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5cd77233b7
Brings ms-agent-python to one-to-one parity with langgraph-python (the D5
north star). Playwright e2e suite goes from 49/108 (~26%) → 164/178 (~92%),
33 of 37 cells fully green.
Manifest parity:
- Drop 4 MAF-only cells with no LGP analog: agentic-chat-reasoning,
hitl-in-chat-booking, shared-state-write, reasoning-default-render.
Reasoning is handled by reasoning-default + reasoning-custom (LGP);
booking pill folds into hitl-in-chat; shared-state-write was a TODO stub.
- Rename byoc-hashbrown → declarative-hashbrown and byoc-json-render →
declarative-json-render. Demo dir, API route dir, and frontend agent id
follow LGP's naming. Python module files retain the legacy `byoc_*`
prefix and FastAPI paths stay `/byoc-hashbrown` / `/byoc-json-render`
(matches LGP's "module name retains legacy graph id" convention).
- Port LGP `_shared/`, `_shared/interrupt-fallback-slots.ts`, and
`demos/layout.tsx` for one-to-one parity.
Cells ported verbatim from LGP (page + spec):
- agentic-chat, auth, beautiful-chat, chat-customization-css, chat-slots,
declarative-gen-ui, declarative-hashbrown, declarative-json-render,
frontend-tools, frontend-tools-async, gen-ui-agent, gen-ui-interrupt,
gen-ui-tool-based, headless-complete, headless-simple, hitl-in-app,
hitl-in-chat, shared-state-read, shared-state-read-write,
shared-state-streaming, subagents, tool-rendering, plus all four
tool-rendering* variants, a2ui-fixed-schema, agent-config, mcp-apps,
multimodal, open-gen-ui, open-gen-ui-advanced, prebuilt-popup,
prebuilt-sidebar, readonly-state-agent-context, reasoning-default,
reasoning-custom, voice.
Backend infrastructure:
- Swap shared `OpenAIChatClient` (Responses API) → `OpenAIChatCompletionClient`
(ChatCompletions). Root cause of the cross-cell post-tool ChatClientException
family: Responses API is stateful and only sends NEW items per leg,
relying on `previous_response_id` for history. aimock has no view of
that server-side state, so second-leg requests arrived without the
user message — fixture matchers keyed on `userMessage` couldn't fire
and the run fell through to real OpenAI. ChatCompletions sends full
history every leg, matching the LGP wire shape.
- Bump @ag-ui/client ^0.0.43 → ^0.0.53 (matches google-adk/LGP). Fixes
the REASONING_* Zod discriminator trap on the catch-all agent.
- Regenerate package-lock.json in isolation outside the pnpm monorepo so
npm-arborist doesn't resolve transitives against pnpm's hoisted
symlinks (avoid 40+ `../../../node_modules/.pnpm/...` paths in the
lockfile that break `npm ci` inside Docker).
- Add `yaml` (^2.8.4) for the new `src/app/demos/layout.tsx` that reads
manifest.yaml for per-cell page titles (LGP parity).
New / re-added MAF agent backends with LGP-equivalent behavior:
- reasoning_agent.py (uses Responses API explicitly — the only chat
client that emits AG-UI REASONING_MESSAGE_* events; rest of the
integration stays on ChatCompletions).
- tool_rendering_agent.py (non-reasoning sibling of the existing
reasoning_chain variant; shares tool surface via direct imports so
they can never drift apart; routes the three catchall cells to a
non-reasoning backend so the default renderer spec stops failing on
leaked reasoning blocks).
- gen_ui_agent.py — `set_steps` tool + `steps` state schema +
`predict_state_config` mirrors LGP's StateStreamingMiddleware shape.
- shared_state_streaming.py — `write_document` tool with
`predict_state_config` that streams the `document` arg into
`state.document` per-token.
- readonly_state_agent_context.py — minimal agent that consumes
frontend-provided `useAgentContext` entries; no tools.
