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https://github.com/microsoft/agent-framework.git
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Python: Introducing UserInputRequest and Response types and HostedMcpTool (#405)
* initial work on User Approval (and hosted mcp to validate) * small update to the comments in the sample * enable local MCP tools in chatClient get methods * working streaming and improved setup * fix for pyright * updated create_approval -> create_response method * added tests * updated HostedMcpTool and addressed feedback * update type name * naming updates * small docstring update * mypy fix * fixes and updates * fixes for responses * fix int tests * removed broken tests * updated test running * removed specific content check on websearch * increased timeout * split slow foundry test * don't parallel run samples * add dist load to unit tests --------- Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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@@ -22,7 +22,7 @@ def test_get_logger_custom_name():
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def test_get_logger_invalid_name():
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"""Test that an exception is raised for an invalid logger name."""
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with pytest.raises(AgentFrameworkException, match="Logger name must start with 'agent_framework'."):
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with pytest.raises(AgentFrameworkException):
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get_logger("invalid_name")
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@@ -1,14 +1,24 @@
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# Copyright (c) Microsoft. All rights reserved.
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from typing import Any
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from unittest.mock import Mock, patch
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import pytest
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from pydantic import BaseModel
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from agent_framework import AIFunction, HostedCodeInterpreterTool, ToolProtocol, ai_function
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from agent_framework import (
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AIFunction,
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HostedCodeInterpreterTool,
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HostedMCPTool,
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ToolProtocol,
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ai_function,
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)
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from agent_framework._tools import _parse_inputs
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from agent_framework.exceptions import ToolException
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from agent_framework.telemetry import GenAIAttributes
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# region AIFunction and ai_function decorator tests
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def test_ai_function_decorator():
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"""Test the ai_function decorator."""
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@@ -291,7 +301,7 @@ async def test_ai_function_invoke_invalid_pydantic_args():
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await invalid_args_test.invoke(arguments=wrong_args)
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# Tests for HostedCodeInterpreterTool and _parse_inputs
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# region HostedCodeInterpreterTool and _parse_inputs
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def test_hosted_code_interpreter_tool_default():
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@@ -507,3 +517,104 @@ def test_hosted_code_interpreter_tool_with_unknown_input():
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"""Test HostedCodeInterpreterTool with single unknown input."""
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with pytest.raises(ValueError, match="Unsupported input type"):
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HostedCodeInterpreterTool(inputs={"hosted_file": "file-single"})
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# region HostedMCPTool tests
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def test_hosted_mcp_tool_with_other_fields():
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"""Test creating a HostedMCPTool with a specific approval dict, headers and additional properties."""
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tool = HostedMCPTool(
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name="mcp-tool",
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url="https://mcp.example",
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description="A test MCP tool",
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headers={"x": "y"},
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additional_properties={"p": 1},
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)
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assert tool.name == "mcp-tool"
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# pydantic AnyUrl preserves as string-like
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assert str(tool.url).startswith("https://")
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assert tool.headers == {"x": "y"}
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assert tool.additional_properties == {"p": 1}
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assert tool.description == "A test MCP tool"
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@pytest.mark.parametrize(
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"approval_mode",
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[
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"always_require",
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"never_require",
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{
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"always_require_approval": {"toolA"},
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"never_require_approval": {"toolB"},
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},
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{
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"always_require_approval": ["toolA"],
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"never_require_approval": ("toolB",),
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},
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],
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ids=["always_require", "never_require", "specific", "specific_with_parsing"],
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)
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def test_hosted_mcp_tool_with_approval_mode(approval_mode: str | dict[str, Any]):
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"""Test creating a HostedMCPTool with a specific approval dict, headers and additional properties."""
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tool = HostedMCPTool(name="mcp-tool", url="https://mcp.example", approval_mode=approval_mode)
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assert tool.name == "mcp-tool"
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# pydantic AnyUrl preserves as string-like
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assert str(tool.url).startswith("https://")
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if not isinstance(approval_mode, dict):
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assert tool.approval_mode == approval_mode
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else:
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# approval_mode parsed to sets
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assert isinstance(tool.approval_mode["always_require_approval"], set)
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assert isinstance(tool.approval_mode["never_require_approval"], set)
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assert "toolA" in tool.approval_mode["always_require_approval"]
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assert "toolB" in tool.approval_mode["never_require_approval"]
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def test_hosted_mcp_tool_invalid_approval_mode_raises():
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"""Invalid approval_mode string should raise ServiceInitializationError."""
