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FloatChat 🌊 – AI-Powered ARGO Data Explorer

FloatChat is an AI-powered conversational interface for exploring ARGO float oceanographic data. It allows users to query, explore, and visualize oceanographic information using natural language.

📝 Features

  • Chatbot-style interface with ChatGPT-style bubbles
  • Floating input at the bottom for easy conversation
  • Interactive visualizations:
    • Float locations on a map
    • Pressure and other parameter time-series
  • Backend:
    • PostgreSQL for structured ARGO data
    • ChromaDB for vector search and metadata retrieval
    • Retrieval-Augmented Generation (RAG) for natural language query handling

💻 Tech Stack

  • Python 3.x
  • Streamlit – Frontend dashboard and chat interface
  • Plotly & Leaflet – Interactive plots and maps
  • PostgreSQL – Structured ARGO dataset
  • ChromaDB – Vector database for semantic search
  • Flan-T5 / Local LLM – Query interpretation

🚀 Demo Queries

Try the following queries in the chat interface:

  1. Show me the temperature and pressure profiles of ARGO floats near the equator.
  2. Compare salinity levels in the Arabian Sea and Bay of Bengal over the last 6 months.
  3. What are the nearest ARGO floats to latitude 10°N and longitude 75°E?
  4. Show me pressure vs depth for floats in the Indian Ocean.
  5. Plot the pressure trends of ARGO floats in March 2023.

🗂 Project Structure

floatchat/ ├─ front_end/ # Streamlit app and CSS ├─ utils/ # Visualization utilities ├─ backend.py # LLM query handling and RAG ├─ db_config.py # PostgreSQL & ChromaDB connections ├─ requirements.txt # Python dependencies ├─ .env # Environment variables

yaml Copy code

⚡ How to Run

  1. Activate your virtual environment: & D:/my_project/venv/Scripts/Activate.ps1 Run the Streamlit app:

bash Copy code cd D:\floatchat streamlit run front_end/app.py Open in your browser: http://localhost:8501/

📌 Notes Demo uses a subset of 500 ARGO floats for speed.

Designed for internal hackathon PoC.

Fully functional chat + inline visualizations for Indian Ocean ARGO dataset.

🔗 Future Work Full ARGO dataset integration

Additional BGC and satellite data

Enhanced RAG pipeline for advanced queries

Improved UI/UX and multi-modal visualizations

📄 License This README is hackathon-ready, shows all the features, instructions, and tech stack, and looks professional for HR viewing.