Mirrors LGP's `generate_a2ui` outer-emit fixture into 8 non-LGP slugs to close
the production 503 gap on the "Show me my sales dashboard for this quarter."
userMessage. Per /tmp/staging-journal-diff.md, aimock-staging returns 503 on
shape-B traffic (model=gpt-4.1, stream=true, tools=[generate_a2ui],
UA=AsyncOpenAI/Python) for all 8 slugs because no fixture matched.
Slugs patched (one entry each in d6/<slug>/gen-ui-declarative.json):
- llamaindex
- built-in-agent
- ag2
- langroid
- claude-sdk-typescript
- claude-sdk-python
- ms-agent-dotnet
- ms-agent-python
Each entry matches `userMessage` + `context: "<slug>"` and emits a
`generate_a2ui` toolcall with no args, mirroring LGP's sales-dashboard outer
entry. Per-slug unique toolCallId.
Red-green proof (local aimock, ghcr.io/copilotkit/aimock:latest):
RED (baseline main, 8 slugs): HTTP=404 no_fixture_match
GREEN (this branch, 8 slugs): HTTP=200 tool=generate_a2ui id=call_d6_decl_dash_outer_<slug>_001
LGP regression (baseline+fix): HTTP=200 (unchanged)
aimock fixture validation: 737/737 tests pass.
PR scope is intentionally narrow per CLAUDE.md "Scope PRs to flagged
findings": this closes ONE userMessage gap. Shape-A 503s (no tools key) and
other userMessage gaps remain as separate follow-ups.
crewai-crews/ms-agent-python/pydantic-ai catchall AAPL entries still carried stale $189.42/up 1.27% narration and toolCall args lacking price_usd/change_pct. Round 1 CR finding #3 was identified but never given a fix agent. Brought all 3 to canonical shape matching built-in-agent (A5) and csdkts narration (A6): price_usd=338.37, change_pct=-2.96, narration 'AAPL is trading at $338.37, down 2.96% on the day — rendered through the custom wildcard catchall.'
(cherry picked from commit df84657310451500278d0b3d0125c9c490042d2b)
built-in-agent, crewai-crews, ms-agent-python, pydantic-ai: Tokyo turn-1 tool result makes hasToolResult permanently true → AAPL fixture never matched → 30s timeout. Aligned with agno/langroid/llamaindex/strands/claude-sdk-python pattern: rely on userMessage+context (and toolCallId where relevant) as the gate.
(cherry picked from commit 8e313cd1b043cf1c61efb82143171a28d7699c49)
Closed PR #5465 introduced cross-fixture leakage by stripping the
toolName discriminator on shared {userMessage, context} keys: with
aimock's alphabetical first-match-wins ordering,
tool-rendering-custom-catchall.json sorts before
tool-rendering-default-catchall.json, so default-catchall page requests
were served the custom file's content. The probe was structurally blind
because it asserted only DOM testids (copilot-tool-render +
data-tool-name=get_weather) — both fixtures emit get_weather, so the
testid signal passed regardless of which fixture won.
Real LGP-gold pattern is disjoint userMessages between default and
custom catchall fixtures (NOT shared keys discriminated by toolName).
This PR ports the LGP-gold pattern to the other 17 integrations and
adds page-text content assertions to both d5 catchall probes so this
class of regression can't recur silently:
- Probe prompts disjoint between default-catchall and custom-catchall
- Fixture userMessages updated to match the new disjoint prompts
- Page-text content assertions in both d5 catchall probes
(default negatively asserts the custom-catchall leak phrase;
custom positively asserts it)
Local gold-standard red-green proof captured:
- Step A: live staging Playwright baseline (RED-OF-RECORD)
- Step B: local control-plane on origin/main reproduces structural
fragility (probes pass at testid level, custom fixture wins on
default's userMessage path)
- Step C: local control-plane on this branch — both catchall probes
GREEN with the new content-asserting assertions
tool-rendering-default-catchall: pass=true (5443ms)
tool-rendering-custom-catchall: pass=true (8956ms)
cross-tool signature passed
LGP (langgraph-python) was already disjoint; it remains untouched.
The previous 'weather in Tokyo' rename (388c69e68) was a substring of the
main tool-rendering chain pill prompt 'Chain a few tools in this single
turn: get the weather in Tokyo, search flights from SFO to Tokyo, and roll
a d20.' Because aimock loads fixtures alphabetically per integration dir
and uses substring match with first-match-wins, the catchall fixture
(loaded before tool-rendering.json) was intercepting chain pill matches
across 16 integrations.
Rename catchall fixture userMessage to 'forecast for Tokyo' — a phrase
not contained in any other pill prompt. Update the corresponding D5
catchall probe inputs in d5-tool-rendering-{default,custom}-catchall.ts
and the test assertions that pin those inputs.
Call-Site Enumeration: 'weather in Tokyo' remains intentionally in
page.tsx suggestions.ts pills (user-visible UX) and inside the chain
pill prompt itself — neither is in the substring-match path now.
The D5 e2e-deep probe for tool-rendering-{default,custom}-catchall sends
"weather in Tokyo" as the test input (harness/src/probes/scripts/
d5-tool-rendering-{default,custom}-catchall.ts). The fixture userMessage
matcher uses substring match. Main's catchall fixtures had a stale
"check Tokyo weather forecast" string that could not substring-match
the probe input, causing the fixture to miss and the probe to fall
through to the live LLM — surfacing as CV x red D4 on the dashboard.
Rename to the canonical "weather in Tokyo" string across affected
integrations' tool-rendering-{default,custom}-catchall.json files.
No agent or page.tsx changes; fixture content otherwise unchanged.
