Prototype experimental

.gitignore

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+# Node
+node_modules/
+dist/
+.vite/
+
+# Python
+__pycache__/
+*.py[cod]
+*.pyo
+*.egg-info/
+*.egg
+.eggs/
+*.whl
+.venv/
+venv/
+env/
+
+# Byte-compiled / optimized
+*.so
+
+# Jupyter
+.ipynb_checkpoints/
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+.DS_Store
+Thumbs.db
+
+# Environment
+.env
+.env.local
+.env.*.local
+
+# Logs
+*.log
+npm-debug.log*
+
+# macOS
+__MACOSX/
+
+# Model artifacts (large binaries)
+*.pkl
+
+# Misc
+*.bak
+*.tmp

Dockerfile.backend

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+FROM python:3.11-slim
+
+WORKDIR /app
+
+# Copy dependency manifests
+COPY requirements.txt .
+COPY backend/requirements.txt backend/requirements.txt
+COPY earnings/earnings/requirements.txt earnings/earnings/requirements.txt
+COPY drivepulse_stress_model/requirements.txt drivepulse_stress_model/requirements.txt
+
+# Install Python dependencies
+RUN pip install --no-cache-dir -r requirements.txt \
+    && pip install --no-cache-dir -r backend/requirements.txt \
+    && pip install --no-cache-dir -r earnings/earnings/requirements.txt \
+    && pip install --no-cache-dir -r drivepulse_stress_model/requirements.txt
+
+# Copy source code
+COPY backend/ backend/
+COPY earnings/ earnings/
+COPY drivepulse_stress_model/ drivepulse_stress_model/
+
+ENV PYTHONUNBUFFERED=1
+
+EXPOSE 8000
+
+# Match local dev layout: run from /app/backend so imports like `from utils...`
+# and `from data...` resolve the same as `cd backend && python main.py`
+WORKDIR /app/backend
+
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
+
+

Dockerfile.frontend

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+FROM node:20-alpine AS build
+
+WORKDIR /app
+
+COPY frontend/package*.json ./
+RUN npm ci
+
+COPY frontend/ .
+RUN npm run build
+
+FROM nginx:1.27-alpine
+
+WORKDIR /usr/share/nginx/html
+
+COPY --from=build /app/dist ./
+
+COPY nginx.conf /etc/nginx/conf.d/default.conf
+
+EXPOSE 80
+
+CMD ["nginx", "-g", "daemon off;"]
+

Procfile

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+web: uvicorn backend.main:app --host 0.0.0.0 --port ${PORT:-8000}

