The langgraph-python voice cell sat at D4 even when its d5-voice probe
row was green. Root cause: the dashboard's CATALOG_TO_D5_KEY mirror in
showcase/shell-dashboard/src/lib/live-status.ts was missing voice ->
["voice"], so computeMaxPossible capped voice at D4 regardless of probe
state. The harness REGISTRY_TO_D5 already had the entry; only the
dashboard mirror was out of sync.
Separately, the "Play sample" button used to fetch sample.wav and POST
it to /transcribe. With aimock that meant both the sample button AND
the mic returned the same canned response, which made it impossible to
demo the mic path locally without conflating the two affordances.
Reworked the button into a synchronous static-text injector
(onTranscribed(sampleText)) so:
- Sample button = deterministic test/demo affordance, no runtime calls.
- Mic = real Whisper transcription via /transcribe.
Synced across all 18 voice-enabled integrations. Phrase stays "What is
the weather in Tokyo?" so aimock's "weather in Tokyo" substring fixture
still matches.
Also adds the missing d5-voice.test.ts companion (every other d5-* probe
script has one) and trims the langgraph-python qa/voice.md + e2e steps
that depended on the now-removed async behavior.
## Summary
Adds hand-rolled persistent suggestion chips to the `headless-simple`
and `headless-complete` demos in the langgraph-python north-star,
propagates the same surface to the other 17 showcase integrations, and
adds a deterministic aimock fixture so a new chip-click e2e test
("Largest continent") rounds-trips against a stable `Asia is the largest
continent…` response across all 18 demos.
## What changed
**Phase 0 — north-star (commit `7cbc5ea8`)**
- `showcase/aimock/feature-parity.json` — new fixture: `What is the
largest continent?` → `Asia is the largest continent — about 30% of
Earth's land area, home to over 4.6 billion people.`
- `langgraph-python/src/app/demos/headless-{simple,complete}/page.tsx` —
refactor `send` / `handleSubmit` to accept `(override?: string)` so chip
clicks dispatch synchronously without a `setInput` round-trip; render a
persistent `<div data-testid="headless-suggestions">` chip row above the
composer with 5 canonical entries; remove the dead
`useConfigureSuggestions` call from headless-complete (it was
registering suggestions nothing rendered).
- `langgraph-python/tests/e2e/headless-{simple,complete}.spec.ts` —
append one new test in each spec asserting chip click → user message →
`Asia` reply.
**Phase 1 — parity propagation across 17 integrations (commit
`4882c61f`)**
- Spec files `headless-simple.spec.ts` and `headless-complete.spec.ts`
are now byte-identical to the north-star in every integration (10 tests
each = 5 simple + 5 complete; verified via `cmp` for all 34 spec files).
- The 5-entry `suggestions` const is byte-identical between every
integration's simple and complete demos.
- All 17 integrations now expose the same selector surface (canonical
headings, empty-state text, `data-testid="headless-complete-messages"`,
dynamic placeholder, `rounded-br-sm` user bubble, no CopilotChat-default
testids).
**Glue preserved per integration** (verified by post-blitz code review):
- `built-in-agent`: `<CopilotKitProvider runtimeUrl="/api/copilotkit"
useSingleEndpoint>` + `agentId: "default"`
- `google-adk` / `llamaindex`: `agentId: "headless_simple"` /
`"headless_complete"` (Python-style underscores)
- `claude-sdk-typescript`: headless-complete
`runtimeUrl="/api/copilotkit-headless-complete"`
- `spring-ai`: 70-line `deduplicateMessages` adapter workaround +
`useMemo` import preserved verbatim
- All `@region[...]` markers preserved in place
**Adapter-specific decisions worth flagging in review:**
- `google-adk` headless-complete: rewrote `message-list.tsx` from
`msg-user`/`msg-assistant`/`agent-thinking` testid scheme to the
canonical `headless-complete-messages` wrapper; rewrote `input-bar.tsx`
placeholder to canonical dynamic; added the missing subtitle and
empty-state hint
- `ms-agent-dotnet`: extracted inline composer to a new `input-bar.tsx`
to match north-star structure
- `llamaindex`, `ms-agent-python`: added the canonical empty-state hint
(was missing entirely)
- `agno`, `built-in-agent`, `crewai-crews`, `mastra`, `ms-agent-dotnet`,
`pydantic-ai`: replaced per-integration empty-state hint with the
canonical Excalidraw line — chosen for parity over per-integration
accuracy (some demos don't actually wire an Excalidraw tool; alignment
was the explicit goal)
## Verification
- `validate-parity.ts`: 18/18 packages pass, 0 MUST failures
- `aimock-fixtures` test suite: 18/18 pass
- aimock fixture probed directly: `What is the largest continent?`
returns the canonical Asia response
- Each propagation slot reported `tsc --noEmit` clean (0 new errors) +
`playwright --list` shows all 10 expected tests
- Code review (`pr-review-toolkit:code-reviewer`) on the full diff: 0
Critical / Important / Minor findings, 1 stylistic nit (north-star
`input-bar.tsx` `onSubmit` type contravariant-loose, harmless)
## What was NOT done
Live per-integration Playwright runs against rebuilt Docker images. The
17 containers would each need a no-cache rebuild (~5-15 min each = hours
total) and the canonical local-test path is `showcase test <slug>` per
the existing CLI / CI pipeline. Static + structural verification covers
the propagation pattern.
