TalkToFiles: Conversational RAG Chatbot

TalkToFiles is a web application built using Gradio and Haystack, designed to enable users to upload documents and interact with their content through a conversational AI interface. This chatbot leverages Retrieval-Augmented Generation (RAG) to provide accurate and context-aware answers by retrieving information from document content.

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App Demo Link

Features

• Document Upload: Upload multiple files in PDF, Markdown, or Text format.
• Document Store Creation: Automatically preprocess and store document content for querying.
• Conversational Interface: Ask questions and get responses based on uploaded document content.
• Memory Integration: Maintains context throughout the conversation for more natural interactions.

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Tech Stack

• Gradio: Provides the web interface for document uploads and chat functionality.
• Haystack: Powers the RAG pipeline for document preprocessing and retrieval.
• Cohere: Used for query rephrasing and response generation.
• SentenceTransformers: For creating document embeddings.

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Installation

1. Clone the repository:

   git clone <repository-url>

2. Navigate to the project directory:

   cd TalkToFiles

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables:

   • Create a .env file in the root directory.
   • Add your API key for Cohere:

     COHERE_API_KEY=your_api_key_here
     

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Usage

1. Start the application:

   python main.py

2. Upload Documents:

   • Use the interface to upload PDF, Markdown, or Text files.
   • Click the "Create Document Store" button to preprocess and store the documents.

3. Chat with Documents:

   • Type your query in the chat interface.
   • Receive contextually accurate responses based on the document content.

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File Structure

• main.py: Contains the Gradio interface and application logic.
• module.py: Defines the pipelines and components for preprocessing, retrieval, and query handling.

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Example Workflow

1. Upload a PDF document containing information about Artificial Intelligence.
2. Initialize the document store.
3. Ask the chatbot: "What is Artificial Intelligence?"
4. Receive an accurate, document-based response.

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License

This project is licensed under the MIT License. See the LICENSE file for details.