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rag-langgraph-qa-assistant

RAG-powered LangGraph QA Assistant using embeddings and LLM

RAG-Powered LangGraph QA Assistant

This project is a Retrieval-Augmented Generation (RAG) powered AI assistant that answers questions based on a text file (sample.txt) using embeddings and a large language model (LLM).

Features

• Uses FAISS for vector search on text chunks.
• Integrates Sentence Transformers for embeddings.
• Uses FLAN-T5 as the LLM for question answering.
• Provides a Gradio web interface for interactive QA.
• Example questions included in sidebar for quick testing.

Setup Instructions

1. Clone/download this repository.
2. Ensure Python 3.10+ is installed and added to PATH.
3. Install dependencies:

   pip install -r requirements.txt
   

How To Run

1. Open a terminal/command prompt in the project folder.
2. Run: python main.py Or, if your system uses python3: python3 main.py
3. The Gradio web interface will start, and a local URL will be printed in the console.
4. Open this URL in your browser to interact with the assistant.

Note: The FAISS index (faiss_index.bin) is automatically created when you run main.py for the first time.

1d911e5 (Initial commit: RAG LangGraph QA Assistant)