mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Python: [BREAKING]: Introducing Options as TypedDict and Generic (#3140)
* WIP typeddict for options * updated all clients and ChatAgents * updated everything * added ADR * fix mypy * proper typevar imports * fixed import * fixed other imports * slight update in the sample * updated from feedback * fixes * fixed missing covariants and test fixes * fixed typing * updated anthropic thinking config * ruff fixes * fixed int tests * fix tests and mypy * updated integration tests * updated docstring and test fix * improved options handling in obser * mypy fix * updated a host of integration tests * fix tests * bedrock fix
This commit is contained in:
Eduard van Valkenburg
@@ -299,8 +299,7 @@ async def test_azure_assistants_client_get_response_tools() -> None:
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# Test that the client can be used to get a response
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response = await azure_assistants_client.get_response(
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messages=messages,
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tools=[get_weather],
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tool_choice="auto",
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options={"tools": [get_weather], "tool_choice": "auto"},
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)
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assert response is not None
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@@ -352,8 +351,7 @@ async def test_azure_assistants_client_streaming_tools() -> None:
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# Test that the client can be used to get a response
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response = azure_assistants_client.get_streaming_response(
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messages=messages,
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tools=[get_weather],
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tool_choice="auto",
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options={"tools": [get_weather], "tool_choice": "auto"},
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)
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full_message: str = ""
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async for chunk in response:
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@@ -212,7 +212,7 @@ async def test_cmc_with_logit_bias(
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azure_chat_client = AzureOpenAIChatClient()
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await azure_chat_client.get_response(messages=chat_history, logit_bias=token_bias)
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await azure_chat_client.get_response(messages=chat_history, options={"logit_bias": token_bias})
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mock_create.assert_awaited_once_with(
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model=azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"],
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@@ -237,7 +237,7 @@ async def test_cmc_with_stop(
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azure_chat_client = AzureOpenAIChatClient()
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await azure_chat_client.get_response(messages=chat_history, stop=stop)
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await azure_chat_client.get_response(messages=chat_history, options={"stop": stop})
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mock_create.assert_awaited_once_with(
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model=azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"],
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@@ -300,7 +300,7 @@ async def test_azure_on_your_data(
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content = await azure_chat_client.get_response(
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messages=messages_in,
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additional_properties={"extra_body": expected_data_settings},
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options={"extra_body": expected_data_settings},
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)
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assert len(content.messages) == 1
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assert len(content.messages[0].contents) == 1
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@@ -370,7 +370,7 @@ async def test_azure_on_your_data_string(
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content = await azure_chat_client.get_response(
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messages=messages_in,
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additional_properties={"extra_body": expected_data_settings},
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options={"extra_body": expected_data_settings},
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)
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assert len(content.messages) == 1
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assert len(content.messages[0].contents) == 1
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@@ -429,7 +429,7 @@ async def test_azure_on_your_data_fail(
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content = await azure_chat_client.get_response(
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messages=messages_in,
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additional_properties={"extra_body": expected_data_settings},
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options={"extra_body": expected_data_settings},
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)
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assert len(content.messages) == 1
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assert len(content.messages[0].contents) == 1
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@@ -652,8 +652,7 @@ async def test_azure_openai_chat_client_response_tools() -> None:
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# Test that the client can be used to get a response
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response = await azure_chat_client.get_response(
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messages=messages,
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tools=[get_story_text],
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tool_choice="auto",
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options={"tools": [get_story_text], "tool_choice": "auto"},
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)
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assert response is not None
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@@ -709,8 +708,7 @@ async def test_azure_openai_chat_client_streaming_tools() -> None:
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# Test that the client can be used to get a response
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response = azure_chat_client.get_streaming_response(
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messages=messages,
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tools=[get_story_text],
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tool_choice="auto",
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options={"tools": [get_story_text], "tool_choice": "auto"},
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)
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full_message: str = ""
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async for chunk in response:
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@@ -1,26 +1,25 @@
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# Copyright (c) Microsoft. All rights reserved.