- SUPERSEDED annotations on unreachable recorded calculator entries (load-order shadowing is
the only guarantee; model gate is not a safety net)
- GOTCHAS sequenceIndex rewritten to per-X-Test-Id semantics with co-increment/eviction caveats
- hasToolResult paragraph corrected (omission = no gate, thread-global predicate)
- statelessness claim reconciled with sequence counters
- replace Websandbox host-bridge evaluateExpression (never registered in beautiful-chat) with
in-sandbox allowlist-gated Function() eval
- reorder specific calculator pair before generic (first-match-wins)
- allow exponential notation (eE) so chained evaluation of large results works
- drop thread-global hasToolResult gate that broke the pill after other tool-producing pills,
reorder toolCallId follow-ups before leg-1
- mint distinct tool_call_ids per repeat click via sequenceIndex variants + non-sequenced
fallback (fixes second-widget collapse)
- restore google-adk trailing newline
- document ordering invariants, gate tradeoffs, and sequence-counter scoping caveats in
fixture comments
Verified via local Playwright red-green (render, 7+8=15, chained exponent, interleaved pills,
repeat clicks).
The gen-ui-headless-complete probe
(showcase/harness/src/probes/scripts/d5-gen-ui-headless-complete.ts)
references fixtureFile "gen-ui-headless-complete.json", but that file
existed in no D6 slug, so the probe's first leg 503'd under strict.
Add gen-ui-headless-complete.json for all 18 D6 slugs, modeled on the
green langgraph-python headless-complete.json pattern: the four gen-UI
pills (weather/stock/highlight/revenue) with narration (toolCallId)
fixtures FIRST and toolcall (userMessage+context) fixtures AFTER, no
turnIndex gate, so every one of the probe's four sequential turns in one
chat thread matches regardless of prior assistant/tool history. Interrupt
fixtures are intentionally omitted (interrupt-headless is a separate
cluster item).
These 8 fixtures per slug share match keys with the pre-existing
headless-complete.json for the same context (the demos share pills and
are disambiguated at runtime by probe path), which raises the
aimock-fixtures collision-detection exact-duplicate count by 46. Bump
KNOWN_DUPLICATE_CEILING 230 -> 276 to match, consistent with how prior
per-integration feature fixtures bumped the baseline; the substring-shadow
ceiling is unchanged (no new shadows).
Validated: all 732 aimock-fixtures schema/collision tests pass, and a
local aimock --strict run returns 200 for each of the four pills across
turns (langgraph-python + pydantic-ai spearheads, plus spring-ai).
Port the replay-safe toolCallId stripping middleware from the ms-agent-dotnet
sibling route.ts so HITL/interrupt demos match toolCallId-keyed aimock
fixtures across the 2nd-turn request. The strip walks every inbound message
(role=tool, role=assistant.toolCalls[].id, toolCallId, tool_call_id) before
the AG-UI HttpAgent forwards them onto the FastAPI backend, and the outbound
event stream rewrites toolCallId on TOOL_CALL_* events to embed the
deterministic per-run suffix so the next turn's fixture matcher still
keys on the original (suffix-stripped) id.
Wraps the human_in_the_loop, interrupt-adapted, hitl-in-app, and
hitl-in-chat agents with the new replay-safe middleware. Adds gen-ui-agent
set_steps state-snapshot synthesis, readonly-state-agent-context system
message injection, and shared-state-read-write preference-as-system
injection — all ported verbatim from the dotnet sibling so the per-agent
shaping behavior is identical across the MAF runtimes.
chat-slots.json: add the turnIndex:1 "Give me a fun fact" fixture mirrored
from langgraph-python/chat-slots.json so the chat-slots.spec.ts second-
turn assertion ("second assistant turn is also wrapped in the custom
slot") gets a deterministic reply instead of falling through to headless-
simple's fun-fact fixture or the live proxy.
hitl-in-app and hitl-in-chat demo pages were already mirrored from LGP
(only a minor consumerAgentId addition on the in-app suggestions module).
No frontend page changes needed.
The B2 header-forwarding conveyance in src/agents/_header_forwarding.py
is untouched and verified intact (httpx hook + Starlette HTTP middleware
plus ContextVar bridge).
Multimodal diagnosis: the 5-test multimodal.spec.ts timeout is NOT a
routing/wiring gap. The agent_server.py mounts /multimodal FIRST (before
the catch-all "/"), the dedicated Next.js route /api/copilotkit-multimodal
registers the HttpAgent under "multimodal-demo", and the page wires
runtimeUrl + agent correctly. The multimodal fixture's userMessage
"describe the sample image" is the same stale phrasing LGP uses (which
passes at 185/0/2 — the test asserts a /image/i regex on the assistant
transcript, so fallthrough to the proxy still satisfies it). The
remaining suspects are (a) agent_framework_ag_ui's AG-UI -> AF adapter
mishandling inbound `binary` content parts, (b) the dual chat_client
init pattern (multimodal_chat_client built after the global httpx hook
is installed — the hook is idempotent so this should be safe), or
(c) >30s real-OpenAI vision latency under D6 record-replay. Capture
agent_server stderr during a single multimodal run to confirm.
Same pattern as ms-agent-dotnet: full d4 chat.json rewrite + d6 mirrors. Dropped stale
turnIndex gates and broad shadow matchers. Default-catchall now green via page-level
shadcn-catchall-renderer. 11 residual: declarative-gen-ui charts, multimodal conveyance,
tool-rendering, reasoning-chain.
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.
Move monolithic d5-all.json + feature-parity.json + smoke.json into
per-integration directories under d4/<slug>/, d6/<slug>/, and shared/.
Every fixture file is now context-scoped to enable server-side aimock
routing via match.context. Migrated 12 HITL fixtures from main's
d5-all.json additions into shared/_migrated-from-d5-all-hitl.json
for follow-up distribution into per-integration files.
Jordan Ritter