Add 14 fixtures at the top of d5-all.json so they win precedence over
the existing 'weather in Tokyo' / 'd5 beautiful-chat probe: search
flights' substring matches:
- Chain tools: 3 toolCalls in one assistant turn (get_weather Tokyo +
search_flights SFO->Tokyo + roll_d20=11) plus follow-up text.
- Weather in SF: get_weather(San Francisco) + text (deterministic).
- Find flights: dedicated search_flights(SFO,JFK) fixture, no longer
leaks the a2ui beautiful-chat shape.
- Stock price: get_stock_price(AAPL) returning $338.37 / -2.96%.
- Roll a 20-sided die: 5 sequential roll_d20 fixtures with
turnIndex 0..4 (stateless across runs), values [7,14,3,19,20].
Adds deterministic fixtures to d5-all.json (loaded before feature-parity.json
so it wins match precedence) for the Phase 1A genuine-pass cells:
- hitl-in-app refund #12345 and escalate #12347 pills: each emits a
request_user_approval tool call on the first turn, then branches via
sequenceIndex on the second turn (0 = approve response, 1 = reject
response). Test ordering (serial mode in the spec) drives which branch
is claimed first per pill pair.
- frontend-tools-async project-planning, auth, and reading pills: each
emits a query_notes tool call so the async client-side handler runs
against NOTES_DB and renders project-planning / auth / reading-tagged
matches. The reading pill's 2nd-turn narration locks the canonical
leading phrase per spec test #4.
Replaces nothing — purely additive. The dedicated pill-prompt entries
beat the broad 'plan' and showcase-assistant catch-all entries that were
silently winning before.
- Drop the 8 stale tests that asserted travel-planner shapes
(Current Itinerary / supervisor-indicator / .bg-gray-50). They
predated the supervisor + 3-subagent rewrite and could not catch
the 3 production bugs.
- New suite (5 tests, 0 skipped):
1) page loads with composer + 3 verbatim suggestion pills + 3
subagent role indicators (testid-based).
2-4) one test per pill (Write a blog post / Explain a topic /
Summarize a topic). Each clicks the pill, waits for all
three role-scoped subagent cards to reach data-status=
"complete", then asserts each card's subagent-result is
non-empty AND does not contain the showcase-assistant
boilerplate fragments. Test 4 also serves as a regression
gate on the delegations reducer fix — without it, that pill
returns HTTP 400 and the cards never reach complete.
5) clicks any pill, waits for terminal state, then asserts the
critic-card count is exactly 1 and stays at 1 with status
complete across a 5s dwell — catches any return of the
supervisor -> critic loop.
- Aimock fixtures: 3 verbatim pill chains (cold exposure training,
LLM tool calling, reusable rockets) added to both d5-all.json and
the harness source d5/mcp-subagents.json. Each chain drives the
full supervisor flow (turnIndex 0..3) plus three nested sub-agent
fixtures so every Researcher/Writer/Critic card surfaces real
prose instead of showcase boilerplate.
The 5 of 7 open-gen-ui pill prompts (3D axis, neural network, quicksort,
calculator, ping-the-host) currently match the broad userMessage: 'hi'
catch-all in feature-parity.json (substring match on 'hi' inside 'Say hi
to the host', 'this', etc.) and resolve to the showcase-assistant
boilerplate greeting instead of emitting the generateSandboxedUi tool
call. That kills the iframe path on 5/7 of the pills.
Add 7 high-priority verbatim-prompt fixtures in d5-all.json (and the
source-of-truth showcase/harness/fixtures/d5/gen-ui-open.json) that emit
deterministic generateSandboxedUi tool calls with inline HTML + CSS in
the tool result. d5-all.json loads BEFORE feature-parity.json so the
first-match-wins ordering naturally beats the catch-all. Pill fixtures
appear at the top of the file so they also win against intra-bundle
specifics. Inline HTML is intentionally minimal — the assertion bar is
iframe presence + non-empty srcdoc, not iframe DOM introspection
(cross-origin blocked under sandbox=allow-scripts only).
