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Result of 10 parallel QA agents auditing all 30 active demos against
langgraph-python (north-star). Each agent ported drift back to LP-verbatim
across three axes:
1. Agent layer
- tool_rendering_common.py: rebuilt to LP's surface — get_weather,
search_flights(origin, destination), get_stock_price, roll_d20,
roll_dice. Removed the ADK-only query_data.
- tool_rendering_*_agent.py (4 variants): ported LP's travel/concierge
prompt; reasoning-chain variant got LP's chain-two-tools prompt.
- beautiful_chat_agent.py: ported LP's per-tool system prompt; added
manage_sales_todos / get_sales_todos / generate_a2ui; dropped the
redundant schedule_meeting (frontend HITL handles it).
- open_gen_ui_agents.py: ported LP's full SYSTEM_PROMPT for both
variants, including the Websandbox.connection.remote.* contract
for the advanced sandbox demo (was `window.sandbox.*`, which the
LP frontend's Websandbox bridge silently no-ops).
- byoc_agents.py: fused LP's hashbrown + json-render prompts so the
single ADK byoc_agent emits both wire shapes. Aliases exported for
a future per-route split.
- declarative_gen_ui_agent.py: ported LP's a2ui_dynamic SYSTEM_PROMPT.
- a2ui_fixed_agent.py: picked up LP's #4734 regression guard
("exactly ONCE", "do NOT call again").
- agent_config_agent.py: rewrote to read useAgentContext (was
state["config"]); reconciled schema to LP's 3-field camelCase
{tone, expertise, responseLength} with LP's value enums.
- subagents_agent.py: dropped the "running" placeholder; returns
plain str so the LP-verbatim frontend's `result?.trim()` works.
- hitl_in_app_agent.py / hitl_in_chat_book_call_agent.py: prompts +
tool-result shape ({approved, reason}) aligned to LP.
- AGUIToolset() added wherever it was missing on the bespoke agents
(multimodal, mcp_apps, a2ui_fixed) so frontend-registered tools
reach the model.
2. Dedicated runtime routes
- copilotkit-multimodal/route.ts (new) — mirrors LP shape with
ADK's HttpAgent + AGENT_URL pattern.
- copilotkit-agent-config/route.ts (new) — same pattern.
- copilotkit-mcp-apps/route.ts — refreshed.
3. Frontend ports (ADK frontend brought to LP-verbatim where it had
drifted from the parity blitz state)
- tool-rendering family (4 demos): full re-port — WeatherCard,
FlightListCard, StockCard, D20Card, ReasoningBlock, CatchallRenderer,
suggestions, and the page wiring with all useRenderTool /
useDefaultRenderTool / reasoningMessage registrations.
- a2ui-fixed-schema, mcp-apps, multimodal: full frontend re-ports
with their _components/ Tailwind primitives.
- frontend-tools, frontend-tools-async, agent-config: ported LP's
component structure (separate Background, NotesCard with query_notes,
config-context-relay).
- shared-state-read, shared-state-read-write, readonly-state-agent-context:
ported LP's demo-layout + _components + suggestions. recipe-card.tsx
pulled directly from LP (one QA agent had adapted to Unicode glyphs
thinking ADK lacked lucide-react — it doesn't, after the parity blitz).
- shared-state-streaming, subagents, hitl-in-app: ported LP's
DocumentView / supervisor-activity / TicketsPanel structure.
hitl-in-app/page.tsx pulled directly from LP to keep the hyphenated
agent slug aligned with the renamed registry key.
- auth, hitl-in-chat: ported LP's SignInCard-first auth UX and the
time-picker Tailwind port.
- prebuilt-popup: pulled LP's main-content + suggestions split.
4. Test fixtures
- 30 tests/e2e/<slug>.spec.ts ported from LP, several overwriting
stale stubs (shared-state-streaming, subagents, auth, hitl-in-chat,
shared-state-read, agent-config).
- 30 qa/<slug>.md ported from LP with ADK env-var and registry
references substituted (GOOGLE_API_KEY, AGENT_URL, registry.py).
- QA3's byoc-hashbrown / byoc-json-render specs renamed to
declarative-hashbrown / declarative-json-render with internal
URL references substituted (the orchestrator pass had already
renamed the demo dirs + manifest entries).
Frontend changes from QA agents were filtered: kept where they ported
LP-verbatim into ADK, replaced with direct LP pulls where the agent
had made ADK-specific adaptations (one Unicode-glyph case, one
stale-registry-slug case).
Not touched per blitz rules: shared_chat.py, registry.py, manifest.yaml,
src/app/api/copilotkit/route.ts.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2.8 KiB
2.8 KiB
QA: Shared State (Reading) — Google ADK
Prerequisites
- Demo is deployed and accessible
- Agent backend is healthy (check /api/health)
Test Steps
1. Basic Functionality
- Navigate to the shared-state-read demo page
- Verify the recipe card form loads (
data-testid="recipe-card") - Verify the CopilotSidebar opens by default with title "AI Recipe Assistant"
- Send a message via the sidebar
- Verify the agent responds
2. Feature-Specific Checks
Initial Recipe State
- Verify the recipe title input shows "Make Your Recipe"
- Verify the cooking time dropdown defaults to "45 min"
- Verify the skill level dropdown defaults to "Intermediate"
- Verify the default ingredients are displayed:
- Carrots (3 large, grated) with carrot emoji
- All-Purpose Flour (2 cups) with wheat emoji
- Verify the default instruction is displayed: "Preheat oven to 350°F (175°C)"
Suggestions
- Verify "Create Italian recipe" suggestion is visible
- Verify "Make it healthier" suggestion is visible
- Verify "Suggest variations" suggestion is visible
Recipe Editing (Local State)
- Edit the recipe title and verify it updates
- Change the skill level dropdown and verify it updates
- Change the cooking time dropdown and verify it updates
- Toggle a dietary preference (e.g. "Vegetarian") and verify it's pressed
- Click "+ Add Ingredient" (
data-testid="add-ingredient-button") and verify a new empty row appears - Edit an ingredient name and amount
- Remove an ingredient by clicking the "×" button
- Click "+ Add Step" and verify a new instruction row appears
- Edit an instruction and verify it saves
- Remove an instruction by clicking the "×" button
AI-Powered Recipe Updates (useAgent with shared state)
- Click "Create Italian recipe" suggestion
- Verify the agent acknowledges the request (the wired graph is a neutral chat agent and does not mutate state)
- Verify the "Improve with AI" button (
data-testid="improve-button") changes to "Please Wait..." while loading - Click "Improve with AI" and verify the agent responds
Agent Reads Frontend State
- Edit the recipe (change title, add ingredients)
- Ask the agent "What recipe am I making?"
- Verify the agent's response references the current recipe state
3. Error Handling
- Send an empty message (should be handled gracefully)
- Verify no console errors during normal usage
- Verify the "Improve with AI" button is disabled while loading
Expected Results
- Recipe card and sidebar load within 3 seconds
- Agent responds within 10 seconds
- Recipe state syncs from the UI into agent state every edit (agent does not write back)
- No UI errors or broken layouts