add tool_args_partial to RunContext

Author: petersli

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`, `retries`, `tool_call_id`, `tool_name`, `tool_call_approved`, `retry`, `max_retries` and `run_step` fields are available by default, and trying to access `model`, `usage`, `prompt`, `messages`, or `tracer` will raise an error.
+Specifically, only the `deps`, `retries`, `tool_call_id`, `tool_name`, `tool_call_approved`, `retry`, `max_retries`, `run_step` and `tool_args_partial` fields are available by default, and trying to access `model`, `usage`, `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/_output.py

@@ -1083,7 +1083,7 @@ async def call_tool(
     ) -> Any:
         output = await self.processors[name].call(tool_args, ctx, wrap_validation_errors=False)
         for validator in self.output_validators:
-            output = await validator.validate(output, ctx, wrap_validation_errors=False)
+            output = await validator.validate(output, ctx, wrap_validation_errors=False, partial=ctx.tool_args_partial)
         return output
 
 

pydantic_ai_slim/pydantic_ai/_run_context.py

@@ -54,6 +54,8 @@ class RunContext(Generic[AgentDepsT]):
     """The current step in the run."""
     tool_call_approved: bool = False
     """Whether a tool call that required approval has now been approved."""
+    tool_args_partial: bool = False
+    """Whether args are partial in the tool call."""
 
     @property
     def last_attempt(self) -> bool:

pydantic_ai_slim/pydantic_ai/_tool_manager.py

@@ -145,6 +145,7 @@ async def _call_tool(
                 self.ctx,
                 tool_name=name,
                 tool_call_id=call.tool_call_id,
+                tool_args_partial=allow_partial,
                 retry=self.ctx.retries.get(name, 0),
                 max_retries=tool.max_retries,
             )

pydantic_ai_slim/pydantic_ai/durable_exec/temporal/_run_context.py

@@ -9,7 +9,7 @@
 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`, `retries`, `tool_call_id`, `tool_name`, `tool_call_approved`, `retry`, `max_retries` and `run_step` attributes will be available.
+    By default, only the `deps`, `retries`, `tool_call_id`, `tool_name`, `tool_call_approved`, `tool_args_partial`, `retry`, `max_retries` and `run_step` 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].
     """
 
@@ -41,6 +41,7 @@ def serialize_run_context(cls, ctx: RunContext[Any]) -> dict[str, Any]:
             'tool_call_id': ctx.tool_call_id,
             'tool_name': ctx.tool_name,
             'tool_call_approved': ctx.tool_call_approved,
+            'tool_args_partial': ctx.tool_args_partial,
             'retry': ctx.retry,
             'max_retries': ctx.max_retries,
             'run_step': ctx.run_step,