os-insight-x

OS Insight X

This application allows users to interact with Galvin's Operating System textbook by asking questions and receiving accurate, context-aware answers. The system leverages LangChain for document processing and LLMWare for intelligent responses.

Features

• Load and process PDF documents from Galvin's OS textbook.
• Split documents into manageable chunks for efficient retrieval.
• Use pre-trained LLMWare models to generate embeddings and provide answers.
• Simple Streamlit interface for easy interaction.

Model Used

The model used in this project is Industry-BERT for Insurance provided by Hugging Face. It was employed for the operating system question-answering task using the RAG (Retrieval-Augmented Generation) framework.

Prerequisites

• Python
• Streamlit
• Hugging Face Hub API token
• Required Python libraries listed in requirements.txt
• If you encounter any issues during installation, then create anaconda env open its terminal then proceed .

Installation

1. Clone the Repository bash git clone https://github.com/yourusername/os-insight-x.git
2. Create and Activate Anaconda Environment
3. Install Dependencies in Anaconda powershell bash pip install -r requirements.txt
4. Set Up Environment Variables
   • Create a .env file in the project root directory.
   • Add your Hugging Face Hub API token: HUGGINGFACEHUB_API_TOKEN=your_huggingfacehub_api_token
5. Run vector.py bash python run vector.py
6. Run app.py bash streamlit run app.py

Built With

• aiblocks
• llmware
• streamlit