From c85dd251fd6630aa5136156310065d7dd348c708 Mon Sep 17 00:00:00 2001 From: Evan Mattson Date: Wed, 17 Dec 2025 10:30:53 +0900 Subject: [PATCH] Pass kwargs into subworkflows --- .../_workflows/_workflow_executor.py | 8 +- .../tests/workflow/test_workflow_kwargs.py | 152 ++++++++++++++++++ .../getting_started/workflows/README.md | 1 + .../composition/sub_workflow_kwargs.py | 143 ++++++++++++++++ python/uv.lock | 96 +++++------ 5 files changed, 350 insertions(+), 50 deletions(-) create mode 100644 python/samples/getting_started/workflows/composition/sub_workflow_kwargs.py diff --git a/python/packages/core/agent_framework/_workflows/_workflow_executor.py b/python/packages/core/agent_framework/_workflows/_workflow_executor.py index cc028f337c..dccd76403b 100644 --- a/python/packages/core/agent_framework/_workflows/_workflow_executor.py +++ b/python/packages/core/agent_framework/_workflows/_workflow_executor.py @@ -11,6 +11,7 @@ from ._workflow import Workflow from ._checkpoint_encoding import decode_checkpoint_value, encode_checkpoint_value +from ._const import WORKFLOW_RUN_KWARGS_KEY from ._events import ( RequestInfoEvent, WorkflowErrorEvent, @@ -366,8 +367,11 @@ async def process_workflow(self, input_data: object, ctx: WorkflowContext[Any]) logger.debug(f"WorkflowExecutor {self.id} starting sub-workflow {self.workflow.id} execution {execution_id}") try: - # Run the sub-workflow and collect all events - result = await self.workflow.run(input_data) + # Get kwargs from parent workflow's SharedState to propagate to subworkflow + parent_kwargs: dict[str, Any] = await ctx.get_shared_state(WORKFLOW_RUN_KWARGS_KEY) or {} + + # Run the sub-workflow and collect all events, passing parent kwargs + result = await self.workflow.run(input_data, **parent_kwargs) logger.debug( f"WorkflowExecutor {self.id} sub-workflow {self.workflow.id} " diff --git a/python/packages/core/tests/workflow/test_workflow_kwargs.py b/python/packages/core/tests/workflow/test_workflow_kwargs.py index 864258b76c..0e5a5a8d4f 100644 --- a/python/packages/core/tests/workflow/test_workflow_kwargs.py +++ b/python/packages/core/tests/workflow/test_workflow_kwargs.py @@ -490,3 +490,155 @@ async def prepare_final_answer(self, context: MagenticContext) -> ChatMessage: # endregion + + +# region SubWorkflow (WorkflowExecutor) Tests + + +async def test_subworkflow_kwargs_propagation() -> None: + """Test that kwargs are propagated to subworkflows. + + Verifies kwargs passed to parent workflow.run_stream() flow through to agents + in subworkflows wrapped by WorkflowExecutor. + """ + from agent_framework._workflows._workflow_executor import WorkflowExecutor + + # Create an agent inside the subworkflow that captures kwargs + inner_agent = _KwargsCapturingAgent(name="inner_agent") + + # Build the inner (sub) workflow with the agent + inner_workflow = SequentialBuilder().participants([inner_agent]).build() + + # Wrap the inner workflow in a WorkflowExecutor so it can be used as a subworkflow + subworkflow_executor = WorkflowExecutor(workflow=inner_workflow, id="subworkflow_executor") + + # Build the outer (parent) workflow containing the subworkflow + outer_workflow = SequentialBuilder().participants([subworkflow_executor]).build() + + # Define kwargs that should propagate to subworkflow + custom_data = {"api_key": "secret123", "endpoint": "https://api.example.com"} + user_token = {"user_name": "alice", "access_level": "admin"} + + # Run the outer workflow with kwargs + async for event in outer_workflow.run_stream( + "test message for subworkflow", + custom_data=custom_data, + user_token=user_token, + ): + if isinstance(event, WorkflowStatusEvent) and event.state == WorkflowRunState.IDLE: + break + + # Verify that the inner agent was called + assert len(inner_agent.captured_kwargs) >= 1, "Inner agent in subworkflow should have been invoked" + + received_kwargs = inner_agent.captured_kwargs[0] + + # Verify kwargs were propagated from parent workflow to subworkflow agent + assert "custom_data" in received_kwargs, ( + f"Subworkflow agent should receive 'custom_data' kwarg. Received keys: {list(received_kwargs.keys())}" + ) + assert "user_token" in received_kwargs, ( + f"Subworkflow agent should receive 'user_token' kwarg. Received keys: {list(received_kwargs.keys())}" + ) + assert received_kwargs.get("custom_data") == custom_data, ( + f"Expected custom_data={custom_data}, got {received_kwargs.get('custom_data')}" + ) + assert received_kwargs.get("user_token") == user_token, ( + f"Expected user_token={user_token}, got {received_kwargs.get('user_token')}" + ) + + +async def test_subworkflow_kwargs_accessible_via_shared_state() -> None: + """Test that kwargs are accessible via SharedState within subworkflow. + + Verifies that WORKFLOW_RUN_KWARGS_KEY is populated in the subworkflow's