Build a Rural Seed Cooperative Multi-Node Stock Rebalancing Allocator

Monitor regional certified seed inventories across community cooperative depots using Beckn catalog messages. Generate balanced inter-depot stock transfer schedules and localized allocation plans ahead of sowing season demand surges.

District agricultural cooperative officer

Parse inventory levels and certified batch seed numbers across participating primary agricultural cooperative societies.

Model projected taluk-level sowing demand based on synthetic historical distribution quotas.

Calculate inter-depot transfer manifests to resolve localized shortages without exceeding logistics budgets.

Produce Beckn-compliant catalog item update batches reflecting balanced regional availability.

Geographic map and depot balance console displaying stock surpluses, deficit flags, and transfer manifests.

Construct synthetic seed stock levels and distance matrices for 10 simulated rural agricultural depots. Starter examples below are synthetic. They are not downloaded records.

Beckn protocol specifications Applies Beckn protocol catalog management schemas and asynchronous BPP update patterns for inventory syncing.

optuna, pydantic, fastapi. Optuna optimizes multi-depot seed transfer routes to minimize transit distance and logistics expenses. Lightweight API or local model for generating human-readable depot manager transfer justifications.

Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

Eliminates stock deficits in high-demand depots using surpluses from adjacent regional cooperative nodes.

Maintains seed lot traceability codes throughout all planned inter-depot transfers.

Emits normalized catalog update payloads ready for BPP network publication.

```json [ { "input": { "seed_id": "cotton_bt2_certified", "depots": [ { "depot_id": "depot_north", "stock_bags": 500, "projected_demand": 200 }, { "depot_id": "depot_south", "stock_bags": 50, "projected_demand": 250 } ], "transit_cost_per_bag_km": 0.5, "distance_km": 40 }, "expected_output": { "rebalance_status": "BALANCED", "transfer_orders": [ { "from_depot": "depot_north", "to_depot": "depot_south", "quantity_bags": 200, "estimated_cost_inr": 4000 } ], "final_projected_coverage_pct": 100 } }, { "input": { "seed_id": "mustard_hybrid_01", "depots": [ { "depot_id": "depot_east", "stock_bags": 80, "projected_demand": 100 }, { "depot_id": "depot_west", "stock_bags": 40, "projected_demand": 150 } ], "transit_cost_per_bag_km": 0.5, "distance_km": 60 }, "expected_output": { "rebalance_status": "REGIONAL_DEFICIT", "transfer_orders": [], "final_projected_coverage_pct": 48 } } ] ```

Agricultural inventory optimization is simulated; no physical transport work orders or real supplies are committed. Use mock external writes. Require human review before any real deployment.