Adds high-priority verbatim-prompt fixtures for the headless-simple and
headless-complete pill prompts so the deterministic leading phrases stay
locked under aimock:
- headless-simple: 'Say hello in one short sentence' / 'Tell me a one-line
joke' / 'Give me a fun fact' lock the greeting, joke, and fun fact.
- headless-complete: 'Highlight: ship the demo on Friday' is a NEW
high-priority entry that emits a highlight_note tool call with text
'ship the demo on Friday' plus a deterministic narration. Without it
the showcase-assistant catch-all in feature-parity.json wins and the
pill never paints a Highlight card.
- headless-complete: 'chart of revenue over the last six months' emits a
get_revenue_chart tool call plus a deterministic narration leading
phrase 'Here is the chart of revenue over the last six months'.
Weather Tokyo and AAPL fixtures already lock the leading phrases the
headless-complete spec asserts on; they remain unchanged.
Add four production-code testids on demo-layout.tsx:
- identity-name on the user-name display
- identity-timezone on the timezone display
- identity-avatar on the first-letter avatar circle
- activity-<slug> on each activity <label>, kebab-case of activity name
These let Playwright lock the identity card against the published
context defaults (Atai, America/Los_Angeles, A) and assert the
default-checked activity rows ("Viewed the pricing page", "Watched
the product demo video") without depending on assistant text.
Add two verbatim-prompt aimock fixtures to showcase/aimock/d5-all.json
for the demo's suggestion pills:
- "What do you know about me from my context?" leading phrase
"I see you're Atai, and you're in the America/Los_Angeles timezone.
Recently, you viewed the pricing page and watched the product demo
video."
- "Based on my recent activity, what should I try next?" leading phrase
"Since you recently viewed the pricing page and watched the product
demo video, ..."
Pinned to the verbatim message bodies so they don't contend with the
showcase-assistant catch-all fixture.
The aggregated multi-turn probe from #4672 hit a CopilotKit v2 quirk on
/demos/beautiful-chat: only the FIRST useComponent tool call in a
conversation paints its component. Subsequent tool calls emit (the
agent's followup content arrives) but the component never mounts.
Reproduced cleanly without any frontend tool involvement —
pie-chart turn 1 paints 5 svg circles in seconds, bar-chart turn 2
emits "Bar chart rendered above..." but paints zero recharts elements.
The runner can't sidestep this from inside one conversation without a
page.reload() between turns, which the structural Page type doesn't
expose. Splitting into per-pill scripts means each probe gets its own
browser launch — fresh page state, fresh conversation, no useComponent
ordering pollution. CATALOG_TO_D5_KEY maps `beautiful-chat` to all
listed literals; isD5Green requires every key green for the cell to
advance to D5, and per-pill failure isolation surfaces in PB row names.
Coverage in this PR (5 pills):
- beautiful-chat-toggle-theme (frontend tool, html.dark flip)
- beautiful-chat-pie-chart (controlled gen-UI useComponent)
- beautiful-chat-bar-chart (controlled gen-UI useComponent)
- beautiful-chat-search-flights (A2UI fixed-schema FlightCards)
- beautiful-chat-schedule-meeting (HITL with slot-click resolution)
All 5 verified locally end-to-end (5/5 pass against the local stack).
Out of scope, intentionally (track in follow-up):
- Excalidraw — depends on mcp.excalidraw.com reachability
- Calculator — sandboxed iframe; dup of d5-gen-ui-open
- Sales Dashboard — generate_a2ui → render_a2ui chain renders
Metric labels but Row-bound charts don't paint
recharts containers under aimock fixtures (live
pill against same fixture chain shows the
inverse symptom). Suggests aimock's
non-progressive arg streaming differs from a
live LLM in a way the A2UI binder is sensitive
to. Needs separate aimock/binder investigation.
- Task Manager — manage_todos dispatches and agent emits closing
content, but StateStreamingMiddleware's
state.todos propagation doesn't populate the
App pane TodoList through aimock — same suspected
root cause as Sales Dashboard.
