README.md

metadata

title: Sagar's Personal Assistant
emoji: 🌟
colorFrom: purple
colorTo: blue
sdk: streamlit
sdk_version: 1.41.0
app_file: app.py
pinned: false

Sagar's Personal Assistant 🌟

A friendly, personal RAG-based chatbot that answers questions about Sagar using AI and documents (resume.pdf, myself.txt).

Features

• 🤖 Powered by Google AI Studio Gemini 2.5 Flash
• 💬 Friendly, warm personality with emoji responses
• 📚 RAG (Retrieval-Augmented Generation) for accurate answers
• 🎨 Clean Streamlit web interface

Setup

1. Install Dependencies:

   pip install -r requirements.txt
   

2. Environment Variables: Ensure .env exists with your GOOGLE_API_KEY.

Usage

1. Ingest Data: Process your PDFs and text files to create the vector database.

   python src/ingest.py
   

   Run this whenever you add new files to the data/ folder.

2. Run Chatbot (Web Interface): Start the Streamlit web chat interface.

   streamlit run app.py
   

3. Run Chatbot (CLI): Start the command-line interface.

   python src/main.py
   

Project Structure

• data/: Place your PDF and TXT files here.
• app.py: Streamlit web application.
• src/rag.py: Core RAG logic (Retrieval + Generation).
• src/main.py: Command-line interface.
• src/ingest.py: Script to load data and generate embeddings (FAISS).
• src/vectorstore/: Stores the generated FAISS index.