Getting Started

Live Demo

Running locally

Run FalkorDB

Free cloud instance: https://app.falkordb.cloud/signup

Or by running locally with docker:

docker run -p 6379:6379 -p 3000:3000 -it --rm falkordb/falkordb:latest

Config

Create your own .env file from the .env.template file

Install dependencies

Install project dependencies:

uv sync

Start the server:

uv run flask --app api/index.py run --debug

Creating a graph

Process a local source folder:

curl -X POST http://127.0.0.1:5000/analyze_folder -H "Content-Type: application/json" -d '{"path": "<FULL_PATH_TO_FOLDER>", "ignore": [<OPTIONAL_IGNORE_LIST>]}' -H "Authorization: <.ENV_SECRET_TOKEN>"

For example:

curl -X POST http://127.0.0.1:5000/analyze_folder -H "Content-Type: application/json" -d '{"path": "/Users/roilipman/Dev/GraphRAG-SDK", "ignore": ["./.github", "./build"]}' -H "Authorization: OpenSesame"

Working with your graph

Once the source code analysis completes your FalkorDB DB will be populated with a graph representation of your source code, the graph name should be the same as the name of the folder you've requested to analyze, for the example above a graph named: "GraphRAG-SDK".

At the moment only the Python and C languages are supported, we do intend to support additional languages.

At this point you can explore and query your source code using various tools Here are several options:

1. Code-Graph UI
2. FalkorDB Browser
3. One of FalkorDB's clients
4. Use FalkorDB GraphRAG-SDK to connect an LLM for natural language exploration.