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import json
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import os
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from typing import Annotated
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from typing import Annotated, Any
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import pytest
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from azure.identity import AzureCliCredential
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from pydantic import BaseModel
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from pytest import param
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from agent_framework import (
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AgentRunResponse,
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AgentRunResponseUpdate,
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AgentThread,
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ChatAgent,
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ChatClientProtocol,
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ChatMessage,
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ChatResponse,
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ChatResponseUpdate,
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HostedCodeInterpreterTool,
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HostedFileSearchTool,
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HostedMCPTool,
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HostedVectorStoreContent,
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TextContent,
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HostedWebSearchTool,
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ai_function,
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)
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from agent_framework.azure import AzureOpenAIResponsesClient
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@@ -74,7 +73,7 @@ async def delete_vector_store(client: AzureOpenAIResponsesClient, file_id: str,
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def test_init(azure_openai_unit_test_env: dict[str, str]) -> None:
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# Test successful initialization
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azure_responses_client = AzureOpenAIResponsesClient()
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azure_responses_client = AzureOpenAIResponsesClient(credential=AzureCliCredential())
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assert azure_responses_client.model_id == azure_openai_unit_test_env["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"]
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assert isinstance(azure_responses_client, ChatClientProtocol)
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@@ -141,283 +140,286 @@ def test_serialize(azure_openai_unit_test_env: dict[str, str]) -> None:
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assert "User-Agent" not in dumped_settings["default_headers"]
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@pytest.mark.flaky
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@skip_if_azure_integration_tests_disabled
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async def test_azure_responses_client_response() -> None:
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"""Test azure responses client responses."""
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azure_responses_client = AzureOpenAIResponsesClient(credential=AzureCliCredential())
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assert isinstance(azure_responses_client, ChatClientProtocol)
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messages: list[ChatMessage] = []
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messages.append(
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ChatMessage(
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role="user",
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text="Emily and David, two passionate scientists, met during a research expedition to Antarctica. "
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"Bonded by their love for the natural world and shared curiosity, they uncovered a "
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"groundbreaking phenomenon in glaciology that could potentially reshape our understanding "
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"of climate change.",
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)
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)
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messages.append(ChatMessage(role="user", text="who are Emily and David?"))
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# Test that the client can be used to get a response
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response = await azure_responses_client.get_response(messages=messages)
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assert response is not None
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assert isinstance(response, ChatResponse)
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assert "scientists" in response.text
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messages.clear()
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messages.append(ChatMessage(role="user", text="The weather in New York is sunny"))
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messages.append(ChatMessage(role="user", text="What is the weather in New York?"))
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# Test that the client can be used to get a structured response
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structured_response = await azure_responses_client.get_response( # type: ignore[reportAssignmentType]
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messages=messages,
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response_format=OutputStruct,
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)
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assert structured_response is not None
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assert isinstance(structured_response, ChatResponse)
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assert isinstance(structured_response.value, OutputStruct)
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assert structured_response.value.location == "New York"
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assert "sunny" in structured_response.value.weather.lower()
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# region Integration Tests
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@pytest.mark.flaky
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@skip_if_azure_integration_tests_disabled
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async def test_azure_responses_client_response_tools() -> None:
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"""Test azure responses client tools."""
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azure_responses_client = AzureOpenAIResponsesClient(credential=AzureCliCredential())
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assert isinstance(azure_responses_client, ChatClientProtocol)
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messages: list[ChatMessage] = []
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messages.append(ChatMessage(role="user", text="What is the weather in New York?"))
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# Test that the client can be used to get a response
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response = await azure_responses_client.get_response(
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messages=messages,
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tools=[get_weather],
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tool_choice="auto",
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)
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assert response is not None
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assert isinstance(response, ChatResponse)
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assert "sunny" in response.text
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messages.clear()
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messages.append(ChatMessage(role="user", text="What is the weather in Seattle?"))
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# Test that the client can be used to get a response
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structured_response: ChatResponse = await azure_responses_client.get_response( # type: ignore[reportAssignmentType]
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messages=messages,
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tools=[get_weather],
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tool_choice="auto",
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response_format=OutputStruct,
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)
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assert structured_response is not None
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assert isinstance(structured_response, ChatResponse)
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assert isinstance(structured_response.value, OutputStruct)
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assert "Seattle" in structured_response.value.location
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assert "sunny" in structured_response.value.weather.lower()
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@pytest.mark.flaky
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@skip_if_azure_integration_tests_disabled
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async def test_azure_responses_client_streaming() -> None:
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"""Test Azure azure responses client streaming responses."""
