/PS4-GPTeam

RX-Assistant is a RESTful API + Chainlit RAG chatbot using ChromaDB for storage, Google Generative AI for responses, and Hugging Face for embeddings.

Primary LanguagePython

PS4-GPTeam

This repository contains a powerful assistant built using Flask and various machine learning models to extract key information from user queries and documents. It supports various document formats such as PDF, PPT, DOCX, and images, allowing users to upload and extract relevant information dynamically.

Table of Contents

Screenshot

Diagram

Data Flow

Diagram

Video Demonstration

You can watch the demonstration video by clicking the link below:

Watch the Video

Features

  • Extracts key information from various document types using Optical Character Recognition (OCR).
  • Supports multiple actions such as creating orders, checking eligibility, generating leads, and more.
  • Implements a conversational interface that keeps track of user sessions and pending actions.
  • Uses the Gemini and Flan-T5 models for understanding and processing queries.

Installation

  1. Clone the repository:

    git clone https://github.com/HackRx50/PS4-GPTeam.git
cd PS4-GPTeam

  2. Create a virtual environment:

    python3 -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

  3. Install the required packages:

    pip install -r requirements.txt

  4. Set your Google API key:

    export GOOGLE_API_KEY='YOUR_API_KEY'

Usage

To run the application, follow these steps:

  1. Start the Flask application:

    python app.py

    The application will start on http://localhost:3000.

  2. Run the Chainlit interface:

    chainlit run frontend.py

    You can now chat with the assistant through the Chainlit interface.

API Endpoints

Upload Document

  • POST /upload_document
  • Description: Uploads a document and extracts text.
  • Parameters:
    • document: The document file to upload (supports PDF, PPT, DOCX, images, etc.).

Chat

  • POST /chat
  • Description: Sends a query to the assistant and receives a response.
  • Headers:
    • x-user-id: Unique identifier for the user.
    • x-session-id: Unique identifier for the user session.
  • Parameters:
    • query: The user's query as a string.
    • document_id: Optional document ID to use for context.

Contributing

If you would like to contribute to this project, please fork the repository and submit a pull request. Contributions are welcome!

License

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

Author Information