Study Buddy - Personal Study Assistant

Study Buddy is an interactive AI-powered study assistant that helps users engage with their study materials through a chat interface. The application uses LangChain and Ollama to provide intelligent responses based on uploaded PDF documents.

Features

• PDF document processing and analysis
• Interactive chat interface
• Support for multiple LLM models (llama2, mistral)
• Adjustable AI temperature settings
• Conversation memory
• Document embedding and semantic search

Prerequisites

• Python 3.x
• Ollama installed and running on your system

Installation

1. Clone the repository and install the required dependencies:

pip install streamlit langchain faiss-cpu pypdf python-magic-bin llamaindex
pip install langchain-community
pip install "unstructured[pdf]" python-magic

Usage

1. Start the application:

streamlit run app.py

2. Configure the application:

   • Enter the directory path containing your PDF study materials
   • Select your preferred LLM model (llama2 or mistral)
   • Adjust the temperature setting for AI responses
   • Click "Initialize Study Buddy" to process your documents

3. Start chatting with Study Buddy about your study materials

Configuration

The application allows you to configure:

• Document directory path
• LLM model selection (llama2 or mistral)
• AI temperature (0.0 - 1.0)

Technical Stack

• Streamlit: Web interface
• LangChain: LLM framework
• FAISS: Vector store for document embeddings
• Ollama: LLM model provider
• DirectoryLoader: PDF document processing

Project Structure

study-buddy/
├── app.py          # Main application file
├── requirements.txt # Project dependencies
└── README.md       # Project documentation

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.