diff --git a/pyproject.toml b/pyproject.toml index 07d2b3dd8..d9e2d895c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -57,6 +57,7 @@ dev = [ "pytest-cov>=6.1.1", "httpx>=0.28.1", "pytest-pretty>=1.3.0", + "openai-agents[litellm] >= 0.2.3,<0.3" ] [tool.poe.tasks] diff --git a/temporalio/contrib/openai_agents/_invoke_model_activity.py b/temporalio/contrib/openai_agents/_invoke_model_activity.py index 2fc60df02..ed4313537 100644 --- a/temporalio/contrib/openai_agents/_invoke_model_activity.py +++ b/temporalio/contrib/openai_agents/_invoke_model_activity.py @@ -7,13 +7,16 @@ import json from dataclasses import dataclass from datetime import timedelta -from typing import Any, Optional, Union, cast +from typing import Any, Optional, Union from agents import ( AgentOutputSchemaBase, + CodeInterpreterTool, FileSearchTool, FunctionTool, Handoff, + HostedMCPTool, + ImageGenerationTool, ModelProvider, ModelResponse, ModelSettings, @@ -25,13 +28,12 @@ UserError, WebSearchTool, ) -from agents.models.multi_provider import MultiProvider from openai import ( APIStatusError, AsyncOpenAI, - AuthenticationError, - PermissionDeniedError, ) +from openai.types.responses.tool_param import Mcp +from pydantic_core import to_json from typing_extensions import Required, TypedDict from temporalio import activity @@ -41,7 +43,9 @@ @dataclass class HandoffInput: - """Data conversion friendly representation of a Handoff.""" + """Data conversion friendly representation of a Handoff. Contains only the fields which are needed by the model + execution to determine what to handoff to, not the actual handoff invocation, which remains in the workflow context. + """ tool_name: str tool_description: str @@ -52,7 +56,9 @@ class HandoffInput: @dataclass class FunctionToolInput: - """Data conversion friendly representation of a FunctionTool.""" + """Data conversion friendly representation of a FunctionTool. Contains only the fields which are needed by the model + execution to determine what tool to call, not the actual tool invocation, which remains in the workflow context. + """ name: str description: str @@ -60,7 +66,23 @@ class FunctionToolInput: strict_json_schema: bool = True -ToolInput = Union[FunctionToolInput, FileSearchTool, WebSearchTool] +@dataclass +class HostedMCPToolInput: + """Data conversion friendly representation of a HostedMCPTool. Contains only the fields which are needed by the model + execution to determine what tool to call, not the actual tool invocation, which remains in the workflow context. + """ + + tool_config: Mcp + + +ToolInput = Union[ + FunctionToolInput, + FileSearchTool, + WebSearchTool, + ImageGenerationTool, + CodeInterpreterTool, + HostedMCPToolInput, +] @dataclass @@ -152,22 +174,31 @@ async def empty_on_invoke_handoff( # workaround for https://github.com/pydantic/pydantic/issues/9541 # ValidatorIterator returned - input_json = json.dumps(input["input"], default=str) + input_json = to_json(input["input"]) input_input = json.loads(input_json) def make_tool(tool: ToolInput) -> Tool: - if isinstance(tool, FileSearchTool): - return cast(FileSearchTool, tool) - elif isinstance(tool, WebSearchTool): - return cast(WebSearchTool, tool) + if isinstance( + tool, + ( + FileSearchTool, + WebSearchTool, + ImageGenerationTool, + CodeInterpreterTool, + ), + ): + return tool + elif isinstance(tool, HostedMCPToolInput): + return HostedMCPTool( + tool_config=tool.tool_config, + ) elif isinstance(tool, FunctionToolInput): - t = cast(FunctionToolInput, tool) return