kg_builder/README.md

Knowledge Graph Builder

Description

This project builds and queries knowledge graphs from Wikipedia articles using the LangChain library and OpenAI's language models, storing data in a Neo4j database.

Features

• Knowledge Graph Construction: Build graphs from Wikipedia articles.
• Graph-Based Querying: Utilize graphs to answer queries with a Graph Cypher QA Chain.
• Environment Flexibility: Manages dependencies and environment variables through .env files.

Prerequisites

• Python 3.8+
• pip and virtualenv (optional)
• Access to a Neo4j database
• OpenAI API key
• Extra change

Installation

1. Clone the repository:

   git clone git@hf.co:Master-Thesis-Prakhar/GraphRAG
   cd GraphRAG
   

2. Set up a Python virtual environment (optional):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`
   

3. Install the required packages:

   pip install -r requirements.txt
   

4. Set up your environment variables:
   • Copy the .env.example to .env:

     cp .env.example .env
     

   • Edit the .env file to include your specific configurations such as OPENAI_API_KEY, NEO4J_URL, NEO4J_USERNAME, and NEO4J_PASSWORD.

Usage

1. Create Graph

   python3 kg_builder/src/graph_creation.py
   

2. Run the main script:

   python main.py
   

Contributing

Contributions are welcome! To contribute:

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request