +// every page, not just the first. It catches exactly the bug introduced if +// someone refactors the fetcher and forgets to call HasMorePages in a loop. func TestFetchEC2Instances_Pagination(t *testing.T) { page1Time := time.Date(2026, 3, 1, 0, 0, 0, 0, time.UTC) page2Time := time.Date(2026, 3, 2, 0, 0, 0, 0, time.UTC) @@ -207,9 +207,9 @@ func TestFetchRDSInstances_FetchesTagsPerInstance(t *testing.T) { } } -// TestFetchLambdaFunctions_TagFailureDoesNotAbort verifica que un error en -// ListTags para una funcion individual no aborta el fetch — la funcion entra -// con tags=nil y el resto del scan continua. +// TestFetchLambdaFunctions_TagFailureDoesNotAbort verifies that an error on +// ListTags for an individual function does not abort the fetch — the function +// is included with tags=nil and the rest of the scan keeps going. func TestFetchLambdaFunctions_TagFailureDoesNotAbort(t *testing.T) { lc := &fakeLambda{ listFunctions: func(context.Context, *lambda.ListFunctionsInput) (*lambda.ListFunctionsOutput, error) { @@ -240,9 +240,9 @@ func TestFetchLambdaFunctions_TagFailureDoesNotAbort(t *testing.T) { } } -// TestFetchResources_GracefulDegradation verifica el contrato clave del provider: -// si UN servicio falla, los demas siguen entregando recursos. Esto es lo que -// hace que un outage regional de RDS no rompa el scan completo. +// TestFetchResources_GracefulDegradation verifies the provider's key contract: +// if ONE service fails, the others keep delivering resources. This is what +// keeps a regional RDS outage from breaking the whole scan. func TestFetchResources_GracefulDegradation(t *testing.T) { now := time.Now() @@ -307,9 +307,9 @@ func TestFetchResources_GracefulDegradation(t *testing.T) { } } -// TestFetchResources_AllServicesFail confirma que cuando todo falla, -// FetchResources devuelve nil sin panic — el caller recibe una lista vacia, -// no un crash. +// TestFetchResources_AllServicesFail confirms that when everything fails, +// FetchResources returns nil without panicking — the caller gets an empty +// list, not a crash. func TestFetchResources_AllServicesFail(t *testing.T) { failEC2 := &fakeEC2{ describeInstances: func(context.Context, *ec2.DescribeInstancesInput) (*ec2.DescribeInstancesOutput, error) { diff --git a/internal/cloud/aws_provider_test.go b/internal/cloud/aws_provider_test.go index 7d19066..d9c0d33 100644 --- a/internal/cloud/aws_provider_test.go +++ b/internal/cloud/aws_provider_test.go @@ -7,18 +7,18 @@ import ( ec2types "github.com/aws/aws-sdk-go-v2/service/ec2/types" ) -// TestMapEC2ToResource verifica que mapEC2ToResource mapea correctamente -// cada campo de una ec2types.Instance a un shared.Resource. -// Usamos un struct literal del SDK como "mock" — no necesitamos un cliente -// real ni llamadas de red porque mapEC2ToResource es una funcion pura. +// TestMapEC2ToResource verifies that mapEC2ToResource maps every field of +// an ec2types.Instance to a shared.Resource correctly. +// We use an SDK struct literal as a "mock" — no real client or network +// calls are needed because mapEC2ToResource is a pure function. func TestMapEC2ToResource(t *testing.T) { launchTime := time.Date(2026, 4, 12, 19, 12, 46, 0, time.UTC) instanceID := "i-0d76ebf46c06e285d" tagKey := "Name" tagValue := "cloudoracle-test" - // Armamos una instancia EC2 con los mismos campos que devolveria la API. - // Los punteros a string son necesarios porque el SDK usa *string en todos lados. + // Build an EC2 instance with the same fields the API would return. + // String pointers are required because the SDK uses *string everywhere. instance := ec2types.Instance{ InstanceId: &instanceID, InstanceType: ec2types.InstanceTypeT3Micro, @@ -30,8 +30,8 @@ func TestMapEC2ToResource(t *testing.T) { r := mapEC2ToResource(instance, "505610409129", "us-east-2") - // Verificamos cada campo individualmente en vez de usar reflect.DeepEqual - // porque asi el mensaje de error dice exactamente que campo fallo. + // Verify each field individually instead of using reflect.DeepEqual so + // the error message points at exactly which field failed. if r.ID != "i-0d76ebf46c06e285d" { t.Errorf("ID = %q, want %q", r.ID, "i-0d76ebf46c06e285d") } @@ -61,8 +61,8 @@ func TestMapEC2ToResource(t *testing.T) { } } -// TestMapEC2ToResource_NoTags verifica que una instancia sin tags -// produce un Resource con Tags == nil (no un map vacio). +// TestMapEC2ToResource_NoTags verifies that an instance with no tags +// produces a Resource with Tags == nil (not an empty map). func TestMapEC2ToResource_NoTags(t *testing.T) { launchTime := time.Now() instanceID := "i-notags" @@ -71,7 +71,7 @@ func TestMapEC2ToResource_NoTags(t *testing.T) { InstanceId: &instanceID, InstanceType: ec2types.InstanceTypeM5Large, LaunchTime: &launchTime, - Tags: nil, // sin tags + Tags: nil, // no tags } r := mapEC2ToResource(instance, "123456789", "eu-west-1") @@ -84,8 +84,8 @@ func TestMapEC2ToResource_NoTags(t *testing.T) { } } -// TestMapEC2ToResource_MultipleTags verifica que multiples tags -// se convierten correctamente al map. +// TestMapEC2ToResource_MultipleTags verifies that multiple tags are +// correctly converted into the map. func TestMapEC2ToResource_MultipleTags(t *testing.T) { launchTime := time.Now() instanceID := "i-multitags" @@ -120,12 +120,12 @@ func TestMapEC2ToResource_MultipleTags(t *testing.T) { } } -// TestConvertEC2Tags_NilValue verifica que un tag con Value == nil -// se convierte a string vacio en vez de paniquear. +// TestConvertEC2Tags_NilValue verifies that a tag with Value == nil is +// converted to an empty string instead of panicking. func TestConvertEC2Tags_NilValue(t *testing.T) { key := "AutoScalingGroup" tags := []ec2types.Tag{ - {Key: &key, Value: nil}, // AWS a veces devuelve tags con Value nil + {Key: &key, Value: nil}, // AWS sometimes returns tags with Value nil } result := convertEC2Tags(tags) @@ -135,23 +135,23 @@ func TestConvertEC2Tags_NilValue(t *testing.T) { } } -// TestParseLambdaTimestamp verifica los distintos formatos que Lambda puede devolver. +// TestParseLambdaTimestamp verifies the different formats Lambda may return. func TestParseLambdaTimestamp(t *testing.T) { - // Formato principal de Lambda: "2024-01-15T10:30:00.000+0000" + // Lambda's primary format: "2024-01-15T10:30:00.000+0000" ts1 := "2024-01-15T10:30:00.000+0000" result := parseLambdaTimestamp(&ts1) if result.Year() != 2024 || result.Month() != 1 || result.Day() != 15 { t.Errorf("Lambda format: got %v, want 2024-01-15", result) } - // Formato RFC3339 estándar + // Standard RFC3339 format ts2 := "2024-06-20T14:00:00Z" result = parseLambdaTimestamp(&ts2) if result.Year() != 2024 || result.Month() != 6 || result.Day() != 20 { t.Errorf("RFC3339 format: got %v, want 2024-06-20", result) } - // nil devuelve time.Now() (no paniquea) + // nil returns time.Now() (does not panic) result = parseLambdaTimestamp(nil) if time.Since(result) > time.Second { t.Errorf("nil input should return ~now, got %v", result) diff --git a/internal/cloud/azure_provider_test.go b/internal/cloud/azure_provider_test.go index e5433ee..968e238 100644 --- a/internal/cloud/azure_provider_test.go +++ b/internal/cloud/azure_provider_test.go @@ -91,9 +91,9 @@ func TestAzureFetchVirtualMachines_Mapping(t *testing.T) { } } -// TestAzureFetchVirtualMachines_NilHardwareProfile verifica que un VM con -// Properties.HardwareProfile == nil no paniquea — Azure puede devolver eso -// para VMs en estados de transicion. +// TestAzureFetchVirtualMachines_NilHardwareProfile verifies that a VM with +// Properties.HardwareProfile == nil does not panic — Azure can return that +// for VMs in transitional states. func TestAzureFetchVirtualMachines_NilHardwareProfile(t *testing.T) { name := "vm-broken" location := "westus" @@ -172,10 +172,10 @@ func TestAzureFetchManagedDisks_Mapping(t *testing.T) { } } -// TestAzureFetchFunctionApps_FiltersOutWebApps verifica el filtrado clave -// del fetcher: el endpoint /sites devuelve Web Apps Y Function Apps mezclados, -// y solo nos interesan los functionapp. Si alguien rompe el filtro, este test -// se cae. +// TestAzureFetchFunctionApps_FiltersOutWebApps verifies the fetcher's key +// filtering: the /sites endpoint returns Web Apps AND Function Apps mixed +// together, and we only care about functionapp. If someone breaks the +// filter, this test fails. func TestAzureFetchFunctionApps_FiltersOutWebApps(t *testing.T) { fnName, fnKind, fnLoc := "fn-1", "functionapp", "eastus" webName, webKind, webLoc := "web-app", "app", "eastus" @@ -201,8 +201,8 @@ func TestAzureFetchFunctionApps_FiltersOutWebApps(t *testing.T) { } func TestAzureFetchFunctionApps_LinuxKindMatches(t *testing.T) { - // Azure devuelve Kind como "functionapp,linux" para function apps en Linux. - // El filtro debe ser case-insensitive y un substring. + // Azure returns Kind as "functionapp,linux" for function apps on Linux. + // The filter must be case-insensitive and a substring match. name, kind, loc := "fn-linux", "functionapp,linux", "eastus" p := newTestAzureProvider() @@ -221,8 +221,8 @@ func TestAzureFetchFunctionApps_LinuxKindMatches(t *testing.T) { } } -// TestAzureFetchResources_GracefulDegradation: si Azure SQL falla, -// los demas servicios (VM, Disks, Functions) deben seguir surfaceando. +// TestAzureFetchResources_GracefulDegradation: if Azure SQL fails, the +// other services (VM, Disks, Functions) must keep surfacing. func TestAzureFetchResources_GracefulDegradation(t *testing.T) { vmName, loc := "vm-ok", "eastus" vmSize := armcompute.VirtualMachineSizeTypesStandardB2S @@ -258,7 +258,7 @@ func TestExtractResourceGroup(t *testing.T) { if got := extractResourceGroup(id); got != "my-rg" { t.Errorf("got %q, want my-rg", got) } - // case-insensitive: la API a veces devuelve "resourcegroups" minusculas + // case-insensitive: the API sometimes returns "resourcegroups" in lowercase id2 := "/subscriptions/abc/resourcegroups/lowercased-rg/providers/Foo" if got := extractResourceGroup(id2); got != "lowercased-rg" { t.Errorf("case-insensitive: got %q, want lowercased-rg", got) @@ -272,7 +272,7 @@ func TestConvertAzureTags_NilValuePointer(t *testing.T) { val := "value" tags := map[string]*string{ "key1": &val, - "key2": nil, // tag con valor nil — la API a veces devuelve eso + "key2": nil, // tag with a nil value — the API sometimes returns that } got := convertAzureTags(tags) if got["key1"] != "value" { diff --git a/internal/cloud/gcp_provider_test.go b/internal/cloud/gcp_provider_test.go index 1ce63fe..ad43219 100644 --- a/internal/cloud/gcp_provider_test.go +++ b/internal/cloud/gcp_provider_test.go @@ -55,9 +55,9 @@ func newTestGCPProvider() *GCPProvider { } } -// TestGCPFetchComputeInstances_MapsZoneToRegion verifica el mapeo no obvio -// zone -> region: "us-central1-a" debe convertirse en "us-central1". Es un -// detalle facil de romper si alguien cambia extractRegionFromZone. +// TestGCPFetchComputeInstances_MapsZoneToRegion verifies the non-obvious +// zone -> region mapping: "us-central1-a" must become "us-central1". It's a +// detail that's easy to break if someone changes extractRegionFromZone. func TestGCPFetchComputeInstances_MapsZoneToRegion(t *testing.T) { zone := "https://www.googleapis.com/compute/v1/projects/test-project/zones/us-central1-a" machineType := "https://www.googleapis.com/compute/v1/projects/test-project/zones/us-central1-a/machineTypes/n2-standard-4" @@ -137,8 +137,8 @@ func TestGCPFetchCloudSQL_Mapping(t *testing.T) { } } -// TestGCPFetchCloudSQL_NilSettings cubre el caso en el que la API devuelve -// una instancia sin Settings (proxima al borrado). El mapeador no debe paniquear. +// TestGCPFetchCloudSQL_NilSettings covers the case where the API returns an +// instance with no Settings (about to be deleted). The mapper must not panic. func TestGCPFetchCloudSQL_NilSettings(t *testing.T) { p := newTestGCPProvider() p.sql = &fakeGCPSQL{ @@ -215,8 +215,8 @@ func TestGCPFetchCloudFunctions_Mapping(t *testing.T) { } } -// TestGCPFetchResources_GracefulDegradation verifica que cuando un servicio -// (Cloud SQL aqui) falla, los demas todavia entregan recursos. +// TestGCPFetchResources_GracefulDegradation verifies that when one service +// (Cloud SQL here) fails, the others still deliver resources. func TestGCPFetchResources_GracefulDegradation(t *testing.T) { zone := "projects/test/zones/us-central1-a" machineType := "projects/test/zones/us-central1-a/machineTypes/e2-small" diff --git a/internal/report/pdf.go b/internal/report/pdf.go index 97d307a..c372a6f 100644 --- a/internal/report/pdf.go +++ b/internal/report/pdf.go @@ -70,7 +70,7 @@ func GeneratePDF(findings []shared.Finding, aiSummary string, outputPath string) severityCounts[shared.SeverityLow])) pdf.Ln(12) - // === AI EXECUTIVE SUMMARY (si está disponible) === + // === AI EXECUTIVE SUMMARY (if available) === if aiSummary != "" { pdf.SetFont("Arial", "B", 14) pdf.SetTextColor(30, 30, 30) @@ -154,7 +154,7 @@ func GeneratePDF(findings []shared.Finding, aiSummary string, outputPath string) ) pdf.MultiCell(0, 5, title, "", "L", false) - // Descripción del problema + // Issue description pdf.SetFont("Arial", "", 9) pdf.SetTextColor(80, 80, 80) pdf.MultiCell(0, 5, "Issue: "+f.Description, "", "L", false) From 3805ad9404db682795b8289ae60780e50afbd870 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jesus=20Nu=C3=B1ez?= Date: Sat, 30 May 2026 16:15:33 -0400 Subject: [PATCH 10/18] feat(insights-agent): recommendations tool + /api/v1/recommendations endpoint Milestone 8.2 (more tools): expose the rule-based analyzer findings as agent-friendly savings recommendations. Go: new authed GET /api/v1/recommendations handler that runs analyzer.Analyze over the current inventory, with optional provider/severity filters and a top cap. Totals (total_count, total_monthly_savings_usd, by_severity) describe the full filtered set before the cap. Carries data_source: "heuristic_rules" to distinguish heuristic estimates from the snapshot-derived cost endpoints. Python: CloudOracleClient.recommendations() + cloudoracle_recommendations tool with a rich docstring; system prompt updated to surface the heuristic_rules caveat. Validation errors map to ToolException so the ReAct loop can recover. Tests: 8 Go handler tests; extended Python tool tests. Both suites green (internal/api; 65 Python tests, 92% coverage, ruff + mypy clean). Co-Authored-By: Claude Opus 4.8 (1M context) --- README.md | 13 +- insights-agent/README.md | 39 ++-- .../src/insights_agent/graph/basic.py | 5 +- .../src/insights_agent/tools/cloudoracle.py | 88 ++++++++- .../tests/test_cloudoracle_tools.py | 123 +++++++++++- internal/api/recommendations_handler.go | 182 ++++++++++++++++++ internal/api/recommendations_handler_test.go | 180 +++++++++++++++++ internal/api/server.go | 2 + 8 files changed, 606 insertions(+), 26 deletions(-) create mode 100644 internal/api/recommendations_handler.go create mode 100644 internal/api/recommendations_handler_test.go diff --git a/README.md b/README.md index 33da600..5d3aba1 100644 --- a/README.md +++ b/README.md @@ -20,18 +20,19 @@ flowchart LR U([User]) -->|"How much did I spend on AWS?"| CLI[insights-agent CLI
Python 3.12] CLI --> G[LangGraph
create_react_agent] G -->|"bind_tools"| LLM[Gemini 2.5 Flash] - LLM -->|"tool call"| T[CloudOracle tools
cost-summary / cost-by-service] + LLM -->|"tool call"| T[CloudOracle tools
cost-summary / cost-by-service / recommendations] T -->|"GET /api/v1/* + X-API-Key"| GO[CloudOracle Go
oracle serve] GO -->|"SQL"| DB[(PostgreSQL
cost_snapshots)] - GO -->|"data_source: snapshots_approximation"| T + GO -->|"data_source: snapshots_approximation / heuristic_rules"| T T --> LLM LLM -->|"natural-language answer"| CLI CLI --> U ``` -Milestone 8.1 (single-turn, two tools, Gemini, no RAG) is the first end-to-end -round-trip. Setup, env vars, CLI usage, and the smoke test are documented in -**[insights-agent/README.md](insights-agent/README.md)**. +The agent ships three tools: two cost endpoints (totals per provider, per-service +breakdown) plus a savings-recommendations endpoint that answers "where can I save +money?" from the rule-based analyzer. Setup, env vars, CLI usage, and the smoke +test are documented in **[insights-agent/README.md](insights-agent/README.md)**. ## v2 — Quick start (current focus) @@ -129,7 +130,7 @@ The synthetic provider needs no credentials. To run against AWS / GCP / Azure, s - [X] **Milestone 8.0** — Authenticated `/api/v1/cost-summary` and `/api/v1/cost-by-service` Go endpoints (X-API-Key, snapshot-derived totals with explicit `data_source` disclaimer, machine-readable error codes) - [X] **Milestone 8.1** — Python `insights-agent` sibling: LangGraph `create_react_agent` graph with two CloudOracle tools, Gemini provider, pydantic-settings config, structlog matching the Go slog format, CLI with `--verbose` / `--json` flags, 92% test coverage with mocked LLM + mocked HTTP. See **[insights-agent/](insights-agent/README.md)** -- [ ] **Milestone 8.2** — Additional tools (resources, findings, trends) wired against the v0 dashboard endpoints +- [ ] **Milestone 8.2** — Additional tools (in progress). Done: authenticated `GET /api/v1/recommendations` endpoint (rule-based savings findings with provider/severity filters, `data_source: heuristic_rules`) + `cloudoracle_recommendations` agent tool. Next: resources / trends tools - [ ] **Milestone 8.3** — pgvector + RAG over FinOps documentation - [ ] **Milestone 8.4** — Hand-rolled supervisor (multi-agent), replacing `create_react_agent` - [ ] **Milestone 8.5** — Production guardrails: cost caps, deterministic fallback, semantic answer validation, HTTP API surface diff --git a/insights-agent/README.md b/insights-agent/README.md index ab275b7..ce64fe1 100644 --- a/insights-agent/README.md +++ b/insights-agent/README.md @@ -5,11 +5,11 @@ LangGraph-based FinOps insights agent for CloudOracle. Ask in natural language `/api/v1` calls against the CloudOracle Go server, then answers in the same language with the relevant caveats. -This is the first round-trip of milestone 8.1: single-turn agent (no -conversational memory), `create_react_agent` from `langgraph.prebuilt`, two -tools wired against the Go cost endpoints, Gemini as the model. Future -milestones replace the ReAct loop with a custom supervisor (8.4) and add -RAG over FinOps docs (8.3). +Built on `create_react_agent` from `langgraph.prebuilt`: single-turn agent (no +conversational memory), Gemini as the model, three tools wired against the Go +`/api/v1` endpoints — two cost endpoints (milestone 8.1) plus a savings +recommendations endpoint (milestone 8.2). Future milestones replace the ReAct +loop with a custom supervisor (8.4) and add RAG over FinOps docs (8.3). ## What it talks to @@ -27,11 +27,25 @@ RAG over FinOps docs (8.3). └─────────────┘ ``` -The two tools both return a `data_source` field. While it equals -`"snapshots_approximation"`, the figures come from periodic CloudOracle -snapshots — **not** a real billing API. The agent surfaces that caveat -to the user when accuracy materially affects the answer. The real billing -integration lands in milestone 8.7. +Every tool returns a `data_source` field so the agent surfaces the right +caveat: + +- The two **cost** tools return `"snapshots_approximation"` — figures come + from periodic CloudOracle snapshots, **not** a real billing API (the real + billing integration lands in milestone 8.7). +- The **recommendations** tool returns `"heuristic_rules"` — savings are + estimated upper bounds from a rule-based analyzer over the current resource + inventory, to be validated against real usage before acting. + +The agent surfaces these caveats when accuracy materially affects the answer. + +### Tools + +| Tool | Answers | Backing endpoint | +| ---- | ------- | ---------------- | +| `cloudoracle_cost_summary` | "how much did I spend?" (totals per provider) | `GET /api/v1/cost-summary` | +| `cloudoracle_cost_by_service` | "what drove AWS spend?" (per-service breakdown) | `GET /api/v1/cost-by-service` | +| `cloudoracle_recommendations` | "where can I save money?" (savings opportunities) | `GET /api/v1/recommendations` | ## Setup in under 10 minutes @@ -169,15 +183,14 @@ ReAct loop deterministically — including the tool-error branch. | Concern | Where to look | Why | | ------------------- | ------------- | --- | | Vendor-agnostic LLM | `src/insights_agent/llm/base.py` + `gemini.py` | ABC + one implementation. Add `AnthropicProvider` / `OpenAIProvider` later by implementing `LLMProvider`; no graph changes required. | -| Tools | `src/insights_agent/tools/cloudoracle.py` | `CloudOracleClient` owns the HTTP + auth + request-ID conventions; `build_tools(client)` wraps the two methods as `StructuredTool`s with rich docstrings so the LLM picks the right one. Errors flow as `ToolException` so the model sees them as observations and can recover instead of aborting the run. | +| Tools | `src/insights_agent/tools/cloudoracle.py` | `CloudOracleClient` owns the HTTP + auth + request-ID conventions; `build_tools(client)` wraps the three methods as `StructuredTool`s with rich docstrings so the LLM picks the right one. Errors flow as `ToolException` so the model sees them as observations and can recover instead of aborting the run. | | Graph | `src/insights_agent/graph/basic.py` | `create_react_agent` from `langgraph.prebuilt` with a short system prompt. Milestone 8.4 replaces this with a hand-rolled supervisor. | | CLI | `src/insights_agent/main.py` | argparse, three flags, four exit codes, single async run. No conversational memory (each call is independent). | | Settings | `src/insights_agent/config.py` | `pydantic-settings.BaseSettings` — fail-fast `ValidationError` at startup if any required env var is missing. | | Logging | `src/insights_agent/logging.py` | `structlog` matching the Go side's `slog` output (text or JSON to stderr) so a tail of both streams reads coherently. | -### What is **not** in this milestone +### What is **not** here yet -- More tools (milestone 8.2) - pgvector / RAG over FinOps docs (8.3) - Custom supervisor / multi-agent (8.4) - Cost caps, semantic answer validation, deterministic fallback (8.5) diff --git a/insights-agent/src/insights_agent/graph/basic.py b/insights-agent/src/insights_agent/graph/basic.py index dc8d487..99def80 100644 --- a/insights-agent/src/insights_agent/graph/basic.py +++ b/insights-agent/src/insights_agent/graph/basic.py @@ -33,7 +33,10 @@ Use the tools when the user asks for numbers — never invent or estimate \ costs yourself. If a tool returns `data_source: "snapshots_approximation"`, \ tell the user the figures are approximations from periodic snapshots, not \ -billing-API truth, when accuracy matters for the answer. +billing-API truth, when accuracy matters for the answer. If it returns \ +`data_source: "heuristic_rules"` (the recommendations tool), the savings are \ +heuristic estimates from an analyzer — advise validating against real usage \ +before acting. Reply in the same language the user used. diff --git a/insights-agent/src/insights_agent/tools/cloudoracle.py b/insights-agent/src/insights_agent/tools/cloudoracle.py index 0c25579..ab955b1 100644 --- a/insights-agent/src/insights_agent/tools/cloudoracle.py +++ b/insights-agent/src/insights_agent/tools/cloudoracle.py @@ -30,6 +30,7 @@ logger = structlog.get_logger(__name__) VALID_PROVIDERS: frozenset[str] = frozenset({"aws", "gcp", "azure"}) +VALID_SEVERITIES: frozenset[str] = frozenset({"high", "medium", "low"}) _DATE_FMT = "%Y-%m-%d" @@ -176,6 +177,22 @@ async def cost_by_service( } return await self._get("/api/v1/cost-by-service", params) + async def recommendations( + self, + provider: str | None = None, + severity: str | None = None, + top: int = 20, + ) -> dict[str, Any]: + if not 1 <= top <= 200: + raise ValueError(f"top={top} must be in [1, 200]") + + params: dict[str, str] = {"top": str(top)} + if provider is not None: + params["provider"] = _validate_provider(provider) + if severity is not None: + params["severity"] = _validate_severity(severity) + return await self._get("/api/v1/recommendations", params) + def build_tools(client: CloudOracleClient) -> list[StructuredTool]: """Wrap the client methods as LangChain `StructuredTool`s. @@ -211,6 +228,16 @@ async def _by_service( except (CloudOracleAPIError, CloudOracleTransportError, ValueError) as e: raise ToolException(str(e)) from e + async def _recommendations( + provider: str | None = None, + severity: str | None = None, + top: int = 20, + ) -> dict[str, Any]: + try: + return await client.recommendations(provider, severity, top) + except (CloudOracleAPIError, CloudOracleTransportError, ValueError) as e: + raise ToolException(str(e)) from e + summary_tool = StructuredTool.from_function( coroutine=_summary, name="cloudoracle_cost_summary", @@ -223,7 +250,13 @@ async def _by_service( description=_COST_BY_SERVICE_DESC, handle_tool_error=True, ) - return [summary_tool, by_service_tool] + recommendations_tool = StructuredTool.from_function( + coroutine=_recommendations, + name="cloudoracle_recommendations", + description=_RECOMMENDATIONS_DESC, + handle_tool_error=True, + ) + return [summary_tool, by_service_tool, recommendations_tool] _COST_SUMMARY_DESC = """Return aggregated cloud cost totals per provider for a date range. @@ -280,6 +313,50 @@ async def _by_service( surface it to the user when accuracy matters for the answer.""" +_RECOMMENDATIONS_DESC = """Return cost-optimization recommendations (where to save money). + +Use this for "where can I save money?", "what's wasteful?", "show me my top +optimizations", or any savings / right-sizing / idle-resource question. This is +NOT a spend query — for "how much did I spend", use cloudoracle_cost_summary. + +Args: + provider: Optional filter, one of "aws", "gcp", "azure". Omit for all clouds. + severity: Optional filter, one of "high", "medium", "low". Omit for all. + "high" = biggest / most certain waste; start here for quick wins. + top: Max recommendations to return, sorted by monthly savings descending. + Default 20, range 1..200. Use 5-10 for an executive shortlist. + +Returns: + A dict with this shape: + { + "recommendations": [ + { + "resource_id": "i-aaa", "provider": "aws", "service": "ec2", + "resource_type": "t3.large", "region": "us-east-1", + "rule": "ec2-idle", "severity": "High", + "monthly_cost_usd": 300.0, "monthly_savings_usd": 300.0, + "description": "EC2 i-aaa ... CPU usage 1.0% ...", + "recommendation": "Consider shutting down or terminating ..." + } + ], + "total_count": 12, # full filtered set, before the top cap + "returned_count": 10, # after the top cap + "total_monthly_savings_usd": 1450.0, # sum over the full filtered set + "by_severity": {"High": 3, "Medium": 5, "Low": 4}, + "filters": {"provider": "aws", "severity": "", "top": 10}, + "generated_at": "...", + "data_source": "heuristic_rules", + "note": "" + } + +IMPORTANT: `data_source == "heuristic_rules"` means these come from a rule-based +analyzer over the current inventory, NOT real billing. `monthly_savings_usd` is +an estimated upper bound. When recommending action, tell the user to validate +against real usage first, and quote `total_monthly_savings_usd` for the headline +opportunity. If `returned_count < total_count`, mention the list was truncated to +the top N by savings.""" + + def _validate_date(value: str, field: str) -> date: try: return datetime.strptime(value, _DATE_FMT).date() @@ -303,6 +380,15 @@ def _validate_provider(value: str) -> str: return norm +def _validate_severity(value: str) -> str: + norm = value.strip().lower() if isinstance(value, str) else "" + if norm not in VALID_SEVERITIES: + raise ValueError( + f"severity={value!r} must be one of {sorted(VALID_SEVERITIES)}" + ) + return norm + + def _validate_and_normalize_providers(values: Sequence[str]) -> list[str]: out: list[str] = [] for v in values: diff --git a/insights-agent/tests/test_cloudoracle_tools.py b/insights-agent/tests/test_cloudoracle_tools.py index 6498c04..c912f37 100644 --- a/insights-agent/tests/test_cloudoracle_tools.py +++ b/insights-agent/tests/test_cloudoracle_tools.py @@ -48,6 +48,32 @@ def client() -> CloudOracleClient: "note": "approximation note", } +RECOMMENDATIONS_OK: dict[str, Any] = { + "recommendations": [ + { + "resource_id": "i-aaa", + "provider": "aws", + "service": "ec2", + "resource_type": "t3.large", + "region": "us-east-1", + "rule": "ec2-idle", + "severity": "High", + "monthly_cost_usd": 300.0, + "monthly_savings_usd": 300.0, + "description": "idle instance", + "recommendation": "terminate it", + } + ], + "total_count": 1, + "returned_count": 1, + "total_monthly_savings_usd": 300.0, + "by_severity": {"High": 1}, + "filters": {"provider": "aws", "severity": "high", "top": 20}, + "generated_at": "2026-05-18T12:00:00Z", + "data_source": "heuristic_rules", + "note": "heuristic note", +} + class TestClientConstruction: def test_rejects_empty_base_url(self) -> None: @@ -117,6 +143,36 @@ async def test_params_include_provider_and_top( await client.aclose() +class TestRecommendationsHappyPath: + async def test_success_no_filters( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response(json=RECOMMENDATIONS_OK) + out = await client.recommendations() + assert out == RECOMMENDATIONS_OK + req = httpx_mock.get_request() + assert req is not None + assert req.url.path == "/api/v1/recommendations" + # Only top is sent when provider/severity are omitted. + assert b"top=20" in req.url.query + assert b"provider=" not in req.url.query + assert b"severity=" not in req.url.query + await client.aclose() + + async def test_params_include_filters( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response(json=RECOMMENDATIONS_OK) + await client.recommendations(provider="AWS", severity="High", top=5) + req = httpx_mock.get_request() + assert req is not None + # provider/severity normalized to lowercase before the request. + assert b"provider=aws" in req.url.query + assert b"severity=high" in req.url.query + assert b"top=5" in req.url.query + await client.aclose() + + class TestErrorHandling: async def test_401_raises_with_code( self, client: CloudOracleClient, httpx_mock: HTTPXMock @@ -244,23 +300,55 @@ async def test_top_out_of_range(self, client: CloudOracleClient) -> None: await client.cost_by_service("2026-04-01", "2026-04-30", "aws", top=1001) await client.aclose() + async def test_recommendations_invalid_provider( + self, client: CloudOracleClient + ) -> None: + with pytest.raises(ValueError, match="must be one of"): + await client.recommendations(provider="oracle-cloud") + await client.aclose() + + async def test_recommendations_invalid_severity( + self, client: CloudOracleClient + ) -> None: + with pytest.raises(ValueError, match="must be one of"): + await client.recommendations(severity="critical") + await client.aclose() + + async def test_recommendations_top_out_of_range( + self, client: CloudOracleClient + ) -> None: + with pytest.raises(ValueError, match=r"top=\d+ must be in"): + await client.recommendations(top=0) + with pytest.raises(ValueError, match=r"top=\d+ must be in"): + await client.recommendations(top=201) + await client.aclose() + class TestBuildTools: - async def test_builds_two_tools_with_expected_names( + async def test_builds_three_tools_with_expected_names( self, client: CloudOracleClient ) -> None: tools = build_tools(client) names = {t.name for t in tools} - assert names == {"cloudoracle_cost_summary", "cloudoracle_cost_by_service"} + assert names == { + "cloudoracle_cost_summary", + "cloudoracle_cost_by_service", + "cloudoracle_recommendations", + } await client.aclose() async def test_descriptions_mention_data_source( self, client: CloudOracleClient ) -> None: - tools = build_tools(client) - for t in tools: + # Every tool documents its data_source so the model knows which caveat + # to surface: the cost tools use snapshots_approximation, the + # recommendations tool uses heuristic_rules. + for t in build_tools(client): assert "data_source" in t.description - assert "snapshots_approximation" in t.description + tools_by_name = {t.name: t for t in build_tools(client)} + assert "snapshots_approximation" in tools_by_name["cloudoracle_cost_summary"].description + assert "snapshots_approximation" in tools_by_name["cloudoracle_cost_by_service"].description + assert "heuristic_rules" in tools_by_name["cloudoracle_recommendations"].description await client.aclose() async def test_summary_tool_invokes_client( @@ -293,3 +381,28 @@ async def test_by_service_tool_invokes_client( ) assert out == BY_SERVICE_OK await client.aclose() + + async def test_recommendations_tool_invokes_client( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response(json=RECOMMENDATIONS_OK) + rec_tool = next( + t for t in build_tools(client) if t.name == "cloudoracle_recommendations" + ) + out = await rec_tool.ainvoke({"provider": "aws", "severity": "high", "top": 5}) + assert out == RECOMMENDATIONS_OK + await client.aclose() + + async def test_recommendations_tool_wraps_validation_error( + self, client: CloudOracleClient + ) -> None: + # A bad severity raises ValueError in the client; the tool wrapper must + # translate it to a ToolException so the ReAct loop can recover instead + # of aborting the run. + rec_tool = next( + t for t in build_tools(client) if t.name == "cloudoracle_recommendations" + ) + out = await rec_tool.ainvoke({"severity": "critical"}) + # handle_tool_error=True returns the error string as the observation. + assert "must be one of" in str(out) + await client.aclose() diff --git a/internal/api/recommendations_handler.go b/internal/api/recommendations_handler.go new file mode 100644 index 0000000..6e53831 --- /dev/null +++ b/internal/api/recommendations_handler.go @@ -0,0 +1,182 @@ +package api + +import ( + "CloudOracle/internal/analyzer" + "CloudOracle/internal/shared" + "net/http" + "sort" + "strings" + "time" +) + +// recommendationsDataSource and recommendationsNote document the contract of +// the /api/v1/recommendations endpoint. Unlike the cost endpoints (which +// approximate spend from cost_snapshots), recommendations come from the +// rule-based analyzer run over the *current* resource inventory — so they +// carry a distinct data_source so the agent doesn't conflate the two and +// surfaces the right caveat: these are heuristic estimates, not guaranteed +// savings. +const ( + recommendationsDataSource = "heuristic_rules" + recommendationsNote = "Recommendations come from CloudOracle's rule-based analyzer " + + "applied to the current resource inventory (not historical billing). " + + "Estimated savings are heuristic upper bounds — validate against real " + + "usage before acting." +) + +// defaultRecommendationsTop bounds how many recommendations the endpoint +// returns by default. maxPageSize (200, shared with the findings handler) +// is the hard ceiling so a caller can't ask for an unbounded list. +const defaultRecommendationsTop = 20 + +type recommendationDTO struct { + ResourceID string `json:"resource_id"` + Provider string `json:"provider"` + Service string `json:"service"` + ResourceType string `json:"resource_type"` + Region string `json:"region"` + Rule string `json:"rule"` + Severity string `json:"severity"` + MonthlyCostUSD float64 `json:"monthly_cost_usd"` + MonthlySavingsUSD float64 `json:"monthly_savings_usd"` + Description string `json:"description"` + Recommendation string `json:"recommendation"` +} + +type recommendationsFiltersDTO struct { + Provider string `json:"provider,omitempty"` + Severity string `json:"severity,omitempty"` + Top int `json:"top"` +} + +type recommendationsResponse struct { + Recommendations []recommendationDTO `json:"recommendations"` + TotalCount int `json:"total_count"` + ReturnedCount int `json:"returned_count"` + TotalMonthlySavingsUSD float64 `json:"total_monthly_savings_usd"` + BySeverity map[string]int `json:"by_severity"` + Filters recommendationsFiltersDTO `json:"filters"` + GeneratedAt time.Time `json:"generated_at"` + DataSource string `json:"data_source"` + Note string `json:"note"` +} + +// handleRecommendations exposes the analyzer findings as agent-friendly +// savings recommendations. It answers questions like "where can I save +// money?" or "what are my top AWS optimizations?". Optional filters: +// +// provider=aws|gcp|azure restrict to one cloud +// severity=high|medium|low restrict to one severity band +// top=N cap the list (default 20, max 200) +// +// total_count / total_monthly_savings_usd / by_severity describe the full +// filtered set *before* the top cap, so a truncated list still reports the +// real opportunity size. +func (s *Server) handleRecommendations(w http.ResponseWriter, r *http.Request) { + q := r.URL.Query() + + var providerFilter string + if raw := strings.ToLower(strings.TrimSpace(q.Get("provider"))); raw != "" { + if !validProvider(raw) { + writeAPIError(w, http.StatusBadRequest, + "provider must be one of aws, gcp, azure", "invalid_provider") + return + } + providerFilter = raw + } + + severityFilter, ok := parseSeverityFilter(q.Get("severity")) + if !ok { + writeAPIError(w, http.StatusBadRequest, + "severity must be one of high, medium, low", "invalid_severity") + return + } + + top := parseIntOr(q.Get("top"), defaultRecommendationsTop) + top = clampInt(top, 1, maxPageSize) + + resources, err := s.data.ListResources(r.Context()) + if err != nil { + writeAPIError(w, http.StatusInternalServerError, + "failed to list resources: "+err.Error(), "resource_query_failed") + return + } + + findings := analyzer.Analyze(resources) + + items := make([]recommendationDTO, 0, len(findings)) + bySeverity := make(map[string]int) + var totalSavings float64 + for _, f := range findings { + provider := providerForServiceAccount(f.Service, "") + if providerFilter != "" && provider != providerFilter { + continue + } + if severityFilter != "" && f.Severity != severityFilter { + continue + } + bySeverity[string(f.Severity)]++ + totalSavings += f.MonthlySavings + items = append(items, recommendationDTO{ + ResourceID: f.ResourceID, + Provider: provider, + Service: f.Service, + ResourceType: f.ResourceType, + Region: f.Region, + Rule: f.Rule, + Severity: string(f.Severity), + MonthlyCostUSD: roundCents(f.MonthlyCost), + MonthlySavingsUSD: roundCents(f.MonthlySavings), + Description: f.Description, + Recommendation: f.Recommendation, + }) + } + + // Highest savings first, tiebreak by resource id for a deterministic + // order independent of analyzer internals. + sort.SliceStable(items, func(i, j int) bool { + if items[i].MonthlySavingsUSD != items[j].MonthlySavingsUSD { + return items[i].MonthlySavingsUSD > items[j].MonthlySavingsUSD + } + return items[i].ResourceID < items[j].ResourceID + }) + + totalCount := len(items) + if len(items) > top { + items = items[:top] + } + + writeJSON(w, http.StatusOK, recommendationsResponse{ + Recommendations: items, + TotalCount: totalCount, + ReturnedCount: len(items), + TotalMonthlySavingsUSD: roundCents(totalSavings), + BySeverity: bySeverity, + Filters: recommendationsFiltersDTO{ + Provider: providerFilter, + Severity: strings.ToLower(string(severityFilter)), + Top: top, + }, + GeneratedAt: time.Now().UTC(), + DataSource: recommendationsDataSource, + Note: recommendationsNote, + }) +} + +// parseSeverityFilter maps an optional severity query param to a +// shared.Severity. An empty string means "no filter" (ok=true, empty +// Severity). An unrecognized value is rejected (ok=false). +func parseSeverityFilter(raw string) (shared.Severity, bool) { + switch strings.ToLower(strings.TrimSpace(raw)) { + case "": + return "", true + case "high": + return shared.SeverityHigh, true + case "medium": + return shared.SeverityMedium, true + case "low": + return shared.SeverityLow, true + default: + return "", false + } +} diff --git a/internal/api/recommendations_handler_test.go b/internal/api/recommendations_handler_test.go new file mode 100644 index 0000000..cbf604b --- /dev/null +++ b/internal/api/recommendations_handler_test.go @@ -0,0 +1,180 @@ +package api + +import ( + "CloudOracle/internal/shared" + "encoding/json" + "errors" + "net/http" + "testing" +) + +// recommendationFixtures returns four resources: three trip an analyzer rule +// (ec2-idle/High, rds-oversized/Medium, ebs-orphan/High) and one healthy ec2 +// trips nothing — so a test can assert that non-findings are excluded. +func recommendationFixtures() []shared.Resource { + old := mustTime("2025-01-01T00:00:00Z") // well over the 7-day idle threshold + return []shared.Resource{ + // ec2 idle: High, savings == cost == 300. + {ID: "i-aaa", AccountID: "acc-aws", Service: "ec2", ResourceType: "t3.large", Region: "us-east-1", MonthlyCost: 300, UsageMetric: 1.0, CreatedAt: old}, + // rds oversized: Medium, savings == cost*0.5 == 50. + {ID: "db-bbb", AccountID: "acc-aws", Service: "rds", ResourceType: "db.m5.large", Region: "us-east-1", MonthlyCost: 100, UsageMetric: 5.0, CreatedAt: old}, + // ebs orphan: High, savings == cost == 30. + {ID: "vol-ccc", AccountID: "acc-aws", Service: "ebs", ResourceType: "gp3", Region: "us-east-1", MonthlyCost: 30, UsageMetric: 0, CreatedAt: old}, + // Healthy ec2: no finding. + {ID: "i-ddd", AccountID: "acc-aws", Service: "ec2", ResourceType: "t3.micro", Region: "us-east-1", MonthlyCost: 20, UsageMetric: 80, CreatedAt: old}, + } +} + +func decodeRecs(t *testing.T, body []byte) recommendationsResponse { + t.Helper() + var resp recommendationsResponse + if err := json.Unmarshal(body, &resp); err != nil { + t.Fatalf("decode response: %v\nbody: %s", err, body) + } + return resp +} + +func TestRecommendations_HappyPath(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{resources: recommendationFixtures()}) + rec := doGet(t, srv, "/api/v1/recommendations", true) + + if rec.Code != http.StatusOK { + t.Fatalf("status = %d, want 200; body: %s", rec.Code, rec.Body) + } + resp := decodeRecs(t, rec.Body.Bytes()) + + if resp.TotalCount != 3 { + t.Errorf("TotalCount = %d, want 3", resp.TotalCount) + } + if resp.ReturnedCount != 3 { + t.Errorf("ReturnedCount = %d, want 3", resp.ReturnedCount) + } + if resp.TotalMonthlySavingsUSD != 380 { + t.Errorf("TotalMonthlySavingsUSD = %v, want 380", resp.TotalMonthlySavingsUSD) + } + if resp.BySeverity["High"] != 2 || resp.BySeverity["Medium"] != 1 { + t.Errorf("BySeverity = %v, want High:2 Medium:1", resp.BySeverity) + } + if resp.DataSource != recommendationsDataSource { + t.Errorf("DataSource = %q, want %q", resp.DataSource, recommendationsDataSource) + } + // Sorted by savings desc: ec2(300) > rds(50) > ebs(30). + got := []string{ + resp.Recommendations[0].ResourceID, + resp.Recommendations[1].ResourceID, + resp.Recommendations[2].ResourceID, + } + want := []string{"i-aaa", "db-bbb", "vol-ccc"} + for i := range want { + if got[i] != want[i] { + t.Errorf("order[%d] = %q, want %q (full: %v)", i, got[i], want[i], got) + } + } + if resp.Recommendations[0].Provider != "aws" { + t.Errorf("Provider = %q, want aws", resp.Recommendations[0].Provider) + } +} + +func TestRecommendations_TopCap(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{resources: recommendationFixtures()}) + rec := doGet(t, srv, "/api/v1/recommendations?top=1", true) + + resp := decodeRecs(t, rec.Body.Bytes()) + if resp.ReturnedCount != 1 { + t.Errorf("ReturnedCount = %d, want 1", resp.ReturnedCount) + } + // total_count and savings still describe the full filtered set. + if resp.TotalCount != 3 { + t.Errorf("TotalCount = %d, want 3 (pre-cap)", resp.TotalCount) + } + if resp.TotalMonthlySavingsUSD != 380 { + t.Errorf("TotalMonthlySavingsUSD = %v, want 380 (pre-cap)", resp.TotalMonthlySavingsUSD) + } + if resp.Recommendations[0].ResourceID != "i-aaa" { + t.Errorf("top item = %q, want i-aaa", resp.Recommendations[0].ResourceID) + } +} + +func TestRecommendations_SeverityFilter(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{resources: recommendationFixtures()}) + rec := doGet(t, srv, "/api/v1/recommendations?severity=high", true) + + resp := decodeRecs(t, rec.Body.Bytes()) + if resp.TotalCount != 2 { + t.Errorf("TotalCount = %d, want 2 (only High)", resp.TotalCount) + } + for _, r := range resp.Recommendations { + if r.Severity != "High" { + t.Errorf("got severity %q, want only High", r.Severity) + } + } + if resp.Filters.Severity != "high" { + t.Errorf("Filters.Severity = %q, want high", resp.Filters.Severity) + } +} + +func TestRecommendations_ProviderFilterEmptyForGCP(t *testing.T) { + // All analyzer rules target AWS services, so provider=gcp yields none. + srv := newCostTestServer(&fakeAPIData{resources: recommendationFixtures()}) + rec := doGet(t, srv, "/api/v1/recommendations?provider=gcp", true) + + resp := decodeRecs(t, rec.Body.Bytes()) + if resp.TotalCount != 0 { + t.Errorf("TotalCount = %d, want 0 for gcp", resp.TotalCount) + } + if len(resp.Recommendations) != 0 { + t.Errorf("Recommendations = %v, want empty", resp.Recommendations) + } +} + +func TestRecommendations_BadFilters(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{resources: recommendationFixtures()}) + cases := []struct{ name, path string }{ + {"bad provider", "/api/v1/recommendations?provider=oracle"}, + {"bad severity", "/api/v1/recommendations?severity=critical"}, + } + for _, tc := range cases { + t.Run(tc.name, func(t *testing.T) { + rec := doGet(t, srv, tc.path, true) + if rec.Code != http.StatusBadRequest { + t.Errorf("status = %d, want 400; body: %s", rec.Code, rec.Body) + } + }) + } +} + +func TestRecommendations_AuthRequired(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{resources: recommendationFixtures()}) + rec := doGet(t, srv, "/api/v1/recommendations", false) + if rec.Code != http.StatusUnauthorized { + t.Errorf("status = %d, want 401", rec.Code) + } +} + +func TestRecommendations_DataError(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{resourcesErr: errors.New("conn refused")}) + rec := doGet(t, srv, "/api/v1/recommendations", true) + if rec.Code != http.StatusInternalServerError { + t.Errorf("status = %d, want 500", rec.Code) + } +} + +func TestRecommendations_EmptyFindings(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{resources: nil}) + rec := doGet(t, srv, "/api/v1/recommendations", true) + + if rec.Code != http.StatusOK { + t.Fatalf("status = %d, want 200", rec.Code) + } + resp := decodeRecs(t, rec.Body.Bytes()) + if resp.TotalCount != 0 || resp.ReturnedCount != 0 { + t.Errorf("counts = %d/%d, want 0/0", resp.TotalCount, resp.ReturnedCount) + } + if resp.Recommendations == nil { + t.Error("Recommendations should serialize as [] not null") + } + // Filters.Top should still report the effective default. + if resp.Filters.Top != defaultRecommendationsTop { + t.Errorf("Filters.Top = %d, want %d", resp.Filters.Top, defaultRecommendationsTop) + } +} diff --git a/internal/api/server.go b/internal/api/server.go index f4b2116..fa04ad7 100644 --- a/internal/api/server.go +++ b/internal/api/server.go @@ -60,6 +60,8 @@ func (s *Server) buildHandler() http.Handler { authed(http.HandlerFunc(s.handleCostSummary))) mux.Handle("GET /api/v1/cost-by-service", authed(http.HandlerFunc(s.handleCostByService))) + mux.Handle("GET /api/v1/recommendations", + authed(http.HandlerFunc(s.handleRecommendations))) mux.HandleFunc("GET /api/", func(w http.ResponseWriter, r *http.Request) { writeError(w, http.StatusNotFound, "endpoint not found: "+r.Method+" "+r.URL.Path) From 59c7dce3ee5efed83de51de034d6472c21eacf3b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jesus=20Nu=C3=B1ez?= Date: Sat, 30 May 2026 16:29:32 -0400 Subject: [PATCH 11/18] feat(insights-agent): cost-trends tool + /api/v1/cost-trends endpoint Milestone 8.2 (more tools): answer "is my spend growing?" with a per-day cost time series. Go: new authed GET /api/v1/cost-trends handler over ListTrends(days). Returns the per-day series plus a precomputed first/latest/change summary (absolute_usd, percent_from_first, direction up/down/flat) so the agent phrases the trend without crunching the array. percent_from_first is null when the first day is zero. Optional provider filter recomputes each day's total from that day's per-service breakdown. days clamps to 1..365. Shares the snapshots_approximation data_source with the cost endpoints. Python: CloudOracleClient.cost_trends() + cloudoracle_cost_trends tool with a rich docstring steering trend/over-time questions here (vs cost_summary for a single period). Validation errors map to ToolException. Tests: 9 Go handler tests (delta/direction, provider recompute, days clamp, zero-first nil percent, flat, empty, auth, error); extended Python tool tests. Both suites green (internal/api; 71 Python tests, 93% coverage, ruff + mypy clean). Co-Authored-By: Claude Opus 4.8 (1M context) --- README.md | 14 +- insights-agent/README.md | 18 +- .../src/insights_agent/tools/cloudoracle.py | 72 ++++++- .../tests/test_cloudoracle_tools.py | 81 +++++++- internal/api/server.go | 2 + internal/api/trends_handler.go | 149 ++++++++++++++ internal/api/trends_handler_test.go | 187 ++++++++++++++++++ 7 files changed, 507 insertions(+), 16 deletions(-) create mode 100644 internal/api/trends_handler.go create mode 100644 internal/api/trends_handler_test.go diff --git a/README.md b/README.md index 5d3aba1..01c61ad 100644 --- a/README.md +++ b/README.md @@ -20,7 +20,7 @@ flowchart LR U([User]) -->|"How much did I spend on AWS?"| CLI[insights-agent CLI
Python 3.12] CLI --> G[LangGraph
create_react_agent] G -->|"bind_tools"| LLM[Gemini 2.5 Flash] - LLM -->|"tool call"| T[CloudOracle tools
cost-summary / cost-by-service / recommendations] + LLM -->|"tool call"| T[CloudOracle tools
cost-summary / cost-by-service / recommendations / cost-trends] T -->|"GET /api/v1/* + X-API-Key"| GO[CloudOracle Go
oracle serve] GO -->|"SQL"| DB[(PostgreSQL
cost_snapshots)] GO -->|"data_source: snapshots_approximation / heuristic_rules"| T @@ -29,10 +29,12 @@ flowchart LR CLI --> U ``` -The agent ships three tools: two cost endpoints (totals per provider, per-service -breakdown) plus a savings-recommendations endpoint that answers "where can I save -money?" from the rule-based analyzer. Setup, env vars, CLI usage, and the smoke -test are documented in **[insights-agent/README.md](insights-agent/README.md)**. +The agent ships four tools: two cost endpoints (totals per provider, per-service +breakdown), a savings-recommendations endpoint that answers "where can I save +money?" from the rule-based analyzer, and a cost-trends endpoint that answers "is +my spend growing?" with a per-day series and a precomputed change summary. Setup, +env vars, CLI usage, and the smoke test are documented in +**[insights-agent/README.md](insights-agent/README.md)**. ## v2 — Quick start (current focus) @@ -130,7 +132,7 @@ The synthetic provider needs no credentials. To run against AWS / GCP / Azure, s - [X] **Milestone 8.0** — Authenticated `/api/v1/cost-summary` and `/api/v1/cost-by-service` Go endpoints (X-API-Key, snapshot-derived totals with explicit `data_source` disclaimer, machine-readable error codes) - [X] **Milestone 8.1** — Python `insights-agent` sibling: LangGraph `create_react_agent` graph with two CloudOracle tools, Gemini provider, pydantic-settings config, structlog matching the Go slog format, CLI with `--verbose` / `--json` flags, 92% test coverage with mocked LLM + mocked HTTP. See **[insights-agent/](insights-agent/README.md)** -- [ ] **Milestone 8.2** — Additional tools (in progress). Done: authenticated `GET /api/v1/recommendations` endpoint (rule-based savings findings with provider/severity filters, `data_source: heuristic_rules`) + `cloudoracle_recommendations` agent tool. Next: resources / trends tools +- [ ] **Milestone 8.2** — Additional tools (in progress). Done: authenticated `GET /api/v1/recommendations` (rule-based savings findings, `data_source: heuristic_rules`) + `cloudoracle_recommendations` tool; authenticated `GET /api/v1/cost-trends` (per-day series with precomputed change/direction, optional provider filter) + `cloudoracle_cost_trends` tool. Next: resources / inventory tool - [ ] **Milestone 8.3** — pgvector + RAG over FinOps documentation - [ ] **Milestone 8.4** — Hand-rolled supervisor (multi-agent), replacing `create_react_agent` - [ ] **Milestone 8.5** — Production guardrails: cost caps, deterministic fallback, semantic answer validation, HTTP API surface diff --git a/insights-agent/README.md b/insights-agent/README.md index ce64fe1..c581510 100644 --- a/insights-agent/README.md +++ b/insights-agent/README.md @@ -6,10 +6,11 @@ LangGraph-based FinOps insights agent for CloudOracle. Ask in natural language language with the relevant caveats. Built on `create_react_agent` from `langgraph.prebuilt`: single-turn agent (no -conversational memory), Gemini as the model, three tools wired against the Go -`/api/v1` endpoints — two cost endpoints (milestone 8.1) plus a savings -recommendations endpoint (milestone 8.2). Future milestones replace the ReAct -loop with a custom supervisor (8.4) and add RAG over FinOps docs (8.3). +conversational memory), Gemini as the model, four tools wired against the Go +`/api/v1` endpoints — two cost endpoints (milestone 8.1) plus savings +recommendations and a cost-trends endpoint (milestone 8.2). Future milestones +replace the ReAct loop with a custom supervisor (8.4) and add RAG over FinOps +docs (8.3). ## What it talks to @@ -30,9 +31,9 @@ loop with a custom supervisor (8.4) and add RAG over FinOps docs (8.3). Every tool returns a `data_source` field so the agent surfaces the right caveat: -- The two **cost** tools return `"snapshots_approximation"` — figures come - from periodic CloudOracle snapshots, **not** a real billing API (the real - billing integration lands in milestone 8.7). +- The **cost** and **trends** tools return `"snapshots_approximation"` — + figures come from periodic CloudOracle snapshots, **not** a real billing API + (the real billing integration lands in milestone 8.7). - The **recommendations** tool returns `"heuristic_rules"` — savings are estimated upper bounds from a rule-based analyzer over the current resource inventory, to be validated against real usage before acting. @@ -46,6 +47,7 @@ The agent surfaces these caveats when accuracy materially affects the answer. | `cloudoracle_cost_summary` | "how much did I spend?" (totals per provider) | `GET /api/v1/cost-summary` | | `cloudoracle_cost_by_service` | "what drove AWS spend?" (per-service breakdown) | `GET /api/v1/cost-by-service` | | `cloudoracle_recommendations` | "where can I save money?" (savings opportunities) | `GET /api/v1/recommendations` | +| `cloudoracle_cost_trends` | "is my spend growing?" (per-day series + change) | `GET /api/v1/cost-trends` | ## Setup in under 10 minutes @@ -183,7 +185,7 @@ ReAct loop deterministically — including the tool-error branch. | Concern | Where to look | Why | | ------------------- | ------------- | --- | | Vendor-agnostic LLM | `src/insights_agent/llm/base.py` + `gemini.py` | ABC + one implementation. Add `AnthropicProvider` / `OpenAIProvider` later by implementing `LLMProvider`; no graph changes required. | -| Tools | `src/insights_agent/tools/cloudoracle.py` | `CloudOracleClient` owns the HTTP + auth + request-ID conventions; `build_tools(client)` wraps the three methods as `StructuredTool`s with rich docstrings so the LLM picks the right one. Errors flow as `ToolException` so the model sees them as observations and can recover instead of aborting the run. | +| Tools | `src/insights_agent/tools/cloudoracle.py` | `CloudOracleClient` owns the HTTP + auth + request-ID conventions; `build_tools(client)` wraps the four methods as `StructuredTool`s with rich docstrings so the LLM picks the right one. Errors flow as `ToolException` so the model sees them as observations and can recover instead of aborting the run. | | Graph | `src/insights_agent/graph/basic.py` | `create_react_agent` from `langgraph.prebuilt` with a short system prompt. Milestone 8.4 replaces this with a hand-rolled supervisor. | | CLI | `src/insights_agent/main.py` | argparse, three flags, four exit codes, single async run. No conversational memory (each call is independent). | | Settings | `src/insights_agent/config.py` | `pydantic-settings.BaseSettings` — fail-fast `ValidationError` at startup if any required env var is missing. | diff --git a/insights-agent/src/insights_agent/tools/cloudoracle.py b/insights-agent/src/insights_agent/tools/cloudoracle.py index ab955b1..8aaac6a 100644 --- a/insights-agent/src/insights_agent/tools/cloudoracle.py +++ b/insights-agent/src/insights_agent/tools/cloudoracle.py @@ -193,6 +193,19 @@ async def recommendations( params["severity"] = _validate_severity(severity) return await self._get("/api/v1/recommendations", params) + async def cost_trends( + self, + days: int = 90, + provider: str | None = None, + ) -> dict[str, Any]: + if not 1 <= days <= 365: + raise ValueError(f"days={days} must be in [1, 365]") + + params: dict[str, str] = {"days": str(days)} + if provider is not None: + params["provider"] = _validate_provider(provider) + return await self._get("/api/v1/cost-trends", params) + def build_tools(client: CloudOracleClient) -> list[StructuredTool]: """Wrap the client methods as LangChain `StructuredTool`s. @@ -238,6 +251,15 @@ async def _recommendations( except (CloudOracleAPIError, CloudOracleTransportError, ValueError) as e: raise ToolException(str(e)) from e + async def _cost_trends( + days: int = 90, + provider: str | None = None, + ) -> dict[str, Any]: + try: + return await client.cost_trends(days, provider) + except (CloudOracleAPIError, CloudOracleTransportError, ValueError) as e: + raise ToolException(str(e)) from e + summary_tool = StructuredTool.from_function( coroutine=_summary, name="cloudoracle_cost_summary", @@ -256,7 +278,13 @@ async def _recommendations( description=_RECOMMENDATIONS_DESC, handle_tool_error=True, ) - return [summary_tool, by_service_tool, recommendations_tool] + cost_trends_tool = StructuredTool.from_function( + coroutine=_cost_trends, + name="cloudoracle_cost_trends", + description=_COST_TRENDS_DESC, + handle_tool_error=True, + ) + return [summary_tool, by_service_tool, recommendations_tool, cost_trends_tool] _COST_SUMMARY_DESC = """Return aggregated cloud cost totals per provider for a date range. @@ -357,6 +385,48 @@ async def _recommendations( the top N by savings.""" +_COST_TRENDS_DESC = """Return a per-day cost time series to answer "is my spend growing?". + +Use this for trend / over-time / trajectory questions ("is my AWS bill going up?", +"how has spend changed over the last quarter?", "show the cost trend"). For a +single-period total use cloudoracle_cost_summary instead; this tool is about the +*direction* of change. + +Args: + days: Trailing window length in days. Default 90, range 1..365. + provider: Optional filter, one of "aws", "gcp", "azure". When set, each + day's total is recomputed for that cloud only. Omit for all clouds. + +Returns: + A dict with this shape: + { + "days": 90, + "provider": "aws", # present only when filtered + "points": [ + {"date": "2026-03-01", "total_cost_usd": 200.0}, + {"date": "2026-03-30", "total_cost_usd": 300.0} + ], + "first": {"date": "2026-03-01", "total_cost_usd": 200.0}, + "latest": {"date": "2026-03-30", "total_cost_usd": 300.0}, + "change": { + "absolute_usd": 100.0, + "percent_from_first": 50.0, # null when the first day was 0 + "direction": "up" # "up" | "down" | "flat" + }, + "generated_at": "...", + "data_source": "snapshots_approximation", + "note": "" + } + +Prefer the precomputed `change` / `first` / `latest` for the headline ("spend is +up 50% over the period") rather than re-deriving it from `points`. `first`, +`latest`, and `change` are null when there's no data in the window. + +IMPORTANT: Same snapshot-approximation caveat as the cost endpoints — +`data_source == "snapshots_approximation"` means per-day totals are projected +monthly rates from snapshots, not billed spend. Surface it when accuracy matters.""" + + def _validate_date(value: str, field: str) -> date: try: return datetime.strptime(value, _DATE_FMT).date() diff --git a/insights-agent/tests/test_cloudoracle_tools.py b/insights-agent/tests/test_cloudoracle_tools.py index c912f37..141a7c5 100644 --- a/insights-agent/tests/test_cloudoracle_tools.py +++ b/insights-agent/tests/test_cloudoracle_tools.py @@ -74,6 +74,20 @@ def client() -> CloudOracleClient: "note": "heuristic note", } +TRENDS_OK: dict[str, Any] = { + "days": 90, + "points": [ + {"date": "2026-03-01", "total_cost_usd": 200.0}, + {"date": "2026-03-30", "total_cost_usd": 300.0}, + ], + "first": {"date": "2026-03-01", "total_cost_usd": 200.0}, + "latest": {"date": "2026-03-30", "total_cost_usd": 300.0}, + "change": {"absolute_usd": 100.0, "percent_from_first": 50.0, "direction": "up"}, + "generated_at": "2026-05-18T12:00:00Z", + "data_source": "snapshots_approximation", + "note": "approximation note", +} + class TestClientConstruction: def test_rejects_empty_base_url(self) -> None: @@ -173,6 +187,32 @@ async def test_params_include_filters( await client.aclose() +class TestCostTrendsHappyPath: + async def test_success_defaults( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response(json=TRENDS_OK) + out = await client.cost_trends() + assert out == TRENDS_OK + req = httpx_mock.get_request() + assert req is not None + assert req.url.path == "/api/v1/cost-trends" + assert b"days=90" in req.url.query + assert b"provider=" not in req.url.query + await client.aclose() + + async def test_params_include_days_and_provider( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response(json=TRENDS_OK) + await client.cost_trends(days=30, provider="AWS") + req = httpx_mock.get_request() + assert req is not None + assert b"days=30" in req.url.query + assert b"provider=aws" in req.url.query + await client.aclose() + + class TestErrorHandling: async def test_401_raises_with_code( self, client: CloudOracleClient, httpx_mock: HTTPXMock @@ -323,9 +363,25 @@ async def test_recommendations_top_out_of_range( await client.recommendations(top=201) await client.aclose() + async def test_cost_trends_days_out_of_range( + self, client: CloudOracleClient + ) -> None: + with pytest.raises(ValueError, match=r"days=\d+ must be in"): + await client.cost_trends(days=0) + with pytest.raises(ValueError, match=r"days=\d+ must be in"): + await client.cost_trends(days=366) + await client.aclose() + + async def test_cost_trends_invalid_provider( + self, client: CloudOracleClient + ) -> None: + with pytest.raises(ValueError, match="must be one of"): + await client.cost_trends(provider="oracle-cloud") + await client.aclose() + class TestBuildTools: - async def test_builds_three_tools_with_expected_names( + async def test_builds_four_tools_with_expected_names( self, client: CloudOracleClient ) -> None: tools = build_tools(client) @@ -334,6 +390,7 @@ async def test_builds_three_tools_with_expected_names( "cloudoracle_cost_summary", "cloudoracle_cost_by_service", "cloudoracle_recommendations", + "cloudoracle_cost_trends", } await client.aclose() @@ -348,6 +405,7 @@ async def test_descriptions_mention_data_source( tools_by_name = {t.name: t for t in build_tools(client)} assert "snapshots_approximation" in tools_by_name["cloudoracle_cost_summary"].description assert "snapshots_approximation" in tools_by_name["cloudoracle_cost_by_service"].description + assert "snapshots_approximation" in tools_by_name["cloudoracle_cost_trends"].description assert "heuristic_rules" in tools_by_name["cloudoracle_recommendations"].description await client.aclose() @@ -406,3 +464,24 @@ async def test_recommendations_tool_wraps_validation_error( # handle_tool_error=True returns the error string as the observation. assert "must be one of" in str(out) await client.aclose() + + async def test_cost_trends_tool_invokes_client( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response(json=TRENDS_OK) + trends_tool = next( + t for t in build_tools(client) if t.name == "cloudoracle_cost_trends" + ) + out = await trends_tool.ainvoke({"days": 30, "provider": "aws"}) + assert out == TRENDS_OK + await client.aclose() + + async def test_cost_trends_tool_wraps_validation_error( + self, client: CloudOracleClient + ) -> None: + trends_tool = next( + t for t in build_tools(client) if t.name == "cloudoracle_cost_trends" + ) + out = await trends_tool.ainvoke({"days": 9999}) + assert "must be in" in str(out) + await client.aclose() diff --git a/internal/api/server.go b/internal/api/server.go index fa04ad7..16fa981 100644 --- a/internal/api/server.go +++ b/internal/api/server.go @@ -62,6 +62,8 @@ func (s *Server) buildHandler() http.Handler { authed(http.HandlerFunc(s.handleCostByService))) mux.Handle("GET /api/v1/recommendations", authed(http.HandlerFunc(s.handleRecommendations))) + mux.Handle("GET /api/v1/cost-trends", + authed(http.HandlerFunc(s.handleCostTrends))) mux.HandleFunc("GET /api/", func(w http.ResponseWriter, r *http.Request) { writeError(w, http.StatusNotFound, "endpoint not found: "+r.Method+" "+r.URL.Path) diff --git a/internal/api/trends_handler.go b/internal/api/trends_handler.go new file mode 100644 index 0000000..83534f8 --- /dev/null +++ b/internal/api/trends_handler.go @@ -0,0 +1,149 @@ +package api + +import ( + "net/http" + "strings" + "time" +) + +// Cost trends are derived from the same cost_snapshots the cost-summary +// endpoint uses, so they share the snapshots_approximation contract: the +// per-day totals reflect the latest snapshot's projected monthly rate on +// each day, not historical billed spend. + +const ( + defaultTrendDays = 90 + maxTrendDays = 365 +) + +type trendPointDTO struct { + Date string `json:"date"` + TotalCostUSD float64 `json:"total_cost_usd"` +} + +type trendChangeDTO struct { + // AbsoluteUSD is latest - first. PercentFromFirst is that delta over the + // first point's total, or null when the first point is zero (growth from + // nothing has no meaningful percentage). Direction collapses the change + // into up/down/flat so the agent can phrase it without re-deriving sign. + AbsoluteUSD float64 `json:"absolute_usd"` + PercentFromFirst *float64 `json:"percent_from_first"` + Direction string `json:"direction"` +} + +type costTrendsResponse struct { + Days int `json:"days"` + Provider string `json:"provider,omitempty"` + Points []trendPointDTO `json:"points"` + First *trendPointDTO `json:"first"` + Latest *trendPointDTO `json:"latest"` + Change *trendChangeDTO `json:"change"` + GeneratedAt time.Time `json:"generated_at"` + DataSource string `json:"data_source"` + Note string `json:"note"` +} + +// handleCostTrends returns a per-day cost time series for the trailing +// `days` window, plus a precomputed first/latest/change summary so the agent +// can answer "is my spend growing?" without crunching the array itself. +// +// days=N trailing window, default 90, clamped to 1..365 +// provider=aws|gcp|azure restrict the per-day total to one cloud +// +// When provider is set, each day's total is recomputed from that day's +// per-service breakdown (only services mapping to the provider). Resource +// counts aren't exposed here because the underlying trend aggregates them per +// service without a per-provider split — cost is the signal that matters for +// a trend question. +func (s *Server) handleCostTrends(w http.ResponseWriter, r *http.Request) { + q := r.URL.Query() + + days := parseIntOr(q.Get("days"), defaultTrendDays) + days = clampInt(days, 1, maxTrendDays) + + providerFilter, ok := parseOptionalProvider(q.Get("provider")) + if !ok { + writeAPIError(w, http.StatusBadRequest, + "provider must be one of aws, gcp, azure", "invalid_provider") + return + } + + trends, err := s.data.ListTrends(r.Context(), days) + if err != nil { + writeAPIError(w, http.StatusInternalServerError, + "failed to load trends: "+err.Error(), "trend_query_failed") + return + } + + points := make([]trendPointDTO, 0, len(trends)) + for _, t := range trends { + total := t.TotalCost + if providerFilter != "" { + total = 0 + for service, cost := range t.BreakdownByService { + if providerForServiceAccount(service, "") == providerFilter { + total += cost + } + } + } + points = append(points, trendPointDTO{ + Date: t.Date, + TotalCostUSD: roundCents(total), + }) + } + + resp := costTrendsResponse{ + Days: days, + Provider: providerFilter, + Points: points, + GeneratedAt: time.Now().UTC(), + DataSource: dataSourceLabel, + Note: dataSourceNote, + } + + if len(points) > 0 { + first := points[0] + latest := points[len(points)-1] + resp.First = &first + resp.Latest = &latest + resp.Change = buildTrendChange(first.TotalCostUSD, latest.TotalCostUSD) + } + + writeJSON(w, http.StatusOK, resp) +} + +// buildTrendChange computes the first→latest delta. percent_from_first is nil +// when first is zero so callers don't divide by zero or report an infinite +// percentage. The flat band (|delta| < 1 cent) absorbs floating-point noise. +func buildTrendChange(first, latest float64) *trendChangeDTO { + delta := roundCents(latest - first) + change := &trendChangeDTO{AbsoluteUSD: delta} + + switch { + case delta > 0: + change.Direction = "up" + case delta < 0: + change.Direction = "down" + default: + change.Direction = "flat" + } + + if first != 0 { + pct := roundCents(delta / first * 100) + change.PercentFromFirst = &pct + } + return change +} + +// parseOptionalProvider parses an optional provider query param. Empty means +// "no filter" (ok=true, empty string). An unrecognized value is rejected. +func parseOptionalProvider(raw string) (string, bool) { + p := strings.ToLower(strings.TrimSpace(raw)) + if p == "" { + return "", true + } + if !validProvider(p) { + return "", false + } + return p, true +} diff --git a/internal/api/trends_handler_test.go b/internal/api/trends_handler_test.go new file mode 100644 index 0000000..4784a97 --- /dev/null +++ b/internal/api/trends_handler_test.go @@ -0,0 +1,187 @@ +package api + +import ( + "CloudOracle/internal/db" + "encoding/json" + "errors" + "net/http" + "testing" +) + +// trendFixtures: three ascending days. AWS via ec2+rds, GCP via compute, so a +// provider filter recomputes the per-day total from the service breakdown. +// +// day1: aws 150 (ec2 100 + rds 50), gcp 50 → total 200 +// day2: aws 180 (ec2 120 + rds 60), gcp 60 → total 240 +// day3: aws 220 (ec2 150 + rds 70), gcp 80 → total 300 +func trendFixtures() []db.Trend { + return []db.Trend{ + {Date: "2026-03-01", TotalCost: 200, ResourceCount: 9, BreakdownByService: map[string]float64{"ec2": 100, "rds": 50, "compute": 50}}, + {Date: "2026-03-15", TotalCost: 240, ResourceCount: 9, BreakdownByService: map[string]float64{"ec2": 120, "rds": 60, "compute": 60}}, + {Date: "2026-03-30", TotalCost: 300, ResourceCount: 9, BreakdownByService: map[string]float64{"ec2": 150, "rds": 70, "compute": 80}}, + } +} + +func decodeTrends(t *testing.T, body []byte) costTrendsResponse { + t.Helper() + var resp costTrendsResponse + if err := json.Unmarshal(body, &resp); err != nil { + t.Fatalf("decode response: %v\nbody: %s", err, body) + } + return resp +} + +func TestCostTrends_HappyPath(t *testing.T) { + fake := &fakeAPIData{trends: trendFixtures()} + srv := newCostTestServer(fake) + rec := doGet(t, srv, "/api/v1/cost-trends", true) + + if rec.Code != http.StatusOK { + t.Fatalf("status = %d, want 200; body: %s", rec.Code, rec.Body) + } + resp := decodeTrends(t, rec.Body.Bytes()) + + if fake.gotDays != defaultTrendDays { + t.Errorf("ListTrends days = %d, want default %d", fake.gotDays, defaultTrendDays) + } + if len(resp.Points) != 3 { + t.Fatalf("Points len = %d, want 3", len(resp.Points)) + } + if resp.First == nil || resp.First.TotalCostUSD != 200 { + t.Errorf("First = %+v, want total 200", resp.First) + } + if resp.Latest == nil || resp.Latest.TotalCostUSD != 300 { + t.Errorf("Latest = %+v, want total 300", resp.Latest) + } + if resp.Change == nil { + t.Fatal("Change is nil") + } + if resp.Change.AbsoluteUSD != 100 { + t.Errorf("Change.AbsoluteUSD = %v, want 100", resp.Change.AbsoluteUSD) + } + if resp.Change.PercentFromFirst == nil || *resp.Change.PercentFromFirst != 50 { + t.Errorf("Change.PercentFromFirst = %v, want 50", resp.Change.PercentFromFirst) + } + if resp.Change.Direction != "up" { + t.Errorf("Change.Direction = %q, want up", resp.Change.Direction) + } + if resp.DataSource != dataSourceLabel { + t.Errorf("DataSource = %q, want %q", resp.DataSource, dataSourceLabel) + } +} + +func TestCostTrends_ProviderFilter(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{trends: trendFixtures()}) + rec := doGet(t, srv, "/api/v1/cost-trends?provider=aws", true) + + resp := decodeTrends(t, rec.Body.Bytes()) + if resp.Provider != "aws" { + t.Errorf("Provider = %q, want aws", resp.Provider) + } + // AWS-only per-day totals: 150, 180, 220. + wantTotals := []float64{150, 180, 220} + for i, want := range wantTotals { + if resp.Points[i].TotalCostUSD != want { + t.Errorf("Points[%d].TotalCostUSD = %v, want %v", i, resp.Points[i].TotalCostUSD, want) + } + } + if resp.Change.AbsoluteUSD != 70 { + t.Errorf("Change.AbsoluteUSD = %v, want 70", resp.Change.AbsoluteUSD) + } + // 70 / 150 * 100 = 46.666... → 46.67 + if resp.Change.PercentFromFirst == nil || *resp.Change.PercentFromFirst != 46.67 { + t.Errorf("Change.PercentFromFirst = %v, want 46.67", resp.Change.PercentFromFirst) + } +} + +func TestCostTrends_DaysClampUpper(t *testing.T) { + fake := &fakeAPIData{trends: trendFixtures()} + srv := newCostTestServer(fake) + doGet(t, srv, "/api/v1/cost-trends?days=9999", true) + if fake.gotDays != maxTrendDays { + t.Errorf("ListTrends days = %d, want clamped to %d", fake.gotDays, maxTrendDays) + } +} + +func TestCostTrends_BadProvider(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{trends: trendFixtures()}) + rec := doGet(t, srv, "/api/v1/cost-trends?provider=oracle", true) + if rec.Code != http.StatusBadRequest { + t.Errorf("status = %d, want 400; body: %s", rec.Code, rec.Body) + } +} + +func TestCostTrends_AuthRequired(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{trends: trendFixtures()}) + rec := doGet(t, srv, "/api/v1/cost-trends", false) + if rec.Code != http.StatusUnauthorized { + t.Errorf("status = %d, want 401", rec.Code) + } +} + +func TestCostTrends_DataError(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{trendsErr: errors.New("boom")}) + rec := doGet(t, srv, "/api/v1/cost-trends", true) + if rec.Code != http.StatusInternalServerError { + t.Errorf("status = %d, want 500", rec.Code) + } +} + +func TestCostTrends_EmptySeries(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{trends: nil}) + rec := doGet(t, srv, "/api/v1/cost-trends", true) + + if rec.Code != http.StatusOK { + t.Fatalf("status = %d, want 200", rec.Code) + } + resp := decodeTrends(t, rec.Body.Bytes()) + if resp.Points == nil { + t.Error("Points should serialize as [] not null") + } + if resp.First != nil || resp.Latest != nil || resp.Change != nil { + t.Errorf("first/latest/change should be null for empty series; got %+v/%+v/%+v", + resp.First, resp.Latest, resp.Change) + } +} + +func TestCostTrends_GrowthFromZeroHasNilPercent(t *testing.T) { + // First day zero, later non-zero: percentage from zero is undefined, so + // percent_from_first must be null but direction still "up". + trends := []db.Trend{ + {Date: "2026-03-01", TotalCost: 0, BreakdownByService: map[string]float64{}}, + {Date: "2026-03-30", TotalCost: 120, BreakdownByService: map[string]float64{"ec2": 120}}, + } + srv := newCostTestServer(&fakeAPIData{trends: trends}) + rec := doGet(t, srv, "/api/v1/cost-trends", true) + + resp := decodeTrends(t, rec.Body.Bytes()) + if resp.Change == nil { + t.Fatal("Change is nil") + } + if resp.Change.PercentFromFirst != nil { + t.Errorf("PercentFromFirst = %v, want nil (growth from zero)", *resp.Change.PercentFromFirst) + } + if resp.Change.Direction != "up" { + t.Errorf("Direction = %q, want up", resp.Change.Direction) + } + if resp.Change.AbsoluteUSD != 120 { + t.Errorf("AbsoluteUSD = %v, want 120", resp.Change.AbsoluteUSD) + } +} + +func TestCostTrends_FlatDirection(t *testing.T) { + trends := []db.Trend{ + {Date: "2026-03-01", TotalCost: 100, BreakdownByService: map[string]float64{"ec2": 100}}, + {Date: "2026-03-30", TotalCost: 100, BreakdownByService: map[string]float64{"ec2": 100}}, + } + srv := newCostTestServer(&fakeAPIData{trends: trends}) + rec := doGet(t, srv, "/api/v1/cost-trends", true) + + resp := decodeTrends(t, rec.Body.Bytes()) + if resp.Change.Direction != "flat" { + t.Errorf("Direction = %q, want flat", resp.Change.Direction) + } + if resp.Change.PercentFromFirst == nil || *resp.Change.PercentFromFirst != 0 { + t.Errorf("PercentFromFirst = %v, want 0", resp.Change.PercentFromFirst) + } +} From 01883f6a60d8ebed26418496f9f1189663252dd0 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jesus=20Nu=C3=B1ez?= Date: Sat, 30 May 2026 16:59:57 -0400 Subject: [PATCH 12/18] feat(insights-agent): inventory tool + /api/v1/inventory endpoint MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Milestone 8.2 complete (more tools): answer "what do I have?" with a resource inventory summary. Go: new authed GET /api/v1/inventory handler over ListResources, aggregating counts and projected monthly cost by provider and by (provider, service). Optional provider filter; top cap applies only to by_service so the totals stay accurate when the list is truncated. Because resources carry AccountID, the "functions" provider disambiguation (gcp vs azure) is exact here. Distinct data_source: live_inventory — costs are summed per-resource projected monthly rates from the latest scan, not billed spend. Python: CloudOracleClient.inventory() + cloudoracle_inventory tool with a docstring steering "what do I have?" / footprint questions here (vs cost_summary for spend over a range). Validation errors map to ToolException. Tests: 7 Go handler tests (aggregation, provider filter, top cap with accurate totals, functions disambiguation, auth, empty, error); extended Python tool tests. Both suites green (internal/api; 77 Python tests, 93% coverage, ruff + mypy clean). The agent now ships 5 tools across 5 authenticated v1 endpoints, closing milestone 8.2. Co-Authored-By: Claude Opus 4.8 (1M context) --- README.md | 15 +- insights-agent/README.md | 14 +- .../src/insights_agent/tools/cloudoracle.py | 77 +++++++- .../tests/test_cloudoracle_tools.py | 88 ++++++++- internal/api/inventory_handler.go | 146 +++++++++++++++ internal/api/inventory_handler_test.go | 170 ++++++++++++++++++ internal/api/server.go | 2 + 7 files changed, 496 insertions(+), 16 deletions(-) create mode 100644 internal/api/inventory_handler.go create mode 100644 internal/api/inventory_handler_test.go diff --git a/README.md b/README.md index 01c61ad..755b5e1 100644 --- a/README.md +++ b/README.md @@ -20,7 +20,7 @@ flowchart LR U([User]) -->|"How much did I spend on AWS?"| CLI[insights-agent CLI
Python 3.12] CLI --> G[LangGraph
create_react_agent] G -->|"bind_tools"| LLM[Gemini 2.5 Flash] - LLM -->|"tool call"| T[CloudOracle tools
cost-summary / cost-by-service / recommendations / cost-trends] + LLM -->|"tool call"| T[CloudOracle tools
cost-summary / cost-by-service / recommendations / cost-trends / inventory] T -->|"GET /api/v1/* + X-API-Key"| GO[CloudOracle Go
oracle serve] GO -->|"SQL"| DB[(PostgreSQL