FunctionTool( - name=t.name, - description=t.description, - params_json_schema=t.params_json_schema, + name=tool.name, + description=tool.description, + params_json_schema=tool.params_json_schema, on_invoke_tool=empty_on_invoke_tool, - strict_json_schema=t.strict_json_schema, + strict_json_schema=tool.strict_json_schema, ) else: raise UserError(f"Unknown tool type: {tool.name}") diff --git a/temporalio/contrib/openai_agents/_temporal_model_stub.py b/temporalio/contrib/openai_agents/_temporal_model_stub.py index e4b7664ca..60601d0df 100644 --- a/temporalio/contrib/openai_agents/_temporal_model_stub.py +++ b/temporalio/contrib/openai_agents/_temporal_model_stub.py @@ -13,10 +13,12 @@ from agents import ( AgentOutputSchema, AgentOutputSchemaBase, - ComputerTool, + CodeInterpreterTool, FileSearchTool, FunctionTool, Handoff, + HostedMCPTool, + ImageGenerationTool, Model, ModelResponse, ModelSettings, @@ -33,6 +35,7 @@ AgentOutputSchemaInput, FunctionToolInput, HandoffInput, + HostedMCPToolInput, ModelActivity, ModelTracingInput, ToolInput, @@ -65,12 +68,18 @@ async def get_response( prompt: Optional[ResponsePromptParam], ) -> ModelResponse: def make_tool_info(tool: Tool) -> ToolInput: - if isinstance(tool, (FileSearchTool, WebSearchTool)): + if isinstance( + tool, + ( + FileSearchTool, + WebSearchTool, + ImageGenerationTool, + CodeInterpreterTool, + ), + ): return tool - elif isinstance(tool, ComputerTool): - raise NotImplementedError( - "Computer search preview is not supported in Temporal model" - ) + elif isinstance(tool, HostedMCPTool): + return HostedMCPToolInput(tool_config=tool.tool_config) elif isinstance(tool, FunctionTool): return FunctionToolInput( name=tool.name, @@ -79,7 +88,7 @@ def make_tool_info(tool: Tool) -> ToolInput: strict_json_schema=tool.strict_json_schema, ) else: - raise ValueError(f"Unknown tool type: {tool.name}") + raise ValueError(f"Unsupported tool type: {tool.name}") tool_infos = [make_tool_info(x) for x in tools] handoff_infos = [ diff --git a/temporalio/contrib/openai_agents/_temporal_openai_agents.py b/temporalio/contrib/openai_agents/_temporal_openai_agents.py index ab8283046..a1f71db71 100644 --- a/temporalio/contrib/openai_agents/_temporal_openai_agents.py +++ b/temporalio/contrib/openai_agents/_temporal_openai_agents.py @@ -34,7 +34,13 @@ from temporalio.contrib.openai_agents._trace_interceptor import ( OpenAIAgentsTracingInterceptor, ) -from temporalio.contrib.pydantic import pydantic_data_converter +from temporalio.contrib.pydantic import ( + PydanticPayloadConverter, + ToJsonOptions, +) +from temporalio.converter import ( + DataConverter, +) from temporalio.worker import Worker, WorkerConfig @@ -137,6 +143,11 @@ def stream_response( raise NotImplementedError() +class _OpenAIPayloadConverter(PydanticPayloadConverter): + def __init__(self) -> None: + super().__init__(ToJsonOptions(exclude_unset=True)) + + class OpenAIAgentsPlugin(temporalio.client.Plugin, temporalio.worker.Plugin): """Temporal plugin for integrating OpenAI agents with Temporal workflows. @@ -232,7 +243,9 @@ def configure_client(self, config: ClientConfig) -> ClientConfig: Returns: The modified client configuration. """ - config["data_converter"] = pydantic_data_converter + config["data_converter"] = DataConverter( + payload_converter_class=_OpenAIPayloadConverter + ) return super().configure_client(config) def configure_worker(self, config: WorkerConfig) -> WorkerConfig: diff --git a/temporalio/contrib/pydantic.py b/temporalio/contrib/pydantic.py index 2e78ac5d8..97f1b6ac3 100644 --- a/temporalio/contrib/pydantic.py +++ b/temporalio/contrib/pydantic.py @@ -13,10 +13,12 @@ Pydantic v1 is not supported. """ +from dataclasses import dataclass from typing import Any, Optional, Type from pydantic import TypeAdapter -from pydantic_core import to_json +from pydantic_core import