RAG Application (Gemini)

Description

The RAG Application (Gemini) is a Streamlit web application designed to question answering system that retrieves information from uploaded PDFs using Google Generative AI and LangChain. Ask questions about the document's content and get detailed, context-aware answers.

Technologies Used

• Streamlit: The web framework used for building the interactive user interface.
• Google Generative AI (Gemini): A powerful language model used for natural language understanding and question answering. You can learn more about Gemini here.
• LangChain: A library for building language-based applications, used for creating custom prompts and managing text data.
• ChromaDB: A vector store used for efficient storage and retrieval of embeddings generated by the Google Generative AI model.

Demo

You can access the live demo here.

Table of Contents

• Installation
• Usage
• Configuration
• Contributing
• License

Installation

1. Clone the repository:

   git clone https://github.com/isurulkh/rag-application-gemini.git

2. Navigate to the project directory:

   cd rag-application-gemini

3. Create a virtual environment (optional but recommended):

   python -m venv venv

4. Activate the virtual environment:

   • On Windows:

     venv\Scripts\activate

   • On macOS/Linux:

     source venv/bin/activate

5. Install the dependencies:

   pip install -r requirements.txt

Usage

1. Run the Streamlit app:

   streamlit run app.py

2. Open your browser and go to http://localhost:8501.

3. [Provide any additional usage instructions].

Configuration

Environment Variables

• GOOGLE_API_KEY: Obtain a Google Generative AI API key from the Google Cloud Console and set it as an environment variable.

  export GOOGLE_API_KEY=your_google_api_key

Contributing

If you would like to contribute to the project, follow these steps:

1. Fork the repository.

2. Create a new branch:

   git checkout -b feature/my-feature

3. Commit your changes:

   git commit -m "Add my feature"

4. Push to the branch:

   git push origin feature/my-feature

5. Create a pull request.

License

This project is licensed under the MIT License.