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ProCode FloatChat

AI-powered chat interface for analyzing oceanographic data. Developed for Smart India Hackathon, FloatChat makes complex scientific datasets accessible through natural language queries.

Python LangChain Streamlit PostgreSQL RAG

Project Overview

FloatChat is an AI-powered application that makes oceanographic data analysis intuitive and accessible. Built during Smart India Hackathon, it combines the ARGO dataset (global ocean measurements) with advanced natural language processing. Instead of writing SQL queries, users ask questions in plain English, and the system intelligently generates appropriate database queries, visualizations, and insights for marine research.

Key Features

  • Natural language query interface for oceanographic data
  • RAG pipeline for accurate data retrieval and analysis
  • Dynamic SQL generation from conversational queries
  • Interactive data visualizations (Plotly, Pydeck)
  • Automated ARGO data ingestion pipeline
  • Data export functionality (CSV, insights)

Technical Stack

Backend & Data
Python, PostgreSQL, PostGIS
AI & ML
LangChain, Groq (Llama 3.1), FAISS
Frontend
Streamlit, Plotly, Pydeck
Deployment
Streamlit Cloud, GitHub

Project Highlights

FloatChat demonstrates advanced proficiency in full-stack AI development, combining advanced RAG techniques with practical oceanographic research applications. The project integrates spatial database queries (PostGIS), real-time LLM inference (Groq), vector similarity search (FAISS), and interactive data visualization. It showcases expertise in turning complex scientific challenges into intuitive, user-friendly solutions for Smart India Hackathon.

ProCode float-chat
Status
✓ Completed