SchemaSerializer, to_json +from pydantic_core.core_schema import any_schema import temporalio.api.common.v1 from temporalio.converter import ( @@ -31,6 +33,13 @@ # implements __get_pydantic_core_schema__ so that pydantic unwraps proxied types. +@dataclass +class ToJsonOptions: + """Options for converting to JSON with pydantic.""" + + exclude_unset: bool = False + + class PydanticJSONPlainPayloadConverter(EncodingPayloadConverter): """Pydantic JSON payload converter. @@ -44,6 +53,11 @@ class PydanticJSONPlainPayloadConverter(EncodingPayloadConverter): See https://docs.pydantic.dev/latest/api/standard_library_types/ """ + def __init__(self, to_json_options: Optional[ToJsonOptions] = None): + """Create a new payload converter.""" + self._schema_serializer = SchemaSerializer(any_schema()) + self._to_json_options = to_json_options + @property def encoding(self) -> str: """See base class.""" @@ -57,8 +71,15 @@ def to_payload(self, value: Any) -> Optional[temporalio.api.common.v1.Payload]: See https://docs.pydantic.dev/latest/api/pydantic_core/#pydantic_core.to_json. """ + data = ( + self._schema_serializer.to_json( + value, exclude_unset=self._to_json_options.exclude_unset + ) + if self._to_json_options + else to_json(value) + ) return temporalio.api.common.v1.Payload( - metadata={"encoding": self.encoding.encode()}, data=to_json(value) + metadata={"encoding": self.encoding.encode()}, data=data ) def from_payload( @@ -85,9 +106,9 @@ class PydanticPayloadConverter(CompositePayloadConverter): :py:class:`PydanticJSONPlainPayloadConverter`. """ - def __init__(self) -> None: + def __init__(self, to_json_options: Optional[ToJsonOptions] = None) -> None: """Initialize object""" - json_payload_converter = PydanticJSONPlainPayloadConverter() + json_payload_converter = PydanticJSONPlainPayloadConverter(to_json_options) super().__init__( *( c diff --git a/tests/contrib/openai_agents/test_openai.py b/tests/contrib/openai_agents/test_openai.py index 6937130b2..17603e49f 100644 --- a/tests/contrib/openai_agents/test_openai.py +++ b/tests/contrib/openai_agents/test_openai.py @@ -1,6 +1,7 @@ import asyncio import json import os +import sys import uuid from dataclasses import dataclass from datetime import timedelta @@ -11,10 +12,17 @@ from agents import ( Agent, AgentOutputSchemaBase, + CodeInterpreterTool, + FileSearchTool, GuardrailFunctionOutput, Handoff, + HostedMCPTool, + ImageGenerationTool, InputGuardrailTripwireTriggered, ItemHelpers, + LocalShellTool, + MCPToolApprovalFunctionResult, + MCPToolApprovalRequest, MessageOutputItem, Model, ModelProvider, @@ -46,6 +54,8 @@ from openai import APIStatusError, AsyncOpenAI, BaseModel from openai.types.responses import ( EasyInputMessageParam, + ResponseCodeInterpreterToolCall, + ResponseFileSearchToolCall, ResponseFunctionToolCall, ResponseFunctionToolCallParam, ResponseFunctionWebSearch, @@ -53,8 +63,14 @@ ResponseOutputMessage, ResponseOutputText, ) +from openai.types.responses.response_file_search_tool_call import Result from openai.types.responses.response_function_web_search import ActionSearch from openai.types.responses.response_input_item_param import Message +from openai.types.responses.response_output_item import ( + ImageGenerationCall, + McpApprovalRequest, + McpCall, +) from openai.types.responses.response_prompt_param import ResponsePromptParam from pydantic import ConfigDict, Field, TypeAdapter @@ -1757,12 +1773,12 @@ async def test_workflow_method_tools(client: Client): async def test_response_serialization(): # This should not be used in another test, or this test needs to change to use another unloaded type - from openai.types.responses.response_output_item import