Architecture details:
- _beautiful-chat-shared.ts factors DOM helpers + per-pill
assertions, mirroring _hitl-shared.ts's pattern for an extended
Page type with click() + a runtime guard
- Each fixture uses unique D5-prefixed userMessage substrings; the
multi-stage Schedule Meeting flow uses hasToolResult false→true
for round disambiguation (no toolCallId leakage since each probe
runs in its own fresh page session)
Promotes /demos/headless-complete to its own D5 feature type so the
dashboard cell can reach D5 instead of riding on the headless-simple
probe (which was navigating to /demos/headless-simple regardless of
which catalog feature triggered it).
- New gen-ui-headless-complete D5 feature type + script that clicks
each suggestion chip via preFill and asserts the right surface
renders: WeatherCard (get_weather), StockCard (get_stock_price),
HighlightNote (frontend useComponent), Excalidraw best-effort, and
the canonical "Asia is the largest continent" text reply.
- Existing gen-ui-headless script now drives both turns by chip
click (Profile card + Largest continent) instead of typing.
- Fixtures pin narration legs with both userMessage AND toolCallId
and order them before the bare userMessage toolCall fixture —
aimock's toolCallId matcher reads the LAST tool message in the
request, but in a multi-turn probe that "last tool" stays on a
previous turn's id until a new tool runs, which would otherwise
hijack a later turn's prompt with a stale narration.
- headless-complete UserBubble + AssistantBubble now carry
data-message-role so the harness conversation runner can detect
message arrivals (mirrors the headless-simple convention).
- Mappings updated in lockstep:
- REGISTRY_TO_D5: headless-complete -> ["gen-ui-headless-complete"]
- CATALOG_TO_D5_KEY (dashboard): same.
Builds on the initial Search Flights-only probe by extending to a
multi-turn ConversationTurn[] that asserts surface-specific render
fingerprints for 7 of the 9 pills in /demos/beautiful-chat.
Pills covered (turn order is load-bearing — see script jsdoc):
1. Toggle Theme — html.dark class flip (toggleTheme frontend tool)
2. Pie Chart — >= 3 svg circles (pieChart useComponent)
3. Bar Chart — recharts container + >= 2 bar rectangles
4. Search Flights — A2UI FlightCard literal fingerprints (#4668 path)
5. Schedule Meeting — MeetingTimePicker mounts; assertion CLICKS a slot
to resolve the HITL pause before subsequent turns
6. Sales Dashboard — A2UI dynamic generate_a2ui → secondary render_a2ui;
"Total Revenue" + recharts container (90s budget)
7. Task Manager — enableAppMode + manage_todos; "To Do" column +
canonical todo title visible. MUST be last
(flips layout, breaks chat input on narrow widths)
Pills intentionally skipped (track in follow-up):
- Excalidraw Diagram — depends on mcp.excalidraw.com reachability,
turning D5 reliability into a 3rd-party uptime bet
- Calculator App — sandboxed iframe makes assertions cross-frame-fragile;
generateSandboxedUi already covered by d5-gen-ui-open
on a different demo route (would duplicate coverage)
Probe uses the runner's structural ConversationPage type for most assertions
(via page.evaluate helpers in the d5-chat-css globalThis-cast pattern, which
keeps the harness's Node-only tsconfig clean of DOM lib types). Schedule
Meeting narrows to an extended Page type with click() — same runtime-guarded
cast used in d5-hitl-text-input — so it can dispatch the HITL slot click.
Fixture file expanded from 2 to 15 entries covering all 7 turns plus their
multi-stage chains (Sales Dashboard primary + secondary LLM + post-tool;
Task Manager enableAppMode → manage_todos → narration). Re-bundled into
showcase/aimock/d5-all.json (additions only — no other fixtures changed).
Conversation runner reports failure_turn so per-pill failure isolation is
preserved on the dashboard's drilldown without needing 7 separate D5 literals.