## Test plan
- [ ] Run `showcase test <slug>` (or equivalent CI job) for at least one
drift-heavy integration: `google-adk` (testid scheme rewrite),
`built-in-agent` (provider glue), `spring-ai` (dedup workaround),
`llamaindex` (added testid + empty-state)
- [ ] Run the existing per-integration Playwright suites for at least
the north-star (`langgraph-python`) to confirm the new chip test passes
against a real backend + aimock
- [ ] Confirm aimock fixture validation still passes after deploy
Search Flights and Sales Dashboard pills both produce visible surfaces
on the langgraph-python beautiful-chat demo. Three independent bugs were
masking each other:
- Flight TypedDict required `id` + `statusIcon`, which the aimock fixture
doesn't supply. langchain rejected the call with `flights.0.id: Field
required` and the agent surfaced the error string as the tool result.
Made the type permissive (only the fields `_build_flight_components`
reads need to be there).
- search_flights now expands flights into literal-children FlightCard
components server-side instead of relying on the structural-children
template form (the binder doesn't reliably expand it for our custom
catalog — sibling demos avoid the form for the same reason).
- Sales Dashboard pill went into a tool-call loop because the
userMessage+toolName fixtures matched both the initial call and the
post-tool turn. Hoisted the toolCallId fixture above them so the
follow-up turn returns content and breaks the loop.
Custom Row/Column reintroduced with `gap` support — the basic catalog's
versions ignore it, leaving cards squished. Children are array-of-strings
only (matches what the agent and fixture emit).
Two new e2e tests cover both pills end-to-end. 3s wait in beforeEach so
the v2 chat provider hydrates before the click dispatches. Full spec:
7/7 green.
## Summary
The `agentic-chat-reasoning` and `reasoning-default-render` cells in
`langgraph-python` and `langgraph-fastapi` never rendered any reasoning
content. Root cause: both agents were configured with `gpt-4o-mini` +
`use_responses_api=False`, so the underlying model produced no reasoning
content blocks and the Chat Completions API has no reasoning summary
surface in the first place. The frontend's `reasoningMessage` slot
stayed empty even though the cells are billed as reasoning demos.
This PR:
- Switches both agents (and their `tool_rendering_reasoning_chain`
siblings) to `gpt-5-mini` through the Responses API with
`reasoning={"effort":"medium","summary":"detailed"}`, mirroring the
`langgraph-typescript` and `pydantic-ai` agents that already worked.
Model is overridable via `OPENAI_REASONING_MODEL`.
- Updates the aimock `d5-all.json` fixture (and the matching harness
`reasoning-display.json`) to set the `reasoning` field on the `show your
reasoning step by step` match. Aimock now emits
`response.reasoning_summary_text.delta` events so the demo renders
deterministically without a real LLM call.
- Adds a `Show reasoning` `useConfigureSuggestions` pill on both
reasoning pages in both integrations so the demo is one click to
exercise.
- Tightens the `d5-reasoning-display` probe to also assert that a
reasoning-role message rendered (`[data-testid="reasoning-block"]` or
`[data-message-role="reasoning"]`), not just that the word "reasoning"
appears in the transcript.
- Un-skips the three streaming reasoning-block tests in
`agentic-chat-reasoning.spec.ts`, adds a suggestion-pill test, and
extends `reasoning-default-render.spec.ts` to cover the default
reasoning slot.
- Updates the `langgraph-python` QA doc to describe the new model +
Responses API setup and the pill flow.
Verified locally end-to-end: clicking the pill at
`/demos/agentic-chat-reasoning` renders the amber `ReasoningBlock` with
the fixture's reasoning text above the final answer bubble.
## Out of scope
Other integrations were audited and intentionally left alone:
- `langgraph-typescript`, `pydantic-ai` already use a reasoning model +
Responses API and work today.
- `agno`, `claude-sdk-python`, `ms-agent-python` use deliberate
workarounds (XML-tag reasoning + custom AGUI handler, Claude
extended-thinking deltas, `think` tool respectively) because their AG-UI
bridges either don't translate Responses-API reasoning items, run a
multi-call CoT loop incompatible with fixture replay, or don't emit
reasoning events at all.
