wehub-resource-sync
58 lines
2.0 KiB
Markdown
58 lines
2.0 KiB
Markdown
# QA: Agent Config Object — PydanticAI
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## Prerequisites
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- Demo deployed and accessible at `/demos/agent-config`
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- Agent backend healthy (check `/api/health`)
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- `OPENAI_API_KEY` set
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## Test Steps
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### 1. Basic Functionality
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- [ ] Navigate to `/demos/agent-config`
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- [ ] Verify the header "Agent Config Object" is visible
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- [ ] Verify the config card renders with three dropdowns (Tone,
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Expertise, Response length)
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- [ ] Default values: tone=professional, expertise=intermediate,
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responseLength=concise
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### 2. Send with defaults
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- [ ] Type "Hello" and send
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- [ ] Within 30 seconds, an assistant response renders — tone should be
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neutral/professional, 1-3 sentences
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### 3. Switch to casual+beginner+detailed
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- [ ] Change tone to "casual", expertise to "beginner", response length
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to "detailed"
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- [ ] Type "What is a neural network?" and send
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- [ ] Within 30 seconds, an assistant response renders — tone should
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feel conversational, explain jargon with analogies, span multiple
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paragraphs
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### 4. Network panel inspection
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- [ ] Open DevTools → Network and send a message after selecting
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"enthusiastic"/"expert"/"detailed"
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- [ ] Verify the request to `/api/copilotkit-agent-config` includes the
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three values somewhere in its body (they land on the AG-UI
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`context` array the TS route appends)
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## PydanticAI-specific note
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The TS runtime route subclasses `HttpAgent` to repack the CopilotKit
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provider's `properties` into an AG-UI `context` entry tagged
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`agent-config-properties`. The Python agent's dynamic
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`@agent.system_prompt` reads that entry at call time and composes the
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prompt from the three axes. This differs from the langgraph-python
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reference (which repacks into `forwardedProps.config.configurable`),
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but the user-visible behaviour is identical.
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## Expected Results
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- Dropdown changes propagate to the next send immediately.
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- Tone / expertise / length axes visibly shift the assistant's style.
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- Request payloads contain the selected values.
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