feat(runtimes): maf subagent delegation demo with queue-merged SUBAGENT_* emission

cockpit/runtimes/microsoft-agent-framework/angular/e2e/fixtures/microsoft-agent-framework.json

@@ -34,6 +34,32 @@
           }
         ]
       }
+    },
+    {
+      "match": { "userMessage": "conference travel", "hasToolResult": true },
+      "response": {
+        "content": "Yes — submit the $900 conference travel expense. It is under the $1,500 travel cap; attach itemized receipts since it exceeds the $75 receipts threshold."
+      }
+    },
+    {
+      "match": { "systemMessage": "expense-policy researcher" },
+      "response": {
+        "content": "- Travel expenses up to $1,500 per trip are reimbursable with manager approval.\n- Any expense over the $75 receipts threshold requires itemized receipts.\n- Conference travel must be filed within 30 days of the trip end date."
+      }
+    },
+    {
+      "match": { "userMessage": "conference travel" },
+      "response": {
+        "toolCalls": [
+          {
+            "name": "research_policy",
+            "arguments": {
+              "category": "travel",
+              "amount": 900
+            }
+          }
+        ]
+      }
     }
   ]
 }

cockpit/runtimes/microsoft-agent-framework/angular/e2e/microsoft-agent-framework.spec.ts

@@ -1,5 +1,6 @@
 // SPDX-License-Identifier: MIT
 import { test, expect } from '@playwright/test';
+import { submitAndWaitForResponse } from '@threadplane-internal/e2e-harness';
 
 // First proof outside unit tests that the neutral Agent contract's interrupt
 // path works against a genuinely non-LangGraph AG-UI backend: the Microsoft
@@ -34,3 +35,22 @@ test.describe('cockpit runtimes/microsoft-agent-framework: expense approval', ()
     await expect(page.getByText(/has been submitted for reimbursement/i)).toBeVisible({ timeout: 30_000 });
   });
 });
+
+// Delegation over the same non-LangGraph bridge: the orchestrator's
+// `research_policy` tool streams the tool-less `policy_researcher`
+// specialist, and the queue-merge emitter (src/subagent_emitter.py)
+// translates its deltas into SUBAGENT_STARTED / attributed TEXT_MESSAGE_* /
+// SUBAGENT_FINISHED wire events. The @threadplane/ag-ui reducer keys the
+// subagent to its spawning toolCallId, so <chat-tool-calls> renders the
+// delegation inline as a <chat-subagent-card> instead of a tool-call chip.
+test.describe('cockpit runtimes/microsoft-agent-framework: subagent delegation', () => {
+  test('rt-maf: delegated policy research renders a streaming subagent card', async ({ page }) => {
+    const bubble = await submitAndWaitForResponse(
+      page,
+      'Should I submit a $900 conference travel expense? Research the policy first',
+    );
+    await expect(page.locator('chat-subagent-card')).toHaveCount(1);
+    await expect(page.locator('chat-subagent-card')).toContainText('policy_researcher');
+    await expect(bubble).toContainText(/policy|expense/i);
+  });
+});

cockpit/runtimes/microsoft-agent-framework/python/pyproject.toml

@@ -10,9 +10,18 @@ dependencies = [
     "uvicorn[standard]>=0.29",
 ]
 
+[dependency-groups]
+dev = [
+    "pytest>=8.0",
+    "pytest-asyncio>=0.23",
+]
+
 [build-system]
 requires = ["hatchling"]
 build-backend = "hatchling.build"
 
 [tool.hatch.build.targets.wheel]
 packages = ["src"]
+
+[tool.pytest.ini_options]
+asyncio_mode = "auto"

cockpit/runtimes/microsoft-agent-framework/python/src/agent.py

@@ -14,8 +14,13 @@
   protocol-standard ``RUN_FINISHED.outcome = {type: 'interrupt', ...}`` and
   resumes from the client's top-level ``resume`` entries.
 
-No subagents surface: the MAF bridge emits no per-subagent
-ACTIVITY_SNAPSHOT/ACTIVITY_DELTA stream (measured red upstream).
+- subagents: ``research_policy`` delegates to the tool-less
+  ``policy_researcher`` specialist Agent and streams its deltas through the
+  ``delegation_*`` helpers in src/subagent_emitter.py, which merge standard
+  ``SUBAGENT_*`` + attributed child ``TEXT_MESSAGE_*`` events into the run
+  stream at the run-wrapper seam (the MAF bridge natively emits NOTHING for
+  nested-agent activity inside a tool — measured red upstream and in
+  docs/wire-capture-subagents.md).
 