SharedState + with kwargs from the parent workflow. + """ + from agent_framework import Executor, WorkflowContext, handler + from agent_framework._workflows._workflow_executor import WorkflowExecutor + + captured_kwargs_from_state: list[dict[str, Any]] = [] + + class _SharedStateReader(Executor): + """Executor that reads kwargs from SharedState for verification.""" + + @handler + async def read_kwargs(self, msgs: list[ChatMessage], ctx: WorkflowContext[list[ChatMessage]]) -> None: + kwargs_from_state = await ctx.get_shared_state(WORKFLOW_RUN_KWARGS_KEY) + captured_kwargs_from_state.append(kwargs_from_state or {}) + await ctx.send_message(msgs) + + # Build inner workflow with SharedState reader + state_reader = _SharedStateReader(id="state_reader") + inner_workflow = SequentialBuilder().participants([state_reader]).build() + + # Wrap as subworkflow + subworkflow_executor = WorkflowExecutor(workflow=inner_workflow, id="subworkflow") + + # Build outer workflow + outer_workflow = SequentialBuilder().participants([subworkflow_executor]).build() + + # Run with kwargs + async for event in outer_workflow.run_stream( + "test", + my_custom_kwarg="should_be_propagated", + another_kwarg=42, + ): + if isinstance(event, WorkflowStatusEvent) and event.state == WorkflowRunState.IDLE: + break + + # Verify the state reader was invoked + assert len(captured_kwargs_from_state) >= 1, "SharedState reader should have been invoked" + + kwargs_in_subworkflow = captured_kwargs_from_state[0] + + assert kwargs_in_subworkflow.get("my_custom_kwarg") == "should_be_propagated", ( + f"Expected 'my_custom_kwarg' in subworkflow SharedState, got: {kwargs_in_subworkflow}" + ) + assert kwargs_in_subworkflow.get("another_kwarg") == 42, ( + f"Expected 'another_kwarg'=42 in subworkflow SharedState, got: {kwargs_in_subworkflow}" + ) + + +async def test_nested_subworkflow_kwargs_propagation() -> None: + """Test kwargs propagation through multiple levels of nested subworkflows. + + Verifies kwargs flow through 3 levels: + - Outer workflow + - Middle subworkflow (WorkflowExecutor) + - Inner subworkflow (WorkflowExecutor) with agent + """ + from agent_framework._workflows._workflow_executor import WorkflowExecutor + + # Innermost agent + inner_agent = _KwargsCapturingAgent(name="deeply_nested_agent") + + # Build inner workflow + inner_workflow = SequentialBuilder().participants([inner_agent]).build() + inner_executor = WorkflowExecutor(workflow=inner_workflow, id="inner_executor") + + # Build middle workflow containing inner + middle_workflow = SequentialBuilder().participants([inner_executor]).build() + middle_executor = WorkflowExecutor(workflow=middle_workflow, id="middle_executor") + + # Build outer workflow containing middle + outer_workflow = SequentialBuilder().participants([middle_executor]).build() + + # Run with kwargs + async for event in outer_workflow.run_stream( + "deeply nested test", + deep_kwarg="should_reach_inner", + ): + if isinstance(event, WorkflowStatusEvent) and event.state == WorkflowRunState.IDLE: + break + + # Verify inner agent was called + assert len(inner_agent.captured_kwargs) >= 1, "Deeply nested agent should be invoked" + + received = inner_agent.captured_kwargs[0] + assert received.get("deep_kwarg") == "should_reach_inner", ( + f"Deeply nested agent should receive 'deep_kwarg'. Got: {received}" + ) + + +# endregion diff --git a/python/samples/getting_started/workflows/README.md b/python/samples/getting_started/workflows/README.md index 805d808540..afe258cbb3 100644 --- a/python/samples/getting_started/workflows/README.md +++ b/python/samples/getting_started/workflows/README.md @@ -64,6 +64,7 @@ Once comfortable with these, explore the rest of the samples below. | Sub-Workflow (Basics) | [composition/sub_workflow_basics.py](./composition/sub_workflow_basics.py) | Wrap a workflow as an executor and orchestrate sub-workflows | | Sub-Workflow: Request Interception | [composition/sub_workflow_request_interception.py](./composition/sub_workflow_request_interception.py) | Intercept and forward sub-workflow requests using @handler for SubWorkflowRequestMessage | | Sub-Workflow: Parallel Requests | [composition/sub_workflow_parallel_requests.py](./composition/sub_workflow_parallel_requests.py) | Multiple specialized interceptors handling different request types from same sub-workflow | +| Sub-Workflow: kwargs Propagation | [composition/sub_workflow_kwargs.py](./composition/sub_workflow_kwargs.py) | Pass custom context (user tokens, config) from parent workflow through to sub-workflow agents | ### control-flow diff --git a/python/samples/getting_started/workflows/composition/sub_workflow_kwargs.py b/python/samples/getting_started/workflows/composition/sub_workflow_kwargs.py new file mode 100644 index 0000000000..1efef28bae --- /dev/null +++ b/python/samples/getting_started/workflows/composition/sub_workflow_kwargs.py @@ -0,0 +1,143 @@ +# Copyright (c) Microsoft. All rights reserved. + +import asyncio +import json +from typing import Annotated, Any + +from agent_framework import ( + ChatMessage, + SequentialBuilder, + WorkflowExecutor, + WorkflowOutputEvent, + ai_function, +) +from agent_framework.openai import OpenAIChatClient + +""" +Sample: Sub-Workflow kwargs Propagation + +This sample demonstrates how custom context (kwargs) flows from a parent workflow +through to agents in sub-workflows. When you pass kwargs to the parent workflow's +run_stream() or run(), they automatically propagate to nested sub-workflows. + +Key Concepts: +- kwargs passed to parent workflow.run_stream() propagate to sub-workflows +- Sub-workflow agents receive the same kwargs as the parent workflow +- Works with nested WorkflowExecutor compositions at any depth +- Useful for passing authentication tokens, configuration, or request context + +Prerequisites: +- OpenAI environment variables configured +""" + + +# Define tools that access custom context via **kwargs +@ai_function +def get_authenticated_data( + resource: Annotated[str, "The resource to fetch"], + **kwargs: Any, +) -> str: + """Fetch data using the authenticated user context from kwargs.""" + user_token = kwargs.get("user_token", {}) + user_name = user_token.get("user_name", "anonymous") + access_level = user_token.get("access_level", "none") + + print(f"\n[get_authenticated_data] kwargs keys: {list(kwargs.keys())}") + print(f"[get_authenticated_data] User: {user_name}, Access: {access_level}") + + return f"Fetched '{resource}' for user {user_name} ({access_level} access)" + + +@ai_function +def call_configured_service( + service_name: Annotated[str, "Name of the service to call"], + **kwargs: Any, +) -> str: + """Call a service using configuration from kwargs.""" + config = kwargs.get("service_config", {}) + services = config.get("services", {}) + + print(f"\n[call_configured_service] kwargs keys: {list(kwargs.keys())}") + print(f"[call_configured_service] Available services: {list(services.keys())}") + + if service_name in services: + endpoint = services[service_name] + return f"Called service '{service_name}' at {endpoint}" + return f"Service '{service_name}' not found in configuration" + + +async def main() -> None: + print("=" * 70) + print("Sub-Workflow kwargs Propagation Demo") + print("=" * 70) + + # Create chat client + chat_client = OpenAIChatClient() + + # Create an agent with tools that use kwargs + inner_agent = chat_client.create_agent( + name="data_agent", + instructions=( + "You are a data access agent. Use the available tools to help users. " + "When asked to fetch data, use get_authenticated_data. " + "When asked to call a service, use call_configured_service." + ), + tools=[get_authenticated_data, call_configured_service], + ) + + # Build the inner (sub) workflow with the agent + inner_workflow = SequentialBuilder().participants([inner_agent]).build() + + # Wrap the inner workflow in a WorkflowExecutor to use it as a sub-workflow + subworkflow_executor = WorkflowExecutor( + workflow=inner_workflow, + id="data_subworkflow", + ) + + # Build the outer (parent) workflow containing the sub-workflow + outer_workflow = SequentialBuilder().participants([subworkflow_executor]).build() + + # Define custom context that will flow through to the sub-workflow's agent + user_token = { + "user_name": "alice@contoso.com", + "access_level": "admin", + "session_id": "sess_12345", + } + + service_config = { + "services": { + "users": "https://api.example.com/v1/users", + "orders": "https://api.example.com/v1/orders", + "inventory": "https://api.example.com/v1/inventory", + }, + "timeout": 30, + } + + print("\nContext being passed to parent workflow:") + print(f" user_token: {json.dumps(user_token, indent=4)}") + print(f" service_config: {json.dumps(service_config, indent=4)}") + print("\n" + "-" * 70) + print("Workflow Execution (kwargs flow: parent -> sub-workflow -> agent -> tool):") + print("-" * 70) + + # Run the OUTER workflow with kwargs + # These kwargs will automatically propagate to the inner sub-workflow + async for event in outer_workflow.run_stream( + "Please fetch my profile data and then call the users service.", + user_token=user_token, + service_config=service_config, + ): + if isinstance(event, WorkflowOutputEvent): + output_data = event.data + if isinstance(output_data, list): + for item in output_data: # type: ignore + if isinstance(item, ChatMessage) and item.text: + print(f"\n[Final Answer]: {item.text}") + + print("\n" + "=" * 70) + print("Sample Complete - kwargs successfully flowed through sub-workflow!") + print("=" * 70) + + +if __name__ == "__main__": 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