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

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.