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azure_responses_client = AzureOpenAIResponsesClient(credential=AzureCliCredential())
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assert isinstance(azure_responses_client, ChatClientProtocol)
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messages: list[ChatMessage] = []
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messages.append(
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ChatMessage(
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role="user",
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text="Emily and David, two passionate scientists, met during a research expedition to Antarctica. "
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"Bonded by their love for the natural world and shared curiosity, they uncovered a "
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"groundbreaking phenomenon in glaciology that could potentially reshape our understanding "
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"of climate change.",
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)
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)
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messages.append(ChatMessage(role="user", text="who are Emily and David?"))
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# Test that the client can be used to get a response
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response = azure_responses_client.get_streaming_response(messages=messages)
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full_message: str = ""
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async for chunk in response:
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assert chunk is not None
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assert isinstance(chunk, ChatResponseUpdate)
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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 "scientists" in full_message
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messages.clear()
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messages.append(ChatMessage(role="user", text="The weather in Seattle is sunny"))
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messages.append(ChatMessage(role="user", text="What is the weather in Seattle?"))
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structured_response = await ChatResponse.from_chat_response_generator(
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azure_responses_client.get_streaming_response(
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messages=messages,
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response_format=OutputStruct,
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@pytest.mark.parametrize(
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"option_name,option_value,needs_validation",
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[
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# Simple ChatOptions - just verify they don't fail
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param("temperature", 0.7, False, id="temperature"),
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param("top_p", 0.9, False, id="top_p"),
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param("max_tokens", 500, False, id="max_tokens"),
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param("seed", 123, False, id="seed"),
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param("user", "test-user-id", False, id="user"),
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param("metadata", {"test_key": "test_value"}, False, id="metadata"),
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param("frequency_penalty", 0.5, False, id="frequency_penalty"),
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param("presence_penalty", 0.3, False, id="presence_penalty"),
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param("stop", ["END"], False, id="stop"),
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param("allow_multiple_tool_calls", True, False, id="allow_multiple_tool_calls"),
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param("tool_choice", "none", True, id="tool_choice_none"),
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# OpenAIResponsesOptions - just verify they don't fail
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param("safety_identifier", "user-hash-abc123", False, id="safety_identifier"),
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param("truncation", "auto", False, id="truncation"),
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param("top_logprobs", 5, False, id="top_logprobs"),
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param("prompt_cache_key", "test-cache-key", False, id="prompt_cache_key"),
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param("max_tool_calls", 3, False, id="max_tool_calls"),
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# Complex options requiring output validation
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param("tools", [get_weather], True, id="tools_function"),
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param("tool_choice", "auto", True, id="tool_choice_auto"),
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param(
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"tool_choice",
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{"mode": "required", "required_function_name": "get_weather"},
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True,
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id="tool_choice_required",
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),
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output_format_type=OutputStruct,
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)
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assert structured_response is not None
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assert isinstance(structured_response, ChatResponse)
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assert isinstance(structured_response.value, OutputStruct)
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assert "Seattle" in structured_response.value.location
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assert "sunny" in structured_response.value.weather.lower()
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param("response_format", OutputStruct, True, id="response_format_pydantic"),
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param(
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"response_format",
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{
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"type": "json_schema",
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"json_schema": {
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"name": "WeatherDigest",
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"strict": True,
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"schema": {
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"title": "WeatherDigest",
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"type": "object",
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"properties": {
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"location": {"type": "string"},
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"conditions": {"type": "string"},
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"temperature_c": {"type": "number"},
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"advisory": {"type": "string"},
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},
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"required": ["location", "conditions", "temperature_c", "advisory"],
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"additionalProperties": False,
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},
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},
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},
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True,
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id="response_format_runtime_json_schema",
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),
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],
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)
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async def test_integration_options(
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option_name: str,
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option_value: Any,
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needs_validation: bool,
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) -> None:
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"""Parametrized test covering all ChatOptions and OpenAIResponsesOptions.
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Tests both streaming and non-streaming modes for each option to ensure
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they don't cause failures. Options marked with needs_validation also
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check that the feature actually works correctly.
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"""
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client = AzureOpenAIResponsesClient(credential=AzureCliCredential())
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# to ensure toolmode required does not endlessly loop
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client.function_invocation_configuration.max_iterations = 1
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for streaming in [False, True]:
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# Prepare test message
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if option_name == "tools" or option_name == "tool_choice":
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# Use weather-related prompt for tool tests
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messages = [ChatMessage(role="user", text="What is the weather in Seattle?")]