ImageGenerationCall + from openai.types.responses.response_output_item import LocalShellCall data = json.loads( - b'{"id": "msg_68757ec43348819d86709f0fcb70316301a1194a3e05b38c","type": "image_generation_call","status": "completed"}' + b'{"id":"", "action":{"command": [],"env": {},"type": "exec"},"call_id":"","status":"completed","type":"local_shell_call"}' ) - call = TypeAdapter(ImageGenerationCall).validate_python(data) + call = TypeAdapter(LocalShellCall).validate_python(data) model_response = ModelResponse( output=[ call, @@ -2020,3 +2036,421 @@ async def test_session(client: Client): workflow_handle, message_contains="Temporal workflows don't support SQLite sessions", ) + + +async def test_lite_llm(client: Client, env: WorkflowEnvironment): + if not os.environ.get("OPENAI_API_KEY"): + pytest.skip("No openai API key") + if sys.version_info < (3, 10): + pytest.skip("Lite LLM does not import below 3.10") + + from agents.extensions.models.litellm_provider import LitellmProvider + + new_config = client.config() + new_config["plugins"] = [ + openai_agents.OpenAIAgentsPlugin( + model_params=ModelActivityParameters( + start_to_close_timeout=timedelta(seconds=30) + ), + model_provider=LitellmProvider(), + ) + ] + client = Client(**new_config) + + async with new_worker( + client, + HelloWorldAgent, + ) as worker: + workflow_handle = await client.start_workflow( + HelloWorldAgent.run, + "Tell me about recursion in programming", + id=f"lite-llm-{uuid.uuid4()}", + task_queue=worker.task_queue, + execution_timeout=timedelta(seconds=10), + ) + await workflow_handle.result() + + +class FileSearchToolModel(StaticTestModel): + responses = [ + ModelResponse( + output=[ + ResponseFileSearchToolCall( + queries=["side character in the Iliad"], + type="file_search_call", + id="id", + status="completed", + results=[ + Result(text="Some scene"), + Result(text="Other scene"), + ], + ), + ResponseOutputMessage( + id="", + content=[ + ResponseOutputText( + text="Patroclus", + annotations=[], + type="output_text", + ) + ], + role="assistant", + status="completed", + type="message", + ), + ], + usage=Usage(), + response_id=None, + ), + ] + + +@workflow.defn +class FileSearchToolWorkflow: + @workflow.run + async def run(self, question: str) -> str: + agent = Agent[str]( + name="File Search Workflow", + instructions="You are a librarian. You should use your tools to source all your information.", + tools=[ + FileSearchTool( + max_num_results=3, + vector_store_ids=["vs_687fd7f5e69c8191a2740f06bc9a159d"], + include_search_results=True, + ) + ], + ) + result = await Runner.run(starting_agent=agent, input=question) + + # A file search was performed + assert any( + isinstance(item, ToolCallItem) + and isinstance(item.raw_item, ResponseFileSearchToolCall) + for item in result.new_items + ) + return result.final_output + + +@pytest.mark.parametrize("use_local_model", [True, False]) +async def test_file_search_tool(client: Client, use_local_model): + if not use_local_model and not os.environ.get("OPENAI_API_KEY"): + pytest.skip("No openai API key") + + new_config = client.config() + new_config["plugins"] = [ + openai_agents.OpenAIAgentsPlugin( + model_params=ModelActivityParameters( + start_to_close_timeout=timedelta(seconds=30) + ), + model_provider=TestModelProvider(FileSearchToolModel()) + if use_local_model + else None, + ) + ] + client = Client(**new_config) + + async with new_worker( + client, + FileSearchToolWorkflow, + ) as worker: + workflow_handle = await client.start_workflow( + FileSearchToolWorkflow.run, + "Tell me about a side character in the Iliad.", + id=f"file-search-tool-{uuid.uuid4()}", + task_queue=worker.task_queue, + execution_timeout=timedelta(seconds=30), + ) + result = await workflow_handle.result() + if use_local_model: + assert result == "Patroclus" + + +class ImageGenerationModel(StaticTestModel): + responses = [ + ModelResponse( + output=[ + ImageGenerationCall( + type="image_generation_call", + id="id", + status="completed", + ), + ResponseOutputMessage( + id="", + content=[ + ResponseOutputText( + text="Patroclus", + annotations=[], + type="output_text", + ) + ], + role="assistant", + status="completed", + type="message", + ), + ], + usage=Usage(), + response_id=None, + ), + ] + + +@workflow.defn +class ImageGenerationWorkflow: + @workflow.run + async def run(self, question: str) -> str: + agent = Agent[str]( + name="Image Generation Workflow", + instructions="You are a helpful agent.", + tools=[ + ImageGenerationTool( + tool_config={"type": "image_generation", "quality": "low"}, + ) + ], + ) + result = await Runner.run(starting_agent=agent, input=question) + + # An image generation was performed + assert any( + isinstance(item, ToolCallItem) + and isinstance(item.raw_item, ImageGenerationCall) + for item in result.new_items + ) + return result.final_output + + +# Can't currently validate against real server, we aren't verified for image generation +@pytest.mark.parametrize("use_local_model", [True]) +async def test_image_generation_tool(client: Client, use_local_model): + if not use_local_model and not os.environ.get("OPENAI_API_KEY"): + pytest.skip("No openai API key") + + new_config = client.config() + new_config["plugins"] = [ + openai_agents.OpenAIAgentsPlugin( + model_params=ModelActivityParameters( + start_to_close_timeout=timedelta(seconds=30) + ), + model_provider=TestModelProvider(ImageGenerationModel()) + if use_local_model + else None, + ) + ] + client = Client(**new_config) + + async with new_worker( + client, + ImageGenerationWorkflow, + ) as worker: + workflow_handle = await client.start_workflow( + ImageGenerationWorkflow.run, + "Create an image of a frog eating a pizza, comic book style.", + id=f"image-generation-tool-{uuid.uuid4()}", + task_queue=worker.task_queue, + execution_timeout=timedelta(seconds=30), + ) + result = await workflow_handle.result() + + +class CodeInterpreterModel(StaticTestModel): + responses = [ + ModelResponse( + output=[ + ResponseCodeInterpreterToolCall( + container_id="", + code="some code", + type="code_interpreter_call", + id="id", + status="completed", + ), + ResponseOutputMessage( + id="", + content=[ + ResponseOutputText( + text="Over 9000", + annotations=[], + type="output_text", + ) + ], + role="assistant", + status="completed", + type="message", + ), + ], + usage=Usage(), + response_id=None, + ), + ] + + +@workflow.defn +class CodeInterpreterWorkflow: + @workflow.run + async def run(self, question: str) -> str: + agent = Agent[str]( + name="Code Interpreter Workflow", + instructions="You are a helpful agent.", + tools=[ + CodeInterpreterTool( + tool_config={ + "type": "code_interpreter", + "container": {"type": "auto"}, + }, + ) + ], + ) + result = await Runner.run(starting_agent=agent, input=question) + + assert any( + isinstance(item, ToolCallItem) + and isinstance(item.raw_item, ResponseCodeInterpreterToolCall) + for item in result.new_items + ) + return result.final_output + + +@pytest.mark.parametrize("use_local_model", [True, False]) +async def test_code_interpreter_tool(client: Client, use_local_model): + if not use_local_model and not os.environ.get("OPENAI_API_KEY"): + pytest.skip("No openai API key") + + new_config = client.config() + new_config["plugins"] = [ + openai_agents.OpenAIAgentsPlugin( + model_params=ModelActivityParameters( + start_to_close_timeout=timedelta(seconds=60) + ), + model_provider=TestModelProvider(CodeInterpreterModel()) + if