From 7078365d546da93db2930067761950a34f974358 Mon Sep 17 00:00:00 2001 From: Xiaolv <2116262909@qq.com> Date: Thu, 10 Sep 2026 14:50:34 +0800 Subject: [PATCH 1/3] feat(skills): add the RoboDojo G05 skill Add one robodojo Skill with a single formal g05 profile: manifest, Skill document, Dora dataflow, and the Gateway / bench-endpoint / benchmark profile configuration for the put_bottles_into_dustbin demo. The profile resolves every node from the installed Node bundles through FORGE_RUNTIME_BIN and reaches profile assets through PAOS_SKILL_ROOT, so the Skill tree carries no benchmark or policy implementation. --- .../skills/forge-skill/robodojo/SKILL.md | 144 ++++++++++++++ .../robodojo/profiles/g05/bench_endpoint.yaml | 13 ++ .../robodojo/profiles/g05/config.yaml | 29 +++ .../robodojo/profiles/g05/dataflow.yaml | 82 ++++++++ .../robodojo/profiles/g05/env.template.sh | 54 +++++ .../robodojo/profiles/g05/gateway.yaml | 188 ++++++++++++++++++ .../skills/forge-skill/robodojo/skill.yaml | 61 ++++++ 7 files changed, 571 insertions(+) create mode 100644 PhyAgentOS/skills/forge-skill/robodojo/SKILL.md create mode 100644 PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/bench_endpoint.yaml create mode 100644 PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/config.yaml create mode 100644 PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/dataflow.yaml create mode 100644 PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/env.template.sh create mode 100644 PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/gateway.yaml create mode 100644 PhyAgentOS/skills/forge-skill/robodojo/skill.yaml diff --git a/PhyAgentOS/skills/forge-skill/robodojo/SKILL.md b/PhyAgentOS/skills/forge-skill/robodojo/SKILL.md new file mode 100644 index 000000000..c9a164b08 --- /dev/null +++ b/PhyAgentOS/skills/forge-skill/robodojo/SKILL.md @@ -0,0 +1,144 @@ +--- +name: robodojo +description: Run the RoboDojo G05 benchmark and report its aggregate score. +metadata: {"PhyAgentOS":{"always":false,"requires":{"runtime":["robodojo"]}}} +--- + +# RoboDojo Benchmark + +Run a RoboDojo benchmark batch in Isaac Sim and report the score the benchmark +produced. Use only these stable Tool IDs: + +- `bench.describe`: Query; return the live task inventory, defaults, and episode + budget limits. Does not touch the simulator state. +- `bench.run`: Action; run one batch of episodes and return its aggregate result. + Long running — minutes per episode. + +Use the PAOS bridge tools `forge_tool_context`, `forge_tool_query`, +`forge_tool_start_action`, `forge_tool_action_status`, `forge_tool_action_result`, +and `forge_tool_cancel_action`. Always pass the stable Forge Tool ID explicitly. +Do not use shell commands and do not construct Gateway HTTP requests directly. + +## What this Skill must not do + +Scoring belongs entirely to the benchmark node. This Skill selects and sequences +Tools, and reports what came back. It must not: + +- compute, recompute, adjust, average, or extrapolate `success_rate` or any other + metric; +- decide whether an individual episode succeeded, failed, or timed out; +- aggregate results across separate `bench.run` invocations into one number; +- convert a partial or failed batch into a score, or present one as if the batch + had completed; +- estimate a score when the result is unavailable. + +If a number is needed and no terminal result exists, say so. Do not produce one. + +## 1. Always describe before running + +Call `bench.describe` first, every time. Never fill `bench.run` arguments from +memory or from an earlier conversation — the installed suite, task count, and +limits are properties of the running profile, not of this document. + +`bench.describe` returns: + +- `benchmark`, `suite`, `policy_id`, `env_cfg_type`, `action_type` — fixed by the + profile. They are read-only context, not parameters you can change. +- `tasks[]` — each with `task_id`, `name`, `language`, `num_init_states`. The + init-state count differs per task; do not assume one task's count applies to + another. +- `defaults` — `num_runs`, `seed`, `max_steps` to use when the user gave no value. +- `limits` — `max_total_episodes`, `max_max_steps`. Hard caps; see §2. + +If `bench.describe` fails with `BENCH_NOT_READY`, the simulator is still starting. +Wait and retry; do not proceed to `bench.run`. + +## 2. Build the bench.run arguments + +All five fields are required. There are no defaults on the wire. + +- `task_ids`: an array of ids taken from `bench.describe`, or `null` for every + task. `null` and `[]` are different — `[]` is