Fix repeated Deep Agents tool calls with identical arguments

CHANGELOG.md

@@ -37,6 +37,8 @@ to include examples, links to docs, or any other relevant information.
 
 ### Fixed
 
+- `temporalio.contrib.deepagents` now runs separate tool calls independently
+  when they use the same tool and arguments.
 - `StrandsPlugin` now disables Botocore retries for its default Bedrock model so
   model request retries are handled exclusively by Temporal.
 - `temporalio.contrib.openai_agents` now honors the `retry-after-ms` and

temporalio/contrib/deepagents/workflow.py

@@ -111,7 +111,11 @@ async def call_tool(
     **opts: Any,
 ) -> _activity.ToolActivityOutput:
     """Dispatch one tool call, reusing a cached result across continue-as-new."""
-    key = _serde.cache_key("tool", activity_input.tool_name, activity_input.args)
+    key = _serde.cache_key(
+        "tool",
+        activity_input.tool_call_id,
+        [activity_input.tool_name, activity_input.args],
+    )
     hit, cached = _serde.cache_lookup(key)
     if hit:
         return _activity.ToolActivityOutput(message=cached)

tests/contrib/deepagents/test_tools.py

@@ -32,9 +32,11 @@
     from temporalio.contrib.deepagents import (  # noqa: E402
         DeepAgentsPlugin,
         activity_as_tool,
+        run_deep_agent,
         tool_as_activity,
     )
     from temporalio.contrib.deepagents._tools import warn_unwrapped_tools  # noqa: E402
+    from temporalio.contrib.deepagents.testing import mock_model_provider  # noqa: E402
 
 INVOKE_TOOL = "deepagents.invoke_tool"
 
@@ -159,6 +161,22 @@ async def run(self, city: str) -> str:
         return str(result["messages"][-1].content)
 
 
+@workflow.defn
+class RepeatedToolCallWorkflow:
+    @workflow.run
+    async def run(self) -> str:
+        tool = tool_as_activity(
+            pairing_weather, start_to_close_timeout=timedelta(seconds=10)
+        )
+        agent = create_deep_agent(model="fake:model", tools=[tool])
+        result = await run_deep_agent(
+            agent,
+            {"messages": [{"role": "user", "content": "Check Paris twice."}]},
+            continue_as_new_after=10_000,
+        )
+        return str(result["messages"][-1].content)
+
+
 @pytest.mark.asyncio
 async def test_wrapped_tool_result_pairs_with_model_tool_call_id(
     env: WorkflowEnvironment,
@@ -236,3 +254,50 @@ def provider(_model_name: str) -> RecordingModel:
         0
     ].tool_call_id
     assert "weather:Paris" in str(tool_messages[0].content)
+
+
+@pytest.mark.asyncio
+async def test_repeated_tool_calls_with_same_args_both_run(
+    env: WorkflowEnvironment,
+) -> None:
+    from langchain_core.messages import AIMessage
+
+    responses = [
+        AIMessage(
+            content="",
+            tool_calls=[
+                {
+                    "name": "pairing_weather",
+                    "args": {"city": "Paris"},
+                    "id": "first-call",
+                }
+            ],
+        ),
+        AIMessage(
+            content="",
+            tool_calls=[
+                {
+                    "name": "pairing_weather",
+                    "args": {"city": "Paris"},
+                    "id": "second-call",
+                }
+            ],
+        ),
+        AIMessage(content="done"),
+    ]
+    plugin = DeepAgentsPlugin(model_provider=mock_model_provider(responses))
+    async with Worker(
+        env.client,
+        task_queue="da-repeated-tool-calls",
+        workflows=[RepeatedToolCallWorkflow],
+        plugins=[plugin],
+    ):
+        handle = await env.client.start_workflow(
+            RepeatedToolCallWorkflow.run,
+            id=f"da-repeated-tool-calls-{uuid.uuid4()}",
+            task_queue="da-repeated-tool-calls",
+        )
+        assert await handle.result() == "done"
+
+    counts = await count_scheduled_activities(handle)
+    assert counts[INVOKE_TOOL] == 2, counts