https://github.com/sinha532/chat_your_pdf

A Generative AI project, which prioritize the RAG pipeline, adapting the Google's gemini-1.5-flash model, which enables the Q&A with the custom knowledge provided. Entitled with web application view with customized authentication and message retrieval option.
https://github.com/sinha532/chat_your_pdf

django-application genai-usecase python3 rag

Last synced: 3 months ago
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A Generative AI project, which prioritize the RAG pipeline, adapting the Google's gemini-1.5-flash model, which enables the Q&A with the custom knowledge provided. Entitled with web application view with customized authentication and message retrieval option.

• Host: GitHub
• URL: https://github.com/sinha532/chat_your_pdf
• Owner: Sinha532
• Created: 2024-08-01T17:23:01.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-08-02T10:56:07.000Z (5 months ago)
• Last Synced: 2024-10-11T07:05:23.632Z (3 months ago)
• Topics: django-application, genai-usecase, python3, rag
• Language: Python
• Homepage: https://chatyourpdf.vercel.app
• Size: 422 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Generative AI Q&A Web Application

This project is a Generative AI-powered web application that prioritizes the Retrieval-Augmented Generation (RAG) pipeline. It leverages Google's `gemini-1.5-flash` model to enable question and answer functionality with custom knowledge provided by the user. The application includes customized authentication and a message retrieval option for an enhanced user experience.

## Features

- **Generative AI Model**: Utilizes Google's `gemini-1.5-flash` model for accurate and context-aware responses.

- **RAG Pipeline**: Combines retrieval and generation capabilities to provide precise answers based on provided documents.

- **Custom Knowledge Integration**: Users can upload custom documents (PDFs) that the AI will use to generate responses.

- **Web Application**: A user-friendly web interface built with Django.

- **Authentication**: Customized user authentication for secure access.

- **Message Retrieval**: Users can retrieve previous interactions and answers.

### Prerequisites

- Python 3.8 or later

- Django

- Streamlit

- LangChain

- Pandas

- FAISS

- PyPDF2

- dotenv

- Bootstrap (for front-end styling)

### Usage

1. **Sign Up / Log In**: Access the application and either sign up for a new account or log in if you already have one.

2. **Upload Document**: Navigate to the upload section and upload your PDF document.

3. **Ask Questions**: Enter your question in the input field and get answers based on the content of the uploaded document.

4. **Retrieve Messages**: View previous interactions and responses.

## Contributing

Contributions are welcome! Please fork the repository and create a pull request with your changes.

## License

This project is licensed under the MIT License.

## Contact

For any questions or suggestions, feel free to contact the project maintainer at [[email protected]].