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README.md

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

  1. 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