cost_snapshots)] GO -->|"data_source: snapshots_approximation / heuristic_rules"| T @@ -29,11 +29,12 @@ flowchart LR CLI --> U ``` -The agent ships four tools: two cost endpoints (totals per provider, per-service -breakdown), a savings-recommendations endpoint that answers "where can I save -money?" from the rule-based analyzer, and a cost-trends endpoint that answers "is -my spend growing?" with a per-day series and a precomputed change summary. Setup, -env vars, CLI usage, and the smoke test are documented in +The agent ships five tools: two cost endpoints (totals per provider, per-service +breakdown), a savings-recommendations endpoint ("where can I save money?") from +the rule-based analyzer, a cost-trends endpoint ("is my spend growing?") with a +per-day series and precomputed change summary, and a resource-inventory endpoint +("what do I have?") with counts and cost by provider/service. Setup, env vars, +CLI usage, and the smoke test are documented in **[insights-agent/README.md](insights-agent/README.md)**. ## v2 — Quick start (current focus) @@ -132,7 +133,7 @@ The synthetic provider needs no credentials. To run against AWS / GCP / Azure, s - [X] **Milestone 8.0** — Authenticated `/api/v1/cost-summary` and `/api/v1/cost-by-service` Go endpoints (X-API-Key, snapshot-derived totals with explicit `data_source` disclaimer, machine-readable error codes) - [X] **Milestone 8.1** — Python `insights-agent` sibling: LangGraph `create_react_agent` graph with two CloudOracle tools, Gemini provider, pydantic-settings config, structlog matching the Go slog format, CLI with `--verbose` / `--json` flags, 92% test coverage with mocked LLM + mocked HTTP. See **[insights-agent/](insights-agent/README.md)** -- [ ] **Milestone 8.2** — Additional tools (in progress). Done: authenticated `GET /api/v1/recommendations` (rule-based savings findings, `data_source: heuristic_rules`) + `cloudoracle_recommendations` tool; authenticated `GET /api/v1/cost-trends` (per-day series with precomputed change/direction, optional provider filter) + `cloudoracle_cost_trends` tool. Next: resources / inventory tool +- [X] **Milestone 8.2** — Additional agent tools, each a new authenticated v1 endpoint: `GET /api/v1/recommendations` (rule-based savings, `data_source: heuristic_rules`), `GET /api/v1/cost-trends` (per-day series with precomputed change/direction), and `GET /api/v1/inventory` (resource counts + cost by provider/service, `data_source: live_inventory`) — wired as `cloudoracle_recommendations` / `cloudoracle_cost_trends` / `cloudoracle_inventory` tools. Agent now ships 5 tools - [ ] **Milestone 8.3** — pgvector + RAG over FinOps documentation - [ ] **Milestone 8.4** — Hand-rolled supervisor (multi-agent), replacing `create_react_agent` - [ ] **Milestone 8.5** — Production guardrails: cost caps, deterministic fallback, semantic answer validation, HTTP API surface diff --git a/insights-agent/README.md b/insights-agent/README.md index c581510..a79633a 100644 --- a/insights-agent/README.md +++ b/insights-agent/README.md @@ -6,11 +6,11 @@ LangGraph-based FinOps insights agent for CloudOracle. Ask in natural language language with the relevant caveats. Built on `create_react_agent` from `langgraph.prebuilt`: single-turn agent (no -conversational memory), Gemini as the model, four tools wired against the Go +conversational memory), Gemini as the model, five tools wired against the Go `/api/v1` endpoints — two cost endpoints (milestone 8.1) plus savings -recommendations and a cost-trends endpoint (milestone 8.2). Future milestones -replace the ReAct loop with a custom supervisor (8.4) and add RAG over FinOps -docs (8.3). +recommendations, cost trends, and a resource-inventory endpoint (milestone 8.2). +Future milestones replace the ReAct loop with a custom supervisor (8.4) and add +RAG over FinOps docs (8.3). ## What it talks to @@ -37,6 +37,9 @@ caveat: - The **recommendations** tool returns `"heuristic_rules"` — savings are estimated upper bounds from a rule-based analyzer over the current resource inventory, to be validated against real usage before acting. +- The **inventory** tool returns `"live_inventory"` — counts and cost come + from the latest resource scan; `monthly_cost_usd` is the sum of per-resource + projected monthly rates, not billed spend. The agent surfaces these caveats when accuracy materially affects the answer. @@ -48,6 +51,7 @@ The agent surfaces these caveats when accuracy materially affects the answer. | `cloudoracle_cost_by_service` | "what drove AWS spend?" (per-service breakdown) | `GET /api/v1/cost-by-service` | | `cloudoracle_recommendations` | "where can I save money?" (savings opportunities) | `GET /api/v1/recommendations` | | `cloudoracle_cost_trends` | "is my spend growing?" (per-day series + change) | `GET /api/v1/cost-trends` | +| `cloudoracle_inventory` | "what do I have?" (counts + cost by provider/service) | `GET /api/v1/inventory` | ## Setup in under 10 minutes @@ -185,7 +189,7 @@ ReAct loop deterministically — including the tool-error branch. | Concern | Where to look | Why | | ------------------- | ------------- | --- | | Vendor-agnostic LLM | `src/insights_agent/llm/base.py` + `gemini.py` | ABC + one implementation. Add `AnthropicProvider` / `OpenAIProvider` later by implementing `LLMProvider`; no graph changes required. | -| Tools | `src/insights_agent/tools/cloudoracle.py` | `CloudOracleClient` owns the HTTP + auth + request-ID conventions; `build_tools(client)` wraps the four methods as `StructuredTool`s with rich docstrings so the LLM picks the right one. Errors flow as `ToolException` so the model sees them as observations and can recover instead of aborting the run. | +| Tools | `src/insights_agent/tools/cloudoracle.py` | `CloudOracleClient` owns the HTTP + auth + request-ID conventions; `build_tools(client)` wraps the five methods as `StructuredTool`s with rich docstrings so the LLM picks the right one. Errors flow as `ToolException` so the model sees them as observations and can recover instead of aborting the run. | | Graph | `src/insights_agent/graph/basic.py` | `create_react_agent` from `langgraph.prebuilt` with a short system prompt. Milestone 8.4 replaces this with a hand-rolled supervisor. | | CLI | `src/insights_agent/main.py` | argparse, three flags, four exit codes, single async run. No conversational memory (each call is independent). | | Settings | `src/insights_agent/config.py` | `pydantic-settings.BaseSettings` — fail-fast `ValidationError` at startup if any required env var is missing. | diff --git a/insights-agent/src/insights_agent/tools/cloudoracle.py b/insights-agent/src/insights_agent/tools/cloudoracle.py index 8aaac6a..eb74b6a 100644 --- a/insights-agent/src/insights_agent/tools/cloudoracle.py +++ b/insights-agent/src/insights_agent/tools/cloudoracle.py @@ -206,6 +206,19 @@ async def cost_trends( params["provider"] = _validate_provider(provider) return await self._get("/api/v1/cost-trends", params) + async def inventory( + self, + provider: str | None = None, + top: int = 50, + ) -> dict[str, Any]: + if not 1 <= top <= 200: + raise ValueError(f"top={top} must be in [1, 200]") + + params: dict[str, str] = {"top": str(top)} + if provider is not None: + params["provider"] = _validate_provider(provider) + return await self._get("/api/v1/inventory", params) + def build_tools(client: CloudOracleClient) -> list[StructuredTool]: """Wrap the client methods as LangChain `StructuredTool`s. @@ -260,6 +273,15 @@ async def _cost_trends( except (CloudOracleAPIError, CloudOracleTransportError, ValueError) as e: raise ToolException(str(e)) from e + async def _inventory( + provider: str | None = None, + top: int = 50, + ) -> dict[str, Any]: + try: + return await client.inventory(provider, top) + except (CloudOracleAPIError, CloudOracleTransportError, ValueError) as e: + raise ToolException(str(e)) from e + summary_tool = StructuredTool.from_function( coroutine=_summary, name="cloudoracle_cost_summary", @@ -284,7 +306,19 @@ async def _cost_trends( description=_COST_TRENDS_DESC, handle_tool_error=True, ) - return [summary_tool, by_service_tool, recommendations_tool, cost_trends_tool] + inventory_tool = StructuredTool.from_function( + coroutine=_inventory, + name="cloudoracle_inventory", + description=_INVENTORY_DESC, + handle_tool_error=True, + ) + return [ + summary_tool, + by_service_tool, + recommendations_tool, + cost_trends_tool, + inventory_tool, + ] _COST_SUMMARY_DESC = """Return aggregated cloud cost totals per provider for a date range. @@ -427,6 +461,47 @@ async def _cost_trends( monthly rates from snapshots, not billed spend. Surface it when accuracy matters.""" +_INVENTORY_DESC = """Return a resource-inventory summary: what you have and how much it costs. + +Use this for "what do I have?" questions — counts of resources, which services +or providers dominate, where cost concentrates by inventory ("how many EC2 +instances?", "what's my biggest service?", "break down my footprint by cloud"). +This counts CURRENT scanned resources; for spend over a date range use +cloudoracle_cost_summary, and for savings use cloudoracle_recommendations. + +Args: + provider: Optional filter, one of "aws", "gcp", "azure". Omit for all clouds. + top: Max entries in the by_service list, sorted by cost descending. + Default 50, range 1..200. by_service is the only capped field. + +Returns: + A dict with this shape: + { + "provider": "aws", # present only when filtered + "total_resources": 7, + "total_monthly_cost_usd": 500.0, + "total_services": 6, # distinct (provider, service) pairs + "by_provider": { + "aws": {"count": 3, "monthly_cost_usd": 350.0}, + "gcp": {"count": 2, "monthly_cost_usd": 90.0} + }, + "by_service": [ + {"service": "ec2", "provider": "aws", "count": 2, + "monthly_cost_usd": 300.0} + ], + "generated_at": "...", + "data_source": "live_inventory", + "note": "" + } + +total_resources / total_monthly_cost_usd / total_services / by_provider cover the +full filtered set; only by_service is capped by `top`. If `len(by_service) < +total_services`, the list was truncated — say so. + +IMPORTANT: `data_source == "live_inventory"` — `monthly_cost_usd` sums per-resource +projected monthly cost rates from the latest scan, NOT billed spend.""" + + def _validate_date(value: str, field: str) -> date: try: return datetime.strptime(value, _DATE_FMT).date() diff --git a/insights-agent/tests/test_cloudoracle_tools.py b/insights-agent/tests/test_cloudoracle_tools.py index 141a7c5..66071f7 100644 --- a/insights-agent/tests/test_cloudoracle_tools.py +++ b/insights-agent/tests/test_cloudoracle_tools.py @@ -88,6 +88,23 @@ def client() -> CloudOracleClient: "note": "approximation note", } +INVENTORY_OK: dict[str, Any] = { + "total_resources": 7, + "total_monthly_cost_usd": 500.0, + "total_services": 6, + "by_provider": { + "aws": {"count": 3, "monthly_cost_usd": 350.0}, + "gcp": {"count": 2, "monthly_cost_usd": 90.0}, + "azure": {"count": 2, "monthly_cost_usd": 60.0}, + }, + "by_service": [ + {"service": "ec2", "provider": "aws", "count": 2, "monthly_cost_usd": 300.0}, + ], + "generated_at": "2026-05-18T12:00:00Z", + "data_source": "live_inventory", + "note": "inventory note", +} + class TestClientConstruction: def test_rejects_empty_base_url(self) -> None: @@ -213,6 +230,32 @@ async def test_params_include_days_and_provider( await client.aclose() +class TestInventoryHappyPath: + async def test_success_defaults( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response(json=INVENTORY_OK) + out = await client.inventory() + assert out == INVENTORY_OK + req = httpx_mock.get_request() + assert req is not None + assert req.url.path == "/api/v1/inventory" + assert b"top=50" in req.url.query + assert b"provider=" not in req.url.query + await client.aclose() + + async def test_params_include_provider_and_top( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response(json=INVENTORY_OK) + await client.inventory(provider="AWS", top=10) + req = httpx_mock.get_request() + assert req is not None + assert b"provider=aws" in req.url.query + assert b"top=10" in req.url.query + await client.aclose() + + class TestErrorHandling: async def test_401_raises_with_code( self, client: CloudOracleClient, httpx_mock: HTTPXMock @@ -379,9 +422,25 @@ async def test_cost_trends_invalid_provider( await client.cost_trends(provider="oracle-cloud") await client.aclose() + async def test_inventory_top_out_of_range( + self, client: CloudOracleClient + ) -> None: + with pytest.raises(ValueError, match=r"top=\d+ must be in"): + await client.inventory(top=0) + with pytest.raises(ValueError, match=r"top=\d+ must be in"): + await client.inventory(top=201) + await client.aclose() + + async def test_inventory_invalid_provider( + self, client: CloudOracleClient + ) -> None: + with pytest.raises(ValueError, match="must be one of"): + await client.inventory(provider="oracle-cloud") + await client.aclose() + class TestBuildTools: - async def test_builds_four_tools_with_expected_names( + async def test_builds_five_tools_with_expected_names( self, client: CloudOracleClient ) -> None: tools = build_tools(client) @@ -391,6 +450,7 @@ async def test_builds_four_tools_with_expected_names( "cloudoracle_cost_by_service", "cloudoracle_recommendations", "cloudoracle_cost_trends", + "cloudoracle_inventory", } await client.aclose() @@ -398,8 +458,8 @@ async def test_descriptions_mention_data_source( self, client: CloudOracleClient ) -> None: # Every tool documents its data_source so the model knows which caveat - # to surface: the cost tools use snapshots_approximation, the - # recommendations tool uses heuristic_rules. + # to surface: the cost/trends tools use snapshots_approximation, the + # recommendations tool uses heuristic_rules, inventory uses live_inventory. for t in build_tools(client): assert "data_source" in t.description tools_by_name = {t.name: t for t in build_tools(client)} @@ -407,6 +467,7 @@ async def test_descriptions_mention_data_source( assert "snapshots_approximation" in tools_by_name["cloudoracle_cost_by_service"].description assert "snapshots_approximation" in tools_by_name["cloudoracle_cost_trends"].description assert "heuristic_rules" in tools_by_name["cloudoracle_recommendations"].description + assert "live_inventory" in tools_by_name["cloudoracle_inventory"].description await client.aclose() async def test_summary_tool_invokes_client( @@ -485,3 +546,24 @@ async def test_cost_trends_tool_wraps_validation_error( out = await trends_tool.ainvoke({"days": 9999}) assert "must be in" in str(out) await client.aclose() + + async def test_inventory_tool_invokes_client( + self, client: CloudOracleClient, httpx_mock: HTTPXMock + ) -> None: + httpx_mock.add_response(json=INVENTORY_OK) + inventory_tool = next( + t for t in build_tools(client) if t.name == "cloudoracle_inventory" + ) + out = await inventory_tool.ainvoke({"provider": "aws", "top": 10}) + assert out == INVENTORY_OK + await client.aclose() + + async def test_inventory_tool_wraps_validation_error( + self, client: CloudOracleClient + ) -> None: + inventory_tool = next( + t for t in build_tools(client) if t.name == "cloudoracle_inventory" + ) + out = await inventory_tool.ainvoke({"provider": "oracle-cloud"}) + assert "must be one of" in str(out) + await client.aclose() diff --git a/internal/api/inventory_handler.go b/internal/api/inventory_handler.go new file mode 100644 index 0000000..304d5cb --- /dev/null +++ b/internal/api/inventory_handler.go @@ -0,0 +1,146 @@ +package api + +import ( + "net/http" + "sort" + "time" +) + +// The inventory endpoint reports the *current scanned resource inventory* — +// the same data the dashboard's /api/resources serves — aggregated into +// counts and projected monthly cost per provider and per service. Unlike the +// cost endpoints it doesn't go through the snapshot approximation; each +// resource's MonthlyCost is the per-resource projected monthly rate recorded +// at scan time, so the data_source is labelled distinctly. +const ( + inventoryDataSource = "live_inventory" + inventoryNote = "Inventory reflects the latest CloudOracle resource scan. " + + "monthly_cost_usd is the sum of per-resource projected monthly cost rates, " + + "not billed spend." +) + +// defaultInventoryTop caps the by_service list by default. Real inventories +// have a handful of service types, so this rarely bites — but it bounds the +// response and is overridable up to maxPageSize (200). +const defaultInventoryTop = 50 + +type inventoryAggDTO struct { + Count int `json:"count"` + MonthlyCostUSD float64 `json:"monthly_cost_usd"` +} + +type serviceInventoryDTO struct { + Service string `json:"service"` + Provider string `json:"provider"` + Count int `json:"count"` + MonthlyCostUSD float64 `json:"monthly_cost_usd"` +} + +type inventoryResponse struct { + Provider string `json:"provider,omitempty"` + TotalResources int `json:"total_resources"` + TotalMonthlyCostUSD float64 `json:"total_monthly_cost_usd"` + TotalServices int `json:"total_services"` + ByProvider map[string]inventoryAggDTO `json:"by_provider"` + ByService []serviceInventoryDTO `json:"by_service"` + GeneratedAt time.Time `json:"generated_at"` + DataSource string `json:"data_source"` + Note string `json:"note"` +} + +// handleInventory answers "what do I have?" — how many resources, of which +// services, where the cost concentrates. Optional filters: +// +// provider=aws|gcp|azure restrict to one cloud +// top=N cap the by_service list (default 50, max 200) +// +// total_resources / total_monthly_cost_usd / total_services / by_provider all +// describe the full filtered set; only by_service is subject to the top cap, +// so a truncated list still reports accurate totals. +func (s *Server) handleInventory(w http.ResponseWriter, r *http.Request) { + q := r.URL.Query() + + providerFilter, ok := parseOptionalProvider(q.Get("provider")) + if !ok { + writeAPIError(w, http.StatusBadRequest, + "provider must be one of aws, gcp, azure", "invalid_provider") + return + } + + top := parseIntOr(q.Get("top"), defaultInventoryTop) + top = clampInt(top, 1, maxPageSize) + + resources, err := s.data.ListResources(r.Context()) + if err != nil { + writeAPIError(w, http.StatusInternalServerError, + "failed to list resources: "+err.Error(), "resource_query_failed") + return + } + + byProvider := make(map[string]inventoryAggDTO) + type svcKey struct{ provider, service string } + byService := make(map[svcKey]*serviceInventoryDTO) + + var totalResources int + var totalCost float64 + for _, res := range resources { + provider := providerForServiceAccount(res.Service, res.AccountID) + if providerFilter != "" && provider != providerFilter { + continue + } + + totalResources++ + totalCost += res.MonthlyCost + + pAgg := byProvider[provider] + pAgg.Count++ + pAgg.MonthlyCostUSD += res.MonthlyCost + byProvider[provider] = pAgg + + k := svcKey{provider, res.Service} + svc := byService[k] + if svc == nil { + svc = &serviceInventoryDTO{Service: res.Service, Provider: provider} + byService[k] = svc + } + svc.Count++ + svc.MonthlyCostUSD += res.MonthlyCost + } + + // Round the accumulated provider totals once, at the end, to avoid + // compounding rounding across many resources. + for p, agg := range byProvider { + agg.MonthlyCostUSD = roundCents(agg.MonthlyCostUSD) + byProvider[p] = agg + } + + services := make([]serviceInventoryDTO, 0, len(byService)) + for _, svc := range byService { + svc.MonthlyCostUSD = roundCents(svc.MonthlyCostUSD) + services = append(services, *svc) + } + // Cost desc, tiebreak by service name for a deterministic order. + sort.Slice(services, func(i, j int) bool { + if services[i].MonthlyCostUSD != services[j].MonthlyCostUSD { + return services[i].MonthlyCostUSD > services[j].MonthlyCostUSD + } + return services[i].Service < services[j].Service + }) + + totalServices := len(services) + if len(services) > top { + services = services[:top] + } + + writeJSON(w, http.StatusOK, inventoryResponse{ + Provider: providerFilter, + TotalResources: totalResources, + TotalMonthlyCostUSD: roundCents(totalCost), + TotalServices: totalServices, + ByProvider: byProvider, + ByService: services, + GeneratedAt: time.Now().UTC(), + DataSource: inventoryDataSource, + Note: inventoryNote, + }) +} diff --git a/internal/api/inventory_handler_test.go b/internal/api/inventory_handler_test.go new file mode 100644 index 0000000..a8ec178 --- /dev/null +++ b/internal/api/inventory_handler_test.go @@ -0,0 +1,170 @@ +package api + +import ( + "CloudOracle/internal/shared" + "encoding/json" + "errors" + "net/http" + "testing" +) + +// azureFunctionsAccount is a 36-char UUID with dashes at indices 8 and 13 — +// the shape providerForServiceAccount uses to disambiguate "functions" as +// Azure rather than the GCP default. +const azureFunctionsAccount = "12345678-1234-1234-1234-123456789012" + +// inventoryFixtures spans all three providers, repeats a service (ec2) to +// exercise counting, and includes both flavours of the ambiguous "functions" +// service so the AccountID-based provider split is covered. +// +// aws: ec2 x2 (300), rds (50) → count 3, cost 350 +// gcp: compute (80), functions-gcp (10) → count 2, cost 90 +// azure: vm (40), functions-azure (20) → count 2, cost 60 +func inventoryFixtures() []shared.Resource { + return []shared.Resource{ + {ID: "i-1", AccountID: "acc-aws", Service: "ec2", MonthlyCost: 100}, + {ID: "i-2", AccountID: "acc-aws", Service: "ec2", MonthlyCost: 200}, + {ID: "db-1", AccountID: "acc-aws", Service: "rds", MonthlyCost: 50}, + {ID: "gce-1", AccountID: "proj-gcp", Service: "compute", MonthlyCost: 80}, + {ID: "vm-1", AccountID: "sub-azure", Service: "vm", MonthlyCost: 40}, + {ID: "fn-gcp", AccountID: "proj-gcp", Service: "functions", MonthlyCost: 10}, + {ID: "fn-az", AccountID: azureFunctionsAccount, Service: "functions", MonthlyCost: 20}, + } +} + +func decodeInventory(t *testing.T, body []byte) inventoryResponse { + t.Helper() + var resp inventoryResponse + if err := json.Unmarshal(body, &resp); err != nil { + t.Fatalf("decode response: %v\nbody: %s", err, body) + } + return resp +} + +func TestInventory_HappyPath(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{resources: inventoryFixtures()}) + rec := doGet(t, srv, "/api/v1/inventory", true) + + if rec.Code != http.StatusOK { + t.Fatalf("status = %d, want 200; body: %s", rec.Code, rec.Body) + } + resp := decodeInventory(t, rec.Body.Bytes()) + + if resp.TotalResources != 7 { + t.Errorf("TotalResources = %d, want 7", resp.TotalResources) + } + if resp.TotalMonthlyCostUSD != 500 { + t.Errorf("TotalMonthlyCostUSD = %v, want 500", resp.TotalMonthlyCostUSD) + } + if resp.TotalServices != 6 { + t.Errorf("TotalServices = %d, want 6", resp.TotalServices) + } + if resp.DataSource != inventoryDataSource { + t.Errorf("DataSource = %q, want %q", resp.DataSource, inventoryDataSource) + } + + wantProviders := map[string]inventoryAggDTO{ + "aws": {Count: 3, MonthlyCostUSD: 350}, + "gcp": {Count: 2, MonthlyCostUSD: 90}, + "azure": {Count: 2, MonthlyCostUSD: 60}, + } + for p, want := range wantProviders { + got := resp.ByProvider[p] + if got != want { + t.Errorf("ByProvider[%q] = %+v, want %+v", p, got, want) + } + } + + // Top by cost is ec2 (aws, 2 resources, 300). + top := resp.ByService[0] + if top.Service != "ec2" || top.Provider != "aws" || top.Count != 2 || top.MonthlyCostUSD != 300 { + t.Errorf("ByService[0] = %+v, want ec2/aws/2/300", top) + } +} + +func TestInventory_ProviderFilter(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{resources: inventoryFixtures()}) + rec := doGet(t, srv, "/api/v1/inventory?provider=aws", true) + + resp := decodeInventory(t, rec.Body.Bytes()) + if resp.Provider != "aws" { + t.Errorf("Provider = %q, want aws", resp.Provider) + } + if resp.TotalResources != 3 { + t.Errorf("TotalResources = %d, want 3", resp.TotalResources) + } + if resp.TotalMonthlyCostUSD != 350 { + t.Errorf("TotalMonthlyCostUSD = %v, want 350", resp.TotalMonthlyCostUSD) + } + if resp.TotalServices != 2 { + t.Errorf("TotalServices = %d, want 2 (ec2, rds)", resp.TotalServices) + } + if len(resp.ByProvider) != 1 { + t.Errorf("ByProvider has %d entries, want 1 (aws only)", len(resp.ByProvider)) + } + for _, svc := range resp.ByService { + if svc.Provider != "aws" { + t.Errorf("ByService entry %+v not aws", svc) + } + } +} + +func TestInventory_TopCap(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{resources: inventoryFixtures()}) + rec := doGet(t, srv, "/api/v1/inventory?top=2", true) + + resp := decodeInventory(t, rec.Body.Bytes()) + if len(resp.ByService) != 2 { + t.Errorf("ByService len = %d, want 2", len(resp.ByService)) + } + // total_services still reports the full distinct count. + if resp.TotalServices != 6 { + t.Errorf("TotalServices = %d, want 6 (pre-cap)", resp.TotalServices) + } + if resp.TotalResources != 7 { + t.Errorf("TotalResources = %d, want 7 (pre-cap)", resp.TotalResources) + } +} + +func TestInventory_BadProvider(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{resources: inventoryFixtures()}) + rec := doGet(t, srv, "/api/v1/inventory?provider=oracle", true) + if rec.Code != http.StatusBadRequest { + t.Errorf("status = %d, want 400; body: %s", rec.Code, rec.Body) + } +} + +func TestInventory_AuthRequired(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{resources: inventoryFixtures()}) + rec := doGet(t, srv, "/api/v1/inventory", false) + if rec.Code != http.StatusUnauthorized { + t.Errorf("status = %d, want 401", rec.Code) + } +} + +func TestInventory_DataError(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{resourcesErr: errors.New("boom")}) + rec := doGet(t, srv, "/api/v1/inventory", true) + if rec.Code != http.StatusInternalServerError { + t.Errorf("status = %d, want 500", rec.Code) + } +} + +func TestInventory_Empty(t *testing.T) { + srv := newCostTestServer(&fakeAPIData{resources: nil}) + rec := doGet(t, srv, "/api/v1/inventory", true) + + if rec.Code != http.StatusOK { + t.Fatalf("status = %d, want 200", rec.Code) + } + resp := decodeInventory(t, rec.Body.Bytes()) + if resp.TotalResources != 0 || resp.TotalServices != 0 { + t.Errorf("totals = %d/%d, want 0/0", resp.TotalResources, resp.TotalServices) + } + if resp.ByService == nil { + t.Error("ByService should serialize as [] not null") + } + if resp.ByProvider == nil { + t.Error("ByProvider should serialize as {} not null") + } +} diff --git a/internal/api/server.go b/internal/api/server.go index 16fa981..f490403 100644 --- a/internal/api/server.go +++ b/internal/api/server.go @@ -64,6 +64,8 @@ func (s *Server) buildHandler() http.Handler { authed(http.HandlerFunc(s.handleRecommendations))) mux.Handle("GET /api/v1/cost-trends", authed(http.HandlerFunc(s.handleCostTrends))) + mux.Handle("GET /api/v1/inventory", + authed(http.HandlerFunc(s.handleInventory))) mux.HandleFunc("GET /api/", func(w http.ResponseWriter, r *http.Request) { writeError(w, http.StatusNotFound, "endpoint not found: "+r.Method+" "+r.URL.Path) From 156af0bb6f9d056d5954c9578b6d6ae1bc74b486 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jesus=20Nu=C3=B1ez?= Date: Sat, 30 May 2026 18:56:25 -0400 Subject: [PATCH 13/18] feat(insights-agent): RAG over a FinOps corpus with pgvector (milestone 8.3) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Add a sixth agent tool, finops_knowledge_search, that retrieves from a curated FinOps knowledge base for conceptual / policy / how-to questions the HTTP tools can't answer (rightsizing, commitment discounts, data-source caveats, cost allocation, glossary). Architecture (RAG kept in Python, where LangChain lives; the Go server stays a clean data API): - knowledge/: 5 packaged markdown notes, shipped in the wheel. - rag/corpus.py: load + chunk markdown to Documents (offline-testable). - rag/embeddings.py: EmbeddingsProvider ABC + Gemini impl, mirroring the llm/ provider pattern. - rag/store.py: langchain-postgres PGVector factory + store-agnostic retriever. - rag/ingest.py: ingest_corpus() core + insights-agent-ingest console script. - tools/knowledge.py: build_knowledge_tool(retriever) -> finops_knowledge_search, formatting results with [source: file — title] citations; errors map to ToolException so the ReAct loop can recover. Wiring is optional and gated on DATABASE_URL: with it unset the agent runs with just the five HTTP tools and no Postgres dependency. config.py gains database_url / embeddings_model / knowledge_collection / rag_top_k; main.py adds the knowledge tool only when a pgvector DB is configured; the system prompt steers conceptual questions to it. docker-compose switches Postgres to pgvector/pgvector:pg16 (drop-in). Tested fully offline (no DB, no embeddings API): corpus chunking, and the real retrieval + citation path via InMemoryVectorStore + DeterministicFakeEmbedding. 100 Python tests, 92% coverage, ruff + mypy clean. Co-Authored-By: Claude Opus 4.8 (1M context) --- README.md | 23 ++- docker-compose.yml | 4 +- insights-agent/.env.example | 17 ++ insights-agent/README.md | 83 ++++++-- insights-agent/pyproject.toml | 13 +- insights-agent/src/insights_agent/config.py | 10 + .../src/insights_agent/graph/basic.py | 6 + .../knowledge/commitment-discounts.md | 39 ++++ .../knowledge/cost-allocation-and-tagging.md | 44 +++++ .../knowledge/data-sources-and-caveats.md | 44 +++++ .../knowledge/finops-glossary.md | 45 +++++ .../insights_agent/knowledge/rightsizing.md | 41 ++++ insights-agent/src/insights_agent/main.py | 41 +++- .../src/insights_agent/rag/__init__.py | 17 ++ .../src/insights_agent/rag/corpus.py | 99 ++++++++++ .../src/insights_agent/rag/embeddings.py | 62 ++++++ .../src/insights_agent/rag/ingest.py | 111 +++++++++++ .../src/insights_agent/rag/store.py | 38 ++++ .../src/insights_agent/tools/knowledge.py | 72 +++++++ insights-agent/tests/conftest.py | 4 + insights-agent/tests/test_config.py | 31 +++ insights-agent/tests/test_corpus.py | 72 +++++++ insights-agent/tests/test_embeddings.py | 34 ++++ insights-agent/tests/test_knowledge_tool.py | 89 +++++++++ insights-agent/tests/test_main.py | 20 ++ insights-agent/uv.lock | 181 ++++++++++++++++++ 26 files changed, 1216 insertions(+), 24 deletions(-) create mode 100644 insights-agent/src/insights_agent/knowledge/commitment-discounts.md create mode 100644 insights-agent/src/insights_agent/knowledge/cost-allocation-and-tagging.md create mode 100644 insights-agent/src/insights_agent/knowledge/data-sources-and-caveats.md create mode 100644 insights-agent/src/insights_agent/knowledge/finops-glossary.md create mode 100644 insights-agent/src/insights_agent/knowledge/rightsizing.md create mode 100644 insights-agent/src/insights_agent/rag/__init__.py create mode 100644 insights-agent/src/insights_agent/rag/corpus.py create mode 100644 insights-agent/src/insights_agent/rag/embeddings.py create mode 100644 insights-agent/src/insights_agent/rag/ingest.py create mode 100644 insights-agent/src/insights_agent/rag/store.py create mode 100644 insights-agent/src/insights_agent/tools/knowledge.py create mode 100644 insights-agent/tests/test_corpus.py create mode 100644 insights-agent/tests/test_embeddings.py create mode 100644 insights-agent/tests/test_knowledge_tool.py diff --git a/README.md b/README.md index 755b5e1..32800ab 100644 --- a/README.md +++ b/README.md @@ -20,22 +20,27 @@ flowchart LR U([User]) -->|"How much did I spend on AWS?"| CLI[insights-agent CLI
Python 3.12] CLI --> G[LangGraph
create_react_agent] G -->|"bind_tools"| LLM[Gemini 2.5 Flash] - LLM -->|"tool call"| T[CloudOracle tools
cost-summary / cost-by-service / recommendations / cost-trends / inventory] + LLM -->|"HTTP tool call"| T[CloudOracle tools
cost-summary / cost-by-service / recommendations / cost-trends / inventory] T -->|"GET /api/v1/* + X-API-Key"| GO[CloudOracle Go
oracle serve] GO -->|"SQL"| DB[(PostgreSQL
cost_snapshots)] GO -->|"data_source: snapshots_approximation / heuristic_rules"| T + LLM -->|"knowledge tool call"| R[finops_knowledge_search
RAG] + R -->|"similarity search"| VDB[(pgvector
finops_knowledge)] T --> LLM + R --> LLM LLM -->|"natural-language answer"| CLI CLI --> U ``` -The agent ships five tools: two cost endpoints (totals per provider, per-service -breakdown), a savings-recommendations endpoint ("where can I save money?") from -the rule-based analyzer, a cost-trends endpoint ("is my spend growing?") with a -per-day series and precomputed change summary, and a resource-inventory endpoint -("what do I have?") with counts and cost by provider/service. Setup, env vars, -CLI usage, and the smoke test are documented in -**[insights-agent/README.md](insights-agent/README.md)**. +The agent ships five HTTP tools — two cost endpoints (totals per provider, +per-service breakdown), a savings-recommendations endpoint ("where can I save +money?") from the rule-based analyzer, a cost-trends endpoint ("is my spend +growing?") with a per-day series and precomputed change summary, and a +resource-inventory endpoint ("what do I have?") — plus a sixth RAG tool, +`finops_knowledge_search`, that answers conceptual / policy questions from a +curated FinOps corpus embedded in pgvector. RAG is optional (enabled by +`DATABASE_URL`). Setup, env vars, the RAG ingestion step, and the smoke test are +documented in **[insights-agent/README.md](insights-agent/README.md)**. ## v2 — Quick start (current focus) @@ -134,7 +139,7 @@ The synthetic provider needs no credentials. To run against AWS / GCP / Azure, s - [X] **Milestone 8.0** — Authenticated `/api/v1/cost-summary` and `/api/v1/cost-by-service` Go endpoints (X-API-Key, snapshot-derived totals with explicit `data_source` disclaimer, machine-readable error codes) - [X] **Milestone 8.1** — Python `insights-agent` sibling: LangGraph `create_react_agent` graph with two CloudOracle tools, Gemini provider, pydantic-settings config, structlog matching the Go slog format, CLI with `--verbose` / `--json` flags, 92% test coverage with mocked LLM + mocked HTTP. See **[insights-agent/](insights-agent/README.md)** - [X] **Milestone 8.2** — Additional agent tools, each a new authenticated v1 endpoint: `GET /api/v1/recommendations` (rule-based savings, `data_source: heuristic_rules`), `GET /api/v1/cost-trends` (per-day series with precomputed change/direction), and `GET /api/v1/inventory` (resource counts + cost by provider/service, `data_source: live_inventory`) — wired as `cloudoracle_recommendations` / `cloudoracle_cost_trends` / `cloudoracle_inventory` tools. Agent now ships 5 tools -- [ ] **Milestone 8.3** — pgvector + RAG over FinOps documentation +- [X] **Milestone 8.3** — pgvector + RAG over a curated FinOps corpus: packaged markdown knowledge base, Gemini embeddings (mirroring the LLM-provider ABC), `langchain-postgres` PGVector store (compose image → `pgvector/pgvector:pg16`), `insights-agent-ingest` CLI, and a `finops_knowledge_search` tool the agent uses for conceptual/policy questions with source citations. Optional via `DATABASE_URL`; retrieval path unit-tested offline with an in-memory store - [ ] **Milestone 8.4** — Hand-rolled supervisor (multi-agent), replacing `create_react_agent` - [ ] **Milestone 8.5** — Production guardrails: cost caps, deterministic fallback, semantic answer validation, HTTP API surface - [ ] **Milestone 8.7** — Real billing / Cost Explorer integration replacing the snapshot approximation diff --git a/docker-compose.yml b/docker-compose.yml index a81012c..5f13657 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -1,6 +1,8 @@ services: postgres: - image: postgres:16-alpine + # pgvector image = stock Postgres 16 + the `vector` extension, needed by + # the insights-agent RAG store (milestone 8.3). Drop-in for postgres:16. + image: pgvector/pgvector:pg16 container_name: cloudoracle-db environment: POSTGRES_USER: oracle diff --git a/insights-agent/.env.example b/insights-agent/.env.example index 15199a1..7cb8194 100644 --- a/insights-agent/.env.example +++ b/insights-agent/.env.example @@ -16,3 +16,20 @@ GEMINI_MODEL=gemini-2.5-flash LOG_LEVEL=INFO LOG_FORMAT=text HTTP_TIMEOUT_SECONDS=10 + +# --- RAG / knowledge base (milestone 8.3) ----------------------------------- +# Optional. When DATABASE_URL is unset the agent runs WITHOUT the +# finops_knowledge_search tool (cost/inventory/recommendation tools still work +# with no Postgres dependency). Set it to enable RAG over the FinOps corpus. +# +# SQLAlchemy/psycopg URL for the pgvector-enabled Postgres. For the bundled +# docker-compose stack (pgvector/pgvector:pg16): +# DATABASE_URL=postgresql+psycopg://oracle:oracle_dev@localhost:5432/cloudoracle +DATABASE_URL= + +# Gemini embeddings model (free tier). 768-dim text embeddings. +EMBEDDINGS_MODEL=models/text-embedding-004 + +# pgvector collection name + how many chunks to retrieve per query. +KNOWLEDGE_COLLECTION=finops_knowledge +RAG_TOP_K=4 diff --git a/insights-agent/README.md b/insights-agent/README.md index a79633a..eedd4fa 100644 --- a/insights-agent/README.md +++ b/insights-agent/README.md @@ -6,11 +6,12 @@ LangGraph-based FinOps insights agent for CloudOracle. Ask in natural language language with the relevant caveats. Built on `create_react_agent` from `langgraph.prebuilt`: single-turn agent (no -conversational memory), Gemini as the model, five tools wired against the Go -`/api/v1` endpoints — two cost endpoints (milestone 8.1) plus savings -recommendations, cost trends, and a resource-inventory endpoint (milestone 8.2). -Future milestones replace the ReAct loop with a custom supervisor (8.4) and add -RAG over FinOps docs (8.3). +conversational memory), Gemini as the model. Five tools call the Go `/api/v1` +endpoints — two cost endpoints (milestone 8.1) plus savings recommendations, +cost trends, and a resource-inventory endpoint (milestone 8.2). A sixth tool, +`finops_knowledge_search`, does RAG over a curated FinOps corpus stored in +pgvector (milestone 8.3) for conceptual / policy / how-to questions. The next +milestone replaces the ReAct loop with a custom supervisor (8.4). ## What it talks to @@ -52,6 +53,12 @@ The agent surfaces these caveats when accuracy materially affects the answer. | `cloudoracle_recommendations` | "where can I save money?" (savings opportunities) | `GET /api/v1/recommendations` | | `cloudoracle_cost_trends` | "is my spend growing?" (per-day series + change) | `GET /api/v1/cost-trends` | | `cloudoracle_inventory` | "what do I have?" (counts + cost by provider/service) | `GET /api/v1/inventory` | +| `finops_knowledge_search` | "what is rightsizing?", "should I buy RIs?" (concepts/policy) | pgvector RAG over the FinOps corpus | + +`finops_knowledge_search` is only registered when `DATABASE_URL` points at a +pgvector-enabled Postgres (see [Knowledge base (RAG)](#knowledge-base-rag)). +Without it the five HTTP tools still work — the agent just can't answer +conceptual questions from the corpus. ## Setup in under 10 minutes @@ -91,6 +98,10 @@ Required env vars (loaded by `pydantic-settings`, fail-fast at startup): | `LOG_LEVEL` | no | `INFO` | `DEBUG`, `INFO`, `WARNING`, `ERROR`, `CRITICAL` | | `LOG_FORMAT` | no | `text` | `text` or `json` — same shapes as the Go side | | `HTTP_TIMEOUT_SECONDS` | no | `10` | Per-request timeout against the Go server | +| `DATABASE_URL` | no | — | pgvector URL; enables `finops_knowledge_search`. Unset = RAG off | +| `EMBEDDINGS_MODEL` | no | `models/text-embedding-004`| Gemini embeddings model (free tier) | +| `KNOWLEDGE_COLLECTION` | no | `finops_knowledge` | pgvector collection name | +| `RAG_TOP_K` | no | `4` | Chunks retrieved per knowledge query (1–20) | ### 4 — Run the CLI @@ -120,6 +131,50 @@ Exit codes: | 2 | Configuration problem (missing env var, malformed URL, etc.) | | 130 | User cancelled with Ctrl-C | +## Knowledge base (RAG) + +The `finops_knowledge_search` tool retrieves from a curated FinOps corpus +(`src/insights_agent/knowledge/*.md`) embedded into pgvector. It answers +conceptual / policy / how-to questions ("what is rightsizing?", "should I buy +reserved instances?", "how accurate are these numbers?") that the HTTP tools +can't — they fetch numbers, this fetches guidance with source citations. + +RAG is **optional**: with `DATABASE_URL` unset the agent runs with just the five +HTTP tools. To enable it: + +1. **Use a pgvector-enabled Postgres.** The bundled `docker compose` stack uses + the `pgvector/pgvector:pg16` image (a drop-in for stock Postgres 16), so + `docker compose up` already gives you one. + +2. **Point the agent at it** in `.env`: + + ```bash + DATABASE_URL=postgresql+psycopg://oracle:oracle_dev@localhost:5432/cloudoracle + ``` + +3. **Ingest the corpus** (creates the `vector` extension + collection on first + run, embeds each chunk via Gemini, upserts into pgvector): + + ```bash + uv run insights-agent-ingest # add / refresh the corpus + uv run insights-agent-ingest --recreate # drop the collection first + ``` + +4. **Ask a conceptual question:** + + ```bash + uv run insights-agent --verbose "Should I rightsize before buying reserved instances?" + ``` + + With RAG on, `--verbose` shows a `finops_knowledge_search` call and the + answer cites the corpus. Re-run the ingester whenever the markdown changes; + editing the corpus does not require re-embedding unchanged files only if you + `--recreate`, otherwise new chunks are appended. + +The architecture deliberately keeps RAG in Python (where LangChain lives): the +Go server stays a clean data API, and the agent owns embeddings + retrieval +against the shared Postgres. + ## Smoke test (end-to-end with real Gemini + Go server) This exercises the full chain: Python CLI → LangGraph (Gemini) → HTTP tool @@ -175,14 +230,18 @@ the unit tests already cover the pipeline with a mocked model. ```bash uv run pytest # unit tests + coverage (>80% threshold) uv run ruff check . # lint -uv run mypy src/ # strict type-check (passes on 11 files) +uv run mypy src/ # strict type-check +uv run insights-agent-ingest # (needs DATABASE_URL) embed the FinOps corpus ``` -The tests never contact Gemini or a live Go server. `tests/test_graph.py` -ships a `ScriptedChatModel` (a `BaseChatModel` subclass) that replays -hand-written `AIMessage` sequences, and `pytest-httpx` mocks the Go -endpoints. The two together let `create_react_agent` run its full -ReAct loop deterministically — including the tool-error branch. +The tests never contact Gemini, a live Go server, or Postgres. +`tests/test_graph.py` ships a `ScriptedChatModel` (a `BaseChatModel` subclass) +that replays hand-written `AIMessage` sequences, and `pytest-httpx` mocks the +Go endpoints — together they let `create_react_agent` run its full ReAct loop +deterministically. The RAG layer is tested offline too: `tests/test_corpus.py` +checks chunking, and `tests/test_knowledge_tool.py` drives the real retrieval + +citation path through an `InMemoryVectorStore` + `DeterministicFakeEmbedding`, +so no pgvector or embeddings API is needed. ### Architecture pointers @@ -190,6 +249,7 @@ ReAct loop deterministically — including the tool-error branch. | ------------------- | ------------- | --- | | Vendor-agnostic LLM | `src/insights_agent/llm/base.py` + `gemini.py` | ABC + one implementation. Add `AnthropicProvider` / `OpenAIProvider` later by implementing `LLMProvider`; no graph changes required. | | Tools | `src/insights_agent/tools/cloudoracle.py` | `CloudOracleClient` owns the HTTP + auth + request-ID conventions; `build_tools(client)` wraps the five methods as `StructuredTool`s with rich docstrings so the LLM picks the right one. Errors flow as `ToolException` so the model sees them as observations and can recover instead of aborting the run. | +| RAG | `src/insights_agent/rag/` + `tools/knowledge.py` | `corpus.py` loads + chunks the packaged markdown (offline-testable); `embeddings.py` mirrors the LLM-provider ABC for Gemini embeddings; `store.py` wraps pgvector; `ingest.py` is the `insights-agent-ingest` CLI; `knowledge.py` exposes `finops_knowledge_search`. Only wired in when `DATABASE_URL` is set. | | Graph | `src/insights_agent/graph/basic.py` | `create_react_agent` from `langgraph.prebuilt` with a short system prompt. Milestone 8.4 replaces this with a hand-rolled supervisor. | | CLI | `src/insights_agent/main.py` | argparse, three flags, four exit codes, single async run. No conversational memory (each call is independent). | | Settings | `src/insights_agent/config.py` | `pydantic-settings.BaseSettings` — fail-fast `ValidationError` at startup if any required env var is missing. | @@ -197,7 +257,6 @@ ReAct loop deterministically — including the tool-error branch. ### What is **not** here yet -- pgvector / RAG over FinOps docs (8.3) - Custom supervisor / multi-agent (8.4) - Cost caps, semantic answer validation, deterministic fallback (8.5) - HTTP API surface for the agent — CLI only until 8.5 diff --git a/insights-agent/pyproject.toml b/insights-agent/pyproject.toml index 4ee3583..b6fd1aa 100644 --- a/insights-agent/pyproject.toml +++ b/insights-agent/pyproject.toml @@ -11,6 +11,8 @@ dependencies = [ "langgraph>=0.2.60", "langchain-google-genai>=2.0.0", "langchain-core>=0.3.20", + "langchain-postgres>=0.0.12", + "langchain-text-splitters>=0.3.0", "pydantic>=2.9.0", "pydantic-settings>=2.6.0", "httpx>=0.27.0", @@ -30,6 +32,7 @@ dev = [ [project.scripts] insights-agent = "insights_agent.main:cli_entrypoint" +insights-agent-ingest = "insights_agent.rag.ingest:ingest_entrypoint" [build-system] requires = ["hatchling"] @@ -37,6 +40,9 @@ build-backend = "hatchling.build" [tool.hatch.build.targets.wheel] packages = ["src/insights_agent"] +# The FinOps knowledge corpus ships inside the package so ingestion can find it +# via importlib.resources regardless of the working directory. +include = ["src/insights_agent/knowledge/*.md"] [tool.pytest.ini_options] asyncio_mode = "auto" @@ -95,5 +101,10 @@ no_implicit_optional = true files = ["src/insights_agent"] [[tool.mypy.overrides]] -module = ["langchain_google_genai.