Include model_id and provider in AGENT_COMPLETE events

docs/configuration/Chapter_15.md

@@ -55,7 +55,7 @@ The `SESSION_START` payload wraps the full wired topology snapshot together with
 | `TOOL_START` | Tool execution begins |
 | `TOOL_END` | Tool execution completes |
 | `INTERRUPT` | Agent pauses for human input |
-| `AGENT_COMPLETE` | Agent finishes — `data` carries `usage` metrics, `text` (final output string), and `message` (raw message dict) |
+| `AGENT_COMPLETE` | Agent finishes — `data` carries `usage` metrics, `model` (`model_id`, `provider`), `text` (final output string), and `message` (raw message dict) |
 | `ERROR` | Model or execution error |
 
 ### Multi-agent events

src/strands_compose/hooks/event_publisher.py

@@ -34,6 +34,7 @@
     BeforeToolCallEvent,
 )
 
+from ..manifest import model_descriptor
 from ..types import EventType, StreamEvent
 
 logger = logging.getLogger(__name__)
@@ -223,6 +224,10 @@ def _on_tool_end(self, event: AfterToolCallEvent) -> None:
     def _on_complete(self, event: AfterInvocationEvent) -> None:
         """Emit AGENT_COMPLETE with usage metrics from EventLoopMetrics.
 
+        Includes a ``model`` dict with ``model_id`` and ``provider`` (same
+        values reported in the session manifest) so consumers can compute
+        cost directly from this event without a manifest round-trip.
+
         Suppressed when the invocation errored — an ERROR event was
         already emitted via :meth:`_on_model_error`.
         """
@@ -250,12 +255,18 @@ def _on_complete(self, event: AfterInvocationEvent) -> None:
         invocation = metrics.latest_agent_invocation
         usage = invocation.usage if invocation else metrics.accumulated_usage
 
+        model = model_descriptor(event.agent)
+
         data: dict[str, Any] = {
             "usage": {
                 "input_tokens": usage.get("inputTokens", 0),
                 "output_tokens": usage.get("outputTokens", 0),
                 "total_tokens": usage.get("totalTokens", 0),
             },
+            "model": {
+                "model_id": model.model_id,
+                "provider": model.provider,
+            },
             "text": str(result) if result is not None else "",
             "message": result.message if result is not None else {},
         }

src/strands_compose/manifest.py

@@ -118,8 +118,12 @@ def _descriptor_or_none(
 # ── Agent descriptor ─────────────────────────────────────────────────────────
 
 
-def _model_descriptor(agent: Agent) -> ModelDescriptor:
-    """Extract a :class:`ModelDescriptor` from an agent's model."""
+def model_descriptor(agent: Agent) -> ModelDescriptor:
+    """Extract a :class:`ModelDescriptor` from an agent's model.
+
+    Public so other components (e.g. :class:`~strands_compose.hooks.EventPublisher`)
+    can derive the same ``model_id``/``provider`` pair without a manifest round-trip.
+    """
     config = agent.model.get_config()
     if isinstance(config, dict):
         model_id = config.get("model_id")
@@ -136,7 +140,7 @@ def _agent_descriptor(name: str, agent: Agent) -> AgentDescriptor:
     return AgentDescriptor(
         name=name,
         description=agent.description,
-        model=_model_descriptor(agent),
+        model=model_descriptor(agent),
         session_manager=_descriptor_or_none(agent._session_manager),
     )
 

tests/runtime/test_event_stream.py

@@ -56,6 +56,17 @@ async def test_text_response_emits_start_tokens_and_complete():
     assert "".join(tokens) == "Hello world"
 
 
+async def test_agent_complete_includes_model_id_and_provider():
+    agent = Agent(model=FakeModel(["hi"], model_id="us.anthropic.claude-sonnet-4-6"))
+    eq = make_event_queue({"a": agent}, entry_name="a")
+
+    events = await _run_agent("hi", agent, eq)
+    complete = next(e for e in events if e.type == EventType.AGENT_COMPLETE)
+
+    assert complete.data["model"]["model_id"] == "us.anthropic.claude-sonnet-4-6"
+    assert complete.data["model"]["provider"] == f"{FakeModel.__module__}.{FakeModel.__qualname__}"
+
+
 async def test_stream_is_bracketed_by_session_end():
     agent = Agent(model=FakeModel(["hi"]))
     eq = make_event_queue({"a": agent}, entry_name="a")