Google ADK Federal Advisory Strategy Analyzer with Gemini
Analyzing public health advisory testimony and strategic plan documents demands multimodal document processing and compliance checking. Build a Google ADK agent powered by Gemini to parse multi-modal hearing transcripts and extract prioritized research funding allocations. Ensure complete source citation verification across 100 percent of extracted metrics.
What you are building
The core problem, expected build, and operating context for this challenge.
Build a multimodal public health intelligence agent using Google ADK and Gemini to extract, structure, and verify strategic research allocations from committee records.
How work is evaluated
Evaluates citation accuracy, funding priority extraction precision, and response generation quality.
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.
citation_completeness
Checks if every extracted priority item includes a timestamp citation.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
extraction_precision
Precision of extracted budget numbers against ground truth text. • target: 0.95 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Initialize Google Agent Development Kit (ADK) agent structure with Gemini 1.5 Pro
Process multimodal inputs (audio transcripts, PDF policy briefs, presentation charts)
Extract structured research grant priority metrics and budget target recommendations
Verify citation alignment against original transcript timestamps
Reference links and supporting material
Transcripts and presentation slides from federal advisory committee meetings regarding autism research strategic plans.
Challenge setup
Evaluates citation accuracy, funding priority extraction precision, and response generation quality.
Challenge input
JSON containing transcript_text and document_image_urls
Google ADK
Required framework for building Vertex AI agent architectures.
Gemini
Provides multi-hour context length and multimodal ingestion.
Evaluated output
JSON with strategic_priorities array, target_funding_millions, and citations
- Checks if every extracted priority item includes a timestamp citation.
- Precision of extracted budget numbers against ground truth text. • target: 0.95 • range: 0-1
- Benchmark: PolicyDoc-Bench
- Extraction Precision target: 0.95
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
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
- Google · Required
- Google Gemini · Optional
- Google ADK · Optional
Evaluation contract
- citation_completeness · Weight 1
- extraction_precision · Weight 1
Metrics
- extraction_precision · Target 0.95
Benchmarks
- PolicyDoc-Bench
- general
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON containing transcript_text and document_image_urls
Output: JSON with strategic_priorities array, target_funding_millions, and citations
Execution harness: Python
Evaluation tools
- Google ADK · Agent Development Framework
- Gemini · Multimodal LLM Provider
Recipe freeze marker
No recipe freeze time is recorded.