always an error, never "all". +- `init_state_ids`: an array, or `null` for every init state shared by all + selected tasks. Validated per task. +- `num_runs`: repeats per (task, init_state) pair. Use `defaults.num_runs` unless + the user asked for more. +- `seed`: base seed. The same seed and the same ids reproduce the same episodes. + Change it only when the user asks for a different sample. +- `max_steps`: a **hard cap on control steps**. The episode is terminated as + `timed_out` if this many steps are reached before the environment ends. The + task native `step_lim` defines its normal end (success / partial / failed); set `max_steps` to at least the task horizon (from `bench.describe` defaults) to allow completion, or lower to force an explicit step-limit stop. + +Episode count is `len(task_ids) x len(init_state_ids) x num_runs`. Keep it at or +below `limits.max_total_episodes`; exceeding it is rejected, not clamped. When the +user asks for something larger, report the cap and the requested count and ask +before splitting the work into several batches. + +Nothing else is selectable. Policy weights, suite, camera set, and GPU are fixed by +the profile. If the user asks to change one of those, say it requires a different +profile — do not try to express it through these arguments. + +## 3. Account for the Action lifecycle + +`bench.run` is an Action. Accepted is not completed. + +1. `forge_tool_start_action` returns an acknowledgement with an `invocation_id` and + `total_episodes`. The batch has not run yet. +2. `forge_tool_action_status` reports `accepted`, `running`, or a terminal phase. + Status is **advisory** — never report a score from it. Poll at a human pace; + a single episode takes minutes. +3. `forge_tool_action_result` is the only authoritative source of the outcome. + +Treat the four terminal outcomes as four different things: + +- `succeeded` — the batch ran to completion. Report per §4. +- `failed` — the batch ended abnormally. Report the error code and the episode + counts; do not present `success_rate` as the headline. +- `cancelled` — stopped on request. Partial counts only. +- `unknown` — **the outcome cannot be recovered**. Side effects have already + happened: GPU time was consumed and a `result.json` may exist on disk. Do not + blindly retry. Report that the outcome is unknown, give the `invocation_id`, and + ask how to proceed. + +Use `forge_tool_cancel_action` only when the user asks to stop. Cancel is accepted, +not immediate — keep polling until a terminal result appears. + +## 4. Reporting rules + +Report these together, always, in this order: + +1. `status` of the batch. +2. `success_rate`, immediately followed by `successes` / `total_episodes`. +3. `completed_episodes` / `total_episodes`. + +`success_rate` is computed over `total_episodes`, not over +`completed_episodes`. When a batch ends early these differ, and `success_rate` +alone reads as "the policy scored low" when the real story is "the batch did not +finish". If `completed_episodes < total_episodes`, say that first, before the +score. + +Also report: + +- `result_path` — the authoritative record on disk. Always include it. +- `timed_out_episodes` when non-zero. +- `obs_republished` when non-zero: observations were re-sent during the run. The + score is still valid, but mention it. +- `episodes[]` per-episode outcomes when the user asks for detail. When + `episodes_truncated` is true the list was too large to inline — point at + `result_path` instead of summarising from an empty array. + +Never present a single number without its denominator. + +## 5. Errors and replanning + +| code | retryable | what to do | +|---|---|---| +| `BENCH_NOT_READY` | yes | Simulator still starting. Wait, retry `bench.describe`. | +| `FORGE_BUSY` | yes | Another batch is running; one simulator per machine. Report which `invocation_id` holds it. Do not queue. | +| `BENCH_INVALID_ARGUMENT` | no | Arguments are wrong. Re-read `bench.describe` and rebuild them. `details` carries the valid range and the requested vs allowed episode count. Never retry unchanged. | +| `BENCH_NODE_UNAVAILABLE` | yes | The benchmark node stopped reporting. The outcome is unknown — see §3. Do not restart the batch without asking. | +| `BENCH_UNKNOWN_INVOCATION` | no | The id is not known here. Do not invent one; start a new run if the user wants one. | +| `FORGE_DEADLINE_EXCEEDED` | no | The gateway stopped tracking; the batch may still be running. Do not start another — that would collide. Report and ask. | + +When two errors are plausible, prefer the more conservative reading: an unknown +outcome is not a failure, and a rejected batch is not a zero score. diff --git a/PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/bench_endpoint.yaml b/PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/bench_endpoint.yaml new file mode 100644 index 000000000..1e094f55f --- /dev/null +++ b/PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/bench_endpoint.yaml @@ -0,0 +1,13 @@ +# bench_endpoint 节点配置（g05 profile，与 build_tower 相同）。 +# 连续多久收不到 bench_report 就把在跑的 invocation 判成 unknown。 +# +# ⚠️ 必须大于 benchmark 节点一次最长的阻塞调用（episode 启动时 reset_episode 要 +# 加载 Isaac Sim 场景，整个循环阻塞几十秒），不是心跳周期的几倍。太小会把正常的 +# 场景加载误判成掉线 → invocation 被写成终态 unknown，然后真结果到达时被丢弃， +# 仿真器还在烧 GPU。 +heartbeat_timeout_s: 180.0 + +# 保留多少条历史 invocation 供对账。 +retention: 8 + +log_level: INFO diff --git a/PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/config.yaml b/PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/config.yaml new file mode 100644 index 000000000..f5b581a53 --- /dev/null +++ b/PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/config.yaml @@ -0,0 +1,29 @@ +# benchmark 节点的服务模式配置(robodojo g05 profile) - 可移植版本。 +# result_dir / record_dir / device_id 允许被环境变量覆盖(见 main.py)。 +benchmark: robodojo +suite: put_bottles_into_dustbin + +env_cfg_type: arx_x5 +device_id: 0 # 可被 ROBODOJO_DEVICE_ID 覆盖 + +serve: true +init_states_per_task: 1 +num_runs: 1 +seed: 0 +max_steps: 700 + +max_total_episodes: 20 +max_max_steps: 2000 + +action_type: joint +policy_id: G05 +additional_info: forge + +camera_map: + image/head: cam_head + image/left_wrist: cam_left_wrist + image/right_wrist: cam_right_wrist + +# 默认相对路径(解析到 bundle 内源码目录); 正式运行请用环境变量覆盖。 +record_dir: results/robodojo/videos +result_dir: results/robodojo diff --git a/PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/dataflow.yaml b/PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/dataflow.yaml new file mode 100644 index 000000000..a5497d5c3 --- /dev/null +++ b/PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/dataflow.yaml @@ -0,0 +1,82 @@ +# 完整链路: gateway -> bench_endpoint -> robodojo_benchmark -> policy(G05) -> Isaac Sim +# 职责边界: benchmark/policy 的实现由 forge_runtime 的 Node 包维护, 本 Skill 只带 +# 描述、清单、g05 profile、dataflow、安装脚本与文档。四个 node 一律走已安装 Node 的 +# 入口 (${FORGE_RUNTIME_BIN}/), Skill 内不再存放节点源码或 launcher。 +# 运行环境经 required_environment 由宿主提供, 并在 dora start 时以 ${VAR} 展开写入 +# 各 node env。 +nodes: + - id: gateway + path: ${FORGE_RUNTIME_BIN}/gateway + args: --config ${PAOS_SKILL_ROOT}/profiles/g05/gateway.yaml + env: + FORGE_GATEWAY_PYTHON: ${FORGE_GATEWAY_PYTHON} + inputs: + tick: dora/timer/millis/50 + bench_tool_in: bench_endpoint/tool_out + outputs: + - tool_response + - bench_tool_out + - id: bench_endpoint + path: ${FORGE_RUNTIME_BIN}/bench_endpoint + args: --config ${PAOS_SKILL_ROOT}/profiles/g05/bench_endpoint.yaml + env: + BENCH_ENDPOINT_PYTHON: ${BENCH_ENDPOINT_PYTHON} + inputs: + tick: dora/timer/millis/50 + tool_in: gateway/bench_tool_out + bench_report: robodojo_benchmark/bench_report + outputs: + - tool_out + - bench_cmd + - id: robodojo_benchmark + path: ${FORGE_RUNTIME_BIN}/robodojo_benchmark + env: + BENCHMARK_CONFIG: ${PAOS_SKILL_ROOT}/profiles/g05/config.yaml + PATH: ${PATH} + ROBODOJO_ENV: ${ROBODOJO_ENV} + ROBODOJO_ROOT: ${ROBODOJO_ROOT} + ROBODOJO_CACHE_ROOT: ${ROBODOJO_CACHE_ROOT} + ROBODOJO_DEVICE_ID: ${ROBODOJO_DEVICE_ID} + ROBODOJO_RESULT_DIR: ${ROBODOJO_RESULT_DIR} + CUDA_HOME: ${CUDA_HOME} + CUDA_VISIBLE_DEVICES: ${CUDA_VISIBLE_DEVICES} + inputs: + action: policy/action + tick: dora/timer/millis/50 + bench_cmd: + source: bench_endpoint/bench_cmd + queue_size: 16 + outputs: + - proprio_state + - image/head + - image/left_wrist + - image/right_wrist + - policy_command + - benchmark_status + - benchmark_result + - bench_report + - id: policy + path: ${FORGE_RUNTIME_BIN}/robodojo_policy + env: + ROBODOJO_ENV: ${ROBODOJO_ENV} + XPOLICYLAB_ROOT: ${XPOLICYLAB_ROOT} + POLICY_NAME: ${POLICY_NAME} + ENV_CFG_TYPE: ${ENV_CFG_TYPE} + ACTION_TYPE: ${ACTION_TYPE} + TASK_NAME: ${TASK_NAME} + G05_CKPT_PATH: ${G05_CKPT_PATH} + G05_PROCESSOR_PATH: ${G05_PROCESSOR_PATH} + CUDA_HOME: ${CUDA_HOME} + CUDA_VISIBLE_DEVICES: ${CUDA_VISIBLE_DEVICES} + ROBODOJO_CACHE_ROOT: ${ROBODOJO_CACHE_ROOT} + inputs: + tick: dora/timer/millis/20 + policy_command: + source: robodojo_benchmark/policy_command + queue_size: 32 + proprio_state: robodojo_benchmark/proprio_state + image/head: robodojo_benchmark/image/head + image/left_wrist: robodojo_benchmark/image/left_wrist + image/right_wrist: robodojo_benchmark/image/right_wrist + outputs: + - action diff --git a/PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/env.template.sh b/PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/env.template.sh new file mode 100644 index 000000000..7572d7eb9 --- /dev/null +++ b/PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/env.template.sh @@ -0,0 +1,54 @@ +#!