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Challenge

Build an Offline Multilingual Micro-Farmer Produce Aggregator

Aggregate smallholder farm harvest estimates using offline dialect speech logs. Compile certified produce lots and synchronize standardized Beckn catalog offerings upon reconnection.

Workflow AutomationHosted by Vera
Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Aggregate smallholder farm harvest estimates using offline dialect speech logs. Compile certified produce lots and synchronize standardized Beckn catalog offerings upon reconnection.

Farmer Producer Organization collection manager

Record spoken daily harvest quantities from multiple farmers in local regional languages offline.

Aggregate crop yields into unified grading categories and log quality indicators locally.

Trigger Bhashini NMT pipelines when cellular connectivity is established to harmonize naming.

Generate a pooled Beckn Core 1.0.0 catalog update payload for manager approval.

Offline PWA with farmer voice entry, local lot aggregation tables, and network sync inspector.

Use mock agricultural grade catalogs and synthetic Bhashini translation response fixtures. Starter examples below are synthetic. They are not downloaded records.

Bhashini documentation Utilizes Bhashini NMT pipeline and language configuration calls mapped to ISO-639 language codes.

mastra-ai, pydantic, sqlite3. Provides modular workflow orchestration for chaining offline state caches with external translation services. Local or hosted LLM to classify unstructured harvest grades into official agricultural standards.

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.

Parse dialect crop terms and vernacular weight units into metric equivalents.

Preserve offline transaction integrity during repeated connection drops.

Construct verified Beckn catalog items with pooled inventory quantities.

Require user sign-off on aggregated lots prior to outbound network synchronization.

```json [ { "input": { "fpo_id": "fpo-kisan-01", "offline_records": [ { "farmer": "Ramesh", "text": "dus quintal desi tamatar tayaar hai", "lang": "hi" }, { "farmer": "Suresh", "text": "pandrah quintal hybrid tamatar tayaar", "lang": "hi" } ] }, "expected_output": { "aggregated_lots": [ { "crop": "tomato", "variety": "desi", "weight_kg": 1000 }, { "crop": "tomato", "variety": "hybrid", "weight_kg": 1500 } ], "sync_ready": true, "beckn_catalog_items": 2 } }, { "input": { "fpo_id": "fpo-kisan-01", "offline_records": [ { "farmer": "Kavita", "text": "thoda gehu bacha hai", "lang": "hi" } ] }, "expected_output": { "aggregated_lots": [], "sync_ready": false, "error": "indefinite_quantity_flagged", "requires_field_measurement": true } } ] ```

Maintains local staging of farm produce without creating binding supply contracts or modifying production systems. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Maintains local staging of farm produce without creating binding supply contracts or modifying production systems. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Parse dialect crop terms and vernacular weight units into metric equivalents. Preserve offline transaction integrity during repeated connection drops. Construct verified Beckn catalog items with pooled inventory quantities. Require user sign-off on aggregated lots prior to outbound network synchronization.

Submission format

Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
4 scoring checks
Binary
1 pass or fail dimensions
Ordinal
3 scaled dimensions
Dimension 1

Complete workflow

Record spoken daily harvest quantities from multiple farmers in local regional languages offline. Aggregate crop yields into unified grading categories and log quality indicators locally. Trigger Bhashini NMT pipelines when cellular connectivity is established to harmonize naming. Generate a pooled Beckn Core 1.0.0 catalog update payload for manager approval.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 2

Correctness and evidence

Parse dialect crop terms and vernacular weight units into metric equivalents. Preserve offline transaction integrity during repeated connection drops. Construct verified Beckn catalog items with pooled inventory quantities. Require user sign-off on aggregated lots prior to outbound network synchronization.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 3

Review interface

Offline PWA with farmer voice entry, local lot aggregation tables, and network sync inspector.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 4

Safe execution

Maintains local staging of farm produce without creating binding supply contracts or modifying production systems.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Record spoken daily harvest quantities from multiple farmers in local regional languages offline.

  • Aggregate crop yields into unified grading categories and log quality indicators locally.

  • Trigger Bhashini NMT pipelines when cellular connectivity is established to harmonize naming.

  • Generate a pooled Beckn Core 1.0.0 catalog update payload for manager approval.

Resources and assets

Reference links and supporting material

Dataset notes

Use mock agricultural grade catalogs and synthetic Bhashini translation response fixtures. Supplied starter examples are synthetic, not source extracts.

Challenge setup

Configuration summary for this challenge.

Challenge input

Input details are not configured.

Mastra AI

TypeScript agent framework.

Evaluated output

No output checks are configured.

Evaluation checks
  • Record spoken daily harvest quantities from multiple farmers in local regional languages offline. Aggregate...
  • Parse dialect crop terms and vernacular weight units into metric equivalents. Preserve offline transaction...
  • Offline PWA with farmer voice entry, local lot aggregation tables, and network sync inspector.
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • 2 configured tools

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

Action Space
  • Mastra AI · Optional
Orchestration
  • Mastra AI · Optional

Evaluation contract

  • Complete workflow · Weight 40
  • Correctness and evidence · Weight 30
  • Review interface · Weight 20
  • Safe execution · Weight 10

Reference cases

  • 2 public reference cases

Workflow tasks

No workflow tasks are configured.

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Build an Offline Multilingual Micro-Farmer Produce Aggregator