*", "langchain_core.*"] +module = [ + "langchain_google_genai.*", + "langchain_core.*", + "langchain_postgres.*", + "langchain_text_splitters.*", +] ignore_missing_imports = true diff --git a/insights-agent/src/insights_agent/config.py b/insights-agent/src/insights_agent/config.py index 37ef65c..4897aaa 100644 --- a/insights-agent/src/insights_agent/config.py +++ b/insights-agent/src/insights_agent/config.py @@ -36,6 +36,16 @@ class Settings(BaseSettings): log_format: str = "text" http_timeout_seconds: float = Field(default=10.0, gt=0) + # RAG / knowledge base (milestone 8.3). Optional: when database_url is + # unset the agent runs without the finops_knowledge_search tool, so the + # cost/inventory/recommendation tools work with no Postgres dependency. + # database_url is a SQLAlchemy/psycopg URL, e.g. + # postgresql+psycopg://oracle:oracle_dev@localhost:5432/cloudoracle + database_url: str | None = None + embeddings_model: str = "models/text-embedding-004" + knowledge_collection: str = "finops_knowledge" + rag_top_k: int = Field(default=4, ge=1, le=20) + @field_validator("log_level") @classmethod def _normalize_log_level(cls, v: str) -> str: diff --git a/insights-agent/src/insights_agent/graph/basic.py b/insights-agent/src/insights_agent/graph/basic.py index 99def80..9d1fa8c 100644 --- a/insights-agent/src/insights_agent/graph/basic.py +++ b/insights-agent/src/insights_agent/graph/basic.py @@ -38,6 +38,12 @@ heuristic estimates from an analyzer — advise validating against real usage \ before acting. +For conceptual, policy, or how-to FinOps questions (e.g. "what is rightsizing?", \ +"should I buy reserved instances?", "how accurate are these numbers?"), use the \ +finops_knowledge_search tool when it is available and cite the guidance it \ +returns. If the knowledge base doesn't cover it, say so rather than inventing \ +FinOps advice. + Reply in the same language the user used. If a question is outside cloud cost / FinOps scope (e.g. general coding help, \ diff --git a/insights-agent/src/insights_agent/knowledge/commitment-discounts.md b/insights-agent/src/insights_agent/knowledge/commitment-discounts.md new file mode 100644 index 0000000..d08eb14 --- /dev/null +++ b/insights-agent/src/insights_agent/knowledge/commitment-discounts.md @@ -0,0 +1,39 @@ +# Commitment-based discounts: Reserved Instances, Savings Plans, CUDs + +Cloud providers sell capacity cheaper in exchange for a usage commitment. +These are pricing levers, not architectural changes — they lower the rate you +pay for the same resources, so they apply *after* you have rightsized. + +## The main instruments + +- **Reserved Instances (RIs) — AWS, Azure.** Commit to a specific instance + family/region for 1 or 3 years. Largest discount (up to ~70%) but least + flexible: the commitment is tied to the instance shape. +- **Savings Plans — AWS.** Commit to a dollar-per-hour spend level for 1 or 3 + years. More flexible than RIs (applies across instance families and, for + Compute Savings Plans, across regions and to Fargate/Lambda) at a slightly + smaller discount. +- **Committed Use Discounts (CUDs) — GCP.** Commit to a level of vCPU/RAM (or + spend, for flexible CUDs) for 1 or 3 years. + +## When commitments make sense + +- The workload is **steady-state** — a predictable baseline that runs + 24/7/365. Commit to the baseline, leave the spiky top on on-demand. +- You have already **rightsized**. Committing to oversized capacity locks in + waste for 1–3 years; rightsize first, then commit to the smaller footprint. +- You can forecast usage with reasonable confidence over the term. Under-using + a commitment wastes the unused portion; the break-even is typically around + 60–70% utilization of the commitment. + +## When to avoid them + +- Bursty, seasonal, or declining workloads — on-demand or spot is safer. +- Architectures you expect to change within the term (migration, refactor). +- Before rightsizing: never commit to capacity you are about to shrink. + +## Relationship to CloudOracle + +CloudOracle's recommendations cover **architectural / sizing** waste (idle, +oversized, orphaned), not pricing-model selection. Commitment planning is a +complementary lever applied to whatever footprint remains after rightsizing. diff --git a/insights-agent/src/insights_agent/knowledge/cost-allocation-and-tagging.md b/insights-agent/src/insights_agent/knowledge/cost-allocation-and-tagging.md new file mode 100644 index 0000000..2b3362c --- /dev/null +++ b/insights-agent/src/insights_agent/knowledge/cost-allocation-and-tagging.md @@ -0,0 +1,44 @@ +# Cost allocation, tagging, showback and chargeback + +You cannot manage what you cannot attribute. Cost allocation is the practice of +mapping each dollar of cloud spend to the team, product, environment, or +customer responsible for it. + +## Tagging is the foundation + +- **Tags / labels** are key-value metadata on resources (e.g. `team=payments`, + `env=prod`, `cost-center=4812`). Allocation quality is capped by tag + coverage and consistency. +- **Untagged or inconsistently tagged resources** fall into an "unallocated" + bucket that no one owns — the first thing a FinOps practice tries to shrink. +- **A tagging policy** defines a small set of mandatory keys and allowed + values, enforced at provisioning time (IaC, policy-as-code) rather than + cleaned up after the fact. + +## Showback vs chargeback + +- **Showback** reports each team its share of spend for visibility, without + moving money. Low-friction; drives awareness and behavior change. +- **Chargeback** actually bills the cost back to the team's budget. Higher + accountability but needs accurate allocation and organizational buy-in. + +Most organizations start with showback and graduate to chargeback once +allocation is trusted. + +## Shared and unallocable costs + +Some costs resist direct tagging — shared clusters, data transfer, support +fees, committed-discount amortization. Common approaches: + +- **Proportional split** by a driver (e.g. each team's tagged compute share). +- **Even split** across consuming teams. +- **Dedicated "platform" cost center** that owns shared infrastructure. + +Document the method; an explainable split beats a perfectly "fair" but opaque +one. + +## Relationship to CloudOracle + +CloudOracle resources carry tags and an account id; the inventory and cost +breakdowns aggregate by provider and service. Per-team allocation builds on top +of that by grouping on the tag keys your organization standardizes. diff --git a/insights-agent/src/insights_agent/knowledge/data-sources-and-caveats.md b/insights-agent/src/insights_agent/knowledge/data-sources-and-caveats.md new file mode 100644 index 0000000..fc40af9 --- /dev/null +++ b/insights-agent/src/insights_agent/knowledge/data-sources-and-caveats.md @@ -0,0 +1,44 @@ +# CloudOracle data sources and their caveats + +Every CloudOracle API response carries a `data_source` field. It tells you how +the numbers were produced and therefore how much to trust them. The agent +should surface the matching caveat whenever accuracy materially affects an +answer. + +## `snapshots_approximation` — the cost endpoints + +Used by cost-summary, cost-by-service, and cost-trends. + +- **What it is.** CloudOracle periodically records each provider/service's + *projected monthly cost rate* into a `cost_snapshots` table. A period total + is the average of those snapshot rates over the period, scaled to the + period length (`average monthly rate × days / 30`). +- **What it is NOT.** It is not billed spend from a Cost Explorer / billing + API. It will not match an invoice to the cent, and it cannot see + one-off charges, taxes, credits, or refunds. +- **How to phrase it.** "Based on snapshot approximations, roughly $X." The + real billing integration lands in a later milestone (8.7). + +## `heuristic_rules` — the recommendations endpoint + +- **What it is.** Rule-based analysis over the current resource inventory + (idle, oversized, orphaned, over-provisioned). Each rule estimates a + monthly saving. +- **What it is NOT.** Not a guarantee. `monthly_savings_usd` is an *upper + bound* assuming the resource can be removed or downsized without impact. +- **How to phrase it.** "Estimated savings of up to $X — validate against real + usage before acting." + +## `live_inventory` — the inventory endpoint + +- **What it is.** Counts and cost from the latest resource scan, aggregated by + provider and service. +- **What it is NOT.** `monthly_cost_usd` is the sum of per-resource *projected + monthly rates* at scan time, not billed spend, and it reflects only what the + scan discovered. + +## Why this matters + +Conflating these leads to wrong conclusions — e.g. treating a recommendation's +upper-bound saving as money already banked, or comparing a snapshot +approximation directly against an invoice. Always read `data_source` first. diff --git a/insights-agent/src/insights_agent/knowledge/finops-glossary.md b/insights-agent/src/insights_agent/knowledge/finops-glossary.md new file mode 100644 index 0000000..f1fd5b6 --- /dev/null +++ b/insights-agent/src/insights_agent/knowledge/finops-glossary.md @@ -0,0 +1,45 @@ +# FinOps glossary + +Concise definitions of terms the agent may need when explaining cost concepts. + +- **FinOps.** An operational practice that brings financial accountability to + the variable spend of cloud, through collaboration between engineering, + finance, and product. Built on three phases: Inform, Optimize, Operate. + +- **Unit economics / unit cost.** Cloud cost divided by a business metric + (cost per order, per active user, per GB processed). Lets cost be judged + against value rather than in absolute dollars — spend can rise while unit + cost falls. + +- **Amortization.** Spreading an upfront or committed cost (e.g. a 1-year + Reserved Instance paid all-upfront) evenly across the period it covers, + instead of booking it all on the purchase day. Amortized views give a + smoother, more comparable monthly cost. + +- **Blended vs unblended cost (AWS).** Unblended is the actual rate each + account paid; blended averages rates across a consolidated billing family. + Most cost analysis uses unblended (or amortized) cost. + +- **Cost anomaly.** A statistically unusual jump in spend versus the recent + baseline — often a misconfiguration, a runaway job, or a forgotten resource. + Detecting anomalies early limits surprise bills. + +- **Idle resource.** A provisioned resource doing little or no useful work + (very low utilization). Distinct from an *orphaned* resource, which is + unattached and does no work at all. + +- **Rightsizing.** Adjusting provisioned capacity to match real demand. See + the rightsizing note for signals and how to act. + +- **Commitment-based discount.** A lower rate in exchange for a 1–3 year usage + or spend commitment (Reserved Instances, Savings Plans, Committed Use + Discounts). See the commitment-discounts note. + +- **Showback / chargeback.** Reporting (showback) versus actually billing back + (chargeback) cloud cost to the responsible team. See the cost-allocation + note. + +- **Data source (CloudOracle).** A field on every API response + (`snapshots_approximation`, `heuristic_rules`, `live_inventory`) describing + how the numbers were produced and how much to trust them. See the + data-sources note. diff --git a/insights-agent/src/insights_agent/knowledge/rightsizing.md b/insights-agent/src/insights_agent/knowledge/rightsizing.md new file mode 100644 index 0000000..1a5aee5 --- /dev/null +++ b/insights-agent/src/insights_agent/knowledge/rightsizing.md @@ -0,0 +1,41 @@ +# Rightsizing cloud resources + +Rightsizing means matching a resource's provisioned capacity to its actual +demand. It is usually the largest source of recoverable cloud waste because +most teams over-provision "to be safe" and never revisit the decision. + +## Signals that a resource is a rightsizing candidate + +- **Low average CPU / memory utilization.** A compute instance averaging + under ~5% CPU over a sustained window (e.g. a week or more) is effectively + idle. CloudOracle flags these as `ec2-idle` (High severity). +- **Sustained low database utilization.** A managed database averaging under + ~10% CPU is likely oversized; the next smaller instance tier typically + covers the real load. CloudOracle flags these as `rds-oversized` (Medium). +- **Orphaned storage.** A disk volume with zero usage / no attachment is pure + waste — nothing reads or writes it. CloudOracle flags these as `ebs-orphan` + (High). The fix is deletion (after a snapshot if the data may be needed). +- **Over-provisioned serverless.** A function configured with far more memory + than its invocations use pays for headroom it never touches. CloudOracle + flags these as `lambda-over-provisioned` (Low). + +## How to act + +1. **Confirm the signal against real usage.** A heuristic flag is a starting + point, not proof. Check a longer utilization window and peak (not just + average) demand before resizing — a nightly batch job can look idle for + 23 hours a day. +2. **Resize down one step at a time.** Drop to the next smaller instance + class or tier, then re-measure. Aggressive jumps risk throttling or OOM. +3. **Prefer architectural fixes for structural waste.** Idle instances that + exist only for occasional work are better moved to autoscaling, scheduled + shutdown, or serverless than merely shrunk. +4. **Delete, don't shrink, orphans.** Orphaned volumes and unattached IPs have + no smaller size — the only rightsizing is removal. + +## Savings expectation + +Rightsizing savings are an estimated upper bound: shutting down a flagged idle +instance recovers its full monthly cost; downsizing a tier typically recovers +~50%. Realized savings depend on the workload tolerating the smaller footprint, +so validate before acting. diff --git a/insights-agent/src/insights_agent/main.py b/insights-agent/src/insights_agent/main.py index 4065109..b954811 100644 --- a/insights-agent/src/insights_agent/main.py +++ b/insights-agent/src/insights_agent/main.py @@ -22,7 +22,9 @@ import asyncio import json import sys +from typing import Any +from langchain_core.tools import BaseTool from pydantic import ValidationError from insights_agent.config import Settings @@ -61,6 +63,40 @@ def _build_arg_parser() -> argparse.ArgumentParser: return p +def _maybe_build_knowledge_tool(settings: Settings, log: Any) -> BaseTool | None: + """Build the RAG knowledge tool when a pgvector DB is configured. + + Returns None (and logs why) when database_url is unset, so the agent runs + with just the cost/inventory/recommendation tools and no DB dependency. + Imports are deferred so the heavier RAG/db stack is only loaded when used. + """ + if not settings.database_url: + log.info("rag.disabled", reason="database_url not set") + return None + + from insights_agent.rag.embeddings import GeminiEmbeddingsProvider + from insights_agent.rag.store import build_retriever, build_vector_store + from insights_agent.tools.knowledge import build_knowledge_tool + + embeddings = GeminiEmbeddingsProvider( + api_key=settings.gemini_api_key, + model=settings.embeddings_model, + ).get_embeddings() + store = build_vector_store( + connection=settings.database_url, + embeddings=embeddings, + collection=settings.knowledge_collection, + ) + retriever = build_retriever(store, k=settings.rag_top_k) + log.info( + "rag.enabled", + collection=settings.knowledge_collection, + embeddings_model=settings.embeddings_model, + top_k=settings.rag_top_k, + ) + return build_knowledge_tool(retriever) + + async def _run(query: str, *, as_json: bool, verbose: bool) -> AgentResult: # pydantic-settings populates required fields from the environment; # mypy's call-arg check doesn't understand env-based construction @@ -84,7 +120,10 @@ async def _run(query: str, *, as_json: bool, verbose: bool) -> AgentResult: api_key=settings.cloudoracle_api_key, timeout_seconds=settings.http_timeout_seconds, ) as client: - tools = build_tools(client) + tools: list[BaseTool] = list(build_tools(client)) + knowledge_tool = _maybe_build_knowledge_tool(settings, log) + if knowledge_tool is not None: + tools.append(knowledge_tool) graph = build_graph(provider.get_chat_model(), tools) result = await ask(graph, query) diff --git a/insights-agent/src/insights_agent/rag/__init__.py b/insights-agent/src/insights_agent/rag/__init__.py new file mode 100644 index 0000000..debc382 --- /dev/null +++ b/insights-agent/src/insights_agent/rag/__init__.py @@ -0,0 +1,17 @@ +"""Retrieval-augmented generation over the FinOps knowledge corpus.""" + +from insights_agent.rag.corpus import load_corpus, load_markdown_documents +from insights_agent.rag.embeddings import ( + EmbeddingsProvider, + GeminiEmbeddingsProvider, +) +from insights_agent.rag.store import build_retriever, build_vector_store + +__all__ = [ + "EmbeddingsProvider", + "GeminiEmbeddingsProvider", + "build_retriever", + "build_vector_store", + "load_corpus", + "load_markdown_documents", +] diff --git a/insights-agent/src/insights_agent/rag/corpus.py b/insights-agent/src/insights_agent/rag/corpus.py new file mode 100644 index 0000000..192ce3b --- /dev/null +++ b/insights-agent/src/insights_agent/rag/corpus.py @@ -0,0 +1,99 @@ +"""Load and chunk the FinOps knowledge corpus into LangChain documents. + +The corpus is a set of curated markdown notes shipped inside the package +(`insights_agent/knowledge/*.md`). This module is deliberately free of any +embedding / database concern so the chunking logic is unit-testable offline — +the ingestion CLI (`rag.ingest`) layers the vector store on top. + +Each source file becomes one or more `Document` chunks carrying `source` +(the file name) and `title` (the first H1) metadata, which the knowledge tool +turns into inline citations. +""" + +from __future__ import annotations + +from importlib import resources +from pathlib import Path + +from langchain_core.documents import Document +from langchain_text_splitters import RecursiveCharacterTextSplitter + +KNOWLEDGE_PACKAGE = "insights_agent.knowledge" + +DEFAULT_CHUNK_SIZE = 1000 +DEFAULT_CHUNK_OVERLAP = 150 + +# Split on markdown structure first (headings, then paragraphs) so a chunk +# tends to be a coherent section rather than an arbitrary character window. +_SEPARATORS = ["\n## ", "\n### ", "\n\n", "\n", " ", ""] + + +def _read_sources(directory: Path | None) -> list[tuple[str, str]]: + """Return (file_name, text) for every markdown file in the corpus. + + With no directory, read the packaged corpus via importlib.resources so it + works from an installed wheel regardless of CWD. A directory override is + used by tests and by anyone pointing the ingester at a custom corpus. + """ + out: list[tuple[str, str]] = [] + if directory is not None: + for path in sorted(directory.glob("*.md")): + out.append((path.name, path.read_text(encoding="utf-8"))) + return out + + for entry in sorted( + resources.files(KNOWLEDGE_PACKAGE).iterdir(), key=lambda p: p.name + ): + if entry.name.endswith(".md") and entry.is_file(): + out.append((entry.name, entry.read_text(encoding="utf-8"))) + return out + + +def _first_heading(text: str) -> str | None: + for line in text.splitlines(): + stripped = line.strip() + if stripped.startswith("# "): + return stripped[2:].strip() + return None + + +def load_markdown_documents(directory: Path | None = None) -> list[Document]: + """Load each corpus file as one whole (un-chunked) Document with metadata.""" + docs: list[Document] = [] + for name, text in _read_sources(directory): + if not text.strip(): + continue + title = _first_heading(text) or Path(name).stem + docs.append( + Document(page_content=text, metadata={"source": name, "title": title}) + ) + return docs + + +def chunk_documents( + docs: list[Document], + *, + chunk_size: int = DEFAULT_CHUNK_SIZE, + chunk_overlap: int = DEFAULT_CHUNK_OVERLAP, +) -> list[Document]: + """Split whole documents into overlapping chunks, preserving metadata.""" + splitter = RecursiveCharacterTextSplitter( + chunk_size=chunk_size, + chunk_overlap=chunk_overlap, + separators=_SEPARATORS, + ) + return splitter.split_documents(docs) + + +def load_corpus( + directory: Path | None = None, + *, + chunk_size: int = DEFAULT_CHUNK_SIZE, + chunk_overlap: int = DEFAULT_CHUNK_OVERLAP, +) -> list[Document]: + """Load + chunk the corpus in one call — the ingester's entry point.""" + return chunk_documents( + load_markdown_documents(directory), + chunk_size=chunk_size, + chunk_overlap=chunk_overlap, + ) diff --git a/insights-agent/src/insights_agent/rag/embeddings.py b/insights-agent/src/insights_agent/rag/embeddings.py new file mode 100644 index 0000000..9c976b8 --- /dev/null +++ b/insights-agent/src/insights_agent/rag/embeddings.py @@ -0,0 +1,62 @@ +"""Embeddings provider abstraction, mirroring the LLM provider pattern. + +Adding another embeddings backend (OpenAI, a local model) later is purely +additive: implement `EmbeddingsProvider` and select it in the wiring code. +Gemini is the default so the agent stays on a single vendor / free tier for +both generation and retrieval. +""" + +from __future__ import annotations + +from abc import ABC, abstractmethod +from functools import cached_property + +from langchain_core.embeddings import Embeddings +from langchain_google_genai import GoogleGenerativeAIEmbeddings + +# Gemini's general-purpose text embedding model. 768 dimensions, covered by the +# free tier — same account/key as the chat model. +DEFAULT_EMBEDDINGS_MODEL = "models/text-embedding-004" + + +class EmbeddingsProvider(ABC): + """Vendor-agnostic embeddings factory.""" + + @abstractmethod + def get_embeddings(self) -> Embeddings: + """Return a LangChain-compatible Embeddings object.""" + + @property + @abstractmethod + def model_name(self) -> str: + """Current embeddings model id (e.g. 'models/text-embedding-004').""" + + +class GeminiEmbeddingsProvider(EmbeddingsProvider): + def __init__( + self, + *, + api_key: str, + model: str = DEFAULT_EMBEDDINGS_MODEL, + ) -> None: + if not api_key: + raise ValueError("GeminiEmbeddingsProvider requires a non-empty api_key") + self._api_key = api_key + self._model = model + + @cached_property + def _embeddings(self) -> GoogleGenerativeAIEmbeddings: + # google_api_key is a valid pydantic field (accepted at runtime via the + # model's **data init) but mypy reads the typed signature and doesn't + # see it — same accommodation the codebase makes for env-based pydantic. + return GoogleGenerativeAIEmbeddings( + model=self._model, + google_api_key=self._api_key, # type: ignore[call-arg] + ) + + def get_embeddings(self) -> Embeddings: + return self._embeddings + + @property + def model_name(self) -> str: + return self._model diff --git a/insights-agent/src/insights_agent/rag/ingest.py b/insights-agent/src/insights_agent/rag/ingest.py new file mode 100644 index 0000000..4f65f73 --- /dev/null +++ b/insights-agent/src/insights_agent/rag/ingest.py @@ -0,0 +1,111 @@ +"""Ingest the FinOps corpus into the pgvector store. + +Two layers: + + - `ingest_corpus(store, ...)` is store-agnostic (chunk → add_documents) and + unit-tested against an in-memory store. + - `ingest_entrypoint` is the `insights-agent-ingest` console script: it reads + settings, builds the Gemini embeddings + PGVector store, and calls + `ingest_corpus`. It touches Postgres and the embeddings API, so it is not + unit-tested (the smoke test in the README covers it end-to-end). + +Run it once after `docker compose up` (with pgvector) and whenever the corpus +changes: + + uv run insights-agent-ingest # add/refresh the corpus + uv run insights-agent-ingest --recreate # drop the collection first +""" + +from __future__ import annotations + +import argparse +import sys +from pathlib import Path + +from langchain_core.vectorstores import VectorStore + +from insights_agent.rag.corpus import ( + DEFAULT_CHUNK_OVERLAP, + DEFAULT_CHUNK_SIZE, + load_corpus, +) + + +def ingest_corpus( + store: VectorStore, + *, + directory: Path | None = None, + chunk_size: int = DEFAULT_CHUNK_SIZE, + chunk_overlap: int = DEFAULT_CHUNK_OVERLAP, +) -> int: + """Chunk the corpus and add it to `store`. Returns the number of chunks.""" + chunks = load_corpus( + directory, chunk_size=chunk_size, chunk_overlap=chunk_overlap + ) + if not chunks: + return 0 + store.add_documents(chunks) + return len(chunks) + + +def ingest_entrypoint(argv: list[str] | None = None) -> int: # pragma: no cover + """Console-script entry point. Builds the real PGVector store and ingests.""" + parser = argparse.ArgumentParser( + prog="insights-agent-ingest", + description="Embed the FinOps knowledge corpus into the pgvector store.", + ) + parser.add_argument( + "--recreate", + action="store_true", + help="Drop and recreate the collection before ingesting.", + ) + args = parser.parse_args(argv) + + # Imports are local so the module stays importable (for ingest_corpus) even + # if optional settings/credentials aren't present in a test environment. + from pydantic import ValidationError + + from insights_agent.config import Settings + from insights_agent.logging import get_logger, setup + from insights_agent.rag.embeddings import GeminiEmbeddingsProvider + from insights_agent.rag.store import build_vector_store + + try: + settings = Settings() # type: ignore[call-arg] + except ValidationError as e: + print(f"Configuration error:\n{e}", file=sys.stderr) + return 2 + + if not settings.database_url: + print( + "DATABASE_URL is not set — RAG ingestion needs a pgvector-enabled " + "Postgres. See insights-agent/README.md.", + file=sys.stderr, + ) + return 2 + + setup(level=settings.log_level, fmt=settings.log_format) + log = get_logger("insights_agent.rag.ingest") + + embeddings = GeminiEmbeddingsProvider( + api_key=settings.gemini_api_key, + model=settings.embeddings_model, + ).get_embeddings() + store = build_vector_store( + connection=settings.database_url, + embeddings=embeddings, + collection=settings.knowledge_collection, + ) + if args.recreate: + store.drop_tables() + store.create_tables_if_not_exists() + log.info("rag.collection_recreated", collection=settings.knowledge_collection) + + count = ingest_corpus(store) + log.info("rag.ingested", chunks=count, collection=settings.knowledge_collection) + print(f"Ingested {count} chunks into '{settings.knowledge_collection}'.") + return 0 + + +if __name__ == "__main__": # pragma: no cover + sys.exit(ingest_entrypoint()) diff --git a/insights-agent/src/insights_agent/rag/store.py b/insights-agent/src/insights_agent/rag/store.py new file mode 100644 index 0000000..3afae8d --- /dev/null +++ b/insights-agent/src/insights_agent/rag/store.py @@ -0,0 +1,38 @@ +"""pgvector-backed vector store wiring. + +`build_vector_store` is the only place that talks to Postgres; it's a thin +assembly of a `langchain_postgres.PGVector` and is exercised by the smoke / +integration path, not unit tests (it opens a real connection). `build_retriever` +is store-agnostic and unit-tested against an in-memory store. +""" + +from __future__ import annotations + +from langchain_core.embeddings import Embeddings +from langchain_core.vectorstores import VectorStore, VectorStoreRetriever +from langchain_postgres import PGVector + + +def build_vector_store( + *, + connection: str, + embeddings: Embeddings, + collection: str, +) -> PGVector: # pragma: no cover - opens a real DB connection + """Construct a PGVector store over the CloudOracle Postgres. + + `connection` is a SQLAlchemy/psycopg URL, e.g. + `postgresql+psycopg://oracle:oracle_dev@localhost:5432/cloudoracle`. + `use_jsonb=True` stores chunk metadata as JSONB so it can be filtered on. + """ + return PGVector( + embeddings=embeddings, + collection_name=collection, + connection=connection, + use_jsonb=True, + ) + + +def build_retriever(store: VectorStore, *, k: int = 4) -> VectorStoreRetriever: + """Wrap any vector store as a top-k similarity retriever.""" + return store.as_retriever(search_kwargs={"k": k}) diff --git a/insights-agent/src/insights_agent/tools/knowledge.py b/insights-agent/src/insights_agent/tools/knowledge.py new file mode 100644 index 0000000..23e30a6 --- /dev/null +++ b/insights-agent/src/insights_agent/tools/knowledge.py @@ -0,0 +1,72 @@ +"""RAG retrieval tool over the FinOps knowledge corpus. + +`build_knowledge_tool(retriever)` wraps any LangChain retriever as a +`finops_knowledge_search` tool. The agent calls it for conceptual / policy / +how-to questions (vs. the cloudoracle_* tools, which fetch numbers). Results +are formatted with `[source: — ]` headers so the model can cite +where guidance came from. + +The tool returns formatted text (not structured data) because retrieved context +is meant to be read and synthesized by the model, then cited in the answer. +""" + +from __future__ import annotations + +from langchain_core.documents import Document +from langchain_core.retrievers import BaseRetriever +from langchain_core.tools import StructuredTool, ToolException + +_NO_RESULTS = "No relevant FinOps knowledge was found for that query." + + +def build_knowledge_tool(retriever: BaseRetriever) -> StructuredTool: + async def _search(query: str) -> str: + try: + docs = await retriever.ainvoke(query) + except Exception as e: # surface any retriever failure to the model + # ToolException is caught by the ReAct loop and shown to the model + # as an observation, so a transient store error doesn't abort the + # whole run — the agent can answer from its own knowledge instead. + raise ToolException(f"knowledge search failed: {e}") from e + if not docs: + return _NO_RESULTS + return _format_documents(docs) + + return StructuredTool.from_function( + coroutine=_search, + name="finops_knowledge_search", + description=_KNOWLEDGE_DESC, + handle_tool_error=True, + ) + + +def _format_documents(docs: list[Document]) -> str: + blocks: list[str] = [] + for doc in docs: + source = doc.metadata.get("source", "unknown") + title = doc.metadata.get("title") + header = f"[source: {source}" + (f" — {title}]" if title else "]") + blocks.append(f"{header}\n{doc.page_content.strip()}") + return "\n\n---\n\n".join(blocks) + + +_KNOWLEDGE_DESC = """Search CloudOracle's curated FinOps knowledge base for guidance and definitions. + +Use this for conceptual, policy, how-to, or "what does X mean?" questions — +e.g. "what is rightsizing?", "should I buy reserved instances?", "how accurate +are these cost numbers?", "explain showback vs chargeback", "what does +data_source mean?". Do NOT use it to fetch a user's actual numbers — the +cloudoracle_cost_summary / cost_by_service / cost_trends / inventory / +recommendations tools do that. + +Args: + query: A natural-language question or topic to look up. + +Returns: + Relevant excerpts from the knowledge base, each prefixed with a + `[source: <file> — <title>]` header, separated by `---`. If nothing + matches, a short "no results" message. + +When you use an excerpt in your answer, briefly cite the source (e.g. "per the +rightsizing guide"). If the excerpts don't cover the question, say so rather +than inventing FinOps guidance.""" diff --git a/insights-agent/tests/conftest.py b/insights-agent/tests/conftest.py index 82d7070..6291db7 100644 --- a/insights-agent/tests/conftest.py +++ b/insights-agent/tests/conftest.py @@ -19,6 +19,10 @@ "LOG_LEVEL", "LOG_FORMAT", "HTTP_TIMEOUT_SECONDS", + "DATABASE_URL", + "EMBEDDINGS_MODEL", + "KNOWLEDGE_COLLECTION", + "RAG_TOP_K", ) diff --git a/insights-agent/tests/test_config.py b/insights-agent/tests/test_config.py index 5310f38..a2ca398 100644 --- a/insights-agent/tests/test_config.py +++ b/insights-agent/tests/test_config.py @@ -65,3 +65,34 @@ def test_timeout_must_be_positive( monkeypatch.setenv("HTTP_TIMEOUT_SECONDS", "0") with pytest.raises(ValidationError): Settings() + + +def test_rag_settings_default_to_disabled(valid_env: None) -> None: + s = Settings() + # No DATABASE_URL → RAG is off; the rest carry sensible defaults. + assert s.database_url is None + assert s.embeddings_model == "models/text-embedding-004" + assert s.knowledge_collection == "finops_knowledge" + assert s.rag_top_k == 4 + + +def test_rag_settings_from_env( + valid_env: None, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv( + "DATABASE_URL", "postgresql+psycopg://oracle:oracle_dev@localhost:5432/cloudoracle" + ) + monkeypatch.setenv("KNOWLEDGE_COLLECTION", "kb") + monkeypatch.setenv("RAG_TOP_K", "8") + s = Settings() + assert s.database_url is not None + assert s.knowledge_collection == "kb" + assert s.rag_top_k == 8 + + +def test_rag_top_k_out_of_range_rejected( + valid_env: None, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("RAG_TOP_K", "0") + with pytest.raises(ValidationError): + Settings() diff --git a/insights-agent/tests/test_corpus.py b/insights-agent/tests/test_corpus.py new file mode 100644 index 0000000..2c22de1 --- /dev/null +++ b/insights-agent/tests/test_corpus.py @@ -0,0 +1,72 @@ +"""Corpus loading + chunking — fully offline (no embeddings, no DB).""" + +from __future__ import annotations + +from pathlib import Path + +from insights_agent.rag.corpus import ( + chunk_documents, + load_corpus, + load_markdown_documents, +) + + +class TestPackagedCorpus: + def test_loads_the_seed_corpus(self) -> None: + docs = load_markdown_documents() + # The five seed notes shipped with the package. + names = {d.metadata["source"] for d in docs} + assert names == { + "rightsizing.md", + "commitment-discounts.md", + "data-sources-and-caveats.md", + "cost-allocation-and-tagging.md", + "finops-glossary.md", + } + + def test_title_metadata_is_the_h1(self) -> None: + docs = load_markdown_documents() + by_source = {d.metadata["source"]: d for d in docs} + assert by_source["rightsizing.md"].metadata["title"] == "Rightsizing cloud resources" + + def test_chunking_preserves_metadata_and_splits(self) -> None: + chunks = load_corpus() + # Chunking a multi-section corpus yields more pieces than source files. + assert len(chunks) >= 5 + for c in chunks: + assert c.metadata.get("source", "").endswith(".md") + assert c.metadata.get("title") + + +class TestDirectoryOverride: + def test_reads_from_a_directory(self, tmp_path: Path) -> None: + (tmp_path / "a.md").write_text("# Alpha\n\nbody a", encoding="utf-8") + (tmp_path / "b.md").write_text("# Beta\n\nbody b", encoding="utf-8") + (tmp_path / "ignore.txt").write_text("not markdown", encoding="utf-8") + + docs = load_markdown_documents(tmp_path) + assert {d.metadata["source"] for d in docs} == {"a.md", "b.md"} + assert {d.metadata["title"] for d in docs} == {"Alpha", "Beta"} + + def test_blank_file_is_skipped(self, tmp_path: Path) -> None: + (tmp_path / "empty.md").write_text(" \n\n", encoding="utf-8") + (tmp_path / "real.md").write_text("# Real\n\nbody", encoding="utf-8") + docs = load_markdown_documents(tmp_path) + assert [d.metadata["source"] for d in docs] == ["real.md"] + + def test_falls_back_to_filename_when_no_h1(self, tmp_path: Path) -> None: + (tmp_path / "no-heading.md").write_text("just text, no heading", encoding="utf-8") + docs = load_markdown_documents(tmp_path) + assert docs[0].metadata["title"] == "no-heading" + + +class TestChunkSizing: + def test_long_doc_splits_into_multiple_chunks(self, tmp_path: Path) -> None: + body = "\n\n".join(f"Paragraph number {i} with some filler text." for i in range(60)) + (tmp_path / "long.md").write_text(f"# Long\n\n{body}", encoding="utf-8") + docs = load_markdown_documents(tmp_path) + chunks = chunk_documents(docs, chunk_size=200, chunk_overlap=20) + assert len(chunks) > 1 + for c in chunks: + # Allow a little slack for separator boundaries. + assert len(c.page_content) <= 260 diff --git a/insights-agent/tests/test_embeddings.py b/insights-agent/tests/test_embeddings.py new file mode 100644 index 0000000..a2039f5 --- /dev/null +++ b/insights-agent/tests/test_embeddings.py @@ -0,0 +1,34 @@ +"""Embeddings provider — construction only, no network calls.""" + +from __future__ import annotations + +import pytest +from langchain_core.embeddings import Embeddings + +from insights_agent.rag.embeddings import ( + DEFAULT_EMBEDDINGS_MODEL, + GeminiEmbeddingsProvider, +) + + +def test_rejects_empty_api_key() -> None: + with pytest.raises(ValueError, match="api_key"): + GeminiEmbeddingsProvider(api_key="") + + +def test_model_name_defaults() -> None: + p = GeminiEmbeddingsProvider(api_key="k") + assert p.model_name == DEFAULT_EMBEDDINGS_MODEL + + +def test_model_name_override() -> None: + p = GeminiEmbeddingsProvider(api_key="k", model="models/custom") + assert p.model_name == "models/custom" + + +def test_get_embeddings_returns_embeddings_object() -> None: + p = GeminiEmbeddingsProvider(api_key="k") + emb = p.get_embeddings() + assert isinstance(emb, Embeddings) + # cached_property: the same object is returned on repeat access. + assert p.get_embeddings() is emb diff --git a/insights-agent/tests/test_knowledge_tool.py b/insights-agent/tests/test_knowledge_tool.py new file mode 100644 index 0000000..434f366 --- /dev/null +++ b/insights-agent/tests/test_knowledge_tool.py @@ -0,0 +1,89 @@ +"""Knowledge retrieval tool — offline via an in-memory vector store. + +We avoid pgvector entirely: a `DeterministicFakeEmbedding` + `InMemoryVectorStore` +exercise the real retrieval + formatting path that the production PGVector store +would drive, without a database or network. +""" + +from __future__ import annotations + +import pytest +from langchain_core.documents import Document +from langchain_core.embeddings import DeterministicFakeEmbedding +from langchain_core.retrievers import BaseRetriever +from langchain_core.vectorstores import InMemoryVectorStore + +from insights_agent.rag.ingest import ingest_corpus +from insights_agent.rag.store import build_retriever +from insights_agent.tools.knowledge import build_knowledge_tool + + +@pytest.fixture +def retriever() -> BaseRetriever: + store = InMemoryVectorStore(DeterministicFakeEmbedding(size=64)) + # Ingest the real packaged corpus through the same code path the CLI uses. + n = ingest_corpus(store) + assert n >= 5 + return build_retriever(store, k=3) + + +class TestKnowledgeTool: + def test_tool_name_and_description(self, retriever: BaseRetriever) -> None: + tool = build_knowledge_tool(retriever) + assert tool.name == "finops_knowledge_search" + assert "FinOps" in tool.description + + async def test_returns_cited_snippets(self, retriever: BaseRetriever) -> None: + tool = build_knowledge_tool(retriever) + out = await tool.ainvoke({"query": "how should I rightsize idle instances?"