- `llamaindex` uses `gpt-4.1` and surfaces reasoning inline as assistant
text. Its bridge (`llama-index-protocols-ag-ui`) does not translate
Responses-API reasoning items into AG-UI events; fixing that needs an
upstream patch and is out of scope here.
## Notes
Committed with `--no-verify` (explicit user request) — this worktree has
no `node_modules`, so the lefthook `test-and-check-packages` step
couldn't run locally. Changes are entirely under `showcase/` and CI runs
the same checks.
## Test plan
- [ ] CI fixture-validation passes on `showcase/aimock/d5-all.json`
- [ ] `showcase test langgraph-python --d5 --verbose` —
`reasoning-display` probe green (asserts `reasoning-block` selector +
keyword)
- [ ] `showcase test langgraph-fastapi --d5 --verbose` — same
- [ ] `nx run @copilotkit/showcase-langgraph-python:test:e2e -- --grep
reasoning` — un-skipped specs pass against the deployed Railway image
- [ ] Manual: visit `/demos/agentic-chat-reasoning` on a deployed
langgraph-python, click `Show reasoning`, confirm amber `REASONING —
Agent reasoning` block renders with italic step text above the final
answer bubble
- [ ] Manual: same on `/demos/reasoning-default-render`, confirm
CopilotKit's default `CopilotChatReasoningMessage` card renders
The agentic-chat-reasoning and reasoning-default-render cells in
langgraph-python and langgraph-fastapi were configured with
gpt-4o-mini + use_responses_api=False, which never produces AG-UI
REASONING_MESSAGE_* events: gpt-4o-mini is not a reasoning model and
the Chat Completions API does not surface reasoning summary items at
all. The frontend's reasoningMessage slot was rendering nothing,
even though the cells were billed as "reasoning" demos.
- Switch both reasoning agents to gpt-5-mini (override via
OPENAI_REASONING_MODEL) routed through the Responses API with
reasoning={"effort":"medium","summary":"detailed"} so the model's
chain of thought streams as content blocks that @ag-ui/langgraph
translates into REASONING_MESSAGE_* events.
- Update the aimock d5-all.json and harness reasoning-display.json
fixtures to include a "reasoning" field so aimock emits
response.reasoning_summary_text.delta SSE events deterministically
in CI without hitting a real LLM.
- Add a "Show reasoning" useConfigureSuggestions pill on both
reasoning demo pages so the user can trigger the fixture-matched
prompt with one click.
- Tighten the d5-reasoning-display probe: it now also asserts a
reasoning-role message rendered via [data-testid="reasoning-block"]
or [data-message-role="reasoning"], so a plain text response
containing the word "reasoning" no longer falsely passes.
- Un-skip the three streaming reasoning-block tests in
langgraph-python's agentic-chat-reasoning.spec.ts and add a
suggestion-pill test; expand the reasoning-default-render spec to
cover the default reasoning slot.
- Update the langgraph-python QA doc to describe the new model +
Responses API setup and the suggestion-pill flow.
## Summary
The hitl-in-chat demo's **"Schedule a 1:1 with Alice next week to review
Q2 goals."** suggestion was being intercepted by the broad `userMessage:
"Alice"` matcher used by the memory/context demo, which returns a
generic "Nice to meet you, Alice! I see you're in Tokyo — wonderful
city..." greeting. The HITL flow never fired and the user saw a
nonsensical reply.
Aimock's matcher uses `text.includes(match.userMessage)` (substring) +
first-fixture-wins by file order, so any message containing "Alice"
hijacked the suggestion before the HITL flow could trigger.
## Fix
Added a fixture pair earlier in `showcase/aimock/feature-parity.json`
with the **full suggestion sentence** as the matcher:
- `hasToolResult: false` → returns a `book_call` toolCall, letting the
frontend `useHumanInTheLoop` render the time-picker.
- `hasToolResult: true` → returns the booking confirmation message.
The substring-match-on-full-sentence is effectively exact — no other
realistic user message will contain that whole sentence — so the broad
`Alice` / `alice` fixtures stay scoped to the memory demo where the user
actually says "I'm Alice" or similar.
## Test plan
- [ ] Click "Schedule a 1:1 with Alice next week to review Q2 goals." in
the langgraph-python hitl-in-chat demo against an aimock-backed
deployment → expect the time-picker card to render and a booking
confirmation after picking a slot.
- [ ] The memory/context demo (where users type "I'm Alice") still gets
the Tokyo greeting — broad fixtures unchanged.
- [x] Pre-commit hooks pass (test, check-packages, commitlint).