- headless_complete_agent.py — three deterministic tools (`get_weather`,
`get_stock_price`, `get_revenue_chart`) mounted at /headless-complete
on the mcp-apps runtime (was routing to catch-all sales agent, which
returned seeded-random weather instead of the deterministic 68°F the
test asserts on).
Wiring:
- copilotkit/route.ts: register the new agents, drop the stale
shared-state-write entry, route all three tool-rendering variants to
the non-reasoning backend (the reasoning-chain cell keeps its own
dedicated path), register reasoning-default + reasoning-custom on
/reasoning, register gen-ui-agent on /gen-ui-agent,
shared-state-streaming on /shared-state-streaming,
readonly-state-agent-context on its dedicated path.
- copilotkit-mcp-apps/route.ts: register headless-complete agent (was
missing — the strict useAgent runtime sync in the newer
@copilotkit/react-core surfaced the gap).
- copilotkit-declarative-hashbrown/route.ts + copilotkit-declarative-json-render/route.ts:
new dedicated runtimes; agent IDs and runtime URLs follow LGP.
- copilotkit-declarative-gen-ui/route.ts: drop non-LGP `openGenerativeUI:
false` for parity.
A2UI tool rename — `render_a2ui` → `_design_a2ui_surface`:
- Ported LGP's `tools/generate_a2ui.py` (LGP renamed the secondary-LLM
tool to `_design_a2ui_surface` to avoid the A2UI middleware's bypass;
shared d5-all.json fixtures key the response on this name).
- Renamed every `render_a2ui` occurrence in src/agents/{a2ui_dynamic,
agent,beautiful_chat}.py and `tools/__init__.py`.
- Updated 4 declarative-gen-ui aimock fixtures to pass `context` arg in
the first-leg `generate_a2ui` tool call (agent_framework doesn't
auto-inject AgentSession into our @tool function so `session=None` and
the secondary-LLM `user_content` was defaulting to a catch-all string
containing "KPI dashboard" — every pill matched the KPI fixture).
Aimock router patch persisted alongside the integration changes:
hasToolResult matcher restricted to scan only messages after the last
user message (was global). The patch lives in F:/projects/cpk/aimock —
upstream PR pending.
Test infrastructure:
- playwright.config.ts: cap local workers at 4 + retries at 1. CI keeps
workers=1, retries=2. `agent_framework.Agent` is reused across requests
and the shared OpenAI HTTP client serialises concurrent SSE streams;
>4 workers makes 30s timeouts inevitable on a few cells. Confirmed
with hard data: workers=1 = 164 passed (16.8 min), workers=4+retries=1
= 164 passed (7.2 min), workers=undefined = 159 passed. Same green
set, ~2x faster. Long-term upstream fix is per-request Agent
instantiation in agent_framework_ag_ui.
Remaining 14 failures across 4 cells documented per-cell in the Notion
D5 sweep doc (declarative-gen-ui A2UI surface mounting, multimodal
attachment forwarding, tool-rendering-default-catchall multi-pill chain,
tool-rendering-reasoning-chain multi-leg chains). Each has a specific
next-pass action.
109 lines
4.6 KiB
TypeScript
109 lines
4.6 KiB
TypeScript
import { test, expect } from "@playwright/test";
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// QA reference: qa/a2ui-fixed-schema.md
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// Demo source: src/app/demos/a2ui-fixed-schema/{page.tsx, a2ui/*}
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// Backend: src/agents/a2ui_fixed.py + src/agents/a2ui_schemas/flight_schema.json
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//
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// Pattern: A2UI FIXED-schema — the component tree lives on the frontend
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// (flight_schema.json has 12 nodes: root, content, title, route, from,
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// arrow, to, meta, airline, price, bookButton, bookButtonLabel) and the
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// agent only streams DATA into the data model via the `display_flight`
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// tool. Our custom renderers (Title, Airport, Arrow, AirlineBadge,
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// PriceTag, Button) bind path strings like "/airline" / "/price" to the
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// incoming data model.
