Adanvced Multidatabased RAG Chatbot

Advanced RAG Q&A Application with LangChain

Overview

This project demonstrates the creation of an advanced Retrieval Augmented Generation (RAG) Q&A application using LangChain. By integrating multiple data sources—Wikipedia, a custom website, and a research paper database (RIVE)—this application provides comprehensive answers by dynamically selecting the most relevant data source for each query.

Highlights

• Integration of Multiple Data Sources: Creates wrappers for Wikipedia, a custom website, and RIVE, enabling interaction with these sources as distinct entities.
• LangChain Agents: Uses LangChain agents to dynamically select the appropriate tool based on user queries.
• Combining Tools: Combines multiple tools into a single list using Python and connects them with the chosen LLM model via create_openai_tool_agent.
• Prompt Templates: Utilizes prompt templates from LangChain’s Hub to guide LLM interactions.
• Agent Execution: Executes the agent and tools using agent_executor to retrieve information and provide comprehensive responses.

Installation

1. Clone the Repository:

   git clone https://github.com/your-repo/advanced-rag-qa-app.git
   cd advanced-rag-qa-app

2. Install Dependencies: pip install -r requirements.txt
3. Set Up Environment Variables: Create a .env file in the root directory and add the following variables:
   • OPENAI_API_KEY=your_openai_api_key
   • WIKIPEDIA_API_KEY=your_wikipedia_api_key
   • CUSTOM_WEBSITE_URL=your_custom_website_url

Usage Run the Application: streamlit run app.py

Interact with the Application: Open the provided URL in your browser to start querying the RAG Q&A application.

Project Structure

app.py: Main script to run the Streamlit app.

config.py: Configuration settings and environment variables.

langchain_utils.py: Utility functions for LangChain integration.

data_sources/: Contains wrappers for Wikipedia, custom website, and RIVE.

templates/: Prompt templates used for guiding LLM interactions.

requirements.txt: List of Python dependencies.

Contributing If you would like to contribute to this project, please fork the repository and submit a pull request with your changes.