Beautiful Chat was capped at D4 in the dashboard because it had no
dedicated D5 probe and was deliberately excluded from CATALOG_TO_D5_KEY
(commit 974494ecb stripped the freeloading "agentic-chat" alias). PR
#4668 fixed the A2UI surface rendering and added e2e tests, but those
land at the D3 tier — D5 is a separate probe with its own driver.
Changes:
- New d5-beautiful-chat probe asserts the A2UI fixed-schema FlightCard
surface renders with literal United/Delta/$349/$289 fingerprints from
the search_flights tool. 60s budget on first card, 5s on siblings.
- New harness/fixtures/d5/beautiful-chat.json with two-stage fixture
(hasToolResult false→true) mirroring the gen-ui-headless pattern.
Fixture spliced into the bundled aimock/d5-all.json.
- New "beautiful-chat" D5FeatureType literal in the registry's union +
runtime mirror.
- d5-feature-mapping.ts: replace "beautiful-chat": ["agentic-chat"]
alias with ["beautiful-chat"] so the probe targets its own dedicated
PB key instead of freeloading agentic-chat's green status.
- live-status.ts CATALOG_TO_D5_KEY: re-add "beautiful-chat":
["beautiful-chat"] so computeMaxPossible lifts the D4 cap to D5.
## 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.
PR #4579 added a `reasoning` field to the "show your reasoning step by
step" fixture so aimock would emit response.reasoning_summary_* deltas
for the OpenAI Responses API path. Side effect: aimock's Chat
Completions handler also emits non-standard `reasoning_content` deltas
(DeepSeek/Qwen-style) ahead of the role/content chunks. Many
integrations' OpenAI client adapters don't expect those deltas and
either hang or fail to parse the stream — manifesting as "assistant
did not respond within 30000ms" across most reasoning cells in
production.
Restore the original content-only fixture. The langgraph-python /
langgraph-fastapi agent fixes from #4579 still work against real
OpenAI (gpt-5-mini + Responses API streams real reasoning summaries),
but the aimock-driven path no longer exercises the role-reasoning
render — keyword-only assertion in the d5 probe handles that.
## 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.
The 6 beautiful-chat demos (spring-ai, strands, langroid, agno,
claude-sdk-typescript, claude-sdk-python) ship three identical
suggestion chips: "Plan a 3-day Tokyo trip", "Explain RAG like I'm
12", and "Draft a launch email". Against the deployed aimock-backed
showcase, all three were broken:
- Tokyo trip: hijacked by the broad `userMessage: "hi"` fixture,
because the substring "hi" appears inside "arc**hi**tecture" in
the prompt. Returned a generic "Hi there! I'm your showcase
assistant..." greeting with nothing about Tokyo.
- RAG explain: no fixture matched, aimock returned an error.
- Launch email: same — no fixture, error.
Add three on-topic fixtures with the full suggestion sentence as
`userMessage` (effectively-exact substring match). Place them
before the broad "hi" fixture in the file so first-match-wins
routes each suggestion to the right response.
Add a `beautiful-chat.spec.ts` regression suite to all 6
integrations: send each suggestion, assert the right keywords
appear in the assistant reply ("Day 1/2/3" for Tokyo,
"open-book/RAG" for RAG, "Subject:/co-pilot" for email), AND
assert the hijacked greeting is absent. If the broad "hi" fixture
re-broadens or the new fixtures are reordered/removed, these
tests fail loudly.
Add D5 voice test that exercises sample-audio transcription via aimock.
Infrastructure: voice in D5 feature type registry + mapping, skipFill
support in conversation runner (9 new tests), inputValue forwarding
in e2e-deep Page wrappers, aimock transcription fixture, tool-free
weather fallback fixture for agents without tools. Verified locally:
D5 suite passes green on langgraph-python (60.4s).