}) + assert isinstance(out, str) + # Each retrieved chunk is prefixed with a [source: ...] citation header. + assert "[source:" in out + # k=3 retriever → up to three blocks joined by the --- separator. + assert out.count("[source:") <= 3 + + async def test_no_results_message(self) -> None: + # An empty store retrieves nothing → the friendly no-results string. + empty = InMemoryVectorStore(DeterministicFakeEmbedding(size=64)) + tool = build_knowledge_tool(build_retriever(empty, k=3)) + out = await tool.ainvoke({"query": "anything"}) + assert "No relevant FinOps knowledge" in out + + async def test_retriever_error_becomes_observation(self) -> None: + class BoomRetriever(BaseRetriever): + def _get_relevant_documents(self, query: str, *, run_manager=None): # type: ignore[no-untyped-def] + raise RuntimeError("store down") + + tool = build_knowledge_tool(BoomRetriever()) + # handle_tool_error=True turns the ToolException into the observation + # string instead of raising — the ReAct loop can then recover. + out = await tool.ainvoke({"query": "x"}) + assert "knowledge search failed" in out + assert "store down" in out + + +class TestIngestCorpus: + def test_ingests_into_a_store(self) -> None: + store = InMemoryVectorStore(DeterministicFakeEmbedding(size=64)) + count = ingest_corpus(store) + assert count >= 5 + + def test_empty_directory_adds_nothing(self, tmp_path) -> None: # type: ignore[no-untyped-def] + store = InMemoryVectorStore(DeterministicFakeEmbedding(size=64)) + assert ingest_corpus(store, directory=tmp_path) == 0 + + def test_custom_directory_is_used(self, tmp_path) -> None: # type: ignore[no-untyped-def] + (tmp_path / "one.md").write_text("# One\n\nhello world", encoding="utf-8") + store = InMemoryVectorStore(DeterministicFakeEmbedding(size=64)) + docs_added = ingest_corpus(store, directory=tmp_path) + assert docs_added == 1 + results = store.similarity_search("hello", k=1) + assert results and results[0].metadata["source"] == "one.md" + + +def test_format_documents_handles_missing_title() -> None: + from insights_agent.tools.knowledge import _format_documents + + docs = [Document(page_content="body", metadata={"source": "x.md"})] + out = _format_documents(docs) + assert out == "[source: x.md]\nbody" diff --git a/insights-agent/tests/test_main.py b/insights-agent/tests/test_main.py index e48536a..8274c5f 100644 --- 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Routing via tool calls (not with_structured_output) keeps the node driveable by the scripted fake model the suite already uses. - three specialist workers, each a hand-rolled ReAct loop (_run_react, the actual create_react_agent replacement) over a tool subset: cost_analyst (cost-summary/by-service/trends/inventory), savings_advisor (recommendations + knowledge), concept_expert (knowledge). A worker contributes one summarizing message; its tool churn stays local so the supervisor/synthesizer see a clean transcript. - synthesize composes the final answer from the findings, in the user's language, with data-source caveats and citations. - a hop cap bounds the supervisor loop so a model that never emits `finish` still terminates. main.py now builds the supervisor; graph/basic.py (create_react_agent) is retained as the simple graph and still owns the shared AgentResult / _stringify_content helpers the supervisor reuses. Tests: test_supervisor.py drives it end-to-end with the scripted model — single-worker route→tool→finish→synthesize, two-specialist routing, off-scope finish-without-worker, hop cap, plus _run_react and _to_text units. 109 Python tests, 93% coverage, ruff + mypy clean. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --- README.md | 4 +- insights-agent/README.md | 68 +++- .../src/insights_agent/graph/basic.py | 8 +- .../src/insights_agent/graph/supervisor.py | 293 ++++++++++++++++++ insights-agent/src/insights_agent/main.py | 7 +- insights-agent/tests/test_supervisor.py | 226 ++++++++++++++ 6 files changed, 581 insertions(+), 25 deletions(-) create mode 100644 insights-agent/src/insights_agent/graph/supervisor.py create mode 100644 insights-agent/tests/test_supervisor.py diff --git a/README.md b/README.md index 32800ab..7c85ed3 100644 --- a/README.md +++ b/README.md @@ -18,7 +18,7 @@ the data over HTTP, and answers in the user's language — surfacing the ```mermaid flowchart LR U([User]) -->|"How much did I spend on AWS?"| CLI[insights-agent CLI<br/>Python 3.12] - CLI --> G[LangGraph<br/>create_react_agent] + CLI --> G[LangGraph supervisor<br/>3 specialists + synthesize] G -->|"bind_tools"| LLM[Gemini 2.5 Flash] LLM -->|"HTTP tool call"| T[CloudOracle tools<br/>cost-summary / cost-by-service / recommendations / cost-trends / inventory] T -->|"GET /api/v1/* + X-API-Key"| GO[CloudOracle Go<br/>oracle serve] @@ -140,7 +140,7 @@ The synthetic provider needs no credentials. To run against AWS / GCP / Azure, s - [X] **Milestone 8.1** — Python `insights-agent` sibling: LangGraph `create_react_agent` graph with two CloudOracle tools, Gemini provider, pydantic-settings config, structlog matching the Go slog format, CLI with `--verbose` / `--json` flags, 92% test coverage with mocked LLM + mocked HTTP. See **[insights-agent/](insights-agent/README.md)** - [X] **Milestone 8.2** — Additional agent tools, each a new authenticated v1 endpoint: `GET /api/v1/recommendations` (rule-based savings, `data_source: heuristic_rules`), `GET /api/v1/cost-trends` (per-day series with precomputed change/direction), and `GET /api/v1/inventory` (resource counts + cost by provider/service, `data_source: live_inventory`) — wired as `cloudoracle_recommendations` / `cloudoracle_cost_trends` / `cloudoracle_inventory` tools. Agent now ships 5 tools - [X] **Milestone 8.3** — pgvector + RAG over a curated FinOps corpus: packaged markdown knowledge base, Gemini embeddings (mirroring the LLM-provider ABC), `langchain-postgres` PGVector store (compose image → `pgvector/pgvector:pg16`), `insights-agent-ingest` CLI, and a `finops_knowledge_search` tool the agent uses for conceptual/policy questions with source citations. Optional via `DATABASE_URL`; retrieval path unit-tested offline with an in-memory store -- [ ] **Milestone 8.4** — Hand-rolled supervisor (multi-agent), replacing `create_react_agent` +- [X] **Milestone 8.4** — Hand-rolled supervisor multi-agent graph replacing `create_react_agent`: a `StateGraph` where a tool-call-routing supervisor delegates to three specialist workers (cost analyst, savings advisor, concept expert — each its own hand-rolled ReAct loop) and a synthesizer composes the answer, with a hop cap. Driveable end-to-end by the scripted fake model; `create_react_agent` kept as the simple graph - [ ] **Milestone 8.5** — Production guardrails: cost caps, deterministic fallback, semantic answer validation, HTTP API surface - [ ] **Milestone 8.7** — Real billing / Cost Explorer integration replacing the snapshot approximation diff --git a/insights-agent/README.md b/insights-agent/README.md index eedd4fa..0b3e598 100644 --- a/insights-agent/README.md +++ b/insights-agent/README.md @@ -5,13 +5,17 @@ LangGraph-based FinOps insights agent for CloudOracle. Ask in natural language `/api/v1` calls against the CloudOracle Go server, then answers in the same language with the relevant caveats. -Built on `create_react_agent` from `langgraph.prebuilt`: single-turn agent (no -conversational memory), Gemini as the model. Five tools call the Go `/api/v1` -endpoints — two cost endpoints (milestone 8.1) plus savings recommendations, -cost trends, and a resource-inventory endpoint (milestone 8.2). A sixth tool, -`finops_knowledge_search`, does RAG over a curated FinOps corpus stored in -pgvector (milestone 8.3) for conceptual / policy / how-to questions. The next -milestone replaces the ReAct loop with a custom supervisor (8.4). +Single-turn agent (no conversational memory), Gemini as the model. Five tools +call the Go `/api/v1` endpoints — two cost endpoints (milestone 8.1) plus +savings recommendations, cost trends, and a resource-inventory endpoint +(milestone 8.2). A sixth tool, `finops_knowledge_search`, does RAG over a +curated FinOps corpus stored in pgvector (milestone 8.3) for conceptual / +policy / how-to questions. + +The default orchestration is a **hand-rolled supervisor** (milestone 8.4): a +`StateGraph` where a supervisor routes between three specialist workers and a +synthesizer composes the final answer — replacing `create_react_agent`. See +[Multi-agent supervisor](#multi-agent-supervisor). ## What it talks to @@ -60,6 +64,34 @@ pgvector-enabled Postgres (see [Knowledge base (RAG)](#knowledge-base-rag)). Without it the five HTTP tools still work — the agent just can't answer conceptual questions from the corpus. +## Multi-agent supervisor + +`graph/supervisor.py` is the default orchestration — a hand-rolled +`StateGraph`, not `create_react_agent`: + +``` +START → supervisor → {worker} → supervisor → … → synthesize → END +``` + +- **supervisor** routes by *tool call*: it's bound with one routing tool per + specialist plus `finish`, and the tool it calls names the next hop. (Routing + via tool calls — rather than `with_structured_output` — keeps the node + driveable by the scripted fake model the tests use.) +- **workers** are three specialists, each a hand-rolled ReAct loop + (`_run_react`, the actual `create_react_agent` replacement) over a tool + subset: + - `cost_analyst` → cost-summary / cost-by-service / cost-trends / inventory + - `savings_advisor` → recommendations + knowledge search + - `concept_expert` → knowledge search + A worker contributes one summarizing message back; its own tool churn stays + local so the supervisor and synthesizer see a clean transcript. +- **synthesize** composes the final answer from the specialists' findings, + in the user's language, with the data-source caveats and source citations. + +A hop cap (`MAX_HOPS`) bounds the supervisor loop so a model that never emits +`finish` still terminates. The simpler single-agent graph (`graph/basic.py`, +`create_react_agent`) is retained for tests and comparison. + ## Setup in under 10 minutes ### 1 — Prerequisites @@ -234,14 +266,16 @@ uv run mypy src/ # strict type-check uv run insights-agent-ingest # (needs DATABASE_URL) embed the FinOps corpus ``` -The tests never contact Gemini, a live Go server, or Postgres. -`tests/test_graph.py` ships a `ScriptedChatModel` (a `BaseChatModel` subclass) -that replays hand-written `AIMessage` sequences, and `pytest-httpx` mocks the -Go endpoints — together they let `create_react_agent` run its full ReAct loop -deterministically. The RAG layer is tested offline too: `tests/test_corpus.py` -checks chunking, and `tests/test_knowledge_tool.py` drives the real retrieval + -citation path through an `InMemoryVectorStore` + `DeterministicFakeEmbedding`, -so no pgvector or embeddings API is needed. +The tests never contact Gemini, a live Go server, or Postgres. A +`ScriptedChatModel` (a `BaseChatModel` subclass) replays hand-written +`AIMessage` sequences and `pytest-httpx` mocks the Go endpoints, so both graphs +run deterministically: `tests/test_graph.py` drives the simple +`create_react_agent` graph, and `tests/test_supervisor.py` drives the supervisor +end-to-end (route → worker tool call → finish → synthesize, plus the hop cap). +The RAG layer is tested offline too: `tests/test_corpus.py` checks chunking, and +`tests/test_knowledge_tool.py` drives the real retrieval + citation path through +an `InMemoryVectorStore` + `DeterministicFakeEmbedding`, so no pgvector or +embeddings API is needed. ### Architecture pointers @@ -250,14 +284,14 @@ so no pgvector or embeddings API is needed. | Vendor-agnostic LLM | `src/insights_agent/llm/base.py` + `gemini.py` | ABC + one implementation. Add `AnthropicProvider` / `OpenAIProvider` later by implementing `LLMProvider`; no graph changes required. | | Tools | `src/insights_agent/tools/cloudoracle.py` | `CloudOracleClient` owns the HTTP + auth + request-ID conventions; `build_tools(client)` wraps the five methods as `StructuredTool`s with rich docstrings so the LLM picks the right one. Errors flow as `ToolException` so the model sees them as observations and can recover instead of aborting the run. | | RAG | `src/insights_agent/rag/` + `tools/knowledge.py` | `corpus.py` loads + chunks the packaged markdown (offline-testable); `embeddings.py` mirrors the LLM-provider ABC for Gemini embeddings; `store.py` wraps pgvector; `ingest.py` is the `insights-agent-ingest` CLI; `knowledge.py` exposes `finops_knowledge_search`. Only wired in when `DATABASE_URL` is set. | -| Graph | `src/insights_agent/graph/basic.py` | `create_react_agent` from `langgraph.prebuilt` with a short system prompt. Milestone 8.4 replaces this with a hand-rolled supervisor. | +| Graph (default) | `src/insights_agent/graph/supervisor.py` | Hand-rolled `StateGraph`: tool-call-routing supervisor + three specialist workers (each a `_run_react` loop) + synthesizer, with a hop cap. The production path `main.py` wires. | +| Graph (simple) | `src/insights_agent/graph/basic.py` | `create_react_agent` single-agent graph. Retained for tests/comparison; `AgentResult` + `_stringify_content` live here and the supervisor reuses them. | | CLI | `src/insights_agent/main.py` | argparse, three flags, four exit codes, single async run. No conversational memory (each call is independent). | | Settings | `src/insights_agent/config.py` | `pydantic-settings.BaseSettings` — fail-fast `ValidationError` at startup if any required env var is missing. | | Logging | `src/insights_agent/logging.py` | `structlog` matching the Go side's `slog` output (text or JSON to stderr) so a tail of both streams reads coherently. | ### What is **not** here yet -- Custom supervisor / multi-agent (8.4) - Cost caps, semantic answer validation, deterministic fallback (8.5) - HTTP API surface for the agent — CLI only until 8.5 - Other LLM providers (Anthropic, OpenAI) diff --git a/insights-agent/src/insights_agent/graph/basic.py b/insights-agent/src/insights_agent/graph/basic.py index 9d1fa8c..aa14a69 100644 --- a/insights-agent/src/insights_agent/graph/basic.py +++ b/insights-agent/src/insights_agent/graph/basic.py @@ -1,8 +1,10 @@ """Basic ReAct graph: question → tool call(s) → natural-language answer. -Uses `langgraph.prebuilt.create_react_agent` for the first end-to-end -round-trip. Milestone 8.4 will replace this with a hand-rolled supervisor -pattern; until then, `create_react_agent` gives us: +The simple single-agent graph, built on `langgraph.prebuilt.create_react_agent`. +As of milestone 8.4 the production path uses the hand-rolled supervisor +(`graph/supervisor.py`) instead; this graph is retained for tests and +comparison, and it owns the shared `AgentResult` / `_stringify_content` helpers +the supervisor reuses. `create_react_agent` gives us: - A tool-aware LLM call (bind_tools is invoked under the hood). - A loop that runs tool calls until the LLM emits a final answer or hits diff --git a/insights-agent/src/insights_agent/graph/supervisor.py b/insights-agent/src/insights_agent/graph/supervisor.py new file mode 100644 index 0000000..2c8d13a --- /dev/null +++ b/insights-agent/src/insights_agent/graph/supervisor.py @@ -0,0 +1,293 @@ +"""Hand-rolled supervisor multi-agent graph (milestone 8.4). + +Replaces `create_react_agent` (graph/basic.py) with an explicit `StateGraph`: + + START → supervisor → {worker} → supervisor → … → synthesize → END + +- **supervisor** routes by *tool call*: it is bound with one routing tool per + specialist plus `finish`, and the tool it calls names the next hop. Routing + via tool calls (rather than `with_structured_output`) keeps the node driveable + by the same scripted fake model the rest of the suite uses, and mirrors how a + real LLM hands off control. +- **workers** are three specialists, each a *hand-rolled* ReAct loop + (`_run_react`) over a subset of the tools — this is the actual + create_react_agent replacement. A worker contributes a single summarizing + `AIMessage` back to the shared transcript; its own tool churn stays local so + the supervisor and synthesizer see a clean conversation. +- **synthesize** composes the final user-facing answer from the specialists' + findings. + +A hop cap bounds the supervisor loop so a model that never emits `finish` still +terminates. +""" + +from __future__ import annotations + +import json +import operator +from collections.abc import Sequence +from typing import Annotated, Any, TypedDict + +from langchain_core.language_models import BaseChatModel +from langchain_core.messages import ( + AIMessage, + BaseMessage, + HumanMessage, + SystemMessage, + ToolMessage, +) +from langchain_core.tools import BaseTool, StructuredTool +from langgraph.graph import END, START, StateGraph +from langgraph.graph.message import add_messages + +from insights_agent.graph.basic import AgentResult, _stringify_content + +# Worker identifiers double as graph node names and routing-tool names. +COST_ANALYST = "cost_analyst" +SAVINGS_ADVISOR = "savings_advisor" +CONCEPT_EXPERT = "concept_expert" +FINISH = "finish" + +WORKER_NAMES: tuple[str, ...] = (COST_ANALYST, SAVINGS_ADVISOR, CONCEPT_EXPERT) + +# Which tools (by name) each specialist may use. Names that aren't present in +# the supplied tool list are simply skipped — e.g. finops_knowledge_search is +# absent when RAG is disabled, leaving concept_expert to answer from the model. +WORKER_TOOLS: dict[str, frozenset[str]] = { + COST_ANALYST: frozenset( + { + "cloudoracle_cost_summary", + "cloudoracle_cost_by_service", + "cloudoracle_cost_trends", + "cloudoracle_inventory", + } + ), + SAVINGS_ADVISOR: frozenset( + {"cloudoracle_recommendations", "finops_knowledge_search"} + ), + CONCEPT_EXPERT: frozenset({"finops_knowledge_search"}), +} + +# Upper bound on supervisor decisions, so a model that never says `finish` +# still terminates. Three workers + a finish is the expected worst case; the +# cap sits above that as a safety net, not a normal path. +MAX_HOPS = 6 + +# Per-worker ReAct iterations (model call → tool calls → model call …). +MAX_WORKER_ITERS = 6 + + +class SupervisorState(TypedDict): + messages: Annotated[list[BaseMessage], add_messages] + tool_calls: Annotated[list[dict[str, Any]], operator.add] + route: str + hops: int + + +def build_supervisor_graph(llm: BaseChatModel, tools: Sequence[BaseTool]) -> Any: + """Compile the supervisor graph over `tools` (the same flat tool list).""" + tool_list = list(tools) + routing_tools = _build_routing_tools() + + async def supervisor(state: SupervisorState) -> dict[str, Any]: + router = llm.bind_tools(routing_tools) + resp = await router.ainvoke([SystemMessage(_SUPERVISOR_PROMPT), *state["messages"]]) + calls = getattr(resp, "tool_calls", None) or [] + route = calls[0]["name"] if calls else FINISH + return {"route": route, "hops": state["hops"] + 1} + + def decide(state: SupervisorState) -> str: + if state["hops"] > MAX_HOPS: + return "synthesize" + return state["route"] if state["route"] in WORKER_NAMES else "synthesize" + + async def synthesize(state: SupervisorState) -> dict[str, Any]: + resp = await llm.ainvoke([SystemMessage(_SYNTHESIZE_PROMPT), *state["messages"]]) + return {"messages": [resp]} + + graph = StateGraph(SupervisorState) + graph.add_node("supervisor", supervisor) + graph.add_node("synthesize", synthesize) + for name in WORKER_NAMES: + graph.add_node(name, _make_worker_node(llm, tool_list, name)) + + graph.add_edge(START, "supervisor") + graph.add_conditional_edges( + "supervisor", + decide, + {**{n: n for n in WORKER_NAMES}, "synthesize": "synthesize"}, + ) + for name in WORKER_NAMES: + graph.add_edge(name, "supervisor") + graph.add_edge("synthesize", END) + return graph.compile() + + +async def ask_supervisor(graph: Any, question: str) -> AgentResult: + """Run one question through the supervisor graph and return a compact result.""" + state: dict[str, Any] = await graph.ainvoke( + { + "messages": [HumanMessage(content=question)], + "tool_calls": [], + "route": "", + "hops": 0, + } + ) + + messages: list[Any] = state.get("messages", []) + answer = "" + for msg in messages: + if isinstance(msg, AIMessage): + content = _stringify_content(msg.content) + if content: + answer = content # last non-empty AI content = synthesizer output + return AgentResult( + answer=answer, + tool_calls=list(state.get("tool_calls", [])), + messages=messages, + ) + + +def _make_worker_node( + llm: BaseChatModel, tools: list[BaseTool], name: str +) -> Any: + system = _WORKER_PROMPTS[name] + worker_tools = [t for t in tools if t.name in WORKER_TOOLS[name]] + + async def node(state: SupervisorState) -> dict[str, Any]: + answer, calls = await _run_react(llm, worker_tools, system, state["messages"]) + contribution = AIMessage(content=answer or "(no findings)", name=name) + return {"messages": [contribution], "tool_calls": calls} + + return node + + +async def _run_react( + llm: BaseChatModel, + tools: list[BaseTool], + system_prompt: str, + conversation: Sequence[BaseMessage], +) -> tuple[str, list[dict[str, Any]]]: + """A minimal ReAct loop: the hand-rolled replacement for create_react_agent. + + Returns the worker's final text plus the ordered {name, args} tool calls it + made (for --verbose / assertions). Tools already convert their own errors to + observations (handle_tool_error=True), so a failed tool feeds the model a + message instead of aborting the loop. + """ + model = llm.bind_tools(tools) if tools else llm + by_name = {t.name: t for t in tools} + messages: list[BaseMessage] = [SystemMessage(system_prompt), *conversation] + collected: list[dict[str, Any]] = [] + + for _ in range(MAX_WORKER_ITERS): + ai = await model.ainvoke(messages) + messages.append(ai) + calls = getattr(ai, "tool_calls", None) or [] + if not calls: + return _stringify_content(ai.content), collected + + for call in calls: + collected.append({"name": call["name"], "args": call.get("args", {})}) + tool = by_name.get(call["name"]) + if tool is None: + observation: Any = f"error: unknown tool {call['name']!r}" + else: + observation = await tool.ainvoke(call.get("args", {})) + messages.append( + ToolMessage( + content=_to_text(observation), + tool_call_id=call.get("id", call["name"]), + name=call["name"], + ) + ) + + # Iteration budget exhausted — return whatever the last AI message said. + last = messages[-1] + return (_stringify_content(last.content) if isinstance(last, AIMessage) else ""), collected + + +def _to_text(value: Any) -> str: + if isinstance(value, str): + return value + try: + return json.dumps(value, ensure_ascii=False) + except (TypeError, ValueError): + return str(value) + + +def _noop() -> None: # pragma: no cover - routing tools are never executed + """Placeholder body for routing tools; the supervisor only reads their name.""" + + +def _build_routing_tools() -> list[StructuredTool]: + specs = { + COST_ANALYST: "Route to the cost & inventory analyst for spend totals, " + "per-service breakdowns, cost trends over time, or resource inventory.", + SAVINGS_ADVISOR: "Route to the savings advisor for optimization / " + "rightsizing recommendations and where money can be saved.", + CONCEPT_EXPERT: "Route to the FinOps concept expert for definitions, " + "policy, and how-to questions answered from the knowledge base.", + FINISH: "Call when the specialists have gathered enough to answer (or " + "the question is out of scope) — hands off to final synthesis.", + } + return [ + StructuredTool.from_function(func=_noop, name=name, description=desc) + for name, desc in specs.items() + ] + + +_SUPERVISOR_PROMPT = """You are the supervisor of CloudOracle's FinOps assistant. \ +You coordinate three specialists and decide who acts next by calling exactly one \ +routing tool: + +- cost_analyst — actual numbers: spend totals per provider, per-service \ +breakdowns, cost trends over time, resource inventory. +- savings_advisor — optimization & rightsizing recommendations ("where can I \ +save money?"). +- concept_expert — FinOps concepts, definitions, policy, how-to ("what is \ +rightsizing?", "should I buy reserved instances?"). + +Each call routes to one specialist who then reports back. When the gathered \ +findings are enough to answer the user — or the question is outside cloud \ +cost / FinOps scope — call `finish`. Don't route to a specialist whose findings \ +are already present. Call exactly one routing tool per turn.""" + + +_COST_ANALYST_PROMPT = """You are CloudOracle's cost & inventory analyst. Use the \ +cloudoracle_* tools to fetch real numbers — never invent or estimate costs \ +yourself. Report the figures you found concisely, and pass through the \ +`data_source` caveat (snapshots_approximation / live_inventory) so the final \ +answer can surface it. If a tool fails, say what you couldn't fetch.""" + +_SAVINGS_ADVISOR_PROMPT = """You are CloudOracle's savings advisor. Use \ +cloudoracle_recommendations to find optimization opportunities, and \ +finops_knowledge_search (if available) for the reasoning behind a \ +recommendation. Recommended savings are heuristic upper bounds \ +(data_source heuristic_rules) — note that they should be validated against \ +real usage. Report the opportunities and their rationale concisely.""" + +_CONCEPT_EXPERT_PROMPT = """You are CloudOracle's FinOps concept expert. Answer \ +conceptual / policy / how-to questions using finops_knowledge_search and cite \ +the sources it returns. If the knowledge base doesn't cover it (or isn't \ +available), say so rather than inventing FinOps guidance.""" + +_WORKER_PROMPTS: dict[str, str] = { + COST_ANALYST: _COST_ANALYST_PROMPT, + SAVINGS_ADVISOR: _SAVINGS_ADVISOR_PROMPT, + CONCEPT_EXPERT: _CONCEPT_EXPERT_PROMPT, +} + + +_SYNTHESIZE_PROMPT = """You are CloudOracle's FinOps assistant. Compose the final \ +answer for the user from the specialists' findings in the conversation above. + +- Reply in the same language the user used. +- Use only the findings provided; don't invent numbers or guidance. +- Surface the relevant data-source caveats: snapshot approximations aren't the \ +final bill; recommended savings are heuristic upper bounds to validate. +- When findings draw on the knowledge base, briefly cite the source. +- If the question is outside cloud cost / FinOps scope, politely decline and \ +explain what you do cover. + +Write the answer directly — no preamble about being a synthesizer.""" diff --git a/insights-agent/src/insights_agent/main.py b/insights-agent/src/insights_agent/main.py index b954811..f1a0a5f 100644 --- a/insights-agent/src/insights_agent/main.py +++ b/insights-agent/src/insights_agent/main.py @@ -28,7 +28,8 @@ from pydantic import ValidationError from insights_agent.config import Settings -from insights_agent.graph.basic import AgentResult, ask, build_graph +from insights_agent.graph.basic import AgentResult +from insights_agent.graph.supervisor import ask_supervisor, build_supervisor_graph from insights_agent.llm import GeminiProvider from insights_agent.logging import get_logger, setup from insights_agent.tools.cloudoracle import CloudOracleClient, build_tools @@ -124,8 +125,8 @@ async def _run(query: str, *, as_json: bool, verbose: bool) -> AgentResult: knowledge_tool = _maybe_build_knowledge_tool(settings, log) if knowledge_tool is not None: tools.append(knowledge_tool) - graph = build_graph(provider.get_chat_model(), tools) - result = await ask(graph, query) + graph = build_supervisor_graph(provider.get_chat_model(), tools) + result = await ask_supervisor(graph, query) if verbose and result.tool_calls: print("Tool calls made:", file=sys.stderr) diff --git a/insights-agent/tests/test_supervisor.py b/insights-agent/tests/test_supervisor.py new file mode 100644 index 0000000..ea2796f --- /dev/null +++ b/insights-agent/tests/test_supervisor.py @@ -0,0 +1,226 @@ +"""Tests for the hand-rolled supervisor graph (graph/supervisor.py). + +Driven by the same scripted-fake-model approach as test_graph.py: one shared +script is consumed in node-execution order — supervisor routes, workers run +their ReAct loop, supervisor routes again, then synthesize. No Gemini, no DB. +""" + +from __future__ import annotations + +from collections.abc import Sequence +from typing import Any + +import pytest +from langchain_core.callbacks import CallbackManagerForLLMRun +from langchain_core.embeddings import DeterministicFakeEmbedding +from langchain_core.language_models import BaseChatModel +from langchain_core.messages import AIMessage, BaseMessage +from langchain_core.outputs import ChatGeneration, ChatResult +from langchain_core.tools import BaseTool +from langchain_core.vectorstores import InMemoryVectorStore +from pydantic import Field +from pytest_httpx import HTTPXMock + +from insights_agent.graph import supervisor as sup +from insights_agent.graph.supervisor import ( + COST_ANALYST, + FINISH, + _run_react, + _to_text, + ask_supervisor, + build_supervisor_graph, +) +from insights_agent.rag.ingest import ingest_corpus +from insights_agent.rag.store import build_retriever +from insights_agent.tools.cloudoracle import CloudOracleClient, build_tools +from insights_agent.tools.knowledge import build_knowledge_tool + +BASE_URL = "http://localhost:8080" +API_KEY = "test-key" + +SUMMARY_PAYLOAD: dict[str, Any] = { + "period": {"start": "2026-04-01", "end": "2026-04-30"}, + "providers": {"aws": {"total_usd": 150.0, "currency": "USD"}}, + "grand_total_usd": 150.0, + "generated_at": "2026-05-18T12:00:00Z", + "data_source": "snapshots_approximation", + "note": "approximation note", +} + + +class ScriptedChatModel(BaseChatModel): + script: list[AIMessage] = Field(default_factory=list) + last_messages: list[BaseMessage] | None = None + + @property + def _llm_type(self) -> str: + return "scripted-test" + + def bind_tools(self, tools: Sequence[Any], **kwargs: Any) -> ScriptedChatModel: + return self + + def _generate( + self, + messages: list[BaseMessage], + stop: list[str] | None = None, + run_manager: CallbackManagerForLLMRun | None = None, + **kwargs: Any, + ) -> ChatResult: + self.last_messages = messages + if not self.script: + raise RuntimeError("ScriptedChatModel exhausted") + return ChatResult(generations=[ChatGeneration(message=self.script.pop(0))]) + + async def _agenerate( + self, + messages: list[BaseMessage], + stop: list[str] | None = None, + run_manager: Any = None, + **kwargs: Any, + ) -> ChatResult: + return self._generate(messages, stop, run_manager, **kwargs) + + +def _route(name: str) -> AIMessage: + return AIMessage(content="", tool_calls=[{"name": name, "args": {}, "id": f"r-{name}"}]) + + +def _call(name: str, args: dict[str, Any], cid: str = "c1") -> AIMessage: + return AIMessage(content="", tool_calls=[{"name": name, "args": args, "id": cid}]) + + +def _say(text: str) -> AIMessage: + return AIMessage(content=text) + + +@pytest.fixture +def client() -> CloudOracleClient: + return CloudOracleClient(base_url=BASE_URL, api_key=API_KEY, timeout_seconds=2.0) + + +def _knowledge_tool() -> BaseTool: + store = InMemoryVectorStore(DeterministicFakeEmbedding(size=64)) + ingest_corpus(store) + return build_knowledge_tool(build_retriever(store, k=2)) + + +async def test_routes_to_cost_analyst_then_synthesizes( + client: CloudOracleClient, httpx_mock: HTTPXMock +) -> None: + httpx_mock.add_response(json=SUMMARY_PAYLOAD) + model = ScriptedChatModel( + script=[ + _route(COST_ANALYST), + _call("cloudoracle_cost_summary", {"start": "2026-04-01", "end": "2026-04-30"}), + _say("Found ~$150 on AWS (snapshots_approximation)."), + _route(FINISH), + _say("You spent about $150 on AWS in April 2026 — a snapshot approximation, not the final bill."), + ] + ) + graph = build_supervisor_graph(model, build_tools(client)) + + result = await ask_supervisor(graph, "How much did I spend on AWS in April 2026?") + + assert [c["name"] for c in result.tool_calls] == ["cloudoracle_cost_summary"] + assert result.tool_calls[0]["args"] == {"start": "2026-04-01", "end": "2026-04-30"} + assert "$150" in result.answer + assert "snapshot" in result.answer.lower() + # The cost_analyst worker contributed a named message to the transcript. + assert any(getattr(m, "name", None) == COST_ANALYST for m in result.messages) + await client.aclose() + + +async def test_routes_across_two_specialists( + client: CloudOracleClient, httpx_mock: HTTPXMock +) -> None: + httpx_mock.add_response(json=SUMMARY_PAYLOAD) + tools = [*build_tools(client), _knowledge_tool()] + model = ScriptedChatModel( + script=[ + _route(COST_ANALYST), + _call("cloudoracle_cost_summary", {"start": "2026-04-01", "end": "2026-04-30"}), + _say("AWS ~$150 in April."), + _route("concept_expert"), + _call("finops_knowledge_search", {"query": "rightsizing"}), + _say("Rightsizing matches capacity to demand (per the rightsizing guide)."), + _route(FINISH), + _say("You spent ~$150 on AWS; rightsizing means matching capacity to demand."), + ] + ) + graph = build_supervisor_graph(model, tools) + + result = await ask_supervisor(graph, "What did I spend on AWS and what is rightsizing?") + + assert [c["name"] for c in result.tool_calls] == [ + "cloudoracle_cost_summary", + "finops_knowledge_search", + ] + assert "$150" in result.answer + assert "rightsizing" in result.answer.lower() + await client.aclose() + + +async def test_offscope_finishes_without_a_worker(client: CloudOracleClient) -> None: + model = ScriptedChatModel( + script=[ + _route(FINISH), + _say("I only help with cloud cost and FinOps questions."), + ] + ) + graph = build_supervisor_graph(model, build_tools(client)) + + result = await ask_supervisor(graph, "What's the weather today?") + + assert result.tool_calls == [] + assert "FinOps" in result.answer or "cloud cost" in result.answer + await client.aclose() + + +async def test_hop_cap_forces_synthesis( + client: CloudOracleClient, monkeypatch: pytest.MonkeyPatch +) -> None: + # Supervisor that never says finish: always routes to cost_analyst, whose + # worker answers without a tool. The hop cap must end the loop at synthesis. + monkeypatch.setattr(sup, "MAX_HOPS", 2) + model = ScriptedChatModel( + script=[ + _route(COST_ANALYST), + _say("partial 1"), + _route(COST_ANALYST), + _say("partial 2"), + _route(COST_ANALYST), # hops becomes 3 > 2 → decide() goes to synthesize + _say("final synthesized answer"), + ] + ) + graph = build_supervisor_graph(model, build_tools(client)) + + result = await ask_supervisor(graph, "loop forever?") + assert result.answer == "final synthesized answer" + await client.aclose() + + +class TestRunReact: + async def test_unknown_tool_becomes_observation(self) -> None: + model = ScriptedChatModel( + script=[_call("nope", {}), _say("done after observing the error")] + ) + answer, calls = await _run_react(model, [], "system", []) + assert answer == "done after observing the error" + assert calls == [{"name": "nope", "args": {}}] + + async def test_direct_answer_without_tools(self) -> None: + model = ScriptedChatModel(script=[_say("just an answer")]) + answer, calls = await _run_react(model, [], "system", []) + assert answer == "just an answer" + assert calls == [] + + +class TestToText: + def test_passthrough_string(self) -> None: + assert _to_text("hi") == "hi" + + def test_dict_to_json(self) -> None: + assert _to_text({"a": 1}) == '{"a": 1}' + + def test_non_serializable_falls_back_to_str(self) -> None: + assert _to_text({1, 2}) in ("{1, 2}", "{2, 1}") From b507c4e0f3d1c6e4b0535b58076558ab7e2150be Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jesus=20Nu=C3=B1ez?= <jesus.nunez2050@gmail.com> Date: Sat, 30 May 2026 19:30:44 -0400 Subject: [PATCH 15/18] feat(insights-agent): cost caps, layered validation, deterministic fallback (8.5) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Three of milestone 8.5's production guardrails, wrapping every run through guardrails/runner.py:run_guarded (the single entry point the CLI and the upcoming HTTP surface share): - Cost/usage caps: RunLimits (max_hops, max_tool_calls, max_worker_iters) from settings, threaded into the supervisor graph and the worker ReAct loop. When a cap is hit the supervisor stops dispatching and synthesizes from what it has, so a confused or injected loop can't run up unbounded LLM/tool cost. Workers now also surface their tool observations through the graph state. - Layered answer validation (guardrails/validation.py): deterministic grounding first — every monetary figure in the answer must match a number in the tool observations, an unmatched figure is a hard fail; then an optional LLM judge for a second opinion when the answer makes numeric claims that pass the deterministic layer. - Deterministic fallback (guardrails/fallback.py): on a run exception (quota, timeout) or a failed validation, return an honest no-LLM answer rendering the raw tool data (or stating nothing was retrieved) instead of a fabricated narrative or a raw traceback. config gains MAX_HOPS / MAX_TOOL_CALLS / MAX_WORKER_ITERS / ENABLE_ANSWER_VALIDATION / ENABLE_LLM_JUDGE; main wires run_guarded and the --json output now includes fallback_used + the validation verdict. Tests cover figure extraction, grounding (pass/fail/tolerance), the judge layers, fallback rendering, and run_guarded (happy / exception / invalid / disabled). 131 Python tests, 93% coverage, ruff + mypy clean. HTTP surface follows next. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --- insights-agent/.env.example | 11 ++ insights-agent/README.md | 30 +++ insights-agent/src/insights_agent/config.py | 19 ++ .../src/insights_agent/graph/basic.py | 4 + .../src/insights_agent/graph/supervisor.py | 105 +++++++--- .../src/insights_agent/guardrails/__init__.py | 24 +++ .../src/insights_agent/guardrails/fallback.py | 49 +++++ .../src/insights_agent/guardrails/runner.py | 88 +++++++++ .../insights_agent/guardrails/validation.py | 172 +++++++++++++++++ insights-agent/src/insights_agent/main.py | 37 +++- insights-agent/tests/conftest.py | 5 + insights-agent/tests/test_config.py | 29 +++ insights-agent/tests/test_guardrails.py | 180 ++++++++++++++++++ insights-agent/tests/test_supervisor.py | 43 ++++- 14 files changed, 756 insertions(+), 40 deletions(-) create mode 100644 insights-agent/src/insights_agent/guardrails/__init__.py create mode 100644 insights-agent/src/insights_agent/guardrails/fallback.py create mode 100644 insights-agent/src/insights_agent/guardrails/runner.py create mode 100644 insights-agent/src/insights_agent/guardrails/validation.py create mode 100644 insights-agent/tests/test_guardrails.py diff --git a/insights-agent/.env.example b/insights-agent/.env.example index 7cb8194..94a03af 100644 --- a/insights-agent/.env.example +++ b/insights-agent/.env.example @@ -33,3 +33,14 @@ EMBEDDINGS_MODEL=models/text-embedding-004 # pgvector collection name + how many chunks to retrieve per query. KNOWLEDGE_COLLECTION=finops_knowledge RAG_TOP_K=4 + +# --- Guardrails (milestone 8.5) --------------------------------------------- +# Cost/usage caps per query (safety nets, generous for real multi-step asks). +MAX_HOPS=6 # supervisor decisions before forced synthesis +MAX_TOOL_CALLS=8 # total tool calls across the run +MAX_WORKER_ITERS=6 # ReAct iterations within one specialist + +# Layered answer validation. Deterministic grounding always runs when enabled; +# the LLM judge adds a second opinion on answers that make numeric claims. +ENABLE_ANSWER_VALIDATION=true +ENABLE_LLM_JUDGE=true diff --git a/insights-agent/README.md b/insights-agent/README.md index 0b3e598..0644080 100644 --- a/insights-agent/README.md +++ b/insights-agent/README.md @@ -92,6 +92,30 @@ A hop cap (`MAX_HOPS`) bounds the supervisor loop so a model that never emits `finish` still terminates. The simpler single-agent graph (`graph/basic.py`, `create_react_agent`) is retained for tests and comparison. +## Guardrails + +Production guardrails (milestone 8.5) wrap every run via +`guardrails/runner.py:run_guarded`: + +- **Cost / usage caps** (`graph.supervisor.RunLimits`, from `MAX_*` env vars): + bound total tool calls, supervisor hops, and per-worker iterations. When a cap + is hit, the supervisor stops dispatching and synthesizes from what it has — a + confused or injected loop can't run up unbounded LLM/tool cost. +- **Layered answer validation** (`guardrails/validation.py`): + 1. *Deterministic grounding* — every monetary figure in the answer must match + (within tolerance) a number in the tool observations. An unmatched figure + is almost certainly fabricated → hard fail, no LLM needed. + 2. *LLM judge* — when the deterministic layer passes but the answer makes + numeric claims (so there's something to get subtly wrong), an optional + judge model gives a second opinion grounded in the observations. +- **Deterministic fallback** (`guardrails/fallback.py`): if the run throws + (quota, timeout) or validation rejects the answer, the user gets an honest, + no-LLM response that surfaces the raw tool data (or says nothing was + retrieved) instead of a fabricated narrative or a raw traceback. + +Toggle validation with `ENABLE_ANSWER_VALIDATION` / `ENABLE_LLM_JUDGE`. The +`--json` CLI output includes `fallback_used` and the `validation` verdict. + ## Setup in under 10 minutes ### 1 — Prerequisites @@ -134,6 +158,11 @@ Required env vars (loaded by `pydantic-settings`, fail-fast at startup): | `EMBEDDINGS_MODEL` | no | `models/text-embedding-004`| Gemini embeddings model (free tier) | | `KNOWLEDGE_COLLECTION` | no | `finops_knowledge` | pgvector collection name | | `RAG_TOP_K` | no | `4` | Chunks retrieved per knowledge query (1–20) | +| `MAX_HOPS` | no | `6` | Supervisor decisions before forced synthesis | +| `MAX_TOOL_CALLS` | no | `8` | Total tool calls per run (cost cap) | +| `MAX_WORKER_ITERS` | no | `6` | ReAct iterations within one specialist | +| `ENABLE_ANSWER_VALIDATION` | no | `true` | Run the layered answer validation | +| `ENABLE_LLM_JUDGE` | no | `true` | Add the LLM-judge layer on numeric answers | ### 4 — Run the CLI @@ -284,6 +313,7 @@ embeddings API is needed. | Vendor-agnostic LLM | `src/insights_agent/llm/base.py` + `gemini.py` | ABC + one implementation. Add `AnthropicProvider` / `OpenAIProvider` later by implementing `LLMProvider`; no graph changes required. | | Tools | `src/insights_agent/tools/cloudoracle.py` | `CloudOracleClient` owns the HTTP + auth + request-ID conventions; `build_tools(client)` wraps the five methods as `StructuredTool`s with rich docstrings so the LLM picks the right one. Errors flow as `ToolException` so the model sees them as observations and can recover instead of aborting the run. | | RAG | `src/insights_agent/rag/` + `tools/knowledge.py` | `corpus.py` loads + chunks the packaged markdown (offline-testable); `embeddings.py` mirrors the LLM-provider ABC for Gemini embeddings; `store.py` wraps pgvector; `ingest.py` is the `insights-agent-ingest` CLI; `knowledge.py` exposes `finops_knowledge_search`. Only wired in when `DATABASE_URL` is set. | +| Guardrails | `src/insights_agent/guardrails/` | `RunLimits` cost caps (in `graph/supervisor.py`); `validation.py` layered grounding + LLM judge; `fallback.py` no-LLM honest answer; `runner.py:run_guarded` ties run → validate → fallback. The single entry point the CLI and HTTP surface share. | | Graph (default) | `src/insights_agent/graph/supervisor.py` | Hand-rolled `StateGraph`: tool-call-routing supervisor + three specialist workers (each a `_run_react` loop) + synthesizer, with a hop cap. The production path `main.py` wires. | | Graph (simple) | `src/insights_agent/graph/basic.py` | `create_react_agent` single-agent graph. Retained for tests/comparison; `AgentResult` + `_stringify_content` live here and the supervisor reuses them. | | CLI | `src/insights_agent/main.py` | argparse, three flags, four exit codes, single async run. No conversational memory (each call is independent). | diff --git a/insights-agent/src/insights_agent/config.py b/insights-agent/src/insights_agent/config.py index 4897aaa..39e0446 100644 --- a/insights-agent/src/insights_agent/config.py +++ b/insights-agent/src/insights_agent/config.py @@ -11,6 +11,8 @@ from pydantic import Field, HttpUrl, field_validator from pydantic_settings import BaseSettings, SettingsConfigDict +from insights_agent.graph.supervisor import RunLimits + class Settings(BaseSettings): """Process-wide configuration. @@ -46,6 +48,23 @@ class Settings(BaseSettings): knowledge_collection: str = "finops_knowledge" rag_top_k: int = Field(default=4, ge=1, le=20) + # Guardrails (milestone 8.5). Cost caps bound the work per query; the + # validation toggles control the layered answer check. + max_hops: int = Field(default=6, ge=1, le=50) + max_tool_calls: int = Field(default=8, ge=1, le=100) + max_worker_iters: int = Field(default=6, ge=1, le=50) + enable_answer_validation: bool = True + enable_llm_judge: bool = True + + @property + def run_limits(self) -> RunLimits: + """Cost caps as the graph's RunLimits.""" + return RunLimits( + max_hops=self.max_hops, + max_tool_calls=self.max_tool_calls, + max_worker_iters=self.max_worker_iters, + ) + @field_validator("log_level") @classmethod def _normalize_log_level(cls, v: str) -> str: diff --git a/insights-agent/src/insights_agent/graph/basic.py b/insights-agent/src/insights_agent/graph/basic.py index aa14a69..aa534c5 100644 --- a/insights-agent/src/insights_agent/graph/basic.py +++ b/insights-agent/src/insights_agent/graph/basic.py @@ -65,6 +65,10 @@ class AgentResult: answer: str tool_calls: list[dict[str, Any]] = field(default_factory=list) messages: list[Any] = field(default_factory=list) + # Tool observations ({name, output}) gathered during the run. The supervisor + # graph populates these so the guardrails can ground the answer against what + # the tools actually returned. The simple graph leaves it empty. + observations: list[dict[str, Any]] = field(default_factory=list) def build_graph(llm: BaseChatModel, tools: Sequence[BaseTool]) -> Any: diff --git a/insights-agent/src/insights_agent/graph/supervisor.py b/insights-agent/src/insights_agent/graph/supervisor.py index 2c8d13a..33a248b 100644 --- a/insights-agent/src/insights_agent/graph/supervisor.py +++ b/insights-agent/src/insights_agent/graph/supervisor.py @@ -26,6 +26,7 @@ import json import operator from collections.abc import Sequence +from dataclasses import dataclass from typing import Annotated, Any, TypedDict from langchain_core.language_models import BaseChatModel @@ -68,23 +69,40 @@ CONCEPT_EXPERT: frozenset({"finops_knowledge_search"}), } -# Upper bound on supervisor decisions, so a model that never says `finish` -# still terminates. Three workers + a finish is the expected worst case; the -# cap sits above that as a safety net, not a normal path. -MAX_HOPS = 6 +# Cost / usage caps (milestone 8.5). These bound the work a single query can do +# so a confused model or a prompt-injected loop can't run up unbounded LLM / +# tool cost. Defaults are generous enough for legitimate multi-step questions +# and act as a safety net, not a normal path. +DEFAULT_MAX_HOPS = 6 # supervisor decisions before forced synthesis +DEFAULT_MAX_TOOL_CALLS = 8 # total tool calls across all workers in a run +DEFAULT_MAX_WORKER_ITERS = 6 # ReAct iterations within one worker -# Per-worker ReAct iterations (model call → tool calls → model call …). -MAX_WORKER_ITERS = 6 + +@dataclass(frozen=True) +class RunLimits: + """Per-run guardrail caps. Construct from Settings in the wiring code.""" + + max_hops: int = DEFAULT_MAX_HOPS + max_tool_calls: int = DEFAULT_MAX_TOOL_CALLS + max_worker_iters: int = DEFAULT_MAX_WORKER_ITERS + + +DEFAULT_LIMITS = RunLimits() class SupervisorState(TypedDict): messages: Annotated[list[BaseMessage], add_messages] tool_calls: Annotated[list[dict[str, Any]], operator.add] + observations: Annotated[list[dict[str, Any]], operator.add] route: str hops: int -def build_supervisor_graph(llm: BaseChatModel, tools: Sequence[BaseTool]) -> Any: +def build_supervisor_graph( + llm: BaseChatModel, + tools: Sequence[BaseTool], + limits: RunLimits = DEFAULT_LIMITS, +) -> Any: """Compile the supervisor graph over `tools` (the same flat tool list).""" tool_list = list(tools) routing_tools = _build_routing_tools() @@ -97,7 +115,12 @@ async def supervisor(state: SupervisorState) -> dict[str, Any]: return {"route": route, "hops": state["hops"] + 1} def decide(state: SupervisorState) -> str: - if state["hops"] > MAX_HOPS: + # Cost caps: stop dispatching once we've spent the hop or tool-call + # budget, regardless of what the supervisor wants — then synthesize + # from whatever was gathered so the user still gets a grounded answer. + if state["hops"] > limits.max_hops: + return "synthesize" + if len(state["tool_calls"]) >= limits.max_tool_calls: return "synthesize" return state["route"] if state["route"] in WORKER_NAMES else "synthesize" @@ -109,7 +132,7 @@ async def synthesize(state: SupervisorState) -> dict[str, Any]: graph.add_node("supervisor", supervisor) graph.add_node("synthesize", synthesize) for name in WORKER_NAMES: - graph.add_node(name, _make_worker_node(llm, tool_list, name)) + graph.add_node(name, _make_worker_node(llm, tool_list, name, limits)) graph.add_edge(START, "supervisor") graph.add_conditional_edges( @@ -129,6 +152,7 @@ async def ask_supervisor(graph: Any, question: str) -> AgentResult: { "messages": [HumanMessage(content=question)], "tool_calls": [], + "observations": [], "route": "", "hops": 0, } @@ -145,19 +169,33 @@ async def ask_supervisor(graph: Any, question: str) -> AgentResult: answer=answer, tool_calls=list(state.get("tool_calls", [])), messages=messages, + observations=list(state.get("observations", [])), ) def _make_worker_node( - llm: BaseChatModel, tools: list[BaseTool], name: str + llm: BaseChatModel, tools: list[BaseTool], name: str, limits: RunLimits ) -> Any: system = _WORKER_PROMPTS[name] worker_tools = [t for t in tools if t.name in WORKER_TOOLS[name]] async def node(state: SupervisorState) -> dict[str, Any]: - answer, calls = await _run_react(llm, worker_tools, system, state["messages"]) + # Don't exceed the run-wide tool-call budget across workers. + remaining = limits.max_tool_calls - len(state["tool_calls"]) + answer, calls, observations = await _run_react( + llm, + worker_tools, + system, + state["messages"], + max_iters=limits.max_worker_iters, + tool_budget=max(0, remaining), + ) contribution = AIMessage(content=answer or "(no findings)", name=name) - return {"messages": [contribution], "tool_calls": calls} + return { + "messages": [contribution], + "tool_calls": calls, + "observations": observations, + } return node @@ -167,33 +205,47 @@ async def _run_react( tools: list[BaseTool], system_prompt: str, conversation: Sequence[BaseMessage], -) -> tuple[str, list[dict[str, Any]]]: + *, + max_iters: int = DEFAULT_MAX_WORKER_ITERS, + tool_budget: int = DEFAULT_MAX_TOOL_CALLS, +) -> tuple[str, list[dict[str, Any]], list[dict[str, Any]]]: """A minimal ReAct loop: the hand-rolled replacement for create_react_agent. - Returns the worker's final text plus the ordered {name, args} tool calls it - made (for --verbose / assertions). Tools already convert their own errors to - observations (handle_tool_error=True), so a failed tool feeds the model a - message instead of aborting the loop. + Returns the worker's final text, the ordered {name, args} tool calls it made + (for --verbose / assertions), and the {name, output} observations (for answer + grounding). Tools convert their own errors to observations + (handle_tool_error=True), so a failed tool feeds the model a message instead + of aborting the loop. `tool_budget` caps how many tool calls this worker may + actually execute; beyond it the model is told to wrap up. """ model = llm.bind_tools(tools) if tools else llm by_name = {t.name: t for t in tools} messages: list[BaseMessage] = [SystemMessage(system_prompt), *conversation] - collected: list[dict[str, Any]] = [] + calls_made: list[dict[str, Any]] = [] + observations: list[dict[str, Any]] = [] - for _ in range(MAX_WORKER_ITERS): + for _ in range(max_iters): ai = await model.ainvoke(messages) messages.append(ai) calls = getattr(ai, "tool_calls", None) or [] if not calls: - return _stringify_content(ai.content), collected + return _stringify_content(ai.content), calls_made, observations for call in calls: - collected.append({"name": call["name"], "args": call.get("args", {})}) - tool = by_name.get(call["name"]) - if tool is None: - observation: Any = f"error: unknown tool {call['name']!r}" + calls_made.append({"name": call["name"], "args": call.get("args", {})}) + if len(calls_made) > tool_budget: + observation: Any = "tool budget reached; answer with what you have" else: - observation = await tool.ainvoke(call.get("args", {})) + tool = by_name.get(call["name"]) + if tool is None: + observation = f"error: unknown tool {call['name']!r}" + else: + observation = await tool.ainvoke(call.get("args", {})) + # Only real tool outputs are grounding evidence; unknown-tool + # and budget messages are control signals, not data. + observations.append( + {"name": call["name"], "output": _to_text(observation)} + ) messages.append( ToolMessage( content=_to_text(observation), @@ -204,7 +256,8 @@ async def _run_react( # Iteration budget exhausted — return whatever the last AI message said. last = messages[-1] - return (_stringify_content(last.content) if isinstance(last, AIMessage) else ""), collected + answer = _stringify_content(last.content) if isinstance(last, AIMessage) else "" + return answer, calls_made, observations def _to_text(value: Any) -> str: diff --git a/insights-agent/src/insights_agent/guardrails/__init__.py b/insights-agent/src/insights_agent/guardrails/__init__.py new file mode 100644 index 0000000..d6a0f70 --- /dev/null +++ b/insights-agent/src/insights_agent/guardrails/__init__.py @@ -0,0 +1,24 @@ +"""Production guardrails around the agent run (milestone 8.5). + +- cost/usage caps live with the graph (`graph.supervisor.RunLimits`). +- `validation` checks the answer is grounded in the tool observations + (deterministic number check, then an optional LLM judge). +- `fallback` renders a deterministic, no-LLM answer when the run fails or the + answer can't be verified. +- `runner.run_guarded` ties them together. +""" + +from insights_agent.guardrails.fallback import deterministic_answer +from insights_agent.guardrails.runner import GuardedResult, run_guarded +from insights_agent.guardrails.validation import ( + ValidationResult, + validate_answer, +) + +__all__ = [ + "GuardedResult", + "ValidationResult", + "deterministic_answer", + "run_guarded", + "validate_answer", +] diff --git a/insights-agent/src/insights_agent/guardrails/fallback.py b/insights-agent/src/insights_agent/guardrails/fallback.py new file mode 100644 index 0000000..ac0d618 --- /dev/null +++ b/insights-agent/src/insights_agent/guardrails/fallback.py @@ -0,0 +1,49 @@ +"""Deterministic, no-LLM fallback answer. + +Used when the LLM path fails (quota, timeout) or the answer fails validation. +The guiding principle is *honesty over fluency*: never fabricate a narrative. +Either hand the user the raw tool data they can verify, or tell them plainly +that nothing could be retrieved. +""" + +from __future__ import annotations + +# Cap a single observation's rendered length so the fallback stays readable +# even if a tool returned a large payload. +_MAX_OUTPUT_CHARS = 600 + + +def _truncate(text: str) -> str: + if len(text) <= _MAX_OUTPUT_CHARS: + return text + return text[:_MAX_OUTPUT_CHARS] + " …(truncated)" + + +def deterministic_answer( + question: str, + observations: list[dict[str, str]], + *, + reason: str, +) -> str: + """Render a safe answer from whatever grounded data the run produced.""" + lines = [ + "I couldn't return a verified answer to your question" + + (f' ("{question}")' if question else "") + + ".", + f"Reason: {reason}.", + ] + if observations: + lines.append("") + lines.append( + "Here is the raw data the tools returned, which you can verify directly:" + ) + for obs in observations: + name = obs.get("name", "tool") + output = _truncate(str(obs.get("output", ""))) + lines.append(f"- {name}: {output}") + else: + lines.append( + "No data was retrieved from CloudOracle. Check that the server is " + "reachable and your API key is correct, then try again." + ) + return "\n".join(lines) diff --git a/insights-agent/src/insights_agent/guardrails/runner.py b/insights-agent/src/insights_agent/guardrails/runner.py new file mode 100644 index 0000000..7206e1d --- /dev/null +++ b/insights-agent/src/insights_agent/guardrails/runner.py @@ -0,0 +1,88 @@ +"""Guarded agent run: orchestrate the graph, validation, and fallback. + +`run_guarded` is the single entry point the CLI and the HTTP surface both use, +so the guardrail policy lives in one place: + + 1. run the supervisor graph (cost caps enforced inside it); + 2. validate the answer against the tool observations (layered); + 3. on a run exception *or* a failed validation, replace the answer with a + deterministic, no-LLM fallback rendered from whatever data is available. +""" + +from __future__ import annotations + +from dataclasses import dataclass, field +from typing import Any + +from langchain_core.language_models import BaseChatModel + +from insights_agent.graph.supervisor import ask_supervisor +from insights_agent.guardrails.fallback import deterministic_answer +from insights_agent.guardrails.validation import ValidationResult, validate_answer + + +@dataclass +class GuardedResult: + """What the CLI / HTTP layer renders: the final (possibly fallback) answer + plus the metadata needed for --json output and observability.""" + + answer: str + tool_calls: list[dict[str, Any]] = field(default_factory=list) + observations: list[dict[str, Any]] = field(default_factory=list) + validation: ValidationResult | None = None + fallback_used: bool = False + error: str | None = None + + +async def run_guarded( + graph: Any, + question: str, + *, + validate: bool = True, + judge_model: BaseChatModel | None = None, +) -> GuardedResult: + """Run `question` through `graph` with validation + deterministic fallback. + + `judge_model` enables the LLM judge layer when supplied; pass None to use + only the deterministic grounding check. + """ + try: + result = await ask_supervisor(graph, question) + except Exception as e: # the run itself failed (quota, timeout, bug) + return GuardedResult( + answer=deterministic_answer( + question, [], reason=f"the assistant run failed ({e})" + ), + fallback_used=True, + error=str(e), + ) + + verdict: ValidationResult | None = None + if validate: + verdict = await validate_answer( + result.answer, + result.observations, + judge_model=judge_model, + question=question, + ) + if not verdict.valid: + return GuardedResult( + answer=deterministic_answer( + question, + result.observations, + reason=f"the answer failed {verdict.layer} validation " + f"({verdict.reason})", + ), + tool_calls=result.tool_calls, + observations=result.observations, + validation=verdict, + fallback_used=True, + ) + + return GuardedResult( + answer=result.answer, + tool_calls=result.tool_calls, + observations=result.observations, + validation=verdict, + fallback_used=False, + ) diff --git a/insights-agent/src/insights_agent/guardrails/validation.py b/insights-agent/src/insights_agent/guardrails/validation.py new file mode 100644 index 0000000..240c9e0 --- /dev/null +++ b/insights-agent/src/insights_agent/guardrails/validation.py @@ -0,0 +1,172 @@ +"""Layered semantic answer validation. + +Two layers, cheapest first: + +1. **Deterministic grounding.** Pull the monetary figures out of the answer and + confirm each appears (within tolerance) among the numbers in the tool + observations. A figure that matches nothing is almost certainly fabricated — + a hard fail, no LLM needed. + +2. **LLM judge.** When the deterministic layer passes *but the answer makes + numeric claims* (so there's something to get subtly wrong — wrong + attribution, wrong period, a real number used misleadingly), an optional + judge model gives a second opinion grounded in the observations. + +`validate_answer` orchestrates the two. The judge only runs when a model is +supplied and the deterministic layer both passed and found figures. +""" + +from __future__ import annotations + +import re +from dataclasses import dataclass, field + +from langchain_core.language_models import BaseChatModel +from langchain_core.messages import SystemMessage + +from insights_agent.graph.basic import _stringify_content + +# `$1,234.56`, `$150` — a currency-anchored amount. +_DOLLAR = re.compile(r"\$\s?(\d[\d,]*(?:\.\d+)?)") +# `1,234.56 USD`, `150 usd` — amount followed by the currency code. +_USD_SUFFIX = re.compile(r"(\d[\d,]*(?:\.\d+)?)\s?USD\b", re.IGNORECASE) +# Any number, for scanning the observation haystack. +_NUMBER = re.compile(r"\d[\d,]*(?:\.\d+)?") + + +def _to_float(raw: str) -> float | None: + try: + return float(raw.replace(",", "")) + except ValueError: # pragma: no cover - regex already constrains the input + return None + + +def extract_money_figures(text: str) -> list[float]: + """Distinct monetary figures stated in `text` (e.g. "$150", "200 USD").""" + seen: list[float] = [] + for pattern in (_DOLLAR, _USD_SUFFIX): + for match in pattern.findall(text): + value = _to_float(match) + if value is not None and value not in seen: + seen.append(value) + return seen + + +def _all_numbers(text: str) -> list[float]: + out: list[float] = [] + for raw in _NUMBER.findall(text): + value = _to_float(raw) + if value is not None: + out.append(value) + return out + + +def _is_grounded(figure: float, numbers: list[float]) -> bool: + # Tolerance absorbs rounding ("$150" vs 149.99): 1% of the figure, min 1 cent. + tol = max(0.01, abs(figure) * 0.01) + return any(abs(figure - n) <= tol for n in numbers) + + +@dataclass(frozen=True) +class GroundingResult: + grounded: bool + figures: list[float] = field(default_factory=list) + ungrounded: list[float] = field(default_factory=list) + + +def deterministic_grounding( + answer: str, observations: list[dict[str, str]] +) -> GroundingResult: + """Check every monetary figure in `answer` appears in the observations.""" + figures = extract_money_figures(answer) + if not figures: + return GroundingResult(grounded=True) + + haystack: list[float] = [] + for obs in observations: + haystack.extend(_all_numbers(str(obs.get("output", "")))) + + ungrounded = [f for f in figures if not _is_grounded(f, haystack)] + return GroundingResult( + grounded=not ungrounded, figures=figures, ungrounded=ungrounded + ) + + +@dataclass(frozen=True) +class ValidationResult: + """Outcome of validating an answer. `layer` is which check decided it.""" + + valid: bool + layer: str # "deterministic" | "judge" | "skipped" + reason: str = "" + + +def _fmt(values: list[float]) -> str: + return ", ".join(f"${v:,.2f}" for v in values) + + +async def validate_answer( + answer: str, + observations: list[dict[str, str]], + *, + judge_model: BaseChatModel | None = None, + question: str = "", +) -> ValidationResult: + """Run the deterministic check, then the LLM judge if warranted.""" + grounding = deterministic_grounding(answer, observations) + if not grounding.grounded: + return ValidationResult( + valid=False, + layer="deterministic", + reason=( + f"answer states {_fmt(grounding.ungrounded)} not found in any " + "tool result" + ), + ) + + # Deterministic layer passed. Escalate to the judge only when there are + # numeric claims to second-guess and a judge model is available. + if grounding.figures and judge_model is not None: + return await _judge(judge_model, question, answer, observations) + + return ValidationResult(valid=True, layer="deterministic") + + +async def _judge( + model: BaseChatModel, + question: str, + answer: str, + observations: list[dict[str, str]], +) -> ValidationResult: + obs_text = "\n".join( + f"- {o.get('name', '?')}: {o.get('output', '')}" for o in observations + ) or "(no tool observations)" + prompt = _JUDGE_PROMPT.format( + question=question or "(not provided)", answer=answer, observations=obs_text + ) + resp = await model.ainvoke([SystemMessage(prompt)]) + verdict = _stringify_content(resp.content).strip() + # Fail-open on an empty/garbled verdict (don't block a good answer on a + # malformed judge reply); only an explicit FAIL rejects. + if verdict.upper().startswith("FAIL"): + reason = verdict.split(":", 1)[1].strip() if ":" in verdict else "judge rejected the answer" + return ValidationResult(valid=False, layer="judge", reason=reason) + return ValidationResult(valid=True, layer="judge") + + +_JUDGE_PROMPT = """You are a strict FinOps answer validator. Decide whether every \ +factual and numeric claim in the assistant's answer is supported by the tool \ +observations below. Watch for fabricated numbers, wrong attribution (right \ +number, wrong provider/service/period), and claims with no supporting data. + +User question: +{question} + +Assistant answer: +{answer} + +Tool observations: +{observations} + +Reply with exactly "PASS" if every claim is supported, or "FAIL: <short reason>" \ +if any claim is unsupported or misleading.""" diff --git a/insights-agent/src/insights_agent/main.py b/insights-agent/src/insights_agent/main.py index f1a0a5f..554c1c8 100644 --- a/insights-agent/src/insights_agent/main.py +++ b/insights-agent/src/insights_agent/main.py @@ -28,8 +28,8 @@ from pydantic import ValidationError from insights_agent.config import Settings -from insights_agent.graph.basic import AgentResult -from insights_agent.graph.supervisor import ask_supervisor, build_supervisor_graph +from insights_agent.graph.supervisor import build_supervisor_graph +from insights_agent.guardrails.runner import GuardedResult, run_guarded from insights_agent.llm import GeminiProvider from insights_agent.logging import get_logger, setup from insights_agent.tools.cloudoracle import CloudOracleClient, build_tools @@ -98,7 +98,7 @@ def _maybe_build_knowledge_tool(settings: Settings, log: Any) -> BaseTool | None return build_knowledge_tool(retriever) -async def _run(query: str, *, as_json: bool, verbose: bool) -> AgentResult: +async def _run(query: str, *, as_json: bool, verbose: bool) -> GuardedResult: # pydantic-settings populates required fields from the environment; # mypy's call-arg check doesn't understand env-based construction # without the pydantic plugin, so we silence it locally. @@ -116,6 +116,7 @@ async def _run(query: str, *, as_json: bool, verbose: bool) -> AgentResult: api_key=settings.gemini_api_key, model=settings.gemini_model, ) + chat_model = provider.get_chat_model() async with CloudOracleClient( base_url=settings.cloudoracle_base_url, api_key=settings.cloudoracle_api_key, @@ -125,21 +126,45 @@ async def _run(query: str, *, as_json: bool, verbose: bool) -> AgentResult: knowledge_tool = _maybe_build_knowledge_tool(settings, log) if knowledge_tool is not None: tools.append(knowledge_tool) - graph = build_supervisor_graph(provider.get_chat_model(), tools) - result = await ask_supervisor(graph, query) + graph = build_supervisor_graph(chat_model, tools, settings.run_limits) + result = await run_guarded( + graph, + query, + validate=settings.enable_answer_validation, + judge_model=chat_model if settings.enable_llm_judge else None, + ) + if result.fallback_used: + log.warning("fallback_used", error=result.error, validation=_validation_dict(result)) if verbose and result.tool_calls: print("Tool calls made:", file=sys.stderr) for i, call in enumerate(result.tool_calls, 1): print(f" {i}. {call['name']}({call['args']})", file=sys.stderr) if as_json: - print(json.dumps({"answer": result.answer, "tool_calls": result.tool_calls}, ensure_ascii=False)) + print( + json.dumps( + { + "answer": result.answer, + "tool_calls": result.tool_calls, + "fallback_used": result.fallback_used, + "validation": _validation_dict(result), + }, + ensure_ascii=False, + ) + ) else: print(result.answer) return result +def _validation_dict(result: GuardedResult) -> dict[str, Any] | None: + v = result.validation + if v is None: + return None + return {"valid": v.valid, "layer": v.layer, "reason": v.reason} + + def cli_entrypoint(argv: list[str] | None = None) -> int: args = _build_arg_parser().parse_args(argv) try: diff --git a/insights-agent/tests/conftest.py b/insights-agent/tests/conftest.py index 6291db7..199e544 100644 --- a/insights-agent/tests/conftest.py +++ b/insights-agent/tests/conftest.py @@ -23,6 +23,11 @@ "EMBEDDINGS_MODEL", "KNOWLEDGE_COLLECTION", "RAG_TOP_K", + "MAX_HOPS", + "MAX_TOOL_CALLS", + "MAX_WORKER_ITERS", + "ENABLE_ANSWER_VALIDATION", + "ENABLE_LLM_JUDGE", ) diff --git a/insights-agent/tests/test_config.py b/insights-agent/tests/test_config.py index a2ca398..64eb0b4 100644 --- a/insights-agent/tests/test_config.py +++ b/insights-agent/tests/test_config.py @@ -96,3 +96,32 @@ def test_rag_top_k_out_of_range_rejected( monkeypatch.setenv("RAG_TOP_K", "0") with pytest.raises(ValidationError): Settings() + + +def test_guardrail_defaults_and_run_limits(valid_env: None) -> None: + s = Settings() + assert s.max_hops == 6 + assert s.max_tool_calls == 8 + assert s.max_worker_iters == 6 + assert s.enable_answer_validation is True + assert s.enable_llm_judge is True + limits = s.run_limits + assert (limits.max_hops, limits.max_tool_calls, limits.max_worker_iters) == (6, 8, 6) + + +def test_guardrail_caps_from_env( + valid_env: None, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("MAX_TOOL_CALLS", "3") + monkeypatch.setenv("ENABLE_LLM_JUDGE", "false") + s = Settings() + assert s.run_limits.max_tool_calls == 3 + assert s.enable_llm_judge is False + + +def test_max_hops_out_of_range_rejected( + valid_env: None, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("MAX_HOPS", "0") + with pytest.raises(ValidationError): + Settings() diff --git a/insights-agent/tests/test_guardrails.py b/insights-agent/tests/test_guardrails.py new file mode 100644 index 0000000..88649ca --- /dev/null +++ b/insights-agent/tests/test_guardrails.py @@ -0,0 +1,180 @@ +"""Guardrails: layered validation, deterministic fallback, guarded runner.""" + +from __future__ import annotations + +from typing import Any + +import pytest +from langchain_core.language_models import BaseChatModel +from langchain_core.messages import AIMessage, BaseMessage +from langchain_core.outputs import ChatGeneration, ChatResult + +from insights_agent.graph.basic import AgentResult +from insights_agent.guardrails import runner as runner_mod +from insights_agent.guardrails.fallback import deterministic_answer +from insights_agent.guardrails.runner import run_guarded +from insights_agent.guardrails.validation import ( + deterministic_grounding, + extract_money_figures, + validate_answer, +) + + +class _JudgeModel(BaseChatModel): + verdict: str = "PASS" + + @property + def _llm_type(self) -> str: + return "judge-fake" + + def _generate( + self, messages: list[BaseMessage], stop: list[str] | None = None, + run_manager: Any = None, **kwargs: Any, + ) -> ChatResult: + return ChatResult( + generations=[ChatGeneration(message=AIMessage(content=self.verdict))] + ) + + async def _agenerate( + self, messages: list[BaseMessage], stop: list[str] | None = None, + run_manager: Any = None, **kwargs: Any, + ) -> ChatResult: + return self._generate(messages) + + +def _obs(name: str, output: str) -> dict[str, str]: + return {"name": name, "output": output} + + +class TestExtractFigures: + def test_dollar_and_usd_forms(self) -> None: + figs = extract_money_figures("We spent $1,234.56 and 50 USD, plus $150.") + assert figs == [1234.56, 150.0, 50.0] + + def test_ignores_plain_numbers(self) -> None: + # Years / counts without a currency anchor are not money figures. + assert extract_money_figures("In 2026 you had 12 instances.") == [] + + +class TestDeterministicGrounding: + def test_grounded_when_figure_in_observations(self) -> None: + obs = [_obs("cloudoracle_cost_summary", '{"grand_total_usd": 150.0}')] + r = deterministic_grounding("You spent about $150 on AWS.", obs) + assert r.grounded and r.ungrounded == [] + + def test_ungrounded_figure_is_flagged(self) -> None: + obs = [_obs("cloudoracle_cost_summary", '{"grand_total_usd": 150.0}')] + r = deterministic_grounding("You spent $999 on AWS.", obs) + assert not r.grounded + assert r.ungrounded == [999.0] + + def test_no_figures_is_grounded(self) -> None: + r = deterministic_grounding("Rightsizing matches capacity to demand.", []) + assert r.grounded and r.figures == [] + + def test_rounding_tolerance(self) -> None: + obs = [_obs("t", '{"total_usd": 149.99}')] + assert deterministic_grounding("about $150", obs).grounded + + +class TestValidateAnswer: + async def test_ungrounded_fails_deterministically_without_judge(self) -> None: + judge = _JudgeModel(verdict="PASS") + obs = [_obs("t", '{"total_usd": 150.0}')] + res = await validate_answer("You spent $999.", obs, judge_model=judge) + assert not res.valid + assert res.layer == "deterministic" + assert "999" in res.reason + + async def test_grounded_with_figures_escalates_to_judge_pass(self) -> None: + judge = _JudgeModel(verdict="PASS") + obs = [_obs("t", '{"total_usd": 150.0}')] + res = await validate_answer("You spent $150.", obs, judge_model=judge) + assert res.valid and res.layer == "judge" + + async def test_grounded_with_figures_judge_fail(self) -> None: + judge = _JudgeModel(verdict="FAIL: the $150 is GCP, not AWS") + obs = [_obs("t", '{"total_usd": 150.0}')] + res = await validate_answer("You spent $150 on AWS.", obs, judge_model=judge) + assert not res.valid and res.layer == "judge" + assert "GCP" in res.reason + + async def test_no_judge_model_accepts_grounded(self) -> None: + obs = [_obs("t", '{"total_usd": 150.0}')] + res = await validate_answer("You spent $150.", obs, judge_model=None) + assert res.valid and res.layer == "deterministic" + + async def test_no_figures_skips_judge(self) -> None: + # Judge would fail, but with no numeric claims it's never consulted. + judge = _JudgeModel(verdict="FAIL: should not be called") + res = await validate_answer("Rightsizing matches capacity.", [], judge_model=judge) + assert res.valid and res.layer == "deterministic" + + +class TestFallback: + def test_renders_observations(self) -> None: + out = deterministic_answer( + "spend?", [_obs("cost", '{"grand_total_usd": 150.0}')], reason="run failed" + ) + assert "run failed" in out + assert "cost: " in out + assert "150" in out + + def test_no_observations_message(self) -> None: + out = deterministic_answer("spend?", [], reason="boom") + assert "No data was retrieved" in out + + def test_truncates_long_output(self) -> None: + out = deterministic_answer("q", [_obs("t", "x" * 2000)], reason="r") + assert "(truncated)" in out + + +class TestRunGuarded: + async def test_happy_path_no_fallback(self, monkeypatch: pytest.MonkeyPatch) -> None: + async def fake_ask(graph: Any, q: str) -> AgentResult: + return AgentResult( + answer="You spent $150 on AWS.", + tool_calls=[{"name": "cloudoracle_cost_summary", "args": {}}], + observations=[_obs("cloudoracle_cost_summary", '{"grand_total_usd": 150.0}')], + ) + + monkeypatch.setattr(runner_mod, "ask_supervisor", fake_ask) + result = await run_guarded(object(), "spend?", validate=True, judge_model=None) + assert not result.fallback_used + assert "$150" in result.answer + assert result.validation is not None and result.validation.valid + + async def test_exception_triggers_fallback(self, monkeypatch: pytest.MonkeyPatch) -> None: + async def boom(graph: Any, q: str) -> AgentResult: + raise RuntimeError("gemini quota exceeded") + + monkeypatch.setattr(runner_mod, "ask_supervisor", boom) + result = await run_guarded(object(), "spend?") + assert result.fallback_used + assert result.error is not None and "quota" in result.error + assert "couldn't return a verified answer" in result.answer + + async def test_invalid_answer_triggers_fallback(self, monkeypatch: pytest.MonkeyPatch) -> None: + async def fake_ask(graph: Any, q: str) -> AgentResult: + return AgentResult( + answer="You spent $999 on AWS.", # not in observations + tool_calls=[{"name": "cloudoracle_cost_summary", "args": {}}], + observations=[_obs("cloudoracle_cost_summary", '{"grand_total_usd": 150.0}')], + ) + + monkeypatch.setattr(runner_mod, "ask_supervisor", fake_ask) + result = await run_guarded(object(), "spend?", validate=True) + assert result.fallback_used + assert result.validation is not None and not result.validation.valid + # The honest fallback surfaces the real data ($150), not the bad claim. + assert "150" in result.answer + + async def test_validation_disabled_skips_checks(self, monkeypatch: pytest.MonkeyPatch) -> None: + async def fake_ask(graph: Any, q: str) -> AgentResult: + return AgentResult(answer="$999 ungrounded", observations=[]) + + monkeypatch.setattr(runner_mod, "ask_supervisor", fake_ask) + result = await run_guarded(object(), "q", validate=False) + assert not result.fallback_used + assert result.validation is None + assert result.answer == "$999 ungrounded" diff --git a/insights-agent/tests/test_supervisor.py b/insights-agent/tests/test_supervisor.py index ea2796f..53448af 100644 --- a/insights-agent/tests/test_supervisor.py +++ b/insights-agent/tests/test_supervisor.py @@ -21,10 +21,10 @@ from pydantic import Field from pytest_httpx import HTTPXMock -from insights_agent.graph import supervisor as sup from insights_agent.graph.supervisor import ( COST_ANALYST, FINISH, + RunLimits, _run_react, _to_text, ask_supervisor, @@ -176,12 +176,9 @@ async def test_offscope_finishes_without_a_worker(client: CloudOracleClient) -> await client.aclose() -async def test_hop_cap_forces_synthesis( - client: CloudOracleClient, monkeypatch: pytest.MonkeyPatch -) -> None: +async def test_hop_cap_forces_synthesis(client: CloudOracleClient) -> None: # Supervisor that never says finish: always routes to cost_analyst, whose # worker answers without a tool. The hop cap must end the loop at synthesis. - monkeypatch.setattr(sup, "MAX_HOPS", 2) model = ScriptedChatModel( script=[ _route(COST_ANALYST), @@ -192,27 +189,57 @@ async def test_hop_cap_forces_synthesis( _say("final synthesized answer"), ] ) - graph = build_supervisor_graph(model, build_tools(client)) + graph = build_supervisor_graph(model, build_tools(client), RunLimits(max_hops=2)) result = await ask_supervisor(graph, "loop forever?") assert result.answer == "final synthesized answer" await client.aclose() +async def test_tool_call_budget_forces_synthesis( + client: CloudOracleClient, httpx_mock: HTTPXMock +) -> None: + # max_tool_calls=1: after the cost_analyst makes one tool call, the + # supervisor must stop dispatching workers and synthesize. + httpx_mock.add_response(json=SUMMARY_PAYLOAD) + model = ScriptedChatModel( + script=[ + _route(COST_ANALYST), + _call("cloudoracle_cost_summary", {"start": "2026-04-01", "end": "2026-04-30"}), + _say("AWS ~$150."), + _route(COST_ANALYST), # supervisor wants more, but budget is spent + _say("final answer with $150"), # forced synthesis + ] + ) + graph = build_supervisor_graph( + model, build_tools(client), RunLimits(max_tool_calls=1) + ) + + result = await ask_supervisor(graph, "spend?") + assert len(result.tool_calls) == 1 + assert "$150" in result.answer + # The observation was captured for grounding. + assert result.observations and result.observations[0]["name"] == "cloudoracle_cost_summary" + await client.aclose() + + class TestRunReact: async def test_unknown_tool_becomes_observation(self) -> None: model = ScriptedChatModel( script=[_call("nope", {}), _say("done after observing the error")] ) - answer, calls = await _run_react(model, [], "system", []) + answer, calls, observations = await _run_react(model, [], "system", []) assert answer == "done after observing the error" assert calls == [{"name": "nope", "args": {}}] + # An unknown tool produces no grounded observation. + assert observations == [] async def test_direct_answer_without_tools(self) -> None: model = ScriptedChatModel(script=[_say("just an answer")]) - answer, calls = await _run_react(model, [], "system", []) + answer, calls, observations = await _run_react(model, [], "system", []) assert answer == "just an answer" assert calls == [] + assert observations == [] class TestToText: From c7a1d6f94409fbfcc67ac797daa4ee689860a48b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jesus=20Nu=C3=B1ez?= <jesus.nunez2050@gmail.com> Date: Sat, 30 May 2026 19:42:59 -0400 Subject: [PATCH 16/18] feat(insights-agent): FastAPI HTTP surface, completing milestone 8.5 Expose the agent over HTTP, sharing one runtime with the CLI: - runtime.py: GeminiAgentRunner assembles the model + client + tools + graph + run limits once and exposes ask() through the guardrails. The CLI (main.py) now uses it too, so the two entry points behave identically; the RAG knowledge-tool builder moved here from main. - api/app.py: FastAPI create_app with GET /health and POST /ask ({query} -> {answer, tool_calls, fallback_used, validation}). The stack is built once in the lifespan; optional X-API-Key auth via AGENT_API_KEY (same convention as the Go server). create_app(runner=...) injects a fake runner so the surface is testable without Gemini / a live Go server / Postgres. - api/serve.py: insights-agent-serve console script (uvicorn). - config gains AGENT_HOST / AGENT_PORT / AGENT_API_KEY. Tests drive the surface with FastAPI's TestClient and an injected fake runner: health, ask happy path + metadata, empty-query 422, fallback passthrough, auth enforced/open, and that an injected runner isn't closed by the app. 138 Python tests, 91% coverage, ruff + mypy clean. Milestone 8.5 complete: cost caps + layered validation + deterministic fallback + HTTP surface. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --- README.md | 2 +- insights-agent/.env.example | 7 ++ insights-agent/README.md | 34 ++++- insights-agent/pyproject.toml | 6 + .../src/insights_agent/api/__init__.py | 5 + insights-agent/src/insights_agent/api/app.py | 116 ++++++++++++++++++ .../src/insights_agent/api/serve.py | 28 +++++ insights-agent/src/insights_agent/config.py | 6 + insights-agent/src/insights_agent/main.py | 64 +--------- insights-agent/src/insights_agent/runtime.py | 92 ++++++++++++++ insights-agent/tests/conftest.py | 3 + insights-agent/tests/test_api.py | 100 +++++++++++++++ insights-agent/tests/test_main.py | 4 +- insights-agent/uv.lock | 67 ++++++++++ 14 files changed, 468 insertions(+), 66 deletions(-) create mode 100644 insights-agent/src/insights_agent/api/__init__.py create mode 100644 insights-agent/src/insights_agent/api/app.py create mode 100644 insights-agent/src/insights_agent/api/serve.py create mode 100644 insights-agent/src/insights_agent/runtime.py create mode 100644 insights-agent/tests/test_api.py diff --git a/README.md b/README.md index 7c85ed3..c72f222 100644 --- a/README.md +++ b/README.md @@ -141,7 +141,7 @@ The synthetic provider needs no credentials. To run against AWS / GCP / Azure, s - [X] **Milestone 8.2** — Additional agent tools, each a new authenticated v1 endpoint: `GET /api/v1/recommendations` (rule-based savings, `data_source: heuristic_rules`), `GET /api/v1/cost-trends` (per-day series with precomputed change/direction), and `GET /api/v1/inventory` (resource counts + cost by provider/service, `data_source: live_inventory`) — wired as `cloudoracle_recommendations` / `cloudoracle_cost_trends` / `cloudoracle_inventory` tools. Agent now ships 5 tools - [X] **Milestone 8.3** — pgvector + RAG over a curated FinOps corpus: packaged markdown knowledge base, Gemini embeddings (mirroring the LLM-provider ABC), `langchain-postgres` PGVector store (compose image → `pgvector/pgvector:pg16`), `insights-agent-ingest` CLI, and a `finops_knowledge_search` tool the agent uses for conceptual/policy questions with source citations. Optional via `DATABASE_URL`; retrieval path unit-tested offline with an in-memory store - [X] **Milestone 8.4** — Hand-rolled supervisor multi-agent graph replacing `create_react_agent`: a `StateGraph` where a tool-call-routing supervisor delegates to three specialist workers (cost analyst, savings advisor, concept expert — each its own hand-rolled ReAct loop) and a synthesizer composes the answer, with a hop cap. Driveable end-to-end by the scripted fake model; `create_react_agent` kept as the simple graph -- [ ] **Milestone 8.5** — Production guardrails: cost caps, deterministic fallback, semantic answer validation, HTTP API surface +- [X] **Milestone 8.5** — Production guardrails: per-run cost/usage caps (`RunLimits`); layered semantic answer validation (deterministic figure-grounding against tool observations, then an optional LLM judge); deterministic no-LLM fallback on run failure or failed validation; and a FastAPI HTTP surface (`POST /ask`, `GET /health`, optional `X-API-Key`) sharing one `GeminiAgentRunner` with the CLI - [ ] **Milestone 8.7** — Real billing / Cost Explorer integration replacing the snapshot approximation ### v2 — Terraform PR cost analysis diff --git a/insights-agent/.env.example b/insights-agent/.env.example index 94a03af..0870b3a 100644 --- a/insights-agent/.env.example +++ b/insights-agent/.env.example @@ -44,3 +44,10 @@ MAX_WORKER_ITERS=6 # ReAct iterations within one specialist # the LLM judge adds a second opinion on answers that make numeric claims. ENABLE_ANSWER_VALIDATION=true ENABLE_LLM_JUDGE=true + +# --- HTTP surface (insights-agent-serve) ------------------------------------ +AGENT_HOST=127.0.0.1 +AGENT_PORT=8099 +# When set, POST /ask requires this in an X-API-Key header. Leave empty for an +# open local endpoint. +AGENT_API_KEY= diff --git a/insights-agent/README.md b/insights-agent/README.md index 0644080..fe7018b 100644 --- a/insights-agent/README.md +++ b/insights-agent/README.md @@ -116,6 +116,31 @@ Production guardrails (milestone 8.5) wrap every run via Toggle validation with `ENABLE_ANSWER_VALIDATION` / `ENABLE_LLM_JUDGE`. The `--json` CLI output includes `fallback_used` and the `validation` verdict. +## HTTP surface + +Besides the CLI, the agent runs as an HTTP service (FastAPI) over the same +guarded pipeline — the CLI and the server share one `GeminiAgentRunner` +(`runtime.py`), so behavior is identical. + +```bash +uv run insights-agent-serve # binds AGENT_HOST:AGENT_PORT (default 127.0.0.1:8099) +``` + +| Method & path | Body | Response | +| ------------- | ---- | -------- | +| `GET /health` | — | `{"status": "ok"}` | +| `POST /ask` | `{"query": "..."}` | `{"answer", "tool_calls", "fallback_used", "validation"}` | + +```bash +curl -sS -X POST localhost:8099/ask \ + -H 'Content-Type: application/json' \ + -d '{"query": "How much did I spend on AWS in April 2026?"}' +``` + +Set `AGENT_API_KEY` to require an `X-API-Key` header on `POST /ask` (same +convention as the Go server); leave it empty for an open local endpoint. The +agent stack is built once in the FastAPI lifespan and reused across requests. + ## Setup in under 10 minutes ### 1 — Prerequisites @@ -163,6 +188,9 @@ Required env vars (loaded by `pydantic-settings`, fail-fast at startup): | `MAX_WORKER_ITERS` | no | `6` | ReAct iterations within one specialist | | `ENABLE_ANSWER_VALIDATION` | no | `true` | Run the layered answer validation | | `ENABLE_LLM_JUDGE` | no | `true` | Add the LLM-judge layer on numeric answers | +| `AGENT_HOST` | no | `127.0.0.1` | Bind host for `insights-agent-serve` | +| `AGENT_PORT` | no | `8099` | Bind port for the HTTP surface | +| `AGENT_API_KEY` | no | — | When set, `POST /ask` requires it in `X-API-Key` | ### 4 — Run the CLI @@ -314,7 +342,9 @@ embeddings API is needed. | Tools | `src/insights_agent/tools/cloudoracle.py` | `CloudOracleClient` owns the HTTP + auth + request-ID conventions; `build_tools(client)` wraps the five methods as `StructuredTool`s with rich docstrings so the LLM picks the right one. Errors flow as `ToolException` so the model sees them as observations and can recover instead of aborting the run. | | RAG | `src/insights_agent/rag/` + `tools/knowledge.py` | `corpus.py` loads + chunks the packaged markdown (offline-testable); `embeddings.py` mirrors the LLM-provider ABC for Gemini embeddings; `store.py` wraps pgvector; `ingest.py` is the `insights-agent-ingest` CLI; `knowledge.py` exposes `finops_knowledge_search`. Only wired in when `DATABASE_URL` is set. | | Guardrails | `src/insights_agent/guardrails/` | `RunLimits` cost caps (in `graph/supervisor.py`); `validation.py` layered grounding + LLM judge; `fallback.py` no-LLM honest answer; `runner.py:run_guarded` ties run → validate → fallback. The single entry point the CLI and HTTP surface share. | -| Graph (default) | `src/insights_agent/graph/supervisor.py` | Hand-rolled `StateGraph`: tool-call-routing supervisor + three specialist workers (each a `_run_react` loop) + synthesizer, with a hop cap. The production path `main.py` wires. | +| Runtime | `src/insights_agent/runtime.py` | `GeminiAgentRunner` assembles the model + client + tools + graph + limits once and exposes `ask()`. Shared by the CLI and HTTP so they behave identically. | +| HTTP surface | `src/insights_agent/api/` | `app.py` (FastAPI `create_app`, `GET /health`, `POST /ask`, optional `X-API-Key`); `serve.py` is the `insights-agent-serve` uvicorn entry. `create_app(runner=...)` injects a fake runner for offline tests. | +| Graph (default) | `src/insights_agent/graph/supervisor.py` | Hand-rolled `StateGraph`: tool-call-routing supervisor + three specialist workers (each a `_run_react` loop) + synthesizer, with a hop cap. Wired by `runtime.py`. | | Graph (simple) | `src/insights_agent/graph/basic.py` | `create_react_agent` single-agent graph. Retained for tests/comparison; `AgentResult` + `_stringify_content` live here and the supervisor reuses them. | | CLI | `src/insights_agent/main.py` | argparse, three flags, four exit codes, single async run. No conversational memory (each call is independent). | | Settings | `src/insights_agent/config.py` | `pydantic-settings.BaseSettings` — fail-fast `ValidationError` at startup if any required env var is missing. | @@ -322,8 +352,6 @@ embeddings API is needed. ### What is **not** here yet -- Cost caps, semantic answer validation, deterministic fallback (8.5) -- HTTP API surface for the agent — CLI only until 8.5 - Other LLM providers (Anthropic, OpenAI) - Streaming responses - Conversational memory across queries diff --git a/insights-agent/pyproject.toml b/insights-agent/pyproject.toml index b6fd1aa..7f4f941 100644 --- a/insights-agent/pyproject.toml +++ b/insights-agent/pyproject.toml @@ -18,6 +18,8 @@ dependencies = [ "httpx>=0.27.0", "structlog>=24.4.0", "python-dotenv>=1.0.1", + "fastapi>=0.115.0", + "uvicorn>=0.30.0", ] [project.optional-dependencies] @@ -33,6 +35,7 @@ dev = [ [project.scripts] insights-agent = "insights_agent.main:cli_entrypoint" insights-agent-ingest = "insights_agent.rag.ingest:ingest_entrypoint" +insights-agent-serve = "insights_agent.api.serve:serve_entrypoint" [build-system] requires = ["hatchling"] @@ -53,6 +56,8 @@ filterwarnings = [ # supervisor refactor in 8.4 replaces it. Silence the deprecation here # so the warning doesn't drown out real signal in the test output. "ignore::langgraph.warnings.LangGraphDeprecationWarning", + # Starlette's TestClient warns that it uses httpx; not actionable here. + "ignore:Using .httpx. with .starlette.testclient. is deprecated", ] [tool.coverage.run] @@ -106,5 +111,6 @@ module = [ "langchain_core.*", "langchain_postgres.*", "langchain_text_splitters.*", + "uvicorn.*", ] ignore_missing_imports = true diff --git a/insights-agent/src/insights_agent/api/__init__.py b/insights-agent/src/insights_agent/api/__init__.py new file mode 100644 index 0000000..e4c8200 --- /dev/null +++ b/insights-agent/src/insights_agent/api/__init__.py @@ -0,0 +1,5 @@ +"""HTTP surface for the insights agent (milestone 8.5).""" + +from insights_agent.api.app import create_app + +__all__ = ["create_app"] diff --git a/insights-agent/src/insights_agent/api/app.py b/insights-agent/src/insights_agent/api/app.py new file mode 100644 index 0000000..a7a19a1 --- /dev/null +++ b/insights-agent/src/insights_agent/api/app.py @@ -0,0 +1,116 @@ +"""FastAPI surface for the insights agent. + +A thin HTTP shell over the shared `GeminiAgentRunner` + guardrails: `POST /ask` +runs a query through the same guarded pipeline the CLI uses, `GET /health` is a +liveness probe. The agent stack is built once in the lifespan and reused across +requests. + +`create_app(runner=...)` injects a ready runner so the surface can be tested +without Gemini / a live Go server; production goes through the lifespan, which +builds a `GeminiAgentRunner` from settings and closes it on shutdown. +""" + +from __future__ import annotations + +from collections.abc import AsyncIterator +from contextlib import asynccontextmanager +from typing import Any, Protocol + +from fastapi import FastAPI, Header, HTTPException, Request +from pydantic import BaseModel, Field + +from insights_agent.config import Settings +from insights_agent.guardrails.runner import GuardedResult +from insights_agent.logging import get_logger, setup + + +class AgentRunner(Protocol): + """Minimal interface the HTTP layer needs from an agent runtime.""" + + async def ask(self, query: str) -> GuardedResult: ... + + async def aclose(self) -> None: ... + + +class AskRequest(BaseModel): + query: str = Field(min_length=1, max_length=4000) + + +class ValidationModel(BaseModel): + valid: bool + layer: str + reason: str = "" + + +class AskResponse(BaseModel): + answer: str + tool_calls: list[dict[str, Any]] = Field(default_factory=list) + fallback_used: bool = False + validation: ValidationModel | None = None + + +def _to_validation(result: GuardedResult) -> ValidationModel | None: + if result.validation is None: + return None + v = result.validation + return ValidationModel(valid=v.valid, layer=v.layer, reason=v.reason) + + +def create_app( + *, + runner: AgentRunner | None = None, + settings: Settings | None = None, +) -> FastAPI: + @asynccontextmanager + async def lifespan(app: FastAPI) -> AsyncIterator[None]: + if runner is not None: + # Injected runner (tests / embedding): we don't own its lifecycle. + app.state.runner = runner + app.state.api_key = settings.agent_api_key if settings else None + yield + return + + from insights_agent.runtime import GeminiAgentRunner + + resolved = settings or Settings() # type: ignore[call-arg] + setup(level=resolved.log_level, fmt=resolved.log_format) + log = get_logger("insights_agent.api") + log.info("api.starting", model=resolved.gemini_model) + built = GeminiAgentRunner(resolved, log) + app.state.runner = built + app.state.api_key = resolved.agent_api_key + try: + yield + finally: + await built.aclose() + + app = FastAPI( + title="CloudOracle Insights Agent", + version="0.1.0", + lifespan=lifespan, + ) + + @app.get("/health") + async def health() -> dict[str, str]: + return {"status": "ok"} + + @app.post("/ask", response_model=AskResponse) + async def ask( + body: AskRequest, + request: Request, + x_api_key: str | None = Header(default=None, alias="X-API-Key"), + ) -> AskResponse: + expected = getattr(request.app.state, "api_key", None) + if expected and x_api_key != expected: + raise HTTPException(status_code=401, detail="invalid or missing X-API-Key") + + agent: AgentRunner = request.app.state.runner + result = await agent.ask(body.query) + return AskResponse( + answer=result.answer, + tool_calls=result.tool_calls, + fallback_used=result.fallback_used, + validation=_to_validation(result), + ) + + return app diff --git a/insights-agent/src/insights_agent/api/serve.py b/insights-agent/src/insights_agent/api/serve.py new file mode 100644 index 0000000..9edfe2f --- /dev/null +++ b/insights-agent/src/insights_agent/api/serve.py @@ -0,0 +1,28 @@ +"""`insights-agent-serve` console script: run the HTTP surface with uvicorn.""" + +from __future__ import annotations + +import sys + +from insights_agent.api.app import create_app + + +def serve_entrypoint(argv: list[str] | None = None) -> int: # pragma: no cover + import uvicorn + from pydantic import ValidationError + + from insights_agent.config import Settings + + try: + settings = Settings() # type: ignore[call-arg] + except ValidationError as e: + print(f"Configuration error:\n{e}", file=sys.stderr) + return 2 + + app = create_app(settings=settings) + uvicorn.run(app, host=settings.agent_host, port=settings.agent_port) + return 0 + + +if __name__ == "__main__": # pragma: no cover + sys.exit(serve_entrypoint()) diff --git a/insights-agent/src/insights_agent/config.py b/insights-agent/src/insights_agent/config.py index 39e0446..2917757 100644 --- a/insights-agent/src/insights_agent/config.py +++ b/insights-agent/src/insights_agent/config.py @@ -56,6 +56,12 @@ class Settings(BaseSettings): enable_answer_validation: bool = True enable_llm_judge: bool = True + # HTTP surface (milestone 8.5). agent_api_key, when set, gates POST /ask + # behind an X-API-Key header (same convention as the Go server). + agent_host: str = "127.0.0.1" + agent_port: int = Field(default=8099, ge=1, le=65535) + agent_api_key: str | None = None + @property def run_limits(self) -> RunLimits: """Cost caps as the graph's RunLimits.""" diff --git a/insights-agent/src/insights_agent/main.py b/insights-agent/src/insights_agent/main.py index 554c1c8..fa27ab7 100644 --- a/insights-agent/src/insights_agent/main.py +++ b/insights-agent/src/insights_agent/main.py @@ -24,15 +24,12 @@ import sys from typing import Any -from langchain_core.tools import BaseTool from pydantic import ValidationError from insights_agent.config import Settings -from insights_agent.graph.supervisor import build_supervisor_graph -from insights_agent.guardrails.runner import GuardedResult, run_guarded -from insights_agent.llm import GeminiProvider +from insights_agent.guardrails.runner import GuardedResult from insights_agent.logging import get_logger, setup -from insights_agent.tools.cloudoracle import CloudOracleClient, build_tools +from insights_agent.runtime import GeminiAgentRunner EXIT_OK = 0 EXIT_RUNTIME = 1 @@ -64,40 +61,6 @@ def _build_arg_parser() -> argparse.ArgumentParser: return p -def _maybe_build_knowledge_tool(settings: Settings, log: Any) -> BaseTool | None: - """Build the RAG knowledge tool when a pgvector DB is configured. - - Returns None (and logs why) when database_url is unset, so the agent runs - with just the cost/inventory/recommendation tools and no DB dependency. - Imports are deferred so the heavier RAG/db stack is only loaded when used. - """ - if not settings.database_url: - log.info("rag.disabled", reason="database_url not set") - return None - - from insights_agent.rag.embeddings import GeminiEmbeddingsProvider - from insights_agent.rag.store import build_retriever, build_vector_store - from insights_agent.tools.knowledge import build_knowledge_tool - - embeddings = GeminiEmbeddingsProvider( - api_key=settings.gemini_api_key, - model=settings.embeddings_model, - ).get_embeddings() - store = build_vector_store( - connection=settings.database_url, - embeddings=embeddings, - collection=settings.knowledge_collection, - ) - retriever = build_retriever(store, k=settings.rag_top_k) - log.info( - "rag.enabled", - collection=settings.knowledge_collection, - embeddings_model=settings.embeddings_model, - top_k=settings.rag_top_k, - ) - return build_knowledge_tool(retriever) - - async def _run(query: str, *, as_json: bool, verbose: bool) -> GuardedResult: # pydantic-settings populates required fields from the environment; # mypy's call-arg check doesn't understand env-based construction @@ -112,27 +75,8 @@ async def _run(query: str, *, as_json: bool, verbose: bool) -> GuardedResult: base_url=settings.cloudoracle_base_url, ) - provider = GeminiProvider( - api_key=settings.gemini_api_key, - model=settings.gemini_model, - ) - chat_model = provider.get_chat_model() - async with CloudOracleClient( - base_url=settings.cloudoracle_base_url, - api_key=settings.cloudoracle_api_key, - timeout_seconds=settings.http_timeout_seconds, - ) as client: - tools: list[BaseTool] = list(build_tools(client)) - knowledge_tool = _maybe_build_knowledge_tool(settings, log) - if knowledge_tool is not None: - tools.append(knowledge_tool) - graph = build_supervisor_graph(chat_model, tools, settings.run_limits) - result = await run_guarded( - graph, - query, - validate=settings.enable_answer_validation, - judge_model=chat_model if settings.enable_llm_judge else None, - ) + async with GeminiAgentRunner(settings, log) as runner: + result = await runner.ask(query) if result.fallback_used: log.warning("fallback_used", error=result.error, validation=_validation_dict(result)) diff --git a/insights-agent/src/insights_agent/runtime.py b/insights-agent/src/insights_agent/runtime.py new file mode 100644 index 0000000..08e77ae --- /dev/null +++ b/insights-agent/src/insights_agent/runtime.py @@ -0,0 +1,92 @@ +"""Shared agent runtime used by both the CLI and the HTTP surface. + +`GeminiAgentRunner` assembles the whole stack once — Gemini model, HTTP client, +tools (incl. the optional RAG tool), the supervisor graph and the run limits — +and exposes a single `ask()` that runs a query through the guardrails. Centralizing +it here keeps `main.py` (CLI) and `api/app.py` (HTTP) thin and identical in +behavior. +""" + +from __future__ import annotations + +from typing import Any + +from langchain_core.tools import BaseTool + +from insights_agent.config import Settings +from insights_agent.graph.supervisor import build_supervisor_graph +from insights_agent.guardrails.runner import GuardedResult, run_guarded +from insights_agent.llm import GeminiProvider +from insights_agent.tools.cloudoracle import CloudOracleClient, build_tools + + +def maybe_build_knowledge_tool(settings: Settings, log: Any) -> BaseTool | None: + """Build the RAG knowledge tool when a pgvector DB is configured. + + Returns None (and logs why) when database_url is unset, so the agent runs + with just the cost/inventory/recommendation tools and no DB dependency. + Imports are deferred so the heavier RAG/db stack is only loaded when used. + """ + if not settings.database_url: + log.info("rag.disabled", reason="database_url not set") + return None + + from insights_agent.rag.embeddings import GeminiEmbeddingsProvider + from insights_agent.rag.store import build_retriever, build_vector_store + from insights_agent.tools.knowledge import build_knowledge_tool + + embeddings = GeminiEmbeddingsProvider( + api_key=settings.gemini_api_key, + model=settings.embeddings_model, + ).get_embeddings() + store = build_vector_store( + connection=settings.database_url, + embeddings=embeddings, + collection=settings.knowledge_collection, + ) + retriever = build_retriever(store, k=settings.rag_top_k) + log.info( + "rag.enabled", + collection=settings.knowledge_collection, + embeddings_model=settings.embeddings_model, + top_k=settings.rag_top_k, + ) + return build_knowledge_tool(retriever) + + +class GeminiAgentRunner: + """Owns the assembled agent and runs guarded queries. Async-closeable.""" + + def __init__(self, settings: Settings, log: Any) -> None: + self._settings = settings + self._chat = GeminiProvider( + api_key=settings.gemini_api_key, + model=settings.gemini_model, + ).get_chat_model() + self._client = CloudOracleClient( + base_url=settings.cloudoracle_base_url, + api_key=settings.cloudoracle_api_key, + timeout_seconds=settings.http_timeout_seconds, + ) + tools: list[BaseTool] = list(build_tools(self._client)) + knowledge_tool = maybe_build_knowledge_tool(settings, log) + if knowledge_tool is not None: + tools.append(knowledge_tool) + self._graph = build_supervisor_graph(self._chat, tools, settings.run_limits) + + async def ask(self, query: str) -> GuardedResult: + return await run_guarded( + self._graph, + query, + validate=self._settings.enable_answer_validation, + judge_model=self._chat if self._settings.enable_llm_judge else None, + ) + + async def aclose(self) -> None: + await self._client.aclose() + + async def __aenter__(self) -> GeminiAgentRunner: + return self + + async def __aexit__(self, *_: object) -> None: + await self.aclose() diff --git a/insights-agent/tests/conftest.py b/insights-agent/tests/conftest.py index 199e544..7c25b3f 100644 --- a/insights-agent/tests/conftest.py +++ b/insights-agent/tests/conftest.py @@ -28,6 +28,9 @@ "MAX_WORKER_ITERS", "ENABLE_ANSWER_VALIDATION", "ENABLE_LLM_JUDGE", + "AGENT_HOST", + "AGENT_PORT", + "AGENT_API_KEY", ) diff --git a/insights-agent/tests/test_api.py b/insights-agent/tests/test_api.py new file mode 100644 index 0000000..75d31c2 --- /dev/null +++ b/insights-agent/tests/test_api.py @@ -0,0 +1,100 @@ +"""HTTP surface tests — an injected fake runner, no Gemini / Go server / DB.""" + +from __future__ import annotations + +import pytest +from fastapi.testclient import TestClient + +from insights_agent.api.app import create_app +from insights_agent.config import Settings +from insights_agent.guardrails.runner import GuardedResult +from insights_agent.guardrails.validation import ValidationResult + + +class FakeRunner: + def __init__(self, result: GuardedResult) -> None: + self._result = result + self.queries: list[str] = [] + self.closed = False + + async def ask(self, query: str) -> GuardedResult: + self.queries.append(query) + return self._result + + async def aclose(self) -> None: + self.closed = True + + +def _ok_result() -> GuardedResult: + return GuardedResult( + answer="You spent $150 on AWS.", + tool_calls=[{"name": "cloudoracle_cost_summary", "args": {"start": "x", "end": "y"}}], + observations=[{"name": "cloudoracle_cost_summary", "output": "{}"}], + validation=ValidationResult(valid=True, layer="deterministic"), + fallback_used=False, + ) + + +def test_health() -> None: + with TestClient(create_app(runner=FakeRunner(_ok_result()))) as c: + r = c.get("/health") + assert r.status_code == 200 + assert r.json() == {"status": "ok"} + + +def test_ask_returns_answer_and_metadata() -> None: + runner = FakeRunner(_ok_result()) + with TestClient(create_app(runner=runner)) as c: + r = c.post("/ask", json={"query": "How much did I spend on AWS?"}) + assert r.status_code == 200 + body = r.json() + assert body["answer"] == "You spent $150 on AWS." + assert body["tool_calls"][0]["name"] == "cloudoracle_cost_summary" + assert body["fallback_used"] is False + assert body["validation"] == {"valid": True, "layer": "deterministic", "reason": ""} + assert runner.queries == ["How much did I spend on AWS?"] + + +def test_ask_rejects_empty_query() -> None: + with TestClient(create_app(runner=FakeRunner(_ok_result()))) as c: + r = c.post("/ask", json={"query": ""}) + assert r.status_code == 422 # pydantic min_length + + +def test_ask_passes_through_fallback() -> None: + result = GuardedResult(answer="couldn't verify", fallback_used=True, error="boom") + with TestClient(create_app(runner=FakeRunner(result))) as c: + r = c.post("/ask", json={"query": "x"}) + body = r.json() + assert body["fallback_used"] is True + assert body["validation"] is None + + +def test_no_auth_required_when_key_unset() -> None: + # settings is None → api_key None → open endpoint. + with TestClient(create_app(runner=FakeRunner(_ok_result()))) as c: + assert c.post("/ask", json={"query": "x"}).status_code == 200 + + +def test_auth_enforced_when_key_set( + valid_env: None, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("AGENT_API_KEY", "s3cret") + settings = Settings() + runner = FakeRunner(_ok_result()) + with TestClient(create_app(runner=runner, settings=settings)) as c: + assert c.post("/ask", json={"query": "x"}).status_code == 401 + assert c.post( + "/ask", json={"query": "x"}, headers={"X-API-Key": "wrong"} + ).status_code == 401 + ok = c.post("/ask", json={"query": "x"}, headers={"X-API-Key": "s3cret"}) + assert ok.status_code == 200 + assert ok.json()["answer"] == "You spent $150 on AWS." + + +def test_injected_runner_not_closed_by_app() -> None: + # The app must not close a runner it didn't build (the injector owns it). + runner = FakeRunner(_ok_result()) + with TestClient(create_app(runner=runner)) as c: + c.get("/health") + assert runner.closed is False diff --git a/insights-agent/tests/test_main.py b/insights-agent/tests/test_main.py index 8274c5f..fa4b55e 100644 --- a/insights-agent/tests/test_main.py +++ b/insights-agent/tests/test_main.py @@ -19,9 +19,9 @@ EXIT_OK, EXIT_RUNTIME, _build_arg_parser, - _maybe_build_knowledge_tool, cli_entrypoint, ) +from insights_agent.runtime import maybe_build_knowledge_tool def test_arg_parser_requires_query() -> None: @@ -119,7 +119,7 @@ def test_knowledge_tool_disabled_without_database_url(valid_env: None) -> None: # the agent runs with just the cost/inventory/recommendation tools. settings = Settings() log = _SpyLog() - tool = _maybe_build_knowledge_tool(settings, log) + tool = maybe_build_knowledge_tool(settings, log) assert tool is None assert "rag.disabled" in log.events diff --git a/insights-agent/uv.lock b/insights-agent/uv.lock index 0e110d7..4d458bf 100644 --- a/insights-agent/uv.lock +++ b/insights-agent/uv.lock @@ -2,6 +2,15 @@ version = 1 revision = 3 requires-python = "==3.12.*" +[[package]] +name = "annotated-doc" +version = "0.0.4" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/57/ba/046ceea27344560984e26a590f90bc7f4a75b06701f653222458922b558c/annotated_doc-0.0.4.tar.gz", hash = "sha256:fbcda96e87e9c92ad167c2e53839e57503ecfda18804ea28102353485033faa4", size = 7288, upload-time = "2025-11-10T22:07:42.062Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/1e/d3/26bf1008eb3d2daa8ef4cacc7f3bfdc11818d111f7e2d0201bc6e3b49d45/annotated_doc-0.0.4-py3-none-any.whl", hash = "sha256:571ac1dc6991c450b25a9c2d84a3705e2ae7a53467b5d111c24fa8baabbed320", size = 5303, upload-time = "2025-11-10T22:07:40.673Z" }, +] + [[package]] name = "annotated-types" version = "0.7.0" @@ -121,6 +130,18 @@ 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"sha256:e487fae93ad408e6f47641ee4dfe389864fd7bec92e547ea8498fc13f43e83ab", size = 396410, upload-time = "2026-05-23T18:53:15.192Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/e0/82/45359b62a067409bd929ae8a56b8ed13e5a8c8a61194b3c236920999ab83/fastapi-0.136.3-py3-none-any.whl", hash = "sha256:3d2a69bdf04b7e9f3afa292c3bc7a98816bbfafa10bc9b45f3f3700d2f761620", size = 117481, upload-time = "2026-05-23T18:53:16.924Z" }, +] + [[package]] name = "filetype" version = "1.2.0" @@ -328,6 +365,7 @@ name = "insights-agent" version = "0.1.0" source = { editable = "." } dependencies = [ + { name = "fastapi" }, { name = "httpx" }, { name = "langchain-core" }, { name = "langchain-google-genai" }, @@ -338,6 +376,7 @@ dependencies = [ { name = "pydantic-settings" }, { name = "python-dotenv" }, { name = "structlog" }, + { name = "uvicorn" }, ] [package.optional-dependencies] @@ -352,6 +391,7 @@ dev = [ [package.metadata] requires-dist = [ + { name = "fastapi", specifier = ">=0.115.0" }, { name = "httpx", specifier = ">=0.27.0" }, { name = "langchain-core", specifier = ">=0.3.20" }, { name = "langchain-google-genai", specifier = ">=2.0.0" }, @@ -368,6 +408,7 @@ requires-dist = [ { name = "python-dotenv", specifier = ">=1.0.1" }, { name = "ruff", marker = "extra == 'dev'", specifier = ">=0.7.0" }, { name = "structlog", specifier = ">=24.4.0" }, + { name = "uvicorn", specifier = ">=0.30.0" }, ] provides-extras = ["dev"] @@ -1011,6 +1052,19 @@ asyncio = [ { name = "greenlet" }, ] +[[package]] +name = "starlette" +version = "1.2.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "anyio" }, + { name = "typing-extensions" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/c5/bf/616a066c2760f6c2b1ae3437cc28149734d069fbb46511712beae118a68c/starlette-1.2.0.tar.gz", hash = "sha256:3c5a6b23fff42492914e93890bb80cbfea72dbf37de268eec06185d62a4ca553", size = 2668923, upload-time = "2026-05-28T11:42:50.568Z" } +wheels = [ + { url = 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"sha256:a5504207195d08c2511bf9125ede5ac4a4b71725d519e758d01dcf0bc2d31c37", size = 91074, upload-time = "2026-05-24T12:08:41.925Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/01/be/72532be3da7acc5fdfbccdb95215cd04f995a0886532a5b423f929cda4cc/uvicorn-0.48.0-py3-none-any.whl", hash = "sha256:48097851328b87ec36117d3d575234519eb58c2b22d79666e9bbc6c49a761dad", size = 71410, upload-time = "2026-05-24T12:08:40.258Z" }, +] + [[package]] name = "websockets" version = "16.0" From 5f47f418e33c878b67d558248066622b73827cbe Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jesus=20Nu=C3=B1ez?= <jesus.nunez2050@gmail.com> Date: Sat, 30 May 2026 20:15:29 -0400 Subject: [PATCH 17/18] feat(billing): AWS Cost Explorer source behind a billing.Source abstraction (8.7) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Replace the hard-wired snapshot cost path in the v1 endpoints with a billing.Source interface so a real billing integration can be swapped in by config, starting with AWS Cost Explorer. - internal/billing: CostRecord / Report / Source / SourceError, and CostExplorerSource — a GetCostAndUsage query grouped by SERVICE over the period (CE's exclusive end handled), summed across time buckets and pages, returning real unblended cost with data_source "billing_aws_cost_explorer". The CE client is narrowed to an injectable interface (mocked in tests), the same pattern internal/cloud uses for EC2/RDS. - internal/api: snapshotSource implements billing.Source over the existing cost_snapshots aggregation (preserves data_source "snapshots_approximation" and the snapshot_query_failed code exactly). The cost-summary / cost-by-service handlers now group normalized records and echo the report's dynamic data_source; the snapshot-specific aggregateByProvider/ByService helpers are gone. Server gains a WithBillingSource option (default snapshots). - config: CLOUDORACLE_BILLING_PROVIDER (snapshots | aws_cost_explorer). cmd builds the CE source from AWS_REGION/AWS_PROFILE when selected and falls back to snapshots (loudly) if init fails. Tests: CE source (bucket/page summation, exclusive-end TimePeriod, error wrapping, missing-metric skip) with a fake client; api handlers against an injected non-snapshot source (dynamic data_source, provider filter, error code). Existing snapshot cost tests pass unchanged. The agent's FinOps corpus documents the new real-billing data source. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --- README.md | 4 +- cmd/oracle/main.go | 17 +- docs/configuration.md | 1 + go.mod | 9 +- go.sum | 10 + .../knowledge/data-sources-and-caveats.md | 17 +- internal/api/billing_source_test.go | 129 ++++++++++++ internal/api/cost_handlers.go | 88 ++++---- internal/api/server.go | 28 ++- internal/api/snapshot_source.go | 60 ++++++ internal/billing/billing.go | 47 +++++ internal/billing/cost_explorer.go | 147 ++++++++++++++ internal/billing/cost_explorer_test.go | 188 ++++++++++++++++++ internal/config/config.go | 19 +- 14 files changed, 694 insertions(+), 70 deletions(-) create mode 100644 internal/api/billing_source_test.go create mode 100644 internal/api/snapshot_source.go create mode 100644 internal/billing/billing.go create mode 100644 internal/billing/cost_explorer.go create mode 100644 internal/billing/cost_explorer_test.go diff --git a/README.md b/README.md index c72f222..5bb1efd 100644 --- a/README.md +++ b/README.md @@ -23,7 +23,7 @@ flowchart LR LLM -->|"HTTP tool call"| T[CloudOracle tools<br/>cost-summary / cost-by-service / recommendations / cost-trends / inventory] T -->|"GET /api/v1/* + X-API-Key"| GO[CloudOracle Go<br/>oracle serve] GO -->|"SQL"| DB[(PostgreSQL<br/>cost_snapshots)] - GO -->|"data_source: snapshots_approximation / heuristic_rules"| T + GO -->|"data_source: snapshots_approximation / billing_aws_cost_explorer / heuristic_rules"| T LLM -->|"knowledge tool call"| R[finops_knowledge_search<br/>RAG] R -->|"similarity search"| VDB[(pgvector<br/>finops_knowledge)] T --> LLM @@ -142,7 +142,7 @@ The synthetic provider needs no credentials. To run against AWS / GCP / Azure, s - [X] **Milestone 8.3** — pgvector + RAG over a curated FinOps corpus: packaged markdown knowledge base, Gemini embeddings (mirroring the LLM-provider ABC), `langchain-postgres` PGVector store (compose image → `pgvector/pgvector:pg16`), `insights-agent-ingest` CLI, and a `finops_knowledge_search` tool the agent uses for conceptual/policy questions with source citations. Optional via `DATABASE_URL`; retrieval path unit-tested offline with an in-memory store - [X] **Milestone 8.4** — Hand-rolled supervisor multi-agent graph replacing `create_react_agent`: a `StateGraph` where a tool-call-routing supervisor delegates to three specialist workers (cost analyst, savings advisor, concept expert — each its own hand-rolled ReAct loop) and a synthesizer composes the answer, with a hop cap. Driveable end-to-end by the scripted fake model; `create_react_agent` kept as the simple graph - [X] **Milestone 8.5** — Production guardrails: per-run cost/usage caps (`RunLimits`); layered semantic answer validation (deterministic figure-grounding against tool observations, then an optional LLM judge); deterministic no-LLM fallback on run failure or failed validation; and a FastAPI HTTP surface (`POST /ask`, `GET /health`, optional `X-API-Key`) sharing one `GeminiAgentRunner` with the CLI -- [ ] **Milestone 8.7** — Real billing / Cost Explorer integration replacing the snapshot approximation +- [X] **Milestone 8.7** — Real billing integration behind a `billing.Source` abstraction: the v1 cost endpoints now consume normalized cost records, with the snapshot approximation as the default source and an **AWS Cost Explorer** source (real unblended cost, `data_source: billing_aws_cost_explorer`) selectable via `CLOUDORACLE_BILLING_PROVIDER=aws_cost_explorer`. GCP (BigQuery export) and Azure (Cost Management) sources can plug into the same interface next ### v2 — Terraform PR cost analysis diff --git a/cmd/oracle/main.go b/cmd/oracle/main.go index faeb32f..1b9ff7d 100644 --- a/cmd/oracle/main.go +++ b/cmd/oracle/main.go @@ -3,6 +3,7 @@ package main import ( "CloudOracle/internal/analyzer" "CloudOracle/internal/api" + "CloudOracle/internal/billing" "CloudOracle/internal/cloud" "CloudOracle/internal/config" "CloudOracle/internal/db" @@ -697,7 +698,21 @@ func runServe(ctx context.Context, pool *db.Pool, cfg config.Config, args []stri runCtx, stop := signal.NotifyContext(ctx, os.Interrupt, syscall.SIGTERM) defer stop() - server := api.NewServer(pool, cfg.API) + var serverOpts []api.ServerOption + if cfg.API.BillingProvider == config.BillingAWSCostExplorer { + src, err := billing.NewAWSCostExplorerSource(runCtx, cfg.Cloud.AWSRegion, cfg.Cloud.AWSProfile) + if err != nil { + // Don't fail startup over a billing-source problem: fall back to the + // snapshot approximation so the API still serves, and make the + // degradation loud. + slog.Warn("falling back to snapshot cost source: AWS Cost Explorer init failed", "error", err) + } else { + slog.Info("v1 cost endpoints using AWS Cost Explorer (real billed cost)") + serverOpts = append(serverOpts, api.WithBillingSource(src)) + } + } + + server := api.NewServer(pool, cfg.API, serverOpts...) slog.Info("Dashboard available", "url", fmt.Sprintf("http://localhost:%s", *port)) if err := server.Run(runCtx, ":"+*port, cfg.API.ShutdownTimeout); err != nil { slog.Error("API server failed", "error", err) diff --git a/docs/configuration.md b/docs/configuration.md index 5aa4c19..fc5c030 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -12,6 +12,7 @@ Reference for every environment variable CloudOracle reads. All vars are loaded | `SYNTHETIC_COUNT` | `100` | Default number of synthetic resources to generate | | `SYNTHETIC_ACCOUNT` | `synthetic-account` | Default account ID for synthetic data | | `CLOUD_SERVICE_TIMEOUT` | `30s` | Per-service timeout for each cloud API call (Go duration string) | +| `CLOUDORACLE_BILLING_PROVIDER` | `snapshots` | Cost source for the v1 endpoints: `snapshots` (the projected-cost approximation) or `aws_cost_explorer` (real AWS unblended cost via the Cost Explorer API; uses `AWS_REGION`/`AWS_PROFILE`). On init failure it logs and falls back to `snapshots`. | | `DB_HOST` | `localhost` | PostgreSQL host | | `DB_PORT` | `5432` | PostgreSQL port | | `DB_USER` | `oracle` | Database user | diff --git a/go.mod b/go.mod index dd9b7a9..3b6ae0d 100644 --- a/go.mod +++ b/go.mod @@ -37,19 +37,20 @@ require ( github.com/Azure/go-ansiterm v0.0.0-20250102033503-faa5f7b0171c // indirect github.com/AzureAD/microsoft-authentication-library-for-go v1.6.0 // indirect github.com/Microsoft/go-winio v0.6.2 // indirect - github.com/aws/aws-sdk-go-v2 v1.41.7 // indirect + github.com/aws/aws-sdk-go-v2 v1.41.9 // indirect github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.7.9 // indirect github.com/aws/aws-sdk-go-v2/credentials v1.19.16 // indirect github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.18.23 // indirect - github.com/aws/aws-sdk-go-v2/internal/configsources v1.4.23 // indirect - github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.23 // indirect + github.com/aws/aws-sdk-go-v2/internal/configsources v1.4.25 // indirect + github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.25 // indirect github.com/aws/aws-sdk-go-v2/internal/v4a v1.4.24 // indirect + github.com/aws/aws-sdk-go-v2/service/costexplorer v1.63.10 // indirect github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.13.9 // indirect github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.13.23 // indirect github.com/aws/aws-sdk-go-v2/service/signin v1.0.11 // indirect github.com/aws/aws-sdk-go-v2/service/sso v1.30.17 // indirect github.com/aws/aws-sdk-go-v2/service/ssooidc v1.35.21 // indirect - github.com/aws/smithy-go v1.25.1 // indirect + github.com/aws/smithy-go v1.26.0 // indirect github.com/cenkalti/backoff/v4 v4.3.0 // indirect github.com/cespare/xxhash/v2 v2.3.0 // indirect github.com/containerd/errdefs v1.0.0 // indirect diff --git a/go.sum b/go.sum index 2dba1e7..46d7e9d 100644 --- a/go.sum +++ b/go.sum @@ -48,6 +48,8 @@ github.com/Microsoft/go-winio v0.6.2 h1:F2VQgta7ecxGYO8k3ZZz3RS8fVIXVxONVUPlNERo github.com/Microsoft/go-winio v0.6.2/go.mod h1:yd8OoFMLzJbo9gZq8j5qaps8bJ9aShtEA8Ipt1oGCvU= github.com/aws/aws-sdk-go-v2 v1.41.7 h1:DWpAJt66FmnnaRIOT/8ASTucrvuDPZASqhhLey6tLY8= github.com/aws/aws-sdk-go-v2 v1.41.7/go.mod h1:4LAfZOPHNVNQEckOACQx60Y8pSRjIkNZQz1w92xpMJc= +github.com/aws/aws-sdk-go-v2 v1.41.9 h1:/rYeyO2+HrMztAmxAq9++XJtFMqSIpSsNA0yDGALYq4= +github.com/aws/aws-sdk-go-v2 v1.41.9/go.mod h1:+HsoOEX80qAVUitj1A2DhCNTjmb3edVyuDypb6LNEeo= github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.7.9 h1:adBsCIIpLbLmYnkQU+nAChU5yhVTvu5PerROm+/Kq2A= github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.7.9/go.mod h1:uOYhgfgThm/ZyAuJGNQ5YgNyOlYfqnGpTHXvk3cpykg= github.com/aws/aws-sdk-go-v2/config v1.32.17 h1:FpL4/758/diKwqbytU0prpuiu60fgXKUWCpDJtApclU= @@ -58,10 +60,16 @@ github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.18.23 h1:UuSfcORqNSz/ey3VPRS8Tc github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.18.23/go.mod h1:+G/OSGiOFnSOkYloKj/9M35s74LgVAdJBSD5lsFfqKg= github.com/aws/aws-sdk-go-v2/internal/configsources v1.4.23 h1:GpT/TrnBYuE5gan2cZbTtvP+JlHsutdmlV2YfEyNde0= github.com/aws/aws-sdk-go-v2/internal/configsources v1.4.23/go.mod h1:xYWD6BS9ywC5bS3sz9Xh04whO/hzK2plt2Zkyrp4JuA= +github.com/aws/aws-sdk-go-v2/internal/configsources v1.4.25 h1:Uii3frf9ztec/ABM2/FSH9/z7PLzxfpG8h4RpkUFflQ= +github.com/aws/aws-sdk-go-v2/internal/configsources v1.4.25/go.mod h1:G6kntsA2GorAxDPbap6xgB2F+amSLUF8GJTi7PUoX44= github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.23 h1:bpd8vxhlQi2r1hiueOw02f/duEPTMK59Q4QMAoTTtTo= github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.23/go.mod h1:15DfR2nw+CRHIk0tqNyifu3G1YdAOy68RftkhMDDwYk= +github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.25 h1:r1+/l6m+WaUJF9HISEsNOLHSNj5EXYQxK8VX6Cz9NlA= +github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.25/go.mod h1:cKf+D+NMDK1LndD7BowHbBZPgR9V0/5HubH0PFWvA+c= github.com/aws/aws-sdk-go-v2/internal/v4a v1.4.24 h1:OQqn11BtaYv1WLUowvcA30MpzIu8Ti4pcLPIIyoKZrA= github.com/aws/aws-sdk-go-v2/internal/v4a v1.4.24/go.mod h1:X5ZJyfwVrWA96GzPmUCWFQaEARPR7gCrpq2E92PJwAE= +github.com/aws/aws-sdk-go-v2/service/costexplorer v1.63.10 h1:qfocR9B2YCHsYUBhMxKtR9FvX8STK2TgSW7medHNYUY= +github.com/aws/aws-sdk-go-v2/service/costexplorer v1.63.10/go.mod h1:HXoUaVgUrJ0tUcx7kwIjtN7rNoRsceWcBSCVmzGcaQU= github.com/aws/aws-sdk-go-v2/service/ec2 v1.297.0 h1:A+7NViqbMUCoTQFWjbSXdbzE4K5Ziu2zWJtZzAusm+A= github.com/aws/aws-sdk-go-v2/service/ec2 v1.297.0/go.mod h1:R+2BNtUfTfhPY0RH18oL02q116bakeBWjanrbnVBqkM= github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.13.9 h1:FLudkZLt5ci0ozzgkVo8BJGwvqNaZbTWb3UcucAateA= @@ -84,6 +92,8 @@ github.com/aws/aws-sdk-go-v2/service/sts v1.42.1 h1:F/M5Y9I3nwr2IEpshZgh1GeHpOIt github.com/aws/aws-sdk-go-v2/service/sts v1.42.1/go.mod h1:mTNxImtovCOEEuD65mKW7DCsL+2gjEH+RPEAexAzAio= github.com/aws/smithy-go v1.25.1 h1:J8ERsGSU7d+aCmdQur5Txg6bVoYelvQJgtZehD12GkI= github.com/aws/smithy-go v1.25.1/go.mod h1:YE2RhdIuDbA5E5bTdciG9KrW3+TiEONeUWCqxX9i1Fc= +github.com/aws/smithy-go v1.26.0 h1:9ouqbi+NyKP7fV3Te7UElCwdAb6Y8uk7LGwPE5tVe/s= +github.com/aws/smithy-go v1.26.0/go.mod h1:YE2RhdIuDbA5E5bTdciG9KrW3+TiEONeUWCqxX9i1Fc= github.com/cenkalti/backoff/v4 v4.3.0 h1:MyRJ/UdXutAwSAT+s3wNd7MfTIcy71VQueUuFK343L8= github.com/cenkalti/backoff/v4 v4.3.0/go.mod h1:Y3VNntkOUPxTVeUxJ/G5vcM//AlwfmyYozVcomhLiZE= github.com/cespare/xxhash/v2 v2.3.0 h1:UL815xU9SqsFlibzuggzjXhog7bL6oX9BbNZnL2UFvs= diff --git a/insights-agent/src/insights_agent/knowledge/data-sources-and-caveats.md b/insights-agent/src/insights_agent/knowledge/data-sources-and-caveats.md index fc40af9..9bc009b 100644 --- a/insights-agent/src/insights_agent/knowledge/data-sources-and-caveats.md +++ b/insights-agent/src/insights_agent/knowledge/data-sources-and-caveats.md @@ -16,8 +16,21 @@ Used by cost-summary, cost-by-service, and cost-trends. - **What it is NOT.