Here’s a README.md template for your project, explaining its purpose and mentioning that it’s still in progress:

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Local AI-Powered Document Assistant

Welcome to the Local AI-Powered Document Assistant project! This tool is designed to process and analyze unstructured documents locally using DeepSeek 8B (via Ollama) and Retrieval-Augmented Generation (RAG). It aims to provide semantic search, summarization, and question-answering capabilities while ensuring privacy and offline functionality.

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🚀 Project Overview

The goal of this project is to create a local AI-powered assistant that can:

• Process and analyze unstructured documents (PDFs, text files, etc.).
• Enable semantic search and summarization using a vector database (FAISS) and LangChain.
• Provide a user-friendly web interface (built with Streamlit) for uploading documents, asking questions, and viewing results—all running offline for enhanced privacy and security.

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🛠️ Current Progress

• DeepSeek 8B installed locally using Ollama on macOS.
• Virtual environment set up for the project.
• Next Steps:
  • Integrate FAISS for vector storage and retrieval.
  • Implement LangChain for RAG-based document processing.
  • Build the Streamlit web interface for user interaction.

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🧩 Tech Stack

• AI Model: DeepSeek 8B (via Ollama)
• Frameworks: LangChain, FAISS
• Web Interface: Streamlit
• Programming Language: Python 3.9+
• Environment: Virtual environment (e.g., venv or conda)

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📂 Project Structure

Local-AI-Document-Assistant/
├── .env                  # Environment variables
├── requirements.txt      # Python dependencies
├── app/                  # Streamlit web app
│   ├── main.py           # Main application logic
│   └── utils/            # Utility functions
├── data/                 # Folder for uploaded documents
├── models/               # Local AI model files
└── README.md             # Project documentation

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🚧 Work in Progress

This project is currently under development. I’m actively working on integrating the AI model, building the document processing pipeline, and creating the user interface. Stay tuned for updates!

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🤝 Contributing

If you’re interested in contributing or have suggestions, feel free to reach out or submit a pull request. Let’s build something amazing together!

• Email: [email protected]
• LinkedIn: https://www.linkedin.com/in/sriram-vivek-58a673269/

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📄 License

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

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⚡ Making document processing smarter, faster, and more private ⚡

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