/usr/bin/env bash +# robodojo / g05 部署环境模板。 +# +# 用法： +# cp env.template.sh env..sh +# 把下面的 /path/to/... 换成目标机真实值（不要提交带个人路径的副本） +# source env..sh +# python scripts/precheck_robodojo_env.py # GPU-free 预检 +# +# 注意：只包含本 Skill 需要的必要变量，不要用 `env | sort` 导出全量环境。 +# 值里不要带引号包住路径（避免把路径当命令）。 + +# ---------- 工具协议（forge_gateway / forge_tool 源码经 PYTHONPATH 使用） ---------- +# forge_bench 里 install 了版本化依赖 forge-msgs==1.0.1、dora-rs==0.4.1。 +export FORGE_GATEWAY_PYTHON=/path/to/forge_bench/python +# NOTE(node bundles): forge_gateway / forge_tool are shipped inside the installed +# forge_runtime + robodojo_endpoint Node bundles; FORGE_PKGS_ROOT is NOT needed. +export BENCH_ENDPOINT_PYTHON=/path/to/forge_bench/python +# NOTE(node bundles): bench_endpoint is shipped inside the robodojo_endpoint Node bundle; +# BENCH_ENDPOINT_SRC is NOT needed. + +# ---------- RoboDojo / XPolicyLab ---------- +# ROBODOJO_ENV 需 python 3.11(3.11.x)、torch 2.7.0+cu128、isaaclab 0.54.3、 +# isaacsim 5.1.0.0、opencv-python(cv2)。benchmark 录像用 cv2，不需要 ffmpeg。 +export ROBODOJO_ENV=/path/to/robodojo/envs/RoboDojo +export ROBODOJO_ROOT=/path/to/robodojo/repo # 需含 env/ task/ utils/ src/ +export XPOLICYLAB_ROOT=/path/to/robodojo/repo/XPolicyLab # G05 adapter 在 policy/G05 +export ROBODOJO_CACHE_ROOT=/path/to/robodojo/cache # 派生 HF_HOME/MODELSCOPE_CACHE/...；不设则跳过 + +# ---------- G05 模型 / processor ---------- +export G05_CKPT_PATH=/path/to/.../checkpoints/checkpoint # 约 33.9GB，可读 +export G05_PROCESSOR_PATH=/path/to/G05/hf_processor # 需含 config.json/tokenizer.json/tokenizer_config.json 等 + +# ---------- policy 选择（profile 固定） ---------- +export POLICY_NAME=G05 +export ENV_CFG_TYPE=arx_x5 +export ACTION_TYPE=joint +export TASK_NAME=put_bottles_into_dustbin + +# ---------- CUDA / GPU ---------- +# CUDA_HOME 需含 bin/、lib64/。CUDA_VISIBLE_DEVICES 决定策略进程可见 GPU； +# benchmark 的 ROBODOJO_DEVICE_ID 相对“当前可见集合”编号，必须 < 可见 GPU 个数。 +export CUDA_HOME=/path/to/cuda +export CUDA_VISIBLE_DEVICES=0,1 +export ROBODOJO_DEVICE_ID=0 +export ROBODOJO_RESULT_DIR=/path/to/result_dir # 结果落盘目录，需可写 + +# 可选：录像目录；不设则用 profile 默认相对路径。 +# export ROBODOJO_RECORD_DIR=/path/to/record_dir +# dora CLI lives in the bin dir above; paos skill start needs dora on PATH. +export PATH="/path/to/forge_bench/bin:$PATH" +export PAOS_SRC_ROOT=/path/to/paos_src/phyagentos +# Which python runs the PAOS CLI (paos env); used by scripts/accept_robodojo_skill.sh. +export PAOS_PY=/path/to/paos/bin/python diff --git a/PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/gateway.yaml b/PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/gateway.yaml new file mode 100644 index 000000000..da0c2313a --- /dev/null +++ b/PhyAgentOS/skills/forge-skill/robodojo/profiles/g05/gateway.yaml @@ -0,0 +1,188 @@ +# Forge Gateway 配置：把 bench_endpoint 暴露成两个 Tool。 +# +# 与 build_tower 的区别：port 改 19011，避免端口冲突。specs / providers 的 +# 结构性约定完全相同（endpoint_id、input_id/output_id 与 dataflow 通道一一对应， +# 对不上会静默失败，tool 永远 ready:false）。 + +host: 127.0.0.1 +port: 19011 + +# benchmark 场景没有关节流也没有图像流经过网关，两个都留空。 +joint_order: [] +image_input_ids: [] + +readiness: + require_proprio_state: false + require_images: false + +agent: + enabled: false + +tools: + enabled: true + lease_ttl_ms: 3000 + # ⚠️ 每次调用的 deadline，Query 与 Action 共用一个。按「一批最长跑多久」来定， + # 上限由 config.yaml 的 max_total_episodes 兜着。 + invoke_timeout_ms: 3600000 + request_input_id: tool_request + response_output_id: tool_response + + specs: + - tool_id: bench.describe + implementation_id: robodojo.benchmark + endpoint_id: bench.runner + operation: describe + semantics: query + description: >- + Return the live benchmark inventory: available tasks, per-task init state + counts, default parameters, and episode budget limits. Call this before + bench.run; never assume task ids or counts. + input_schema: + type: object + additionalProperties: false + properties: {} + output_schema: + type: object + additionalProperties: false + required: + - benchmark + - suite + - policy_id + - num_tasks + - tasks + - defaults + - limits + properties: + benchmark: {type: string} + suite: {type: string} + policy_id: {type: string} + env_cfg_type: {type: string} + action_type: {type: string} + num_tasks: {type: integer, minimum: 1} + tasks: + type: array + items: + type: object + additionalProperties: false + required: [task_id, num_init_states] + properties: + task_id: {type: integer, minimum: 0} + name: {type: string} + language: {type: string} + num_init_states: {type: integer, minimum: 1} + joint_names: + type: array + items: {type: string} + camera_ids: + type: array + items: {type: string} + defaults: + type: object + additionalProperties: false + required: [num_runs, seed, max_steps] + properties: + num_runs: {type: integer, minimum: 1} + seed: {type: integer} + max_steps: {type: integer, minimum: 1} + limits: + type: object + additionalProperties: false + properties: + max_total_episodes: {type: integer, minimum: 0} + max_max_steps: {type: integer, minimum: 0} + readiness: [] + + - tool_id: bench.run + implementation_id: robodojo.benchmark + endpoint_id: bench.runner + operation: run + semantics: action + description: >- + Run one benchmark batch (task_ids x init_state_ids x num_runs) and return + the aggregate score. Long running: accepted immediately, poll status and + result. Policy weights, suite, and device (G05 / put_bottles_into_dustbin) + are fixed by the profile and are not selectable here. + input_schema: + type: object + additionalProperties: false + required: [task_ids, init_state_ids, num_runs, seed, max_steps] + properties: + task_ids: + description: Task ids from bench.describe; null means every task. + oneOf: + - type: "null" + - type: array + minItems: 1 + items: {type: integer, minimum: 0} + init_state_ids: + description: Init state ids; null means every init state shared by all selected tasks. + oneOf: + - type: "null" + - type: array + minItems: 1 + items: {type: integer, minimum: 0} + num_runs: {type: integer, minimum: 1} + seed: {type: integer} + max_steps: + description: >- + Hard cap on control steps. The episode is terminated as timed_out if + this many steps are reached before the environment terminates. For + RoboDojo the task's native step_lim defines its normal end (success / + partial / failed); set this to at least the task horizon (from + bench.describe defaults) to allow completion, or lower to force an + explicit step-limit stop. Both max_steps and num_steps count control + steps (policy actions). + type: integer + minimum: 1 + output_schema: + type: object + additionalProperties: false + required: + - status + - success_rate + - successes + - total_episodes + - completed_episodes + - result_path + properties: + status: {enum: [succeeded, failed, cancelled]} + primary_metric: + type: object + properties: + name: {type: string} + value: {type: [number, "null"]} + success_rate: {type: [number, "null"], minimum: 0, maximum: 1} + successes: {type: integer, minimum: 0} + total_episodes: {type: integer, minimum: 0} + completed_episodes: {type: integer, minimum: 0} + valid_episodes: {type: integer, minimum: 0} + timed_out_episodes: {type: integer, minimum: 0} + num_steps: {type: integer, minimum: 0} + mean_policy_latency_ms: {type: [number, "null"]} + elapsed_s: {type: [number, "null"]} + obs_republished: + description: Non-zero means observations were re-sent; the score is still valid. + type: [integer, "null"] + result_path: {type: [string, "null"]} + episodes: + type: array + items: + type: object + additionalProperties: false + properties: + task_id: {type: integer} + init_state_id: {type: integer} + run_index: {type: integer} + seed: {type: [integer, "null"]} + success: {type: boolean} + termination: {type: string} + error_code: {type: [string, "null"]} + episodes_truncated: + description: True when the batch was too large to inline; read result_path instead. + type: boolean + readiness: [] + + providers: + - endpoint_id: bench.runner + input_id: bench_tool_in + output_id: bench_tool_out diff --git a/PhyAgentOS/skills/forge-skill/robodojo/skill.yaml b/PhyAgentOS/skills/forge-skill/robodojo/skill.yaml new file mode 100644 index 000000000..fe0815601 --- /dev/null +++ b/PhyAgentOS/skills/forge-skill/robodojo/skill.yaml @@ -0,0 +1,61 @@ +manifest_version: 2 +name: robodojo +version: 0.1.0 +description: Run the RoboDojo G05 benchmark and return its aggregate score. +skill_document: SKILL.md +gateway_url: http://127.0.0.1:19011 +required_tools: +- bench.describe +- bench.run +profiles: + g05: + dataflow: profiles/g05/dataflow.yaml + required_binaries: + - gateway + - bench_endpoint + - robodojo_benchmark + - robodojo_policy + required_assets: + - profiles/g05/gateway.yaml + - profiles/g05/bench_endpoint.yaml + - profiles/g05/config.yaml + required_environment: + - FORGE_GATEWAY_PYTHON + - BENCH_ENDPOINT_PYTHON + - ROBODOJO_ENV + - ROBODOJO_ROOT + - XPOLICYLAB_ROOT + - G05_CKPT_PATH + - G05_PROCESSOR_PATH + - CUDA_HOME + - CUDA_VISIBLE_DEVICES + - ROBODOJO_CACHE_ROOT + - ROBODOJO_DEVICE_ID + - ROBODOJO_RESULT_DIR + environment: + POLICY_NAME: G05 + ENV_CFG_TYPE: arx_x5 + ACTION_TYPE: joint + PYTHONNOUSERSITE: '1' + OMNI_KIT_ACCEPT_EULA: 'YES' +artifacts: + resolver: registry + nodes: + forge_runtime: + artifact_id: forge-runtime-0.1.0 + version: 0.1.0 + platform: linux + arch: x86_64 + digest: cee927eb587f3f958c1803086e59692f6f7ae373477b3cfd15118d01d76c408e + robodojo_endpoint: + artifact_id: robodojo-endpoint-0.1.0 + version: 0.1.0 + platform: linux + arch: x86_64 + digest: b9a66fb07b04ee1f76bb8221f68f96b35d1f1ce136d3d6cf967cb7a34da8e159 + robodojo_benchmark: + artifact_id: robodojo-benchmark-0.1.0 + version: 0.1.0 + platform: linux + arch: x86_64 + digest: e48cf4e838ba73512ac1eb0c144ea17ea177bb56ad41e524c8332f9a38c19ff2 From bbf7d21a658188c5db74b36232531e24914222c9 Mon Sep 17 00:00:00 2001 From: Xiaolv <2116262909@qq.com> Date: Thu, 10 Sep 2026 14:50:34 +0800 Subject: [PATCH 2/3] feat(robodojo): add install and inventory helpers Add the per-run install helper and the unsigned schema-v3 index template. The helper presigns each bucket_key on every run, verifies expected_sha256 for each downloaded object, writes the generated index to a private temp dir, prepares the isolated instance, and resolves paos/tosutil through --paos/--tosutil, then PAOS_BIN/TOSUTIL, then PATH. check_bundle_inventory.py keeps the template inventory in sync with the Skill files. --- .../docs/paos-forge-packages.template.yaml | 574 ++++++++++++++++++ .../scripts/check_bundle_inventory.py | 167 +++++ .../robodojo/scripts/install_robodojo.py | 264 ++++++++ 3 files changed, 1005 insertions(+) create mode 100644 PhyAgentOS/skills/forge-skill/robodojo/docs/paos-forge-packages.template.yaml create mode 100644 PhyAgentOS/skills/forge-skill/robodojo/scripts/check_bundle_inventory.py create mode 100755 PhyAgentOS/skills/forge-skill/robodojo/scripts/install_robodojo.py diff --git a/PhyAgentOS/skills/forge-skill/robodojo/docs/paos-forge-packages.template.yaml b/PhyAgentOS/skills/forge-skill/robodojo/docs/paos-forge-packages.template.yaml new file mode 100644 index 000000000..dfef4f243 --- /dev/null +++ b/PhyAgentOS/skills/forge-skill/robodojo/docs/paos-forge-packages.template.yaml @@ -0,0 +1,574 @@ +# Unsigned schema-v3 static package index template for the robodojo Skill. +# +# Template-only fields (stripped by scripts/install_robodojo.py): +# bucket_key object key inside TOS bucket phyagentos-resource-inner +# expected_sha256 archive sha256 of the published object; the helper re-downloads the +# object, hashes it, and aborts on mismatch. `null` means the object is +# not published yet (candidate). +# +# `paos skill install --index` requires `direct_download_url`, `sha256` and `size`; the +# helper presigns `bucket_key`, measures size and sha256 itself and writes those three +# fields into a generated index. Never feed this template to `--index` directly. +# +# Scope: benchmark and G05 policy node implementations are NOT part of the Skill bundle. +# They are Forge Nodes built from framework/forge_runtime +# (packages/nodes/benchmarks/robodojo, scripts/build_node_artifacts.py) and locked here by +# node_digest. The published 0.1.0 objects are frozen pre-split snapshots and stay +# untouched; the Skill entry below points at the rebuilt post-split candidate, which still +# needs a new object key or version. +schema_version: 3 +packages: +- kind: skill_bundle + package_key: robodojo + artifact_id: robodojo + version: 0.1.0 + platform: linux + arch: x86_64 + description: Run the RoboDojo G05 benchmark and return its aggregate score. + dependencies: + - forge-runtime-0.1.0 + - robodojo-endpoint-0.1.0 + - robodojo-benchmark-0.1.0 + bucket_key: skill-bundles/robodojo/0.1.0/robodojo-0.1.0.tar.gz + expected_sha256: null + inventory: + - path: README.md + sha256: 56381c08a3c46ce8e82bced526a29a7e331adb6a5e61a634b3826549d98087c9 + size: 7350 + category: file + - path: SKILL.md + sha256: 82aac86d637f634453ca94bbe61de112bff7dd4b63d5659db75ee29e0f1f3ec3 + size: 7310 + category: file + - path: docs/DELIVERY_0.1.0.md + sha256: d430abc97a74f974875b7bb59aba39eb92adc3a96b694c736d6aeccb31c93392 + size: 10969 + category: file + - path: profiles/g05/bench_endpoint.yaml + sha256: 9765a4828104c30b16ebe73f09ea0fafa57ba02c21dda75e7d48d9ef593459e4 + size: 618 + category: file + - path: profiles/g05/config.yaml + sha256: 3ccb45faf483fb08f1e7fbae534bf6e1cb2714223ab98b8ac4c8e6fd2e28372c + size: 740 + category: file + - path: profiles/g05/dataflow.yaml + sha256: 050cc1df9a8e9db86cfa0053e0f0b53767daacf3224cc45c2f62b87285a4ae6a + size: 2957 + category: file + - path: profiles/g05/env.template.sh + sha256: 7ae4e5bec354fe05eeae4f67e20ae91ac4d0b8901392c51f9777c3105d438e22 + size: 2857 + category: file + - path: profiles/g05/gateway.yaml + sha256: c5b49b11ee39d4df38c88514c9dc20f4e490efabec43d837bf2bbe8596ac4eb2 + size: 6788 + category: file + - path: scripts/check_bundle_inventory.py + sha256: 81218a85c909c0be95cd46f9d964a331f57570e7fa2db8fd3a3a26ce9c3d8bb3 + size: 6330 + category: file + - path: scripts/install_robodojo.py + sha256: 266eead1af8162a9c57f09f58da8a4a1efb1402571334b6d612ffc79caebf135 + size: 10422 + category: executable + - path: skill.yaml + sha256: 0c5bbdde16b91c10808ce49090486afe5caeb1ff63631ade484bfb03e43e95b8 + size: 1635 + category: file + backend_url: null + direct_download_url: null + archive: + format: tar.gz + todos: >- + Post-split candidate. The published robodojo-0.1.0.tar.gz (sha256 + 5c7806843e5cff16a8a407254ffe7736c9b1d5d13982bd1b82195c7e4f5bc907) still contains the + vendored nodes/ tree and profiles/g05/bin/; publish the rebuilt archive under a new + object key or version before pointing expected_sha256 at it. The inventory omits + docs/paos-forge-packages.template.yaml, which cannot hash itself. +- kind: node_bundle + package_key: forge-runtime-0.1.0 + artifact_id: forge-runtime-0.1.0 + version: 0.1.0 + platform: linux + arch: x86_64 + install_root: ~/.PhyAgentOS/forge_runtime/nodes/forge_runtime + entrypoints: + gateway: bin/gateway + bucket_key: node-bundles/forge_runtime/0.1.0/forge-runtime-0.1.0-linux-x86_64.tar.gz + expected_sha256: c524ae7038775e48f2b0a6036e621913b35b327ad2c710f8a8e0c5cad9e7613b + node_digest: cee927eb587f3f958c1803086e59692f6f7ae373477b3cfd15118d01d76c408e + inventory: + - path: bin/gateway + sha256: cb134ebbc0f3ed0f804606dd07eda73fa74dad0a4f75f21fe135394fcd687339 + size: 369 + category: executable + - path: forge_gateway/__init__.py + sha256: 51035d2c0bb249b54edb472735e3bb20692df33dc41e99b8d0395e015bc74fe6 + size: 58 + category: file + - path: forge_gateway/__main__.py + sha256: 406b7188a391e7691b262bd978dbeeed3ac654264d533005b48cbad968543e37 + size: 61 + category: file + - 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Nothing reads those entries at install time, so editing any Skill +file makes them stale silently. Run this before publishing: + + python3 scripts/check_bundle_inventory.py --check # exit 1 on drift + python3 scripts/check_bundle_inventory.py --write # rewrite the inventory + +``--write`` regenerates only the Skill inventory block; the header comments and +the node entries keep their formatting. Categories are re-derived from the file +mode, so run ``--write`` on the pack host: a Windows checkout has no executable +bit, and ``--write`` there keeps the categories already recorded instead. +""" +from __future__ import annotations + +import argparse +import hashlib +import os +import sys +from pathlib import Path + +SKILL_ROOT = Path(__file__).resolve().parent.parent +TEMPLATE = SKILL_ROOT / "docs" / "paos-forge-packages.template.yaml" +# The template cannot hash itself, and the packager generates archive-manifest.json. +SKIPPED = {"docs/paos-forge-packages.template.yaml", "archive-manifest.json"} +# Windows checkouts do not carry the executable bit. +CHECK_CATEGORY = os.name != "nt" + + +def sha256_file(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as handle: + for chunk in iter(lambda: handle.read(1 << 20), b""): + digest.update(chunk) + return digest.hexdigest() + + +def filesystem_category(path: Path) -> str: + return "executable" if path.stat().st_mode & 0o111 else "file" + + +def actual_files(root: Path) -> list[dict[str, object]]: + found = [ + { + "path": path.relative_to(root).as_posix(), + "sha256": sha256_file(path), + "size": path.stat().st_size, + "category": filesystem_category(path), + } + for path in root.rglob("*") + if path.is_file() and path.relative_to(root).as_posix() not in SKIPPED + ] + return sorted(found, key=lambda item: str(item["path"])) + + +def skill_bounds(lines: list[str]) -> tuple[int, int]: + start = next( + (index for index, line in enumerate(lines) if line.strip() == "- kind: skill_bundle"), + None, + ) + if start is None: + raise SystemExit(f"{TEMPLATE} has no skill_bundle entry") + end = next( + (index for index in range(start + 1, len(lines)) if lines[index].startswith("- kind:")), + len(lines), + ) + return start, end + + +def