beepboop

apps/web/tasks/production-ml-pipeline/README.md

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+# Production ML Pipeline
+
+Objective: Get the plant disease identification ML pipeline to full production readiness with real model inference, proper class mapping, and production-grade error handling.
+
+Status legend: [ ] todo, [~] in-progress, [x] done
+
+## Tasks
+
+- [ ] 01 — PlantVillage class inventory and knowledge base mapping → `01-plantvillage-class-inventory.md`
+- [ ] 02 — Label mapping layer implementation → `02-label-mapping-implementation.md`
+- [ ] 03 — TensorFlow.js model loading verification and fixes → `03-model-loading-verification.md`
+- [ ] 04 — Confidence calibration for PlantVillage model → `04-confidence-calibration.md`
+- [ ] 05 — Real model integration into identification pipeline → `05-pipeline-integration.md`
+- [ ] 06 — Plant-context-aware identification → `06-plant-context-identification.md`
+- [ ] 07 — End-to-end integration testing → `07-end-to-end-testing.md`
+- [ ] 08 — Production hardening and observability → `08-production-hardening.md`
+
+## Dependencies
+
+- 01 → 02 (mapping data feeds label layer)
+- 02 → 05 (labels feed pipeline)
+- 03 → 05 (verified model loading feeds pipeline)
+- 04 → 05 (calibration feeds pipeline)
+- 05 → 06 (real model enables plant context)
+- 05 → 07 (integrated pipeline enables e2e testing)
+- 07 → 08 (tested pipeline enables production hardening)
+
+## Exit Criteria
+
+- The feature is complete when:
+  - Model loads successfully and produces real (non-mock) predictions
+  - All 38 PlantVillage classes map to valid knowledge base disease IDs
+  - End-to-end pipeline works: upload image → get real disease diagnoses with calibrated confidence
+  - Confidence scores are meaningful (high confidence for clear cases, low for ambiguous)
+  - Plant context optionally boosts relevant predictions
+  - Full integration test suite passes
+  - Error handling, logging, and monitoring in place
+  - No demo mode fallback in production
+  - Rate limiting and input sanitization active
+  - Health endpoint reports model status and inference metrics