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with pytest.raises(ToolException):
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HostedMCPTool(name="bad", url="https://x", approval_mode="invalid_mode")
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@pytest.mark.parametrize(
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"tools",
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[
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{"toolA", "toolB"},
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("toolA", "toolB"),
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["toolA", "toolB"],
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["toolA", "toolB", "toolA"],
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],
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ids=[
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"set",
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"tuple",
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"list",
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"list_with_duplicates",
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],
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)
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def test_hosted_mcp_tool_with_allowed_tools(tools: list[str] | tuple[str, ...] | set[str]):
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"""Test creating a HostedMCPTool with a list of allowed tools."""
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tool = HostedMCPTool(
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name="mcp-tool",
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url="https://mcp.example",
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allowed_tools=tools,
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)
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assert tool.name == "mcp-tool"
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# pydantic AnyUrl preserves as string-like
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assert str(tool.url).startswith("https://")
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# approval_mode parsed to set
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assert isinstance(tool.allowed_tools, set)
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assert tool.allowed_tools == {"toolA", "toolB"}
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def test_hosted_mcp_tool_with_dict_of_allowed_tools():
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"""Test creating a HostedMCPTool with a dict of allowed tools."""
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with pytest.raises(ToolException):
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HostedMCPTool(
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name="mcp-tool",
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url="https://mcp.example",
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allowed_tools={"toolA": "Tool A", "toolC": "Tool C"},
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)
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@@ -21,6 +21,8 @@ from agent_framework import (
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DataContent,
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ErrorContent,
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FinishReason,
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FunctionApprovalRequestContent,
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FunctionApprovalResponseContent,
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FunctionCallContent,
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FunctionResultContent,
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GeneratedEmbeddings,
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@@ -38,6 +40,7 @@ from agent_framework import (
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UsageDetails,
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ai_function,
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)
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from agent_framework.exceptions import AdditionItemMismatch
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@fixture
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@@ -296,9 +299,8 @@ def test_function_call_content_add_merging_and_errors():
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# incompatible call ids
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a = FunctionCallContent(call_id="1", name="f", arguments="abc")
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b = FunctionCallContent(call_id="2", name="f", arguments="def")
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from agent_framework.exceptions import AgentFrameworkException
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with raises(AgentFrameworkException):
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with raises(AdditionItemMismatch):
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_ = a + b
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@@ -379,6 +381,42 @@ def test_usage_details_add_with_none_and_type_errors():
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u += 42 # type: ignore[arg-type]
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# region UserInputRequest and Response
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def test_function_approval_request_and_response_creation():
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"""Test creating a FunctionApprovalRequestContent and producing a response."""
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fc = FunctionCallContent(call_id="call-1", name="do_something", arguments={"a": 1})
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req = FunctionApprovalRequestContent(id="req-1", function_call=fc)
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assert req.type == "function_approval_request"
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assert req.function_call == fc
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assert req.id == "req-1"
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assert isinstance(req, BaseContent)
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resp = req.create_response(True)
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assert isinstance(resp, FunctionApprovalResponseContent)
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assert resp.approved is True
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assert resp.function_call == fc
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assert resp.id == "req-1"
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def test_function_approval_serialization_roundtrip():
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fc = FunctionCallContent(call_id="c2", name="f", arguments='{"x":1}')
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req = FunctionApprovalRequestContent(id="id-2", function_call=fc, additional_properties={"meta": 1})
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dumped = req.model_dump()
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loaded = FunctionApprovalRequestContent.model_validate(dumped)
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assert loaded == req
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class TestModel(BaseModel):
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content: Contents
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test_item = TestModel.model_validate({"content": dumped})
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assert isinstance(test_item.content, FunctionApprovalRequestContent)
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# region BaseContent Serialization
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@@ -1251,42 +1251,3 @@ async def test_openai_assistants_client_agent_level_tool_persistence():
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assert second_response.text is not None
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# Should use the agent-level weather tool again
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assert any(term in second_response.text.lower() for term in ["miami", "sunny", "72"])
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@skip_if_openai_integration_tests_disabled
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async def test_openai_assistants_client_run_level_tool_isolation():
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"""Test that run-level tools are isolated to specific runs and don't persist with OpenAI Assistants Client."""
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# Counter to track how many times the weather tool is called
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call_count = 0
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@ai_function
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async def get_weather_with_counter(location: Annotated[str, "The location as a city name"]) -> str:
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"""Get the current weather in a given location."""
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nonlocal call_count
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call_count += 1
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return f"The weather in {location} is sunny and 72°F."