agent-config: drop the AgentConfigLangGraphAgent subclass and use plain
LangGraphAgent. The subclass repacked CopilotKit provider properties
into forwardedProps.config.configurable.properties so the Python graph
could read them via RunnableConfig.configurable.properties — but
@ag-ui/langgraph@0.0.31 builds the LangGraph SDK request as
{ ..., config, context: { ...input.context, ...config.configurable } }
which merges configurable INTO context. LangGraph 0.6.0+ then rejects
with HTTP 400 'Cannot specify both configurable and context' on every
chat round-trip. Net effect: chat sent the user message, runtime 400'd,
no assistant response ever rendered. Removing the subclass unbreaks
the round-trip; the Python agent falls back to its DEFAULT_* constants
so the demo's frontend toggles no longer steer the system prompt
(known regression, tracked separately pending @ag-ui/langgraph fix
that decouples context from configurable).
byoc:
- D5 probe now sends the 'Sales dashboard' pill prompt (matches the
fixtures added in main:f0a89b843 in feature-parity.json) instead of
the previous generic 'render a byoc hashbrown' prompt that had no
matching JSON-shaped fixture. Removed the now-obsolete byoc.json D5
fixture file and regenerated the d5-all.json bundle (52 -> 50
fixtures).
- Added data-testid='copilot-assistant-message' + data-message-role=
'assistant' to the byoc-hashbrown and byoc-json-render renderer
wrapper divs. The CopilotChat default assistantMessage slot includes
these markers; overriding the slot with a custom JSON-rendering
component dropped them, so the e2e-deep conversation runner's
settle-detection cascade (which counts these selectors) never saw
the response and timed out at 30s. Re-attaching the markers is a
purely additive change that doesn't affect the renderers'
behavior.
- D5 byoc assertion now waits for [data-testid='metric-card'] AND a
chart (bar-chart or pie-chart) to render — a structural check on
the BYOC contract output, not a transcript-keyword check that the
custom renderer would never produce.
E2E status: 31/31 passing locally against
./bin/showcase up langgraph-python aimock with this branch's bundle.
Both BYOC demo pills were getting eaten by older generic substring
fixtures ("dashboard", "revenue by category as a pie chart", "monthly
expenses as a bar chart") — the json-render pills came back as foreign
tool calls (render_pie_chart) and the hashbrown sales pill came back as
the "Working on your request..." placeholder, leaving both renderers
empty.
Add a dedicated fixture per pill keyed on the full pill prompt sentence,
placed before the conflicting generic rules so first-fixture-wins lands
on the right one. Each fixture returns the exact content shape the
demo's renderer expects:
byoc-json-render -> {root, elements} flat spec for <Renderer />
byoc-hashbrown -> {ui:[{<tag>:{props:{...}}}]} for useJsonParser
Removes two pre-existing duplicates that had been added at the bottom of
the file but never matched because the conflicting generic rules came
first.
Beautiful Chat suggestion clicks looped forever because feature-parity.json
tool-calling fixtures lacked an `id` and a paired `toolCallId` followup.
After the agent ran the tool and re-prompted aimock, the same userMessage
substring matched again and the same toolCall was returned indefinitely.
Added explicit ids to 10 broken fixtures (pieChart, barChart, render_*_chart,
scheduleTime, search_flights, toggleTheme) and 11 paired toolCallId
followups returning content summaries — same convention the file already
uses for show_card, weather, etc.
Beautiful Chat layout also showed a black/white split and a broken logo on
the 8 integrations using the full ExampleLayout pattern (crewai-crews,
langgraph-fastapi, langgraph-python, langgraph-typescript, mastra,
ms-agent-dotnet, ms-agent-python, pydantic-ai). Two issues:
1. globals.css hardcoded `body { background: #fafaf9 }` and never defined
the brand tokens (--background, --foreground, --card, --primary, …) that
the layout, mode-toggle, todo card/column, and chart components reference
via Tailwind 4 arbitrary values. ThemeProvider was also adding `dark` to
<html> from system preference, so CopilotKit's chat went dark while body
stayed cream.
2. example-layout/index.tsx renders <img src="/copilotkit-logo.svg" /> but
the file did not exist in any integration's public/.
Added the full token set (light + dark) under :root and :root.dark/.dark,
registered the Tailwind 4 dark variant, switched body to var(--background)
/var(--foreground), and copied copilotkit-logo.svg + copilotkit-logo-mark.svg
into each integration's public/ from examples/integrations/langgraph-python.
