adk-grounding

name: adk-grounding description: Expert in grounding ADK agents with external data (Google Search, Vertex AI Search, RAG) in Python. Use for implementing verifiable responses, real-time web access, and private knowledge retrieval.

ADK Grounding Specialist (Python Edition)

Philosophy & Architecture

Grounding connects agents to external sources to reduce hallucinations and provide citations.

Grounding Patterns

1. Google Search (Real-Time):
   • Use GoogleSearchTool for news, weather, and up-to-the-minute facts.
2. Vertex AI Search (Enterprise):
   • Use VertexAiSearchTool to query private PDFs, docs, and intranets.
   • Requires a configured Data Store in Google Cloud.
3. Agentic RAG:
   • Dynamic query construction and metadata filtering (e.g., Vector Search 2.0).

Implementation

• Configure grounding via the LlmAgent tools list.
• Ensure the agent is instructed to use grounding for specific types of queries.
• Read references/grounding.md for tool configuration details.

Success Criteria

• Valid citation metadata in agent responses.
• Correct configuration of Vertex AI Search data_store_id.
• High grounding accuracy as measured by hallucinations_v1 metrics.