How nikhilpandey-tech/bhoominetra works
BhoomiNetra is a land-acquisition monitoring and decision-support application. Users sign in, review projects and their predicted delay risk, then use explanations, recommendations, simulations, alerts, maps, and reports to guide follow-up. The frontend talks to a FastAPI backend; its ML service calls a separate prediction/explanation service. A separate training pipeline builds model artifacts. The README is empty, and most route and page implementations were not sampled, so those links are limited to documented capabilities and visible entry points.
Main entry points: main.py FastAPI application · train_pipeline.py Train pipeline · App.jsx App shell · database.py Relational database
Components 22
User interface
- BhoomiNetra UI
Frontend/src/main.jsx - App shell
Frontend/src/App.jsx - API client
Frontend/src/lib/api.js - Project views
Frontend/src/pages/projects.jsx - Decision views
Frontend/src/pages/risk-analysis.jsx
Application API
- FastAPI application
backend/app/main.py - Authentication
backend/app/routes/auth.py - Project routes
backend/app/routes/projects.py - Prediction routes
backend/app/routes/predictions.py - Decision services
backend/app/routes/recommendations.py - Operations routes
backend/app/routes - Domain records
backend/app/models - Relational database
backend/app/database/database.py - ML adapter
backend/app/services/ml_service.py
ML runtime
- Prediction service
ml/app.py - Model artifacts
ml/app.py
Model training
- Training entry
ml/run_pipeline.py - Train pipeline
ml/src/train_pipeline.py - Data audit
ml/src/data_audit.py - Model experiments
ml/src/model_selection.py - SHAP explainability
ml/src/explainability.py
Other components
- User
Connections 23
- User → BhoomiNetra UI: uses
- BhoomiNetra UI → App shell: routes to
- App shell → API client: requests
- App shell → Project views: shows
- App shell → Decision views: shows
- API client → FastAPI application: HTTP requests
- FastAPI application → Authentication: mounts
- FastAPI application → Project routes: mounts
- FastAPI application → Prediction routes: mounts
- FastAPI application → Decision services: mounts
- FastAPI application → Operations routes: mounts
- Authentication → Relational database: queries, writes
- Project routes → Relational database: database access
- Prediction routes → ML adapter: prediction calls
- Decision services → Relational database: database access
- Relational database → Domain records: persists
- ML adapter → Prediction service: HTTP calls
- Prediction service → Model artifacts: loads
- Training entry → Train pipeline: runs
- Train pipeline → Data audit: audits data
- Train pipeline → Model experiments: runs experiments
- Train pipeline → SHAP explainability: generates SHAP
- Train pipeline → Model artifacts: writes models