recorded_entries(lines: list[str], start: int, end: int) -> dict[str, dict[str, str]]: + entries: dict[str, dict[str, str]] = {} + current: str | None = None + for line in lines[start:end]: + stripped = line.strip() + if stripped.startswith("- path: "): + current = stripped[len("- path: ") :].strip() + entries[current] = {} + elif current and ":" in stripped: + key, _, value = stripped.partition(":") + if key in {"sha256", "size", "category"}: + entries[current][key] = value.strip() + return entries + + +def render_block(expected: list[dict[str, object]], recorded: dict[str, dict[str, str]]) -> list[str]: + lines = [" inventory:"] + for item in expected: + path = str(item["path"]) + lines.append(f" - path: {path}") + lines.append(f" sha256: {item['sha256']}") + lines.append(f" size: {item['size']}") + # Keep a recorded category on hosts that cannot report the mode; otherwise + # derive it from the file so a Linux pack host stays authoritative. + category = item["category"] if CHECK_CATEGORY else recorded.get(path, {}).get( + "category", item["category"] + ) + lines.append(f" category: {category}") + return lines + + +def rewrite(lines: list[str], start: int, end: int, block: list[str]) -> list[str]: + output = list(lines[:start]) + index = start + while index < end: + line = lines[index] + if line.strip() == "inventory:": + output.extend(block) + index += 1 + while index < end: + current = lines[index] + if current.startswith(" - path:"): + index += 1 + while index < end and lines[index].startswith(" "): + index += 1 + continue + break + continue + output.append(line) + index += 1 + return output + list(lines[end:]) + + +def main() -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--check", action="store_true", help="report drift (default)") + parser.add_argument("--write", action="store_true", help="rewrite the Skill inventory") + args = parser.parse_args() + + lines = TEMPLATE.read_text(encoding="utf-8").splitlines() + start, end = skill_bounds(lines) + recorded = recorded_entries(lines, start, end) + expected = actual_files(SKILL_ROOT) + by_path = {str(item["path"]): item for item in expected} + + problems: list[str] = [] + for item in expected: + path = str(item["path"]) + entry = recorded.get(path) + if entry is None: + problems.append(f"missing from inventory: {path}") + continue + if entry.get("sha256") != item["sha256"] or entry.get("size") != str(item["size"]): + problems.append(f"stale hash/size: {path}") + elif CHECK_CATEGORY and entry.get("category") != item["category"]: + problems.append(f"stale category: {path}") + for path in sorted(set(recorded) - set(by_path)): + problems.append(f"inventory lists a missing file: {path}") + + if not problems: + print(f"ok: {len(expected)} Skill files match {TEMPLATE.name}") + return 0 + for problem in problems: + print(problem) + if not args.write: + print("run with --write to regenerate the Skill inventory") + return 1 + block = render_block(expected, recorded) + TEMPLATE.write_text("\n".join(rewrite(lines, start, end, block)) + "\n", encoding="utf-8", newline="") + print(f"rewrote the Skill inventory in {TEMPLATE.name}") + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) \ No newline at end of file diff --git a/PhyAgentOS/skills/forge-skill/robodojo/scripts/install_robodojo.py b/PhyAgentOS/skills/forge-skill/robodojo/scripts/install_robodojo.py new file mode 100755 index 000000000..84d8b0037 --- /dev/null +++ b/PhyAgentOS/skills/forge-skill/robodojo/scripts/install_robodojo.py @@ -0,0 +1,264 @@ +#!/usr/bin/env python3 +"""One-shot robodojo install helper (self-contained). + +Reads the unsigned schema-v3 index template shipped next to this script, presigns a fresh +TOS download URL for every ``bucket_key``, downloads each object once to measure ``size`` +and confirm ``expected_sha256``, writes a generated schema-v3 index to a private temp dir, +then calls:: + + paos skill install robodojo --version 0.1.0 --index + +``paos skill install --index`` rejects an index entry that has no ``sha256``/``size``, which +is why the template carries ``bucket_key`` + ``expected_sha256`` instead of a link and a +hand-written size: the helper derives the real values from the object it just downloaded and +aborts on a hash mismatch. + +Requires TOS read permission for the inner bucket plus ``tosutil``; this is a +credential-enabled route, not a credential-less public one. Requires PyYAML (already a PAOS +runtime dependency). + +Self-contained preparation: + * locates the template next to this script (downloaded together from TOS) OR in the repo + layout (