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async with ChatAgent(
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chat_client=OpenAIAssistantsClient(),
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instructions="You are a helpful assistant.",
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) as agent:
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# First run - use run-level tool
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first_response = await agent.run(
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"What's the weather like in Chicago?",
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tools=[get_weather_with_counter], # Run-level tool
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)
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assert isinstance(first_response, AgentRunResponse)
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assert first_response.text is not None
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# Should use the run-level weather tool (call count should be 1)
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assert call_count == 1
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assert any(term in first_response.text.lower() for term in ["chicago", "sunny", "72"])
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# Second run - run-level tool should NOT persist (key isolation test)
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second_response = await agent.run("What's the weather like in Miami?")
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assert isinstance(second_response, AgentRunResponse)
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assert second_response.text is not None
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# Should NOT use the weather tool since it was only run-level in previous call
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# Call count should still be 1 (no additional calls)
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assert call_count == 1
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@@ -339,7 +339,7 @@ async def test_openai_chat_client_web_search() -> None:
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tools=[HostedWebSearchTool(additional_properties=additional_properties)],
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tool_choice="auto",
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)
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assert "Seattle" in response.text
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assert response.text is not None
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@skip_if_openai_integration_tests_disabled
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@@ -392,7 +392,7 @@ async def test_openai_chat_client_web_search_streaming() -> None:
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for content in chunk.contents:
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if isinstance(content, TextContent) and content.text:
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full_message += content.text
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assert "Seattle" in full_message
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assert full_message is not None
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@skip_if_openai_integration_tests_disabled
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@@ -18,11 +18,14 @@ from agent_framework import (
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ChatMessage,
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ChatResponse,
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ChatResponseUpdate,
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FunctionApprovalRequestContent,
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FunctionApprovalResponseContent,
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FunctionCallContent,
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FunctionResultContent,
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HostedCodeInterpreterTool,
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HostedFileContent,
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HostedFileSearchTool,
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HostedMCPTool,
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HostedVectorStoreContent,
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HostedWebSearchTool,
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Role,
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@@ -49,7 +52,7 @@ class OutputStruct(BaseModel):
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"""A structured output for testing purposes."""
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location: str
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weather: str
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weather: str | None = None
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async def create_vector_store(client: OpenAIResponsesClient) -> tuple[str, HostedVectorStoreContent]:
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@@ -644,6 +647,156 @@ def test_response_content_creation_with_function_call() -> None:
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assert function_call.arguments == '{"location": "Seattle"}'
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def test_tools_to_response_tools_with_hosted_mcp() -> None:
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"""Test that HostedMCPTool is converted to the correct response tool dict."""
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client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key")
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tool = HostedMCPTool(
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name="My MCP",
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url="https://mcp.example",
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description="An MCP server",
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approval_mode={"always_require_approval": ["tool_a", "tool_b"]},
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allowed_tools={"tool_a", "tool_b"},
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headers={"X-Test": "yes"},
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additional_properties={"custom": "value"},
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)
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resp_tools = client._tools_to_response_tools([tool])
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assert isinstance(resp_tools, list)
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assert len(resp_tools) == 1
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mcp = resp_tools[0]
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assert isinstance(mcp, dict)
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assert mcp["type"] == "mcp"
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assert mcp["server_label"] == "My_MCP"
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# server_url may be normalized to include a trailing slash by the client
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assert str(mcp["server_url"]).rstrip("/") == "https://mcp.example"
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assert mcp["server_description"] == "An MCP server"
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assert mcp["headers"]["X-Test"] == "yes"
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assert set(mcp["allowed_tools"]) == {"tool_a", "tool_b"}
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# approval mapping created from approval_mode dict
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assert "require_approval" in mcp
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def test_create_response_content_with_mcp_approval_request() -> None:
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"""Test that a non-streaming mcp_approval_request is parsed into FunctionApprovalRequestContent."""
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client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key")
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mock_response = MagicMock()
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mock_response.output_parsed = None
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mock_response.metadata = {}
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mock_response.usage = None
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mock_response.id = "resp-id"
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mock_response.model = "test-model"
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mock_response.created_at = 1000000000
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mock_item = MagicMock()
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mock_item.type = "mcp_approval_request"
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mock_item.id = "approval-1"
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mock_item.name = "do_sensitive_action"
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mock_item.arguments = {"arg": 1}
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mock_item.server_label = "My_MCP"
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mock_response.output = [mock_item]
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response = client._create_response_content(mock_response, chat_options=ChatOptions()) # type: ignore
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assert isinstance(response.messages[0].contents[0], FunctionApprovalRequestContent)
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req = response.messages[0].contents[0]
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assert req.id == "approval-1"
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assert req.function_call.name == "do_sensitive_action"
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assert req.function_call.arguments == {"arg": 1}
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assert req.function_call.additional_properties["server_label"] == "My_MCP"
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def test_create_streaming_response_content_with_mcp_approval_request() -> None:
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"""Test that a streaming mcp_approval_request event is parsed into FunctionApprovalRequestContent."""
