Overview

This repository contains a Streamlit application that integrates multiple components from the LangChain library and Google Generative AI to create an interactive, AI-powered chatbot. The chatbot can process, retrieve, and respond to user queries based on a pre-loaded PDF document. The system employs a vector database for efficient information retrieval and ensures responses are safe by leveraging Google's safety settings.

Features

• Google Generative AI Integration: Utilizes the ChatGoogleGenerativeAI model for generating human-like responses.
• PDF Document Processing: Loads and processes PDF documents into chunks for efficient retrieval.
• Vector Database: Stores processed text chunks in a vector database using Chroma, allowing for fast and accurate query retrieval.
• Streamlit Interface: Provides a simple and interactive user interface for chat-based interaction.
• Safety Settings: Configured to block harmful content using Google's safety settings.

Installation

Prerequisites

Ensure you have the following installed:

• Python 3.8+
• Streamlit
• Google Generative AI
• LangChain
• dotenv

Setup

1. Clone the repository:

   git clone https://github.com/yourusername/your-repo-name.git
   cd your-repo-name

2. Create a virtual environment and activate it:

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

3. Install the required dependencies:

   pip install -r requirements.txt

4. Set up your environment variables by creating a .env file in the root directory:

   GOOGLE_API_KEY=your_google_api_key
   

5. Place the PDF document in the docs directory:

   docs/Merged_Ayurbeat_Everyday_Ayurveda.pdf
   

Usage

1. Run the Streamlit application:

   streamlit run app.py

2. The application will start by checking if a vector database already exists. If not, it will process the provided PDF document, split it into chunks, and create a vector database.

3. Once the setup is complete, the application will load the vector database and present a chat interface.

4. Enter your query in the chat input, and the chatbot will respond based on the content of the processed PDF.

File Structure

• app.py: Main script containing the logic for the Streamlit application.
• docs/: Directory containing the PDF document to be processed.
• per_dir/: Directory where the vector database will be persisted.
• .env: Environment variables, including the Google API key.

Configuration

• Google API Key: Required for using Google Generative AI. Store it in the .env file.
• PDF Loader: Currently set to load a specific PDF document. Modify the path in the script to use a different document.
• Safety Settings: Configurable via the HarmCategory and HarmBlockThreshold parameters in the ChatGoogleGenerativeAI initialization.

Dependencies

The project relies on the following Python packages:

• langchain_chroma
• langchain_google_genai
• google-generativeai
• langchain_community
• dotenv
• streamlit

Ensure all dependencies are installed using the provided requirements.txt.

License

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

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By following the instructions in this README, you can set up and run the AI-powered chatbot that processes and responds to user queries based on the content of a PDF document. The chatbot is designed to provide safe, contextually relevant information while ensuring user interactions are positive and constructive.