use_local_model + else None, + ) + ] + client = Client(**new_config) + + async with new_worker( + client, + CodeInterpreterWorkflow, + ) as worker: + workflow_handle = await client.start_workflow( + CodeInterpreterWorkflow.run, + "What is the square root of273 * 312821 plus 1782?", + id=f"code-interpreter-tool-{uuid.uuid4()}", + task_queue=worker.task_queue, + execution_timeout=timedelta(seconds=60), + ) + result = await workflow_handle.result() + if use_local_model: + assert result == "Over 9000" + + +class HostedMCPModel(StaticTestModel): + responses = [ + ModelResponse( + output=[ + McpApprovalRequest( + arguments="", + name="", + server_label="gitmcp", + type="mcp_approval_request", + id="id", + ) + ], + usage=Usage(), + response_id=None, + ), + ModelResponse( + output=[ + McpCall( + arguments="", + name="", + server_label="", + type="mcp_call", + id="id", + output="Mcp output", + ), + ResponseOutputMessage( + id="", + content=[ + ResponseOutputText( + text="Some language", + annotations=[], + type="output_text", + ) + ], + role="assistant", + status="completed", + type="message", + ), + ], + usage=Usage(), + response_id=None, + ), + ] + + +@workflow.defn +class HostedMCPWorkflow: + @workflow.run + async def run(self, question: str) -> str: + requested_approval = False + + def approve(_: MCPToolApprovalRequest) -> MCPToolApprovalFunctionResult: + nonlocal requested_approval + requested_approval = True + return MCPToolApprovalFunctionResult(approve=True) + + agent = Agent[str]( + name="Hosted MCP Workflow", + instructions="You are a helpful agent.", + tools=[ + HostedMCPTool( + tool_config={ + "type": "mcp", + "server_label": "gitmcp", + "server_url": "https://gitmcp.io/openai/codex", + "require_approval": "always", + }, + on_approval_request=approve, + ) + ], + ) + result = await Runner.run(starting_agent=agent, input=question) + assert requested_approval + assert any( + isinstance(item, ToolCallItem) and isinstance(item.raw_item, McpCall) + for item in result.new_items + ) + return result.final_output + + +@pytest.mark.parametrize("use_local_model", [True, False]) +async def test_hosted_mcp_tool(client: Client, use_local_model): + if not use_local_model and not os.environ.get("OPENAI_API_KEY"): + pytest.skip("No openai API key") + + new_config = client.config() + new_config["plugins"] = [ + openai_agents.OpenAIAgentsPlugin( + model_params=ModelActivityParameters( + start_to_close_timeout=timedelta(seconds=120) + ), + model_provider=TestModelProvider(HostedMCPModel()) + if use_local_model + else None, + ) + ] + client = Client(**new_config) + + async with new_worker( + client, + HostedMCPWorkflow, + ) as worker: + workflow_handle = await client.start_workflow( + HostedMCPWorkflow.run, + "Which language is this repo written in?", + id=f"hosted-mcp-tool-{uuid.uuid4()}", + task_queue=worker.task_queue, + execution_timeout=timedelta(seconds=120), + ) + result = await workflow_handle.result() + if use_local_model: + assert result == "Some language" diff --git a/uv.lock b/uv.lock index aca59377e..82cc7ee6b 100644 --- a/uv.lock +++ b/uv.lock @@ -6,6 +6,131 @@ resolution-markers = [ "python_full_version < '3.10'", ] +[[package]] +name = "aiohappyeyeballs" +version = "2.6.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760, upload-time = "2025-03-12T01:42:48.764Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/0f/15/5bf3b99495fb160b63f95972b81750f18f7f4e02ad051373b669d17d44f2/aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8", size = 15265, upload-time = 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