Multi_collabration_chatbot

Multi-Agent Collaboration Chatbot

This project is a multi-agent collaboration chatbot designed to answer questions related to stock markets using multiple tools and APIs. It intelligently combines:

• LanceDB: For retrieving information from uploaded PDF documents.
• Polygon API: For real-time finance-related data.
• Tavily Search: For advanced internet search capabilities.

The chatbot is powered by Streamlit, providing an intuitive web interface for uploading documents and asking questions.

---

Features

1. PDF Document Knowledge Base:

   • Upload stock market-related PDF files to build a knowledge base.
   • Extracts and indexes document content using LanceDB for quick retrieval.

2. Tool Integration:

   • LanceDB: Used for answering questions based on uploaded PDFs.
   • Polygon API: Fetches real-time finance-related data (e.g., stock prices, company financials).
   • Bing Search: Retrieves news and additional web content.
   • Tavily Search: Provides an advanced internet search experience.

3. Fallback Mechanism:

   • The chatbot first attempts to answer questions using the uploaded documents.
   • If no relevant answer is found, it intelligently switches to other tools (e.g., Polygon API, Bing, or Tavily).

4. Streamlit Interface:

   • User-friendly interface to upload documents, ask questions, and get responses.

---

How It Works

1. Uploading Documents

Users must upload PDF files related to the stock market to build a document-based knowledge base. These documents are processed and split into manageable chunks for efficient retrieval.

2. Question Answering Flow

• Document-Based Retrieval:
  • The chatbot first searches the uploaded PDFs for an answer using LanceDB.
• Fallback to Other Tools:
  • If no relevant information is found in the documents, the chatbot uses:
    • Polygon API: For finance-related real-time data (e.g., stock prices, financial statements).
    • Bing or Tavily: For internet-based queries or news.

Example Use Case

Scenario: Stock Market Q&A System

1. Upload a PDF file containing information about the stock market.
2. Ask questions like:
   • "What is gap up & down in share ? Answer is featched using RAG- Lancedb Tool
   • "What are the financial statements of AAPL ?" Answer is fetched using the Polygon Tool
   • "Latest news about the S&P 500?"
     • Answer is retrieved using Tavily Tool

---

Prerequisites

1. Install Dependencies

Ensure you have Python installed and set up a virtual environment. Then, install the required libraries:

pip install -r requirements.txt

2. Set Up APIs

Obtain API keys for:

• Polygon API https://polygon.io/docs/stocks/getting-started
• Tavily Search API https://tavily.com/getting-started

Add these keys to your environment variables or configuration file.

---

Running the Application

1. Clone the repository.
2. Navigate to the project directory.
3. Run the Streamlit application:

   streamlit run main.py

4. Open the provided URL in your browser.