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RAG-nificent: Real-time Accessible PDFs, Reports, and Guidelines

Lightning Chatbot Logo

RAG-nificent is a state-of-the-art repository that leverages the power of Retrieval-Augmented Generation (RAG) to provide instant answers and references from a curated directory of PDFs containing UN guidelines and other regulatory documents. This system is designed to aid researchers, policy makers, and the public in quickly finding specific information within extensive documents.

Features

  • Conversational Interface: Engage with the system using natural language queries to receive responses directly sourced from the PDFs.
  • Direct Citation: Every response from the system includes a direct link to the source PDF page, ensuring traceability and verification.
  • PDF Directory: A predefined set of key PDF documents, currently including UN guidelines on major health topics such as schistosomiasis and malaria.

Demo

RAG-nificent Demo

How It Works

The application utilizes a combination of OpenAI embeddings, Pinecone vector search, and a conversational interface to provide a seamless retrieval experience. When a query is made, the system:

  1. Converts the query into embeddings.
  2. Searches for the most relevant document sections using Pinecone's vector search.
  3. Returns the answer along with citations and links to the source documents.

Setup

  1. Clone the repository:

    git clone https://github.com/yourusername/RAG-nificent.git

  2. Install dependencies:

    pip install -r requirements.txt

  3. Set environment variables in a .env (also see .env.examplefile:

    • PINECONE_INDEX_NAME
    • PINECONE_NAME_SPACE
    • OPENAI_API_KEY
    • PINECONE_API_KEY

  4. Create a Pinecone index with the same name as PINECONE_INDEX_NAME. Set it up with dimensions=1536 and metric=cosine.

  5. Place your PDFs in the pdf_data directory and run data_ingestion.py

  6. Run the application:

    chainlit run app.py

Source Documents

The system currently includes guidelines from the following PDFs with direct links to the documents:

License

This project is licensed under the MIT License.