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- Added `LifespanNetIndia` and `DiseaseNetMulti` PyTorch models. - Implemented `VCFStreamer` for WGS support. - Added SHAP-based explainability and Backtracking insights. - Updated Streamlit UI with new Dashboard. - Trained models on synthetic data.
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- Added `GenomicBigDataset` for streaming Parquet files. - Updated `train_models.py` to support real data via `--data_dir`. - Added `DATA_INGESTION.md` documentation.
- Scaled `LifespanNetIndia` and `DiseaseNetMulti` to 100 input features. - Added `src/data/biomarkers.py` with 100 clinical definitions. - Updated `streamlit_app.py` to allow CSV upload for clinical data and show biomarker details. - Updated training script to generate 100-dim synthetic data.
- Implemented `DrugGeneGNN` for personalized drug response prediction. - Added `ReportGenerator` to create professional PDF clinical reports. - Updated UI with Pharmacogenomics tab and Report Download button. - Added Clinician Mode toggle. Co-authored-by: VedantMadane <6527493+VedantMadane@users.noreply.github.com>
- Fix `pyproject.toml` build target to correctly include `src` packages (fixes "Unable to determine which files to ship"). - Add `fpdf` and `python-multipart` to `requirements.txt` and `pyproject.toml`. - Run `ruff format` to fix code style issues. - Add `tests/smoke_test.py` to verify key modules and report generation. Co-authored-by: VedantMadane <6527493+VedantMadane@users.noreply.github.com>
- Resolve unused imports and variables in `scripts/download_data.py`. - Fix ambiguous variable name in `demo.py`. - Ensure `pyproject.toml` correctly targets `src` for build. - Confirm `python-multipart` and `fpdf` are in `requirements.txt`. - Add `tests/smoke_test.py` to verify GNN and Report features. Co-authored-by: VedantMadane <6527493+VedantMadane@users.noreply.github.com>
- Reformat `src/models/lifespan_net.py` using `ruff format`. - Fix ambiguous variable names and unused variables manually. - Add `python-multipart` and `fpdf` to `requirements.txt` and `pyproject.toml`. - Add `tests/smoke_test.py` to verify GNN and Report features. Co-authored-by: VedantMadane <6527493+VedantMadane@users.noreply.github.com>
- Confirmed `fastapi`, `uvicorn`, and `python-multipart` are correctly required. - Verified API server starts and responds to health check locally. - Verified code quality with `ruff check` and `pytest`. - (No code changes in this commit, just verification and ensuring CI environment consistency). Co-authored-by: VedantMadane <6527493+VedantMadane@users.noreply.github.com>
- Refactor `src/api/server.py` to use lazy imports for heavy modules (`src.data`, `src.models`). - This prevents `uvicorn` startup from timing out in CI environments where `torch`/`pandas` import takes >5s. - Update Pydantic models to use `json_schema_extra` to fix deprecation warnings. - Verified locally that server starts instantly and passes health check. Co-authored-by: VedantMadane <6527493+VedantMadane@users.noreply.github.com>
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Implemented AI-driven analysis for Dirghayu:
LifespanNetIndiafor biological age andDiseaseNetMultifor CVD, T2D, and Cancer risk.PR created automatically by Jules for task 7839210459985380420 started by @VedantMadane