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Challenge

Agri-Stack Multilingual Advisory Agent with Google ADK & Gemini

Smallholder farmers struggle to navigate complex digital public infrastructure tools for crop advisory and subsidy registration. Build a voice-enabled agri-stack advisory agent using Google ADK and Gemini on Vertex AI to answer farmer queries with 90% accuracy.

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Challenge brief

What you are building

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

Develop an agricultural advisory and government scheme assistant for Indian farmers using Google ADK and Gemini on Vertex AI.

Delivery guide

How work is evaluated

Evaluation

Evaluates crop diagnosis accuracy and subsidy recommendation relevancy for Indian farmers.

Datasets

Shared data for this challenge

Review public datasets and any private uploads tied to your build.

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
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

check_treatment_safety

Verifies that recommended chemical treatments match approved ICAR guidelines

Binary check

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

Dimension 2

advisory_accuracy

Accuracy of disease identification and scheme routing against agronomic gold labels • target: 0.9 • range: 0-1

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

  • Build multimodal agent tools using Google ADK (Agent Development Kit)

  • Integrate Gemini Flash multimodal vision capabilities for crop disease analysis

  • Process voice and text inputs in Indian regional languages (Hindi, Kannada, Telugu)

  • Connect with ICAR and Krishi Vigyan Kendra public agri databases

Resources and assets

Reference links and supporting material

Dataset notes

Agronomic diagnostic dataset containing crop disease images, regional soil health cards, and e-NAM mandi prices.

How this agent runs

Evaluates crop diagnosis accuracy and subsidy recommendation relevancy for Indian farmers.

Challenge input

JSON containing query_text, region_state, and optional_image_uri

Google ADK

Google's Agent Development Kit for building agents with Gemini on Vertex AI.

Evaluated output

JSON with diagnosis, recommended_pesticide, and eligible_scheme

Checks for
  • Verifies that recommended chemical treatments match approved ICAR guidelines
  • Accuracy of disease identification and scheme routing against agronomic gold labels • target: 0.9 • range: 0-1
Proof of success
  • Benchmark: Indian Agronomic Multilingual Advisory Benchmark
  • Advisory Accuracy target: 0.9
  • 1 public reference case
Runtime evidence
  • Python execution harness
  • Python sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • Google ADK · Required
  • Google Gemini · Optional
  • Google · Optional

Evaluation contract

  • check_treatment_safety · Weight 1
  • advisory_accuracy · Weight 1

Recipe state

This is a preview. The configuration can change before the evaluation recipe is locked.

Frequently Asked Questions about Agri-Stack Multilingual Advisory Agent with Google ADK & Gemini