Build an Offline-First Multilingual Kirana Daily Ledger and Beckn Sync
Capture regional voice sales entries and offline stock adjustments on local devices. Reconcile buffered changes and export verified Beckn inventory update payloads when network connectivity is detected.
What you are building
The core problem, expected build, and operating context for this challenge.
Capture regional voice sales entries and offline stock adjustments on local devices. Reconcile buffered changes and export verified Beckn inventory update payloads when network connectivity is detected.
Small township retail shopkeeper
Record spoken daily stock adjustments in regional audio or localized text offline.
Normalize colloquial units into metric standards and build local SQLite transaction journals.
Detect network availability to run mock Bhashini translation pipelines into standard schema descriptors.
Generate Beckn Core 1.0.0 post-fulfillment inventory sync payloads for human shopkeeper confirmation.
Offline-capable web dashboard with audio upload button, local SQLite cache viewer, and sync confirmation modal.
Use mock Bhashini API fixtures for NMT and synthetic Beckn retail catalog templates from GitHub repository. Starter examples below are synthetic. They are not downloaded records.
Beckn protocol specifications Implements Beckn Core 1.0.0 message and context packet structures for asynchronous catalog and post-fulfillment updates.
pydantic-ai, fastapi, sqlite3. Ensures type-safe validation of offline inventory journals and schema compliance for Beckn transaction packets. Local quantized Llama model or hosted Claude API for dialect term extraction.
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 vernacular item names and informal measures into metric quantities within local storage.
Validate outgoing Beckn payload against version 1.0.0 context and message schema constraints.
Queue offline transactions without loss during simulated network disconnection drills.
Display human reconciliation diff before dispatching server-to-server catalog updates.
```json [ { "input": { "store_id": "kirana-rural-102", "connectivity": "offline", "log_entry": { "spoken_text": "chana dal 5 bori aayi aur 3 packet tel bika", "language_code": "hi" } }, "expected_output": { "journal_status": "buffered", "parsed_items": [ { "item": "chana_dal", "delta": 5, "unit": "bag_50kg", "action": "restock" }, { "item": "cooking_oil", "delta": -3, "unit": "packet_1l", "action": "sale" } ], "sync_pending": true } }, { "input": { "store_id": "kirana-rural-102", "connectivity": "online", "log_entry": { "spoken_text": "namak khatam ho gaya", "language_code": "hi" } }, "expected_output": { "journal_status": "synchronized", "parsed_items": [ { "item": "table_salt", "delta": 0, "unit": "packet_1kg", "action": "out_of_stock" } ], "beckn_payload": { "context": { "domain": "nic2004:52110", "action": "update", "core_version": "1.0.0" }, "message": { "items": [ { "id": "salt-1", "quantity": { "available": { "count": 0 } } } ] } }, "sync_pending": false } } ] ```
Simulates all Beckn network posts; does not alter production retail inventory or execute monetary settlements. Use mock external writes. Require human review before any real deployment.
Participation guide
Simulates all Beckn network posts; does not alter production retail inventory or execute monetary settlements. Use mock external writes and human review.
How work is evaluated
Parse vernacular item names and informal measures into metric quantities within local storage. Validate outgoing Beckn payload against version 1.0.0 context and message schema constraints. Queue offline transactions without loss during simulated network disconnection drills. Display human reconciliation diff before dispatching server-to-server catalog updates.
Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
Complete workflow
Record spoken daily stock adjustments in regional audio or localized text offline. Normalize colloquial units into metric standards and build local SQLite transaction journals. Detect network availability to run mock Bhashini translation pipelines into standard schema descriptors. Generate Beckn Core 1.0.0 post-fulfillment inventory sync payloads for human shopkeeper confirmation.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Correctness and evidence
Parse vernacular item names and informal measures into metric quantities within local storage. Validate outgoing Beckn payload against version 1.0.0 context and message schema constraints. Queue offline transactions without loss during simulated network disconnection drills. Display human reconciliation diff before dispatching server-to-server catalog updates.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Review interface
Offline-capable web dashboard with audio upload button, local SQLite cache viewer, and sync confirmation modal.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Safe execution
Simulates all Beckn network posts; does not alter production retail inventory or execute monetary settlements.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Record spoken daily stock adjustments in regional audio or localized text offline.
Normalize colloquial units into metric standards and build local SQLite transaction journals.
Detect network availability to run mock Bhashini translation pipelines into standard schema descriptors.
Generate Beckn Core 1.0.0 post-fulfillment inventory sync payloads for human shopkeeper confirmation.
Reference links and supporting material
Use mock Bhashini API fixtures for NMT and synthetic Beckn retail catalog templates from GitHub repository. Supplied starter examples are synthetic, not source extracts.
Challenge setup
Configuration summary for this challenge.
Challenge input
Input details are not configured.
Pydantic AI
Typed Python agent framework.
Evaluated output
No output checks are configured.
- Record spoken daily stock adjustments in regional audio or localized text offline. Normalize colloquial uni...
- Parse vernacular item names and informal measures into metric quantities within local storage. Validate out...
- Offline-capable web dashboard with audio upload button, local SQLite cache viewer, and sync confirmation mo...
- 2 public reference cases
- 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.
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Configured tools
- Pydantic AI · Optional
- Pydantic 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
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