Production showcase-aimock was running a week-old image because fixture
file changes in showcase/aimock/ did not trigger a CI rebuild. This adds
showcase-aimock to the Build & Deploy workflow matrix so it auto-deploys
on merge, creates a thin Dockerfile that bakes fixture files into the
image, documents the local-vs-production parity requirement in
docker-compose.local.yml, and adds an aimock fixture deployment section
to the RUNBOOK.
Add 3 fixtures for the independent LLM calls made by each sub-agent
tool (research_agent, writing_agent, critique_agent) so the demo works
without --proxy-only mode. Interleave them with supervisor fixtures for
readability. Rebuild d5-all.json bundle.
aimock v1.16.0 ships native turnIndex matching — counts assistant
messages in the request's message array instead of relying on
toolCallId in the last tool message. Stateless, concurrent-safe,
fixture-ordering-insensitive.
Removes all toolCallId match criteria from 9 D5 fixture files (8
source + 1 bundle), adds turnIndex values, and reorders fixtures
to natural 0→N reading order.
aimock sequenceIndex counter is server-global, causing fixture match
failures when multiple integrations run concurrently. Replace with
stateless toolCallId matching.
agent-config — empty stream
The /demos/agent-config runtime returned RUN_ERROR on every send. The
existing route wrapper repacked the provider's properties into
forwardedProps.config.configurable.properties so the agent could read
them via RunnableConfig["configurable"]["properties"]. LangGraph 1.x
(deployed langgraph 1.1.x / langgraph-api 0.7.x) now rejects any run
that sends configurable with "Cannot specify both configurable and
context. Prefer setting context alone." because it auto-injects an
empty context and refuses both channels at once.
Switch to LangGraph 1.x's context API: route wrapper repacks user props
onto forwardedProps.context instead, the Python graph defines
context_schema=AgentConfigContext and reads via the
Runtime[AgentConfigContext] parameter, and RunnableConfig is no longer
consulted. Unit tests updated to pass the flat context dict directly.
Add context to RESERVED_FORWARDED_PROPS_KEYS so a caller that
explicitly sets forwardedProps.context is preserved (and merged with
provider-supplied properties) instead of being treated as a user prop
and double-wrapped.
multimodal — PDF "doesn't work"
The multimodal pipeline (legacy-shape rewrite shim → ag-ui-langgraph
converter → _PdfFlattenMiddleware running pypdf) is fine; sample.pdf
extraction shows up correctly in the run state snapshot. The visible
breakage is the aimock fixture file: aimock matches userMessage as a
substring, and the generic "hi" fixture lives early enough to swallow
any prompt containing "this" — including "What is in this PDF?" and
"What is in this image?" — short-circuiting before the request reaches
real OpenAI and returning a generic "I'm your showcase assistant"
greeting that never references the attachment.
Add two more-specific fixtures ("this PDF", "this image") ahead of the
"hi" entry so multimodal prompts return responses grounded in the
bundled samples. The "hi" fixture stays in place so the several E2E
specs that fill literal "hi" still match it.
Aimock's Gemini adapter synthesizes tool_call_ids (call_gemini_<name>_N)
that don't match the D5 fixture IDs (call_d5_<name>_001). This breaks
ALL two-leg and multi-leg fixtures for google-adk and any future Gemini
backend because Gemini's functionResponse format has no id field.
sequenceIndex counts per-userMessage matches regardless of provider,
making fixtures provider-agnostic.
Also adds missing generate_haiku fixtures to d5-all.json (were in
gen-ui-custom.json but never bundled) and fixes hitl-text-input
fixture arg name→attendee to match frontend schema.
Documents the D5 e2e-deep Chromium memory envelope (4 services x 2
features = 8 concurrent contexts, ~2.4GB peak) and the two tuning
knobs operators should adjust if OOM occurs.
D5 probes hit real LLMs instead of fixtures because the 8 D5 fixture
files in showcase/ops/fixtures/d5/ were never loaded into aimock.