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//
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// This is a pure-presentation demo: the "Book flight" Button is inert —
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// schema-swap-on-action will be wired up once the Python SDK exposes
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// `action_handlers=` on `a2ui.render` (see comment in a2ui_fixed.py).
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//
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// No data-testid anywhere in the demo. Assertions ride on:
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// - verbatim label text hardcoded in flight_schema.json ("Flight
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// Details", "Book flight") — these are literal `text` constants,
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// NOT data-model bindings, so they do not leak a {path} object
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// even if the data model is absent.
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// - brand colour fingerprints unique to each renderer (mint #189370
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// price, lilac #BEC2FF airline badge border, black #010507 book
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// button background).
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//
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// W8-8: on Railway, `display_flight` occasionally stalls the secondary
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// LLM stage; render budget is 60s.
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test.describe("A2UI Fixed Schema (flight card)", () => {
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test.setTimeout(120_000);
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test.beforeEach(async ({ page }) => {
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await page.goto("/demos/a2ui-fixed-schema");
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});
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test("page loads with chat input and no flight card rendered", async ({
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page,
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}) => {
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await expect(page.getByPlaceholder("Type a message")).toBeVisible();
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// "Flight Details" is the title literal from flight_schema.json. It
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// must NOT be on the page before the agent emits an a2ui_operations
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// container — that would indicate a stale render or a schema leak.
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await expect(page.getByText("Flight Details")).toHaveCount(0);
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});
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test("single suggestion pill renders with verbatim title", async ({
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page,
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}) => {
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const suggestions = page.locator('[data-testid="copilot-suggestion"]');
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await expect(
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suggestions.filter({ hasText: "Find SFO → JFK" }).first(),
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).toBeVisible({ timeout: 15_000 });
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});
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test("search-flights pill renders a flight card matching flight_schema", async ({
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page,
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}) => {
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const suggestions = page.locator('[data-testid="copilot-suggestion"]');
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await suggestions.filter({ hasText: "Find SFO → JFK" }).first().click();
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// Title is a literal in flight_schema.json ("Flight Details").
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// 90s budget: on cold starts the `display_flight` tool call + the
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// a2ui_operations container round-trip can eat most of a minute.
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await expect(page.getByText("Flight Details").first()).toBeVisible({
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timeout: 90_000,
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});
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// Route: Airport renderer formats as monospace 1.5rem; the
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// user-visible content is the uppercase airport code. SFO / JFK are
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// explicit in the prompt so the secondary LLM is extremely likely
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// to bind them verbatim into origin/destination.
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await expect(page.getByText("SFO").first()).toBeVisible({
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timeout: 10_000,
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});
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await expect(page.getByText("JFK").first()).toBeVisible({
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timeout: 10_000,
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});
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// Book flight button label is a literal in flight_schema.json
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// (`bookButtonLabel.text`). Presence = the full 12-node tree
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// rendered, including the Button override.
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await expect(page.getByRole("button", { name: "Book flight" })).toBeVisible(
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{ timeout: 10_000 },
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);
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// Regression guard (#4734): on Railway the deployed agent used to loop
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// `display_flight` indefinitely because the LLM (gpt-4o-mini) couldn't
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// tell the opaque `a2ui.render(...)` JSON return value was a success
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// signal. The fix tightened the docstring + system prompt to spell out
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// "card is rendered, do not call again". Assert that exactly ONE flight
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// card is present after the round-trip — duplicates mean the loop
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// re-emerged.
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const flightDetailsCount = await page.getByText("Flight Details").count();
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expect(flightDetailsCount).toBe(1);
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const bookButtons = await page
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.getByRole("button", { name: "Book flight" })
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.count();
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expect(bookButtons).toBe(1);
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// Regression guard: no A2UI render-error banners on the page.
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await expect(page.getByText(/Catalog not found/i)).toHaveCount(0);
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await expect(
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page.getByText(/Cannot create component .* without a type/i),
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).toHaveCount(0);
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});
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});
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