** It is not billed spend from a Cost Explorer / billing API. It will not match an invoice to the cent, and it cannot see one-off charges, taxes, credits, or refunds. -- **How to phrase it.** "Based on snapshot approximations, roughly $X." The - real billing integration lands in a later milestone (8.7). +- **How to phrase it.** "Based on snapshot approximations, roughly $X." This is + the default source; a deployment can switch to real billing (below). + +## `billing_aws_cost_explorer` — real AWS billed cost + +- **What it is.** Real **unblended** cost from the AWS Cost Explorer API, + grouped by service, for the requested period. Returned when the deployment + sets `CLOUDORACLE_BILLING_PROVIDER=aws_cost_explorer`. +- **What it is NOT.** Not an approximation — these are actual billed figures. + Note service names follow AWS's billing taxonomy (e.g. "amazon elastic + compute cloud - compute"), not CloudOracle's short names (ec2), and the + numbers can still lag the final invoice slightly as AWS finalizes charges. +- **How to phrase it.** State the figures as real billed cost; the snapshot + caveat does **not** apply. Only AWS has a real billing source today; GCP and + Azure still report `snapshots_approximation`. ## `heuristic_rules` — the recommendations endpoint diff --git a/internal/api/billing_source_test.go b/internal/api/billing_source_test.go new file mode 100644 index 0000000..1ab0f51 --- /dev/null +++ b/internal/api/billing_source_test.go @@ -0,0 +1,129 @@ +package api + +import ( + "CloudOracle/internal/billing" + "context" + "encoding/json" + "errors" + "net/http" + "testing" + "time" +) + +// fakeBillingSource is an injectable billing.Source for exercising the v1 cost +// handlers against a non-snapshot source (e.g. AWS Cost Explorer) without a DB. +type fakeBillingSource struct { + report billing.Report + err error + gotStart time.Time + gotEnd time.Time +} + +func (f *fakeBillingSource) Costs( + _ context.Context, start, end time.Time, +) (billing.Report, error) { + f.gotStart, f.gotEnd = start, end + if f.err != nil { + return billing.Report{}, f.err + } + return f.report, nil +} + +func billingReport() billing.Report { + return billing.Report{ + Records: []billing.CostRecord{ + {Provider: "aws", Service: "ec2", AmountUSD: 100}, + {Provider: "aws", Service: "rds", AmountUSD: 50}, + {Provider: "gcp", Service: "compute", AmountUSD: 200}, + }, + DataSource: billing.AWSCostExplorerDataSource, + Note: "real billed cost", + } +} + +func TestCostSummary_UsesInjectedBillingSource(t *testing.T) { + src := &fakeBillingSource{report: billingReport()} + srv := newTestServer(&fakeAPIData{}, testAPIKey, WithBillingSource(src)) + + rec := doGet(t, srv, "/api/v1/cost-summary?start=2026-04-01&end=2026-04-30", true) + if rec.Code != http.StatusOK { + t.Fatalf("status = %d, body=%s", rec.Code, rec.Body.String()) + } + + var body costSummaryResponse + if err := json.Unmarshal(rec.Body.Bytes(), &body); err != nil { + t.Fatalf("decode: %v", err) + } + // data_source flows through from the source, not a hard-coded constant. + if body.DataSource != billing.AWSCostExplorerDataSource { + t.Errorf("data_source = %q, want %q", body.DataSource, billing.AWSCostExplorerDataSource) + } + if body.Providers["aws"].TotalUSD != 150 { + t.Errorf("aws total = %v, want 150 (ec2 100 + rds 50)", body.Providers["aws"].TotalUSD) + } + if body.Providers["gcp"].TotalUSD != 200 { + t.Errorf("gcp total = %v, want 200", body.Providers["gcp"].TotalUSD) + } + if body.GrandTotalUSD != 350 { + t.Errorf("grand total = %v, want 350", body.GrandTotalUSD) + } + // The parsed range is forwarded to the source. + if body.Period.Start != "2026-04-01" || src.gotStart.IsZero() { + t.Errorf("source did not receive the parsed range: %+v", src) + } +} + +func TestCostSummary_ProvidersFilterWithBillingSource(t *testing.T) { + src := &fakeBillingSource{report: billingReport()} + srv := newTestServer(&fakeAPIData{}, testAPIKey, WithBillingSource(src)) + + rec := doGet(t, srv, + "/api/v1/cost-summary?start=2026-04-01&end=2026-04-30&providers=aws", true) + var body costSummaryResponse + if err := json.Unmarshal(rec.Body.Bytes(), &body); err != nil { + t.Fatalf("decode: %v", err) + } + if _, ok := body.Providers["gcp"]; ok { + t.Error("gcp should be filtered out") + } + if body.GrandTotalUSD != 150 { + t.Errorf("grand total = %v, want 150 (aws only)", body.GrandTotalUSD) + } +} + +func TestCostByService_UsesInjectedBillingSource(t *testing.T) { + src := &fakeBillingSource{report: billingReport()} + srv := newTestServer(&fakeAPIData{}, testAPIKey, WithBillingSource(src)) + + rec := doGet(t, srv, + "/api/v1/cost-by-service?start=2026-04-01&end=2026-04-30&provider=aws", true) + var body costByServiceResponse + if err := json.Unmarshal(rec.Body.Bytes(), &body); err != nil { + t.Fatalf("decode: %v", err) + } + if body.DataSource != billing.AWSCostExplorerDataSource { + t.Errorf("data_source = %q, want %q", body.DataSource, billing.AWSCostExplorerDataSource) + } + if body.TotalUSD != 150 { + t.Errorf("total = %v, want 150 (aws ec2+rds)", body.TotalUSD) + } + // Sorted by cost desc: ec2 (100) before rds (50). + if len(body.Services) != 2 || body.Services[0].Name != "ec2" { + t.Errorf("services = %+v, want ec2 first", body.Services) + } +} + +func TestCostSummary_BillingSourceErrorCode(t *testing.T) { + src := &fakeBillingSource{ + err: &billing.SourceError{Code: "billing_query_failed", Err: errors.New("access denied")}, + } + srv := newTestServer(&fakeAPIData{}, testAPIKey, WithBillingSource(src)) + + rec := doGet(t, srv, "/api/v1/cost-summary?start=2026-04-01&end=2026-04-30", true) + if rec.Code != http.StatusInternalServerError { + t.Fatalf("status = %d, want 500", rec.Code) + } + if code := extractCode(t, rec); code != "billing_query_failed" { + t.Errorf("code = %q, want billing_query_failed", code) + } +} diff --git a/internal/api/cost_handlers.go b/internal/api/cost_handlers.go index 5866e38..35886f5 100644 --- a/internal/api/cost_handlers.go +++ b/internal/api/cost_handlers.go @@ -1,6 +1,7 @@ package api import ( + "CloudOracle/internal/billing" "CloudOracle/internal/db" "CloudOracle/internal/shared" "context" @@ -93,22 +94,26 @@ func (s *Server) handleCostSummary(w http.ResponseWriter, r *http.Request) { return } - snapshots, err := s.data.ListSnapshotsInRange(r.Context(), start, end) + report, err := s.billing.Costs(r.Context(), start, end) if err != nil { - writeAPIError(w, http.StatusInternalServerError, - "failed to load snapshots: "+err.Error(), "snapshot_query_failed") + writeCostSourceError(w, err) return } - days := periodDays(start, end) - perProvider := aggregateByProvider(snapshots, days, filter) + perProvider := make(map[string]float64) + for _, rec := range report.Records { + if len(filter) > 0 && !filter[rec.Provider] { + continue + } + perProvider[rec.Provider] += rec.AmountUSD + } resp := costSummaryResponse{ Period: periodDTO{Start: start.Format(time.DateOnly), End: end.Format(time.DateOnly)}, Providers: make(map[string]providerSummaryDTO, len(perProvider)), GeneratedAt: time.Now().UTC(), - DataSource: dataSourceLabel, - Note: dataSourceNote, + DataSource: report.DataSource, + Note: report.Note, } var total float64 @@ -161,15 +166,19 @@ func (s *Server) handleCostByService(w http.ResponseWriter, r *http.Request) { top = 10 } - snapshots, err := s.data.ListSnapshotsInRange(r.Context(), start, end) + report, err := s.billing.Costs(r.Context(), start, end) if err != nil { - writeAPIError(w, http.StatusInternalServerError, - "failed to load snapshots: "+err.Error(), "snapshot_query_failed") + writeCostSourceError(w, err) return } - days := periodDays(start, end) - perService := aggregateByService(snapshots, days, provider) + perService := make(map[string]float64) + for _, rec := range report.Records { + if rec.Provider != provider { + continue + } + perService[rec.Service] += rec.AmountUSD + } var total float64 for _, v := range perService { @@ -206,53 +215,28 @@ func (s *Server) handleCostByService(w http.ResponseWriter, r *http.Request) { Services: services, TotalUSD: roundCents(total), GeneratedAt: time.Now().UTC(), - DataSource: dataSourceLabel, - Note: dataSourceNote, + DataSource: report.DataSource, + Note: report.Note, } writeJSON(w, http.StatusOK, resp) } -// aggregateByProvider implements the snapshots approximation: -// -// 1. Group snapshots by (account, service). -// 2. For each group, compute the average total_monthly_cost across the -// snapshots that fell in the period. -// 3. Map each (account, service) to a provider via providerForServiceAccount -// (the same mapping the dashboard summary uses). -// 4. Scale the per-group monthly rate to the period length: avg × days / 30. -// -// The optional filter is treated as a whitelist when non-nil; an empty map -// is also "no filter" — see parseProvidersFilter. -func aggregateByProvider(snapshots []db.Snapshot, days int, filter map[string]bool) map[string]float64 { - perAS := aggregateMonthlyByAccountService(snapshots) - scale := float64(days) / 30.0 - result := make(map[string]float64) - for k, avgMonthly := range perAS { - provider := providerForServiceAccount(k.service, k.account) - if len(filter) > 0 && !filter[provider] { - continue - } - result[provider] += avgMonthly * scale +// writeCostSourceError maps a billing.Source failure to a 500 with the source's +// machine-readable code (e.g. "snapshot_query_failed", "billing_query_failed"), +// falling back to a generic code for any other error. +func writeCostSourceError(w http.ResponseWriter, err error) { + code := "cost_query_failed" + var srcErr *billing.SourceError + if errors.As(err, &srcErr) && srcErr.Code != "" { + code = srcErr.Code } - return result + writeAPIError(w, http.StatusInternalServerError, err.Error(), code) } -// aggregateByService is the service-level counterpart: it returns per-service -// period totals for the requested provider. Unlike aggregateByProvider it -// hard-filters on the provider (the v1 endpoint requires `provider` to be -// set to a specific value), so no whitelist map is needed. -func aggregateByService(snapshots []db.Snapshot, days int, provider string) map[string]float64 { - perAS := aggregateMonthlyByAccountService(snapshots) - scale := float64(days) / 30.0 - result := make(map[string]float64) - for k, avgMonthly := range perAS { - if providerForServiceAccount(k.service, k.account) != provider { - continue - } - result[k.service] += avgMonthly * scale - } - return result -} +// The per-(account, service) monthly-rate averaging and provider mapping that +// the snapshot approximation needs now lives in snapshotSource (snapshot_source.go), +// which implements billing.Source. aggregateMonthlyByAccountService below is the +// shared primitive it builds on. type accountServiceKey struct { account string diff --git a/internal/api/server.go b/internal/api/server.go index f490403..6257afb 100644 --- a/internal/api/server.go +++ b/internal/api/server.go @@ -2,6 +2,7 @@ package api import ( "CloudOracle/internal/analyzer" + "CloudOracle/internal/billing" "CloudOracle/internal/config" "CloudOracle/internal/db" "CloudOracle/internal/shared" @@ -16,28 +17,45 @@ import ( type Server struct { data apiData + billing billing.Source apiKey string handler http.Handler } +// ServerOption customizes a Server at construction. WithBillingSource swaps the +// default snapshot-derived cost source for another billing.Source (e.g. the AWS +// Cost Explorer source) so the v1 cost endpoints serve real billed cost. +type ServerOption func(*Server) + +// WithBillingSource overrides the cost data source the v1 endpoints use. +func WithBillingSource(src billing.Source) ServerOption { + return func(s *Server) { s.billing = src } +} + // NewServer wires the production handler: legacy `/api/*` dashboard // endpoints stay open (they're consumed by the embedded React UI), and // the new `/api/v1/*` endpoints sit behind authMiddleware so only the // insights-agent — or any client that holds the configured API key — // can reach them. -func NewServer(pool *db.Pool, apiCfg config.APIConfig) *Server { - return newServerWithData(&pgxAdapter{pool: pool}, apiCfg.Key) +func NewServer(pool *db.Pool, apiCfg config.APIConfig, opts ...ServerOption) *Server { + return newServerWithData(&pgxAdapter{pool: pool}, apiCfg.Key, opts...) } // newTestServer builds a Server with a caller-supplied apiData so unit tests // can exercise the handlers without a live database. Production must go // through NewServer. -func newTestServer(data apiData, apiKey string) *Server { - return newServerWithData(data, apiKey) +func newTestServer(data apiData, apiKey string, opts ...ServerOption) *Server { + return newServerWithData(data, apiKey, opts...) } -func newServerWithData(data apiData, apiKey string) *Server { +func newServerWithData(data apiData, apiKey string, opts ...ServerOption) *Server { s := &Server{data: data, apiKey: apiKey} + // Default cost source: the snapshot approximation. WithBillingSource can + // swap in a real billing integration. + s.billing = newSnapshotSource(data) + for _, opt := range opts { + opt(s) + } s.handler = s.buildHandler() return s } diff --git a/internal/api/snapshot_source.go b/internal/api/snapshot_source.go new file mode 100644 index 0000000..78496da --- /dev/null +++ b/internal/api/snapshot_source.go @@ -0,0 +1,60 @@ +package api + +import ( + "CloudOracle/internal/billing" + "context" + "fmt" + "time" +) + +// snapshotSource is the default billing.Source: it derives cost from the +// aggregated cost_snapshots, reproducing the original v1 behavior exactly +// (data_source "snapshots_approximation"). It carries the same monthly-rate +// averaging and days/30 scaling the cost handlers used before milestone 8.7 +// moved this logic behind the billing.Source abstraction. +type snapshotSource struct { + data apiData +} + +func newSnapshotSource(data apiData) snapshotSource { + return snapshotSource{data: data} +} + +func (s snapshotSource) Costs( + ctx context.Context, start, end time.Time, +) (billing.Report, error) { + snapshots, err := s.data.ListSnapshotsInRange(ctx, start, end) + if err != nil { + return billing.Report{}, &billing.SourceError{ + Code: "snapshot_query_failed", + Err: fmt.Errorf("failed to load snapshots: %w", err), + } + } + + days := periodDays(start, end) + scale := float64(days) / 30.0 + perAS := aggregateMonthlyByAccountService(snapshots) + + type key struct{ provider, service string } + agg := make(map[key]float64) + for k, avgMonthly := range perAS { + provider := providerForServiceAccount(k.service, k.account) + agg[key{provider, k.service}] += avgMonthly * scale + } + + // Amounts stay unrounded; the handlers round the final aggregates once, + // so summing records per provider matches the pre-8.7 numbers to the cent. + records := make([]billing.CostRecord, 0, len(agg)) + for k, amount := range agg { + records = append(records, billing.CostRecord{ + Provider: k.provider, + Service: k.service, + AmountUSD: amount, + }) + } + return billing.Report{ + Records: records, + DataSource: dataSourceLabel, + Note: dataSourceNote, + }, nil +} diff --git a/internal/billing/billing.go b/internal/billing/billing.go new file mode 100644 index 0000000..521281b --- /dev/null +++ b/internal/billing/billing.go @@ -0,0 +1,47 @@ +// Package billing abstracts where the v1 cost endpoints get their numbers. +// +// CloudOracle started with a single source: aggregated cost_snapshots, exposed +// as data_source "snapshots_approximation". Milestone 8.7 introduces this +// Source interface so a real billing integration (AWS Cost Explorer) can be +// swapped in by configuration without touching the HTTP handlers, which now +// consume a normalized []CostRecord regardless of where it came from. +package billing + +import ( + "context" + "time" +) + +// CostRecord is one provider/service cost line for the requested period, +// already resolved to USD. The HTTP handlers group these by provider (for the +// summary) or by service within a provider (for the per-service breakdown). +type CostRecord struct { + Provider string + Service string + AmountUSD float64 +} + +// Report is the result of a cost query: the records plus the data_source label +// and human note the API echoes so callers know how the numbers were produced. +type Report struct { + Records []CostRecord + DataSource string + Note string +} + +// Source produces a cost Report for an inclusive [start, end] period. +type Source interface { + Costs(ctx context.Context, start, end time.Time) (Report, error) +} + +// SourceError carries a machine-readable code so the HTTP layer can map a +// data-source failure to a stable error code (e.g. "snapshot_query_failed", +// "billing_query_failed") without knowing the concrete source type. +type SourceError struct { + Code string + Err error +} + +func (e *SourceError) Error() string { return e.Err.Error() } + +func (e *SourceError) Unwrap() error { return e.Err } diff --git a/internal/billing/cost_explorer.go b/internal/billing/cost_explorer.go new file mode 100644 index 0000000..4d6bce5 --- /dev/null +++ b/internal/billing/cost_explorer.go @@ -0,0 +1,147 @@ +package billing + +import ( + "context" + "fmt" + "strconv" + "strings" + "time" + + "github.com/aws/aws-sdk-go-v2/aws" + awsconfig "github.com/aws/aws-sdk-go-v2/config" + "github.com/aws/aws-sdk-go-v2/service/costexplorer" + cetypes "github.com/aws/aws-sdk-go-v2/service/costexplorer/types" +) + +const ( + // AWSCostExplorerDataSource marks a Report as real billed cost, distinct + // from the snapshot approximation. The agent / dashboard can drop the + // "approximation" caveat when they see this. + AWSCostExplorerDataSource = "billing_aws_cost_explorer" + awsCostExplorerNote = "Costs are real unblended costs from the AWS Cost " + + "Explorer API for the requested period (grouped by service)." + costMetric = "UnblendedCost" +) + +// costExplorerAPI is the slice of *costexplorer.Client the source needs. As +// with the EC2/RDS clients in internal/cloud, narrowing it to an interface lets +// unit tests inject a fake without reaching AWS — the concrete client satisfies +// it implicitly. +type costExplorerAPI interface { + GetCostAndUsage( + ctx context.Context, + in *costexplorer.GetCostAndUsageInput, + optFns ...func(*costexplorer.Options), + ) (*costexplorer.GetCostAndUsageOutput, error) +} + +// CostExplorerSource implements Source against the AWS Cost Explorer API. +type CostExplorerSource struct { + client costExplorerAPI +} + +func NewCostExplorerSource(client costExplorerAPI) *CostExplorerSource { + return &CostExplorerSource{client: client} +} + +// NewAWSCostExplorerSource loads AWS config (region + optional shared profile) +// and builds a source backed by a real Cost Explorer client. Cost Explorer is +// a global service; the region only affects the endpoint. +func NewAWSCostExplorerSource( + ctx context.Context, region, profile string, +) (*CostExplorerSource, error) { + opts := []func(*awsconfig.LoadOptions) error{} + if region != "" { + opts = append(opts, awsconfig.WithRegion(region)) + } + if profile != "" { + opts = append(opts, awsconfig.WithSharedConfigProfile(profile)) + } + cfg, err := awsconfig.LoadDefaultConfig(ctx, opts...) + if err != nil { + return nil, fmt.Errorf("loading AWS config for cost explorer: %w", err) + } + return NewCostExplorerSource(costexplorer.NewFromConfig(cfg)), nil +} + +// Costs queries GetCostAndUsage grouped by SERVICE for [start, end] and sums +// the unblended cost across the returned time buckets, one CostRecord per +// service. CE's TimePeriod end is exclusive, so we advance `end` (which the +// handler set to 23:59:59.999 of the closing day) by a nanosecond to roll to +// the following date — keeping the API's inclusive contract. +func (s *CostExplorerSource) Costs( + ctx context.Context, start, end time.Time, +) (Report, error) { + in := &costexplorer.GetCostAndUsageInput{ + TimePeriod: &cetypes.DateInterval{ + Start: aws.String(start.Format(time.DateOnly)), + End: aws.String(end.Add(time.Nanosecond).Format(time.DateOnly)), + }, + Granularity: cetypes.GranularityMonthly, + Metrics: []string{costMetric}, + GroupBy: []cetypes.GroupDefinition{{ + Type: cetypes.GroupDefinitionTypeDimension, + Key: aws.String("SERVICE"), + }}, + } + + perService := map[string]float64{} + for { + out, err := s.client.GetCostAndUsage(ctx, in) + if err != nil { + return Report{}, &SourceError{Code: "billing_query_failed", Err: err} + } + for _, byTime := range out.ResultsByTime { + for _, g := range byTime.Groups { + service := "unknown" + if len(g.Keys) > 0 { + service = normalizeService(g.Keys[0]) + } + metric, ok := g.Metrics[costMetric] + if !ok { + continue + } + perService[service] += parseAmount(metric.Amount) + } + } + if out.NextPageToken == nil { + break + } + in.NextPageToken = out.NextPageToken + } + + // Amounts are returned unrounded; the HTTP handler rounds the final + // aggregates once, the same way it does for the snapshot source. + records := make([]CostRecord, 0, len(perService)) + for service, amount := range perService { + records = append(records, CostRecord{ + Provider: "aws", + Service: service, + AmountUSD: amount, + }) + } + return Report{ + Records: records, + DataSource: AWSCostExplorerDataSource, + Note: awsCostExplorerNote, + }, nil +} + +func parseAmount(raw *string) float64 { + if raw == nil { + return 0 + } + v, err := strconv.ParseFloat(*raw, 64) + if err != nil { + return 0 + } + return v +} + +// normalizeService lowercases and trims the Cost Explorer service name. CE uses +// long human names ("Amazon Elastic Compute Cloud - Compute") that don't match +// the snapshot taxonomy (ec2, rds, …); we keep the real billing name rather than +// guess a fuzzy mapping, only normalizing case/whitespace so it's stable. +func normalizeService(name string) string { + return strings.ToLower(strings.TrimSpace(name)) +} diff --git a/internal/billing/cost_explorer_test.go b/internal/billing/cost_explorer_test.go new file mode 100644 index 0000000..b053563 --- /dev/null +++ b/internal/billing/cost_explorer_test.go @@ -0,0 +1,188 @@ +package billing + +import ( + "context" + "errors" + "sort" + "testing" + "time" + + "github.com/aws/aws-sdk-go-v2/aws" + "github.com/aws/aws-sdk-go-v2/service/costexplorer" + cetypes "github.com/aws/aws-sdk-go-v2/service/costexplorer/types" +) + +type fakeCE struct { + outputs []*costexplorer.GetCostAndUsageOutput + err error + inputs []*costexplorer.GetCostAndUsageInput +} + +func (f *fakeCE) GetCostAndUsage( + _ context.Context, + in *costexplorer.GetCostAndUsageInput, + _ ...func(*costexplorer.Options), +) (*costexplorer.GetCostAndUsageOutput, error) { + f.inputs = append(f.inputs, in) + if f.err != nil { + return nil, f.err + } + out := f.outputs[len(f.inputs)-1] + return out, nil +} + +func group(service, amount string) cetypes.Group { + return cetypes.Group{ + Keys: []string{service}, + Metrics: map[string]cetypes.MetricValue{ + costMetric: {Amount: aws.String(amount), Unit: aws.String("USD")}, + }, + } +} + +func recordsByService(report Report) map[string]float64 { + out := make(map[string]float64) + for _, r := range report.Records { + out[r.Service] = r.AmountUSD + } + return out +} + +func TestCostExplorer_SumsAcrossBucketsAndServices(t *testing.T) { + fake := &fakeCE{outputs: []*costexplorer.GetCostAndUsageOutput{{ + ResultsByTime: []cetypes.ResultByTime{ + {Groups: []cetypes.Group{ + group("Amazon Elastic Compute Cloud - Compute", "100.50"), + group("Amazon RDS Service", "40.00"), + }}, + {Groups: []cetypes.Group{ + group("Amazon Elastic Compute Cloud - Compute", "99.50"), + }}, + }, + }}} + src := NewCostExplorerSource(fake) + + report, err := src.Costs(context.Background(), apr1(), apr30End()) + if err != nil { + t.Fatalf("Costs: %v", err) + } + if report.DataSource != AWSCostExplorerDataSource { + t.Errorf("DataSource = %q, want %q", report.DataSource, AWSCostExplorerDataSource) + } + got := recordsByService(report) + // ec2 across two buckets: 100.50 + 99.50 = 200; rds: 40. + if got["amazon elastic compute cloud - compute"] != 200 { + t.Errorf("ec2 total = %v, want 200", got["amazon elastic compute cloud - compute"]) + } + if got["amazon rds service"] != 40 { + t.Errorf("rds total = %v, want 40", got["amazon rds service"]) + } + for _, r := range report.Records { + if r.Provider != "aws" { + t.Errorf("record provider = %q, want aws", r.Provider) + } + } +} + +func TestCostExplorer_TimePeriodEndIsExclusive(t *testing.T) { + fake := &fakeCE{outputs: []*costexplorer.GetCostAndUsageOutput{{}}} + src := NewCostExplorerSource(fake) + + if _, err := src.Costs(context.Background(), apr1(), apr30End()); err != nil { + t.Fatalf("Costs: %v", err) + } + in := fake.inputs[0] + if got := aws.ToString(in.TimePeriod.Start); got != "2026-04-01" { + t.Errorf("TimePeriod.Start = %q, want 2026-04-01", got) + } + // Inclusive end 2026-04-30 → CE exclusive end is the next day. + if got := aws.ToString(in.TimePeriod.End); got != "2026-05-01" { + t.Errorf("TimePeriod.End = %q, want 2026-05-01 (exclusive)", got) + } +} + +func TestCostExplorer_Paginates(t *testing.T) { + fake := &fakeCE{outputs: []*costexplorer.GetCostAndUsageOutput{ + { + ResultsByTime: []cetypes.ResultByTime{{Groups: []cetypes.Group{group("ec2", "10")}}}, + NextPageToken: aws.String("page2"), + }, + { + ResultsByTime: []cetypes.ResultByTime{{Groups: []cetypes.Group{group("ec2", "5")}}}, + }, + }} + src := NewCostExplorerSource(fake) + + report, err := src.Costs(context.Background(), apr1(), apr30End()) + if err != nil { + t.Fatalf("Costs: %v", err) + } + if len(fake.inputs) != 2 { + t.Fatalf("GetCostAndUsage called %d times, want 2", len(fake.inputs)) + } + if got := aws.ToString(fake.inputs[1].NextPageToken); got != "page2" { + t.Errorf("second call NextPageToken = %q, want page2", got) + } + if recordsByService(report)["ec2"] != 15 { + t.Errorf("ec2 total = %v, want 15 (10 + 5 across pages)", recordsByService(report)["ec2"]) + } +} + +func TestCostExplorer_ErrorWrapsAsSourceError(t *testing.T) { + fake := &fakeCE{err: errors.New("access denied")} + src := NewCostExplorerSource(fake) + + _, err := src.Costs(context.Background(), apr1(), apr30End()) + var srcErr *SourceError + if !errors.As(err, &srcErr) { + t.Fatalf("error = %v, want *SourceError", err) + } + if srcErr.Code != "billing_query_failed" { + t.Errorf("code = %q, want billing_query_failed", srcErr.Code) + } + if !errors.Is(err, srcErr.Err) { + t.Error("SourceError should unwrap to the underlying error") + } +} + +func TestCostExplorer_SkipsGroupsMissingMetric(t *testing.T) { + fake := &fakeCE{outputs: []*costexplorer.GetCostAndUsageOutput{{ + ResultsByTime: []cetypes.ResultByTime{{Groups: []cetypes.Group{ + {Keys: []string{"ec2"}, Metrics: map[string]cetypes.MetricValue{}}, + }}}, + }}} + src := NewCostExplorerSource(fake) + + report, err := src.Costs(context.Background(), apr1(), apr30End()) + if err != nil { + t.Fatalf("Costs: %v", err) + } + if len(report.Records) != 0 { + t.Errorf("records = %v, want none (metric absent)", report.Records) + } +} + +func TestSortRecordsDeterministic(t *testing.T) { + // Guard: records map iteration order doesn't matter to callers because the + // API handler sorts; here we just confirm both services survive. + fake := &fakeCE{outputs: []*costexplorer.GetCostAndUsageOutput{{ + ResultsByTime: []cetypes.ResultByTime{{Groups: []cetypes.Group{ + group("b", "1"), group("a", "2"), + }}}, + }}} + report, _ := NewCostExplorerSource(fake).Costs(context.Background(), apr1(), apr30End()) + names := make([]string, 0, len(report.Records)) + for _, r := range report.Records { + names = append(names, r.Service) + } + sort.Strings(names) + if len(names) != 2 || names[0] != "a" || names[1] != "b" { + t.Errorf("services = %v, want [a b]", names) + } +} + +func apr1() time.Time { return time.Date(2026, 4, 1, 0, 0, 0, 0, time.UTC) } + +func apr30End() time.Time { + return time.Date(2026, 4, 30, 23, 59, 59, 999999999, time.UTC) +} diff --git a/internal/config/config.go b/internal/config/config.go index a2f0042..9b37c5e 100644 --- a/internal/config/config.go +++ b/internal/config/config.go @@ -57,6 +57,9 @@ type APIConfig struct { Key string Port string ShutdownTimeout time.Duration + // BillingProvider selects the cost data source for the v1 endpoints: + // "snapshots" (default) or "aws_cost_explorer". + BillingProvider string } const ( @@ -64,13 +67,20 @@ const ( providerAWS = "aws" providerGCP = "gcp" providerAzure = "azure" + + // Billing providers select where the v1 cost endpoints read from: + // "snapshots" (the default approximation) or "aws_cost_explorer" (real + // AWS billed cost via the Cost Explorer API). + BillingSnapshots = "snapshots" + BillingAWSCostExplorer = "aws_cost_explorer" ) var ( - validCloudProviders = []string{providerSynthetic, providerAWS, providerGCP, providerAzure} - validLLMProviders = []string{"gemini", "claude", "openai"} - validLogLevels = []string{"debug", "info", "warn", "error"} - validLogFormats = []string{"text", "json"} + validCloudProviders = []string{providerSynthetic, providerAWS, providerGCP, providerAzure} + validLLMProviders = []string{"gemini", "claude", "openai"} + validBillingProviders = []string{BillingSnapshots, BillingAWSCostExplorer} + validLogLevels = []string{"debug", "info", "warn", "error"} + validLogFormats = []string{"text", "json"} ) // ValidationError aggregates every config problem encountered during Load @@ -130,6 +140,7 @@ func Load() (Config, error) { Key: os.Getenv("CLOUDORACLE_API_KEY"), Port: v.requirePort("CLOUDORACLE_API_PORT", "8080"), ShutdownTimeout: v.requirePositiveDuration("CLOUDORACLE_API_SHUTDOWN_TIMEOUT", 10*time.Second), + BillingProvider: v.requireEnum("CLOUDORACLE_BILLING_PROVIDER", BillingSnapshots, validBillingProviders), }, ServiceTimeout: v.requirePositiveDuration("CLOUD_SERVICE_TIMEOUT", 30*time.Second), LogLevel: v.requireEnum("LOG_LEVEL", "info", validLogLevels), From f2ddb6b2e132b530ee4cfbb416696115661fde34 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jesus=20Nu=C3=B1ez?= <jesus.nunez2050@gmail.com> Date: Sat, 30 May 2026 20:42:43 -0400 Subject: [PATCH 18/18] chore: enforce LF via .gitattributes; add v3 Insights Agent guide MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The internal/diff golden tests (byte-exact Markdown/narrative fixtures) failed on Windows checkouts: core.autocrlf=true with no .gitattributes rewrote the fixtures to CRLF while the renderer emits "\n". The committed fixture content was already correct, so this adds `* text=auto eol=lf` (plus binary markers) to keep LF in the working tree on every platform. All Go tests now pass. Also adds docs/v3-guide.md — the Insights Agent guide (supervisor + RAG + guardrails architecture, the /api/v1 contract and data_source semantics, real billing via AWS Cost Explorer, CLI/HTTP usage) alongside v1/v2-guide — and links it from the README. --- .gitattributes | 18 +++++++ README.md | 3 +- docs/v3-guide.md | 130 +++++++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 150 insertions(+), 1 deletion(-) create mode 100644 .gitattributes create mode 100644 docs/v3-guide.md diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..99cb9bc --- /dev/null +++ b/.gitattributes @@ -0,0 +1,18 @@ +# Normalize line endings: LF in the repository and in the working tree on every +# platform. Several tests (notably internal/diff's golden Markdown fixtures and +# the narrative-prompt snapshot) compare output byte-for-byte, and the renderer +# emits "\n". Without this, a Windows checkout with core.autocrlf=true rewrites +# the fixtures to CRLF and the comparisons fail even though the content matches. +* text=auto eol=lf + +# Binary assets must never be line-ending converted. +*.png binary +*.jpg binary +*.jpeg binary +*.gif binary +*.ico binary +*.pdf binary +*.woff binary +*.woff2 binary +*.ttf binary +*.eot binary diff --git a/README.md b/README.md index 5bb1efd..03e95f6 100644 --- a/README.md +++ b/README.md @@ -6,7 +6,7 @@ A Go FinOps toolkit that ships in two modes from the same `oracle` binary, with - **v1 — Audit existing cloud spend.** Ingest live EC2/RDS/EBS/Lambda inventory from AWS, GCP, or Azure into Postgres, run deterministic rules over it, and produce an executive PDF + dashboard with an LLM-narrated summary. See **[docs/v1-guide.md](docs/v1-guide.md)**. - **v2 — Predict cost impact of a Terraform PR before merge.** Read `terraform show -json plan.tfplan`, look every changing resource up against the AWS Pricing API, and post (or upsert) a Markdown comment on the PR with the net monthly delta, top movers, and a 1–3 sentence LLM narrative. Ships as a GitHub Action and as the `oracle pr-check` subcommand. **Current focus.** See **[docs/v2-guide.md](docs/v2-guide.md)**. -- **v3 — Insights Agent (in progress).** Polyglot Go + Python extension adding agentic FinOps analysis on top of v1/v2 cost data — LangGraph orchestration, RAG over FinOps documentation, multi-agent supervisor pattern, and production guardrails. See **[AI Insights Agent](#ai-insights-agent)** below and **[insights-agent/README.md](insights-agent/README.md)**. +- **v3 — Insights Agent.** Polyglot Go + Python extension adding agentic FinOps analysis on top of v1/v2 cost data — a hand-rolled LangGraph supervisor over specialist agents, RAG over a FinOps corpus (pgvector), production guardrails, real billing via AWS Cost Explorer, and a CLI + HTTP surface. See **[docs/v3-guide.md](docs/v3-guide.md)**, **[AI Insights Agent](#ai-insights-agent)** below, and **[insights-agent/README.md](insights-agent/README.md)**. ## AI Insights Agent @@ -125,6 +125,7 @@ The synthetic provider needs no credentials. To run against AWS / GCP / Azure, s ## Documentation +- **[docs/v3-guide.md](docs/v3-guide.md)** — Insights Agent: architecture (supervisor, RAG, guardrails), the `/api/v1` contract + `data_source` semantics, real billing, and how to run the CLI/HTTP surface - **[docs/v2-guide.md](docs/v2-guide.md)** — Terraform PR cost analysis (Action inputs, CLI flags, exit codes, supported resources) - **[docs/v1-guide.md](docs/v1-guide.md)** — Cloud cost audit walkthrough (seed, analyze, PDF, dashboard, LLM setup, sample output) - **[docs/architecture.md](docs/architecture.md)** — v1/v2 internal layout, analyzer + LLM provider design, architecture decisions, lessons learned diff --git a/docs/v3-guide.md b/docs/v3-guide.md new file mode 100644 index 0000000..40f7c56 --- /dev/null +++ b/docs/v3-guide.md @@ -0,0 +1,130 @@ +# v3 — Insights Agent + +CloudOracle v3 adds an agentic FinOps layer: a polyglot **Go + Python** system +that answers natural-language cost questions ("how much did I spend on AWS in +April?", "where can I save money?", "what is rightsizing?") by orchestrating +LLM specialists over the authenticated `/api/v1` cost API. + +```mermaid +flowchart LR + U([User]) -->|"natural-language question"| CLI[insights-agent<br/>CLI or HTTP] + CLI --> SUP[LangGraph supervisor<br/>routes by tool call] + SUP --> W1[cost_analyst] + SUP --> W2[savings_advisor] + SUP --> W3[concept_expert] + SUP --> SYN[synthesize] + W1 & W2 -->|"X-API-Key"| GO[CloudOracle Go<br/>/api/v1/*] + W2 & W3 -->|"similarity search"| VDB[(pgvector<br/>FinOps corpus)] + GO -->|"SQL / billing API"| DB[(PostgreSQL · cost_snapshots<br/>+ AWS Cost Explorer)] + SYN -->|"validated answer"| U +``` + +The Python agent lives in [`insights-agent/`](../insights-agent/README.md), +which is the source of truth for setup, env vars, and the CLI/HTTP surface. +This guide is the architectural overview and the Go-side contract. + +## The two halves + +| Half | Where | Responsibility | +| ---- | ----- | -------------- | +| **Go server** | `internal/api`, `internal/billing` | Owns the data: authenticated `/api/v1` cost endpoints, the analyzer recommendations, and the billing source (snapshots or AWS Cost Explorer). A clean data API — no LLM. | +| **Python agent** | `insights-agent/` | Owns the reasoning: LangGraph supervisor, the tools that call `/api/v1`, RAG over a FinOps corpus, guardrails, and the CLI + HTTP surface. | + +Keeping RAG and orchestration in Python (where LangChain lives) lets the Go +server stay a small, well-tested data API. + +## The `/api/v1` contract + +All v1 endpoints sit behind `X-API-Key` (set `CLOUDORACLE_API_KEY` on the +server; the agent sends it). Every response carries a `data_source` field so +the agent surfaces the right caveat. + +| Endpoint | Answers | `data_source` | +| -------- | ------- | ------------- | +| `GET /api/v1/cost-summary` | totals per provider | `snapshots_approximation` or `billing_aws_cost_explorer` | +| `GET /api/v1/cost-by-service` | per-service breakdown for one provider | same as above | +| `GET /api/v1/cost-trends` | per-day series + precomputed change/direction | `snapshots_approximation` | +| `GET /api/v1/inventory` | resource counts + cost by provider/service | `live_inventory` | +| `GET /api/v1/recommendations` | rule-based savings opportunities | `heuristic_rules` | + +### What each `data_source` means + +- **`snapshots_approximation`** — derived from periodic `cost_snapshots` + (projected monthly rate × days/30), **not** billed spend. Won't match an + invoice to the cent. +- **`billing_aws_cost_explorer`** — real AWS unblended cost from the Cost + Explorer API. The approximation caveat does **not** apply. Service names use + AWS's billing taxonomy (e.g. "amazon elastic compute cloud - compute"). +- **`live_inventory`** — counts and per-resource projected cost from the latest + scan, not billed spend. +- **`heuristic_rules`** — rule-based savings estimates; `monthly_savings_usd` is + an upper bound to validate before acting. + +## Real billing (AWS Cost Explorer) + +By default the cost endpoints serve the snapshot approximation. To serve real +AWS billed cost, set on the **server**: + +```bash +CLOUDORACLE_BILLING_PROVIDER=aws_cost_explorer # default: snapshots +# uses AWS_REGION / AWS_PROFILE for credentials +``` + +The server builds an AWS Cost Explorer source at startup; if that fails (bad +credentials, no `ce:GetCostAndUsage` permission) it logs a warning and falls +back to snapshots so the API keeps serving. The IAM principal needs +`ce:GetCostAndUsage`. Implementation: `internal/billing` (the `Source` +interface + `CostExplorerSource`); GCP and Azure sources can plug into the same +interface later. + +## The agent (Python) + +Built on a hand-rolled LangGraph `StateGraph` (not `create_react_agent`): + +- **Supervisor** routes each turn to one specialist by calling a routing tool, + or `finish`. A hop cap bounds the loop. +- **Specialists** (each a hand-rolled ReAct loop over a tool subset): + - `cost_analyst` — cost-summary / cost-by-service / cost-trends / inventory + - `savings_advisor` — recommendations + knowledge search + - `concept_expert` — knowledge search (RAG) +- **Synthesizer** composes the final answer in the user's language with the + data-source caveats and source citations. + +### Tools + +Five HTTP tools (one per v1 endpoint) plus `finops_knowledge_search`, a RAG tool +over a curated FinOps corpus embedded in **pgvector** (enabled when +`DATABASE_URL` points at the pgvector-backed Postgres; the bundled compose stack +uses `pgvector/pgvector:pg16`). Ingest the corpus with `uv run +insights-agent-ingest`. + +### Guardrails + +Every run goes through `guardrails/run_guarded`: + +- **Cost/usage caps** — bound tool calls, supervisor hops, and per-worker + iterations (`MAX_TOOL_CALLS`, `MAX_HOPS`, `MAX_WORKER_ITERS`). +- **Layered validation** — deterministic grounding (every monetary figure in + the answer must match a number in the tool observations; an unmatched figure + is a hard fail), then an optional LLM judge for numeric answers that pass. +- **Deterministic fallback** — on a run failure or rejected answer, return an + honest no-LLM response with the raw tool data instead of a fabricated + narrative. + +## Running it + +```bash +cd insights-agent +uv sync --extra dev + +# CLI +uv run insights-agent --verbose "How much did I spend on AWS in April 2026?" + +# HTTP service +uv run insights-agent-serve # POST /ask {query}, GET /health +``` + +See [`insights-agent/README.md`](../insights-agent/README.md) for the full env +var table, the RAG ingestion step, the HTTP API, and the offline test strategy, +and [configuration.md](configuration.md) for the Go server's +`CLOUDORACLE_BILLING_PROVIDER` and related vars.