Bug: in a single chat session, running both HITL booking flows
back-to-back (Alice 1:1 → then Sales call without refresh) used to
skip the time-picker on the second flow and jump straight to
"Booked ..." text.
Cause: confirmation fixtures were matched on `hasToolResult: true`,
which fires whenever the conversation has ANY tool message in
history. After the first flow finished, the second user message
short-circuited to a confirmation match before the second flow's
toolCall fixture (gated on `hasToolResult: false`) had a chance to
fire. The picker never rendered.
Fix: re-key the two confirmation fixtures on `toolCallId` (the
specific tool_call_id of the matching `book_call` invocation), which
only fires when the LAST conversation message is a tool result with
that id — exactly the moment we want the confirmation. Drop the
`hasToolResult: false` constraint on the toolCall fixtures so they
match a fresh user request regardless of prior tool history.
Add a back-to-back regression test to all 17 hitl-in-chat specs:
walk Alice flow to completion, then sales flow without refresh,
assert two `time-picker-card` elements rendered. If the multi-flow
regression returns, the second card never appears and the test
fails at `toHaveCount(2)`.
The hitl-in-chat demo ships in 17 integrations (langgraph-python plus
16 others — mastra, strands, ag2, agno, crewai-crews,
langgraph-typescript, langgraph-fastapi, pydantic-ai, llamaindex,
langroid, claude-sdk-python, claude-sdk-typescript, ms-agent-python,
ms-agent-dotnet, spring-ai, google-adk). All shipped placeholder e2e
specs that only checked the chat input was visible — none exercised
the actual booking flow.
Replace each with the full booking-flow spec written for
langgraph-python:
1. The "Schedule a 1:1 with Alice" suggestion renders the time-picker
card AND the Tokyo greeting is absent (regression guard against
the broad aimock `userMessage: "Alice"` matcher).
2. Picking a slot transitions to the picked-state card and produces
a "Booked … Alice" assistant follow-up.
3. The "Book a call with sales" suggestion runs the same flow with
the sales attendee.
Also add the matching aimock fixture pair for the sales suggestion
in feature-parity.json — without it, case 3 would only pass against
real OpenAI, not the aimock-backed CI deployments. The pair mirrors
the Alice fixture pair: `book_call` toolCall on first turn,
confirmation message after the picker resolves.
Per-integration coverage matters because each integration has its
own framework-specific HITL wiring (`useHumanInTheLoop` binding to
the agent, agent-side tool registration, run streaming protocol)
that can regress independently of the shared aimock fixture.
Pins the contract that the new full-sentence aimock fixture pair beats
the broad `userMessage: "Alice"` matcher:
1. Sending the suggestion `"Schedule a 1:1 with Alice next week to
review Q2 goals."` renders `[data-testid="time-picker-card"]`,
not the Tokyo greeting. The test explicitly asserts the Tokyo
greeting is absent — `toHaveCount(0)` against
`/Nice to meet you, Alice/i` — so any future broad-match
regression fails here loudly.
2. Clicking a slot transitions to `[data-testid="time-picker-picked"]`
and the assistant follow-up message contains "Booked ... Alice",
verifying the `hasToolResult: true` branch of the fixture pair
also wires through.
The langgraph-python gen-ui-agent demo was the only one of 18
integrations using the V1 `useCoAgentStateRender` hook. That hook
binds renders to messages via per-message claims, so each
state-changing tool call (each `set_steps` invocation) produced its
own card snapshot in the chat — a typical 3-step plan run pushed
~7+ stacked cards instead of one updating card.
Migrate the page to the canonical V2 pattern already used by every
other gen-ui-agent demo (mastra, strands, ag2, agno, crewai-crews,
langgraph-typescript, pydantic-ai, ...): subscribe to live state via
`useAgent` and render a single `InlineAgentStateCard` inside
`messageView.children`. The card now re-renders in place as state
streams — no per-message claims, no duplicates.
Also tighten the agent system prompt with an explicit numbered tool
sequence (1 plan + 6 transitions + final message) to make the
"step 3 stuck in_progress" tail-of-run failure less likely with
gpt-4o-mini. The UI is robust to a missed final transition either
way: when `agent.isRunning` flips to false, the card headlines
"All N steps complete" regardless of step.status.
Replace the stale e2e spec (which targeted a long-removed
`task-progress` test id) with one that pins the contract:
- exactly one `agent-state-card` rendered, even after the run
finishes
- every `agent-step` ends in `data-status="completed"`
The showcase framework directories better reflect their role as
integration examples rather than distributable packages.
Renames showcase/packages/ -> showcase/integrations/ and updates
the test docker-compose file reference accordingly.
Alem Tuzlak