LLM Graph Builder MCP

# Project Overview Welcome to our project! This project is built using FastAPI framework to create a fast and modern API with Python. ## Feature API Endpoint : This project provides various API endpoint to perform specific tasks. Data Validation : Utilize FastAPI data validation and serialization feature. Interactive Documentation : Access Swagger UI and ReDoc for interactive API documentation. ## Getting Started Follow these steps to set up and run the project locally: 1. Clone the Repository: > git clone https://github.com/neo4j-labs/llm-graph-builder.git > cd llm-graph-builder 2. Install Dependency : > pip install -t requirements.txt ## Run backend project using unicorn Run the server: > uvicorn score:app --reload ## Run project using docker ## prerequisite Before proceeding, ensure the following software is installed on your machine Docker: https://www.docker.com/ 1. Build the docker image > docker build -t your_image_name . Replace `your_image_name` with the meaningful name for your Docker image 2. Run the Docker Container > docker run -it -p 8000:8000 your_image_name Replace `8000` with the desired port. ## Access the API Documentation Open your browser and navigate to http://127.0.0.1:8000/docs for Swagger UI or http://127.0.0.1:8000/redocs for ReDoc. ## Project Structure `score.py`: Score entry point for FastAPI application ## Configuration Update the environment variable in `.env` file. Refer example.env in backend folder for more config. `OPENAI_API_KEY`: Open AI key to use incase of openai embeddings `EMBEDDING_MODEL` : "all-MiniLM-L6-v2" or "openai" or "vertexai" `NEO4J_URI` : Neo4j URL `NEO4J_USERNAME` : Neo4J database username `NEO4J_PASSWORD` : Neo4j database user password `AWS_ACCESS_KEY_ID` : AWS Access key ID `AWS_SECRET_ACCESS_KEY` : AWS secret access key ## Contact For questions or support, feel free to contact us at christopher.crosbie@neo4j.com or michael.hunger@neo4j.com