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QA: Agent Config Object — PydanticAI

showcase/integrations/pydantic-ai/qa/agent-config.md

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QA: Agent Config Object — PydanticAI

Prerequisites

  • Demo deployed and accessible at /demos/agent-config
  • Agent backend healthy (check /api/health)
  • OPENAI_API_KEY set

Test Steps

1. Basic Functionality

  • Navigate to /demos/agent-config
  • Verify the header "Agent Config Object" is visible
  • Verify the config card renders with three dropdowns (Tone, Expertise, Response length)
  • Default values: tone=professional, expertise=intermediate, responseLength=concise

2. Send with defaults

  • Type "Hello" and send
  • Within 30 seconds, an assistant response renders — tone should be neutral/professional, 1-3 sentences

3. Switch to casual+beginner+detailed

  • Change tone to "casual", expertise to "beginner", response length to "detailed"
  • Type "What is a neural network?" and send
  • Within 30 seconds, an assistant response renders — tone should feel conversational, explain jargon with analogies, span multiple paragraphs

4. Network panel inspection

  • Open DevTools → Network and send a message after selecting "enthusiastic"/"expert"/"detailed"
  • Verify the request to /api/copilotkit-agent-config includes the three values somewhere in its body (they land on the AG-UI context array the TS route appends)

PydanticAI-specific note

The TS runtime route subclasses HttpAgent to repack the CopilotKit provider's properties into an AG-UI context entry tagged agent-config-properties. The Python agent's dynamic @agent.system_prompt reads that entry at call time and composes the prompt from the three axes. This differs from the langgraph-python reference (which repacks into forwardedProps.config.configurable), but the user-visible behaviour is identical.

Expected Results

  • Dropdown changes propagate to the next send immediately.
  • Tone / expertise / length axes visibly shift the assistant's style.
  • Request payloads contain the selected values.