Railway fetches fixtures from GitHub raw URLs at boot — bundle all
D5 fixtures into d5-all.json and document the updated startCommand
with the new URL appearing before feature-parity.json for match
precedence.
Add 20 new aimock fixtures covering all D5 e2e-deep probe prompts:
- 9 toolCallId second-leg fixtures for tool-call round-trips
- 11 new userMessage fixtures for multi-turn and feature-specific flows
- Explicit tool call IDs on existing weather/pie-chart fixtures
- Correct Alice ordering to prevent substring collision
Without these fixtures, D5 probes hit real OpenAI (401 with test key)
or loop infinitely on tool calls with no second-leg response.
The aimock-fixture-coverage probe scans byoc-json-render.spec.ts and was
flagging two prompts without matching feature-parity.json fixtures:
- "Break down revenue by category as a pie chart"
- "Show me monthly expenses as a bar chart"
Existing pie/bar fixtures used substrings ("revenue distribution by
category", "expenses by category") that don't appear in these prompts,
so the substring matcher returned no hits.
Added two new fixtures with substrings that DO appear in the prompts
("revenue by category as a pie chart", "monthly expenses as a bar
chart") so the coverage probe stays green and aimock returns
deterministic chart data when the BYOC json-render specs run against
the sidecar.
Adds two feature-parity.json fixtures for the langgraph-python
byoc-json-render E2E spec prompts that the
aimock-fixture-coverage probe flagged as uncovered:
- "Break down revenue by category as a pie chart"
- "Show me monthly expenses as a bar chart"
Responses mirror the worked examples baked into the
byoc_json_render_agent system prompt verbatim, so the fixture
output matches what the live LLM would emit (a single
@json-render/react flat-spec JSON object) and the spec
assertions on [data-testid="pie-chart"] /
[data-testid="bar-chart"] resolve deterministically when the
suite runs against the aimock sidecar.
Wire CopilotChat AttachmentsConfig (image + PDF, inline base64) into a
dedicated /demos/multimodal cell backed by a vision-capable LangGraph
agent (gpt-4o). Scoped to its own runtime route so the vision cost
stays on this demo.
- Dedicated /api/copilotkit-multimodal route registering the new
multimodal graph under the multimodal-demo slug
- src/agents/multimodal_agent.py with an AgentMiddleware that flattens
PDF content parts to text server-side via pypdf
- Try with sample image / PDF buttons that drive CopilotChats own
hidden file input via DataTransfer + change event, so the sample and
paperclip paths exercise the same useAttachments pipeline
- public/demo-files/ placeholder — sample.png / sample.pdf binaries
are produced by the user at the end of the Wave 2b rollout
- Manifest + registry + constraints + docs-links wired; normalized
multi-modal -> multimodal in constraints to match the feature
registry id
- QA checklist + Playwright E2E spec (not run yet — pending deploy)
- aimock fixtures for sample prompts so CI runs are deterministic
- Extend the check-binaries hook allowlist to cover the shell-docs and
shell-dojo demo-content.json mirrors (same size as shell/src/data,
already allowed) so regenerated derived data can be committed
9 new userMessage->toolCall/content fixtures in feature-parity.json
for langgraph-python demos. New aimock-fixture-coverage.test.ts
enforces per-spec fixture presence — every E2E spec prompt must
have a matching aimock fixture or be explicitly skipped.
Tighten pie-chart fixture match to avoid beautiful-chat collision:
match specific gen-ui-tool-based prompt text instead of generic
substring that also hits beautiful-chat suggestion pills.
Railway now pulls ghcr.io/copilotkit/aimock:latest directly
via a startCommand that fetches fixtures from GitHub raw URLs.
The wrapper Dockerfile that copied fixtures into the image is
no longer needed.
Also updates README.md to reflect the new architecture:
- References Railway startCommand instead of Dockerfile
- Removes the Dockerfile entry from the fixtures listing
- Updates related workflow descriptions
Alem Tuzlak