README.md

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+# 🚗 DrivePulse
+
+Real-time driver wellness & earnings intelligence platform for ride-hailing drivers. Uses on-device sensor data (accelerometer, gyroscope, microphone) with ML models to detect stressful driving situations and forecast earnings velocity.
+
+---
+
+## Features
+
+- **Dashboard** — Daily trips, earnings, stress score, timeline
+- **Trip Detail** — Map playback, sensor charts, event detection with explainability
+- **Trends** — Weekly/monthly earnings, stress, and velocity charts
+- **Goals** — Set and track daily earnings targets
+- **Predict** — Enter sensor/earnings values → instant ML prediction *(judge-facing)*
+- **Batch Upload** — Upload CSV → run inference on multiple trips at once *(judge-facing)*
+- **Explainability** — Per-event feature contributions, confidence badges
+- **Feedback** — Thumbs up/down on detected events
+- **Auth** — Login / register with demo accounts or new profile
+
+To log **multiple trips at once**, go to the `Trips` tab and use **Import CSV**.
+
+---
+
+## Architecture
+
+```
+Driver-Pulse/
+├── backend/                       # FastAPI REST API (25 endpoints)
+│   ├── main.py                    # Routes, middleware, Pydantic models
+│   ├── data/
+│   │   ├── sample_data.py         # Synthetic trip/route/event generator
+│   │   ├── batch_processor.py     # Loads ML models, runs batch inference
+│   │   ├── trips_import.py        # CSV trip import parser
+│   │   ├── users.py               # In-memory auth store
+│   │   └── config.py              # Batch limits & constants
+│   └── utils/
+│       └── logging.py             # Timestamped structured logging
+│
+├── frontend/                      # React 18 + Vite + Tailwind SPA
+│   └── src/
+│       ├── pages/                 # 8 pages: Home, Dashboard, Trips, TripDetail,
+│       │                          #   Trends, Goals, Predict, BatchUpload
+│       ├── components/            # 16 reusable components
+│       ├── api/client.js          # Centralised API client
+│       └── utils/sanityChecks.js  # Input validation helpers
+│
+├── drivepulse_stress_model/       # Stress Detection ML pipeline
+│   ├── run.py                     # CLI entry (--generate --calibrate --train --demo)
+│   ├── src/
+│   │   ├── generate_data.py       # Synthetic sensor window generator (3,150 samples)
+│   │   ├── train.py               # RF classifier training + evaluation
+│   │   ├── inference.py           # InferenceEngine with rule-based fallback
+│   │   └── hal.py                 # Hardware Abstraction Layer (device calibration)
+│   ├── model/                     # Trained artifacts (rf_model.pkl, baselines, contract)
+│   └── calibration/               # Device calibration profile
+│
+├── earnings/earnings/             # Earnings Forecasting ML pipeline
+│   ├── run.py                     # Sequential pipeline entry
+│   ├── src/
+│   │   ├── build_dataset.py       # Merges drivers + goals + velocity + trips
+│   │   ├── features.py            # 14-feature engineering (lags, rolling avg, rush flags)
+│   │   ├── augment.py             # 5× Gaussian noise augmentation
+│   │   ├── train.py               # RF regressor training + evaluation
+│   │   └── inference.py           # Batch velocity prediction
+│   ├── model/                     # Trained artifacts (rf_model.pkl, contract)
+│   └── data/                      # Source CSVs (drivers, goals, velocity, trips)
+│
+├── streamlit_app.py               # Standalone Streamlit demo (3 tabs)
+├── tests/data/                    # Example CSVs for batch & import testing
+└── requirements.txt               # Root Python dependencies
+```
+
+```mermaid
+flowchart LR
+  browser[Browser_ReactApp] --> api[FastAPI_Backend]
+  api --> tripsStore[InMemory_Trips_+_Goals]
+  api --> stressBatch[Stress_Batch_Processor]
+  api --> earningsBatch[Earnings_Batch_Processor]
+  stressBatch --> stressModel[Stress_Model_Files]
+  earningsBatch --> earningsModel[Earnings_Model_Files]
+```
+
+---
+
+## Setup
+
+### Prerequisites
+- Python 3.9+
+- Node.js 18+
+ - Docker Desktop (for judge-friendly containerisation)
+
+### Install & Run (local dev)
+
+```bash
+# Install Python dependencies
+pip install -r requirements.txt
+
+# Start backend (http://localhost:8000)
+cd backend && python main.py
+
+# In a new terminal — start frontend (http://localhost:5173)
+cd frontend && npm install && npm run dev
+```
+
+Open **http://localhost:5173** in your browser.
+
+---
+
+### Run with Docker
+
+With [Docker Desktop](https://www.docker.com/products/docker-desktop/) running:
+
+```bash
+# From the repo root (Driver-Pulse/)
+docker compose up --build
+```
+
+Then open:
+
+- Frontend: `http://localhost:5173`
+- Backend (direct): `http://localhost:8000/api/health`
+
+The frontend talks to the backend via `/api/*`, which is proxied by Nginx inside the `frontend` container to the `backend` container.
+
+**Judge login (demo account):**
+
+- Username: `judge@uber.com`
+- Password: `hackathon2026`
+
+---
+
+## Tech Stack
+
+| Layer | Tech |
+|-------|------|
+| Frontend | React 18, Vite, Tailwind CSS, Recharts, Leaflet |
+| Backend | FastAPI, Uvicorn |
+| ML | scikit-learn, NumPy, Pandas |
+
+---
+
+## Data Flow
+
+- **Trips & goals**: Manual entry or CSV import hit `/api/trips` or `/api/trips/import-csv`, which update an in-memory trips list. Goals (`/api/goals`) and dashboard (`/api/dashboard`) recompute current earnings, hours, and forecast from those trips.
+- **Batch stress & earnings**: Batch CSV uploads are processed by backend helpers that engineer features, call local models, and return per-row predictions plus summaries as JSON.
+
+---
+
+## Scalability & Modularity
+
+- **Backend**: FastAPI routes in `backend/main.py` delegate to small modules in `backend/data/` for trips, goals, imports, and batch processing, so swapping the in-memory store for a database or separate ML service is a local change.
+- **Frontend**: The React app uses a single API client layer (`frontend/src/api/client.js`) plus page/component separation, making it easy to plug in global state, auth, or feature flags without rewriting screens.
+- **Batch endpoints**: Batch CSV processing is stateless per request, so multiple backend instances can handle uploads in parallel behind a load balancer.
+
+---
+
+## Testing & Validation Notes
+
+- **Frontend sanity checks** — lightweight helpers in `frontend/src/utils/sanityChecks.js` validate money inputs, time ranges, and clamp goal targets.
+- **Example test files** — illustrative, non-wired tests live in `frontend/src/__tests__/` (e.g. `EarningsProgress.test.jsx`, `TripsAddTrip.test.jsx`) to show how key components and behaviours could be validated in a full test setup.