 Model client: Azure OpenAI is the DEFAULT path — when
 ``AZURE_OPENAI_ENDPOINT`` is set the client routes to Azure (key auth via
@@ -32,6 +37,8 @@
 from agent_framework.openai import OpenAIChatCompletionClient
 from pydantic import BaseModel, Field
 
+from . import subagent_emitter
+
 _POLICIES = {
     "meals": {"limit_usd": 300, "receipt_required_over_usd": 25, "notes": "Team meals require attendee count in the memo."},
     "travel": {"limit_usd": 1500, "receipt_required_over_usd": 0, "notes": "Book through the travel portal when possible."},
@@ -97,6 +104,10 @@ def submit_expense(expense: Expense) -> str:
 
 _INSTRUCTIONS = """You are an expense approval copilot.
 
+Before recommending whether to submit an expense, delegate the policy
+research to the specialist by calling `research_policy` with the category
+and amount.
+
 When the user asks to file an expense:
 1. FIRST call `lookup_expense_policy` with the expense category.
 2. THEN call `submit_expense` with the complete structured expense
@@ -138,12 +149,63 @@ def build_chat_client() -> OpenAIChatCompletionClient:
     )
 
 
+policy_researcher = Agent(
+    name="policy_researcher",
+    instructions=(
+        "You are an expense-policy researcher. Given an expense category and "
+        "amount, summarize the applicable policy rules in 3 short bullets."
+    ),
+    client=build_chat_client(),
+)
+
+
+@tool(
+    name="research_policy",
+    description="Delegate policy research for this expense to a specialist.",
+)
+async def research_policy(category: str, amount: float) -> str:
+    """Delegate policy research for this expense to a specialist.
+
+    Streams the ``policy_researcher`` specialist and mirrors each text delta
+    onto the AG-UI wire as attributed SUBAGENT_* / TEXT_MESSAGE_* events via
+    src/subagent_emitter.py (no-ops outside the wrapped run).
+
+    Args:
+        category: Expense category, e.g. 'meals' or 'travel'.
+        amount: Expense amount in USD.
+
+    Returns:
+        The specialist's complete policy summary.
+    """
+    # Deterministically recorded by the run wrapper's pump before this body
+    # runs (the bridge streams TOOL_CALL_START/ARGS/END first); None when
+    # invoked outside a wrapped run.
+    tid = subagent_emitter.current_tool_call_id("research_policy")
+    subagent_emitter.delegation_started(tid, policy_researcher.name)
+    parts: list[str] = []
+    try:
+        prompt = (
+            f"Expense category: {category}. Amount: ${amount:.2f}. "
+            "Summarize the applicable policy rules."
+        )
+        async for update in policy_researcher.run(prompt, stream=True):
+            text = update.text
+            if text:
+                parts.append(text)
+                subagent_emitter.delegation_delta(tid, text)
+    except Exception as exc:
+        subagent_emitter.delegation_error(tid, str(exc))
+        raise
+    subagent_emitter.delegation_finished(tid)
+    return "".join(parts)
+
+
 agent = AgentFrameworkAgent(
     agent=Agent(
         name="expense_approval_copilot",
         instructions=_INSTRUCTIONS,
         client=build_chat_client(),
-        tools=[lookup_expense_policy, submit_expense],
+        tools=[lookup_expense_policy, research_policy, submit_expense],
     ),
     name="ExpenseApprovalCopilot",
     description="Files expense reports with policy lookup, shared state, and human approval.",

cockpit/runtimes/microsoft-agent-framework/python/src/server.py

@@ -3,9 +3,14 @@
 from agent_framework_ag_ui import add_agent_framework_fastapi_endpoint
 
 from .agent import agent
+from .subagent_emitter import wrap_agent_run
 
 app = FastAPI(title="cockpit-runtimes-microsoft-agent-framework")
-add_agent_framework_fastapi_endpoint(app, agent, path="/agent")
+# The wrapper is the SUBAGENT_* injection seam: the endpoint consumes
+# protocol_runner.run, and wrap_agent_run merges the delegation tool's
+# enqueued child events into that stream (src/subagent_emitter.py).
+wrapped_agent = wrap_agent_run(agent)
+add_agent_framework_fastapi_endpoint(app, wrapped_agent, path="/agent")
 
 
 @app.get("/ok")