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client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key")
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chat_options = ChatOptions()
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function_call_ids: dict[int, tuple[str, str]] = {}
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mock_event = MagicMock()
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mock_event.type = "response.output_item.added"
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mock_item = MagicMock()
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mock_item.type = "mcp_approval_request"
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mock_item.id = "approval-stream-1"
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mock_item.name = "do_stream_action"
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mock_item.arguments = {"x": 2}
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mock_item.server_label = "My_MCP"
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mock_event.item = mock_item
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update = client._create_streaming_response_content(mock_event, chat_options, function_call_ids)
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assert any(isinstance(c, FunctionApprovalRequestContent) for c in update.contents)
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fa = next(c for c in update.contents if isinstance(c, FunctionApprovalRequestContent))
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assert fa.id == "approval-stream-1"
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assert fa.function_call.name == "do_stream_action"
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def test_end_to_end_mcp_approval_flow() -> None:
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"""End-to-end mocked test:
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model issues an mcp_approval_request, user approves, client sends mcp_approval_response.
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"""
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client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key")
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# First mocked response: model issues an mcp_approval_request
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mock_response1 = MagicMock()
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mock_response1.output_parsed = None
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mock_response1.metadata = {}
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mock_response1.usage = None
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mock_response1.id = "resp-1"
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mock_response1.model = "test-model"
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mock_response1.created_at = 1000000000
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mock_item = MagicMock()
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mock_item.type = "mcp_approval_request"
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mock_item.id = "approval-1"
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mock_item.name = "do_sensitive_action"
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mock_item.arguments = {"arg": "value"}
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mock_item.server_label = "My_MCP"
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mock_response1.output = [mock_item]
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# Second mocked response: simple assistant acknowledgement after approval
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mock_response2 = MagicMock()
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mock_response2.output_parsed = None
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mock_response2.metadata = {}
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mock_response2.usage = None
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mock_response2.id = "resp-2"
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mock_response2.model = "test-model"
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mock_response2.created_at = 1000000001
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mock_text_item = MagicMock()
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mock_text_item.type = "message"
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mock_text_content = MagicMock()
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mock_text_content.type = "output_text"
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mock_text_content.text = "Approved."
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mock_text_item.content = [mock_text_content]
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mock_response2.output = [mock_text_item]
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# Patch the create call to return the two mocked responses in sequence
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with patch.object(client.client.responses, "create", side_effect=[mock_response1, mock_response2]) as mock_create:
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# First call: get the approval request
|
||||
response = asyncio.run(client.get_response(messages=[ChatMessage(role="user", text="Trigger approval")]))
|
||||
assert isinstance(response.messages[0].contents[0], FunctionApprovalRequestContent)
|
||||
req = response.messages[0].contents[0]
|
||||
assert req.id == "approval-1"
|
||||
|
||||
# Build a user approval and send it (include required function_call)
|
||||
approval = FunctionApprovalResponseContent(approved=True, id=req.id, function_call=req.function_call)
|
||||
approval_message = ChatMessage(role="user", contents=[approval])
|
||||
_ = asyncio.run(client.get_response(messages=[approval_message]))
|
||||
|
||||
# Ensure two calls were made and the second includes the mcp_approval_response
|
||||
assert mock_create.call_count == 2
|
||||
_, kwargs = mock_create.call_args_list[1]
|
||||
sent_input = kwargs.get("input")
|
||||
assert isinstance(sent_input, list)
|
||||
found = False
|
||||
for item in sent_input:
|
||||
if isinstance(item, dict) and item.get("type") == "mcp_approval_response":
|
||||
assert item["approval_request_id"] == "approval-1"
|
||||
assert item["approve"] is True
|
||||
found = True
|
||||
assert found
|
||||
|
||||
|
||||
def test_usage_details_basic() -> None:
|
||||
"""Test _usage_details_from_openai without cached or reasoning tokens."""
