Welcome to the Chainlit-based chatbot project! This project leverages cutting-edge technologies like GraphRAG, query expansion, document segmentation, and embedding using OpenAI's text-embedding-3-small model to deliver exceptional conversational AI capabilities.
- GraphRAG Integration: Enhance response generation using Graph-based Retrieval-Augmented Generation.
- Query Expansion: Improve search accuracy by expanding user queries with related terms.
- Document Segmentation: Efficiently handle large documents by breaking them down into manageable segments.
- Embedding with OpenAI: Leverage OpenAI's state-of-the-art text-embedding-3-small model for effective semantic understanding.
Follow these steps to set up the project on your local machine:
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Clone the Repo
git clone https://github.com/SuperGalaxy0901/GraphRAG-Chainlit.git cd chainlit-chatbot -
Install Dependencies
- Make sure you have Python installed on your system. This project requires Python 3.7 or higher.
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Set up Environment Variables
- Ensure your API keys and necessary credentials are correctly set in your environment variables. You might need
OPENAI_API_KEY, etc.
- Ensure your API keys and necessary credentials are correctly set in your environment variables. You might need
After installation, you can start the chatbot with the following command:
python app.py- Open your browser and navigate to
http://localhost:8000to start chatting! 🤖 - You can type your queries in the chatbox, and the chatbot will respond by leveraging the powerful combination of GraphRAG, query expansion, and document segmentation.
You can configure various settings of the chatbot by editing the settings.yaml file.
- API Keys: Set your OpenAI and other service API keys.
- Segmentation Parameters: Adjust how documents are segmented to suit your use case.
- Model Settings: Customize the embedding model parameters per your needs.