mirror of
https://github.com/CopilotKit/CopilotKit.git
synced 2026-09-14 16:26:20 +08:00
Jordan Ritter
c414fbad23
Refresh d6 fixtures across the rollout cohort: ag2, built-in-agent,
claude-sdk-{python,typescript}, crewai-crews, google-adk, langgraph-fastapi,
langgraph-typescript, langroid, llamaindex, mastra, ms-agent-{dotnet,python},
pydantic-ai, strands. Companion d4/{langgraph-typescript,mastra,ms-agent-dotnet}
chat.json refreshes. Add the missing ms-agent-python/gen-ui-custom.json
to bring the integration up to the standard pill set.
Also narrow aimock/shared/common.json's generic 'hello' fixture to
'hello world' so it no longer shadows D6 pills whose prompts contain
'hello' as a substring (e.g. langgraph-python headless-simple sends
'Say hello in one short sentence.'). 'hello world' is unused by any
current demo pill, so the fixture remains a manual-typing fallback
without poisoning fixture matching.
This is a mid-rollout snapshot — fixture coverage is uneven across
integrations and rides alongside the conveyance shims landed earlier
in this branch.
42 lines
2.2 KiB
JSON
42 lines
2.2 KiB
JSON
{
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"_meta": {
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"description": "D6 fixtures for ms-agent-python / gen-ui-custom (pie chart path)",
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"sourceFile": "harness/fixtures/d5/gen-ui-custom.json",
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"copiedFrom": "langgraph-python",
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"created": "2026-05-29"
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},
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"fixtures": [
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{
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"_comment": "gen-ui-custom pie chart — first leg: emit render_pie_chart tool call. hasToolResult:false ensures this only matches when there's no prior tool result in the conversation. Includes narration content (with 'pie chart' tokens) inline so the D5 probe's last-assistant-text assertion passes even when the runtime does not re-invoke the LLM after a frontend tool result returns (the second-leg fixture below remains a safety net for runtimes that DO loop back). chunkSize: 9999 guards against partial-tool-call JSON.parse classes.",
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"match": {
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"userMessage": "Show me a pie chart of revenue by category",
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"hasToolResult": false,
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"context": "ms-agent-python"
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},
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"response": {
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"content": "Pie chart rendered above — Electronics is the largest slice, followed by Clothing, Food, and Books.",
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"toolCalls": [
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{
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"id": "call_d5_render_pie_chart_001",
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"name": "render_pie_chart",
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"arguments": "{\"title\":\"Revenue by Category\",\"description\":\"Revenue breakdown by product category (Q4)\",\"data\":[{\"label\":\"Electronics\",\"value\":42000},{\"label\":\"Clothing\",\"value\":28000},{\"label\":\"Food\",\"value\":18000},{\"label\":\"Books\",\"value\":12000}]}"
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}
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]
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},
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"chunkSize": 9999
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},
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{
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"_comment": "gen-ui-custom pie chart — second leg: narration after the pie chart tool result lands. Kept as a safety net when the runtime DOES loop back to the LLM. The follow-up text contains 'pie' and 'chart' tokens — the D5 probe asserts their presence.",
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"match": {
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"userMessage": "Show me a pie chart of revenue by category",
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"hasToolResult": true,
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"context": "ms-agent-python"
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},
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"response": {
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"content": "Pie chart rendered above — Electronics is the largest slice, followed by Clothing, Food, and Books."
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},
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"chunkSize": 9999
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}
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]
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}
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