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🚀 GraphRAG Example App

An example application that demonstrates how to use LangChain's graph_vectorstores and CassandraGraphVectorStore to add structured data to RAG (Retrieval-Augmented Generation) applications. The app scrapes content from specified URLs, processes the content, and performs vector similarity and graph traversal searches.

  ____                 _     ____      _    ____ 
 / ___|_ __ __ _ _ __ | |__ |  _ \    / \  / ___|
| |  _| '__/ _` | '_ \| '_ \| |_) |  / _ \| |  _ 
| |_| | | | (_| | |_) | | | |  _ <  / ___ \ |_| |
 \____|_|  \__,_| .__/|_| |_|_| \_\/_/   \_\____|
                |_|                                           
                        *no graph database needed!!!

📦 Installation

  1. Clone the repository:

    git clone https://github.com/datastaxdevs/graph-rag-example.git
cd graphRAG_example

  2. Create and activate a virtual environment:

    python3 -m venv venv
source venv/bin/activate

  3. Install the required dependencies:

    pip install -r requirements.txt

  4. Set up the environment variables:

    • Copy the .env.example file to .env: 
      cp .env.example .env
    • Fill in the required environment variables in the .env file.

🚀 Launch the App

  1. Run the main script: 
    python app.py

This will start the application, scrape the specified URLs, process the content, and perform vector similarity and graph traversal searches.

📜 License

This project is licensed under the MIT License.