Make RunContext.usage available with Temporal

docs/durable_execution/temporal.md

@@ -172,7 +172,7 @@ As workflows and activities run in separate processes, any values passed between
 
 To account for these limitations, tool functions and the [event stream handler](#streaming) running inside activities receive a limited version of the agent's [`RunContext`][pydantic_ai.tools.RunContext], and it's your responsibility to make sure that the [dependencies](../dependencies.md) object provided to [`TemporalAgent.run()`][pydantic_ai.durable_exec.temporal.TemporalAgent.run] can be serialized using Pydantic.
 
-Specifically, only the `deps`, `run_id`, `retries`, `tool_call_id`, `tool_name`, `tool_call_approved`, `retry`, `max_retries`, `run_step` and `partial_output` fields are available by default, and trying to access `model`, `usage`, `prompt`, `messages`, or `tracer` will raise an error.
+Specifically, only the `deps`, `run_id`, `retries`, `tool_call_id`, `tool_name`, `tool_call_approved`, `retry`, `max_retries`, `run_step`, `usage`, and `partial_output` fields are available by default, and trying to access `model`, `prompt`, `messages`, or `tracer` will raise an error.
 If you need one or more of these attributes to be available inside activities, you can create a [`TemporalRunContext`][pydantic_ai.durable_exec.temporal.TemporalRunContext] subclass with custom `serialize_run_context` and `deserialize_run_context` class methods and pass it to [`TemporalAgent`][pydantic_ai.durable_exec.temporal.TemporalAgent] as `run_context_type`.
 
 ### Streaming

pydantic_ai_slim/pydantic_ai/durable_exec/temporal/_run_context.py

@@ -14,7 +14,7 @@
 class TemporalRunContext(RunContext[AgentDepsT]):
     """The [`RunContext`][pydantic_ai.tools.RunContext] subclass to use to serialize and deserialize the run context for use inside a Temporal activity.
 
-    By default, only the `deps`, `run_id`, `retries`, `tool_call_id`, `tool_name`, `tool_call_approved`, `retry`, `max_retries`, `run_step` and `partial_output` attributes will be available.
+    By default, only the `deps`, `run_id`, `retries`, `tool_call_id`, `tool_name`, `tool_call_approved`, `retry`, `max_retries`, `run_step`, `usage`, and `partial_output` attributes will be available.
     To make another attribute available, create a `TemporalRunContext` subclass with a custom `serialize_run_context` class method that returns a dictionary that includes the attribute and pass it to [`TemporalAgent`][pydantic_ai.durable_exec.temporal.TemporalAgent].
     """
 
@@ -51,6 +51,7 @@ def serialize_run_context(cls, ctx: RunContext[Any]) -> dict[str, Any]:
             'max_retries': ctx.max_retries,
             'run_step': ctx.run_step,
             'partial_output': ctx.partial_output,
+            'usage': ctx.usage,
         }
 
     @classmethod

tests/test_temporal.py

@@ -2193,6 +2193,27 @@ def test_temporal_run_context_preserves_run_id():
     assert reconstructed.run_id == 'run-123'
 
 
+def test_temporal_run_context_serializes_usage():
+    ctx = RunContext(
+        deps=None,
+        model=TestModel(),
+        usage=RunUsage(
+            requests=2,
+            tool_calls=1,
+            input_tokens=123,
+            output_tokens=456,
+            details={'foo': 1},
+        ),
+        run_id='run-123',
+    )
+
+    serialized = TemporalRunContext.serialize_run_context(ctx)
+    assert serialized['usage'] == ctx.usage
+
+    reconstructed = TemporalRunContext.deserialize_run_context(serialized, deps=None)
+    assert reconstructed.usage == ctx.usage
+
+
 fastmcp_agent = Agent(
     model,
     name='fastmcp_agent',