Gemini PDF Chatbot

Gemini PDF Chatbot is a Streamlit-based application that allows users to chat with a conversational AI model trained on PDF documents. The chatbot extracts information from uploaded PDF files and answers user questions based on the provided context. https://gemini-chatbot-langchain-b8tcswnjvmw4tdr2hynbx2.streamlit.app//

https://github.com/subedinab/gemini-chatbot-langchain

Demo

Features

• PDF Upload: Users can upload multiple PDF files.
• Text Extraction: Extracts text from uploaded PDF files.
• Conversational AI: Uses the Gemini conversational AI model to answer user questions.
• Chat Interface: Provides a chat interface to interact with the chatbot.

Getting Started

If you have docker installed, you can run the application using the following command:

• Obtain a Google API key and set it in the .env file.

  GOOGLE_API_KEY=your_api_key_here

Your application will be available at http://localhost:8501.

Local Development

Follow these instructions to set up and run this project on your local machine.

Note: This project requires Python 3.10 or higher.

1. Clone the Repository:

   git clone https://github.com/subedinab/gemini-chatbot-langchain.git

2. Install Dependencies:

   pip install -r requirements.txt

3. Set up Google API Key:

   • Obtain a Google API key and set it in the .env file.

   GOOGLE_API_KEY=your_api_key_here

4. Run the Application:

   streamlit run main.py

5. Upload PDFs:

   • Use the sidebar to upload PDF files.
   • Click on "Submit & Process" to extract text and generate embeddings.

6. Chat Interface:

   • Chat with the AI in the main interface.
   • Collect User Information: If the chatbot prompts you to provide contact details, fill out the form and click "Submit."

Project Structure

• app.py: Main application script.
• .env: file which will contain your environment variable.
• requirements.txt: Python packages required for working of the app.
• README.md: Project documentation.

Dependencies

• PyPDF2
• langchain
• Streamlit
• langchain-community
• google.generativeai
• dotenv

Acknowledgments

• Google Gemini: For providing the underlying language model.
• Streamlit: For the user interface framework.