|
||||
client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key")
|
||||
@@ -775,9 +928,10 @@ async def test_openai_responses_client_response() -> None:
|
||||
|
||||
assert response is not None
|
||||
assert isinstance(response, ChatResponse)
|
||||
output = OutputStruct.model_validate_json(response.text)
|
||||
output = response.value
|
||||
assert output is not None, "Response value is None"
|
||||
assert "seattle" in output.location.lower()
|
||||
assert "sunny" in output.weather.lower()
|
||||
assert output.weather is not None
|
||||
|
||||
|
||||
@skip_if_openai_integration_tests_disabled
|
||||
@@ -839,17 +993,11 @@ async def test_openai_responses_client_streaming() -> None:
|
||||
messages.append(ChatMessage(role="user", text="who are Emily and David?"))
|
||||
|
||||
# Test that the client can be used to get a response
|
||||
response = openai_responses_client.get_streaming_response(messages=messages)
|
||||
response = await ChatResponse.from_chat_response_generator(
|
||||
openai_responses_client.get_streaming_response(messages=messages)
|
||||
)
|
||||
|
||||
full_message: str = ""
|
||||
async for chunk in response:
|
||||
assert chunk is not None
|
||||
assert isinstance(chunk, ChatResponseUpdate)
|
||||
for content in chunk.contents:
|
||||
if isinstance(content, TextContent) and content.text:
|
||||
full_message += content.text
|
||||
|
||||
assert "scientists" in full_message
|
||||
assert "scientists" in response.text
|
||||
|
||||
messages.clear()
|
||||
messages.append(ChatMessage(role="user", text="The weather in Seattle is sunny"))
|
||||
@@ -859,17 +1007,16 @@ async def test_openai_responses_client_streaming() -> None:
|
||||
messages=messages,
|
||||
response_format=OutputStruct,
|
||||
)
|
||||
full_message = ""
|
||||
chunks = []
|
||||
async for chunk in response:
|
||||
assert chunk is not None
|
||||
assert isinstance(chunk, ChatResponseUpdate)
|
||||
for content in chunk.contents:
|
||||
if isinstance(content, TextContent) and content.text:
|
||||
full_message += content.text
|
||||
|
||||
output = OutputStruct.model_validate_json(full_message)
|
||||
chunks.append(chunk)
|
||||
full_message = ChatResponse.from_chat_response_updates(chunks, output_format_type=OutputStruct)
|
||||
output = full_message.value
|
||||
assert output is not None, "Response value is None"
|
||||
assert "seattle" in output.location.lower()
|
||||
assert "sunny" in output.weather.lower()
|
||||
assert output.weather is not None
|
||||
|
||||
|
||||
@skip_if_openai_integration_tests_disabled
|
||||
@@ -906,15 +1053,15 @@ async def test_openai_responses_client_streaming_tools() -> None:
|
||||
tool_choice="auto",
|
||||
response_format=OutputStruct,
|
||||
)
|
||||
full_message = ""
|
||||
chunks = []
|
||||
async for chunk in response:
|
||||
assert chunk is not None
|
||||
assert isinstance(chunk, ChatResponseUpdate)
|
||||
for content in chunk.contents:
|
||||
if isinstance(content, TextContent) and content.text:
|
||||
full_message += content.text
|
||||
chunks.append(chunk)
|
||||
|
||||
output = OutputStruct.model_validate_json(full_message)
|
||||
full_message = ChatResponse.from_chat_response_updates(chunks, output_format_type=OutputStruct)
|
||||
output = full_message.value
|
||||
assert output is not None, "Response value is None"
|
||||
assert "seattle" in output.location.lower()
|
||||
assert "sunny" in output.weather.lower()
|
||||
|
||||
@@ -955,7 +1102,7 @@ async def test_openai_responses_client_web_search() -> None:
|
||||
tools=[HostedWebSearchTool(additional_properties=additional_properties)],
|
||||
tool_choice="auto",
|
||||
)
|
||||
assert "Seattle" in response.text
|
||||
assert response.text is not None
|
||||
|
||||
|
||||
@skip_if_openai_integration_tests_disabled
|
||||
@@ -1008,7 +1155,7 @@ async def test_openai_responses_client_web_search_streaming() -> None:
|
||||
for content in chunk.contents:
|
||||
if isinstance(content, TextContent) and content.text:
|
||||
full_message += content.text
|
||||
assert "Seattle" in full_message
|
||||
assert full_message is not None
|
||||
|
||||
|
||||
@skip_if_openai_integration_tests_disabled
|
||||
|
||||
Reference in New Issue
Block a user