Case study / Project archive
FloatChat
A conversational exploration prototype for ARGO ocean-float records and visualizations.
Historical project; AI-assisted development. Individual and team contribution has not been independently verified.
The idea
The problem
Ocean-profile records are awkward to explore through chat alone. Pair filtered retrieval with maps and depth plots that expose the underlying profile context.
The implementation
What I built
The implementation connects question routing, filtered profile views, retrieval context, and scientific-style visualizations. Personal task attribution is not established by the README's placeholder team table.
- Python
- Streamlit
- FAISS
- Plotly
Features
- Route questions by intent and extract region/month filters before visualizing ocean profiles.
- Retrieve profile summaries with FAISS or a cosine-similarity fallback for a prompted answer.
- Plot float maps, temperature/salinity depth profiles, time series, and regional comparisons.
Architecture
- Streamlit coordinates a Python query router, retrieval pipeline, and Plotly visualization module.
- A Parquet-backed profile dataset and summary index feed filters and semantic retrieval; a configured Groq service generates answers.
Engineering decisions
- Label the bundled dataset as synthetic rather than presenting its charts as newly obtained ARGO observations.
Validation and measured results
- Source reviewed on 15 October 2026. The application and its external integrations were not executed in this review.
- The README explicitly lists synthetic Indian Ocean profiles; routing, retrieval, and plotting functions were inspected. No answer-quality or scientific-data validation was rerun.
Limits and unfinished work
- Charts over synthetic profiles do not establish oceanographic findings or coverage of the live ARGO archive.
- Older source can contain superseded descriptions. Numerical impact, adoption, awards, and deployment claims are not carried into this entry.
Evidence and sources
- Reviewed source and implementation
Public README and selected implementation files; source inspection only, without a reproduced runtime or benchmark. Inspected files: router.py, rag_chain.py, visualizer.py.