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elif option_name == "response_format":
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# Use prompt that works well with structured output
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messages = [ChatMessage(role="user", text="The weather in Seattle is sunny")]
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messages.append(ChatMessage(role="user", text="What is the weather in Seattle?"))
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else:
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# Generic prompt for simple options
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messages = [ChatMessage(role="user", text="Say 'Hello World' briefly.")]
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# Build options dict
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options: dict[str, Any] = {option_name: option_value}
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# Add tools if testing tool_choice to avoid errors
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if option_name == "tool_choice":
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options["tools"] = [get_weather]
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if streaming:
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# Test streaming mode
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response_gen = client.get_streaming_response(
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messages=messages,
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options=options,
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)
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output_format = option_value if option_name == "response_format" else None
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response = await ChatResponse.from_chat_response_generator(response_gen, output_format_type=output_format)
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else:
|
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# Test non-streaming mode
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response = await client.get_response(
|
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messages=messages,
|
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options=options,
|
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)
|
||||
|
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assert response is not None
|
||||
assert isinstance(response, ChatResponse)
|
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assert response.text is not None, f"No text in response for option '{option_name}'"
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assert len(response.text) > 0, f"Empty response for option '{option_name}'"
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|
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# Validate based on option type
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if needs_validation:
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if option_name == "tools" or option_name == "tool_choice":
|
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# Should have called the weather function
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text = response.text.lower()
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assert "sunny" in text or "seattle" in text, f"Tool not invoked for {option_name}"
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elif option_name == "response_format":
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if option_value == OutputStruct:
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# Should have structured output
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assert response.value is not None, "No structured output"
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||||
assert isinstance(response.value, OutputStruct)
|
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assert "seattle" in response.value.location.lower()
|
||||
else:
|
||||
# Runtime JSON schema
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assert response.value is None, "No structured output, can't parse any json."
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response_value = json.loads(response.text)
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assert isinstance(response_value, dict)
|
||||
assert "location" in response_value
|
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assert "seattle" in response_value["location"].lower()
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_azure_responses_client_streaming_tools() -> None:
|
||||
"""Test azure responses client streaming tools."""
|
||||
async def test_integration_web_search() -> None:
|
||||
client = AzureOpenAIResponsesClient(credential=AzureCliCredential())
|
||||
|
||||
for streaming in [False, True]:
|
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content = {
|
||||
"messages": "Who are the main characters of Kpop Demon Hunters? Do a web search to find the answer.",
|
||||
"options": {
|
||||
"tool_choice": "auto",
|
||||
"tools": [HostedWebSearchTool()],
|
||||
},
|
||||
}
|
||||
if streaming:
|
||||
response = await ChatResponse.from_chat_response_generator(client.get_streaming_response(**content))
|
||||
else:
|
||||
response = await client.get_response(**content)
|
||||
|
||||
assert response is not None
|
||||
assert isinstance(response, ChatResponse)
|
||||
assert "Rumi" in response.text
|
||||
assert "Mira" in response.text
|
||||
assert "Zoey" in response.text
|
||||
|
||||
# Test that the client will use the web search tool with location
|
||||
additional_properties = {
|
||||
"user_location": {
|
||||
"country": "US",
|
||||
"city": "Seattle",
|
||||
}
|
||||
}
|
||||
content = {
|
||||
"messages": "What is the current weather? Do not ask for my current location.",
|
||||
"options": {
|
||||
"tool_choice": "auto",
|
||||
"tools": [HostedWebSearchTool(additional_properties=additional_properties)],
|
||||
},
|
||||
}
|
||||
if streaming:
|
||||
response = await ChatResponse.from_chat_response_generator(client.get_streaming_response(**content))
|
||||
else:
|
||||
response = await client.get_response(**content)
|
||||
assert response.text is not None
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_integration_client_file_search() -> None:
|
||||
"""Test Azure responses client with file search tool."""
|
||||
azure_responses_client = AzureOpenAIResponsesClient(credential=AzureCliCredential())
|
||||
|
||||
assert isinstance(azure_responses_client, ChatClientProtocol)
|
||||
|
||||
messages: list[ChatMessage] = [ChatMessage(role="user", text="What is the weather in Seattle?")]
|
||||
|
||||
# Test that the client can be used to get a response
|
||||
response = azure_responses_client.get_streaming_response(
|
||||
messages=messages,
|
||||
tools=[get_weather],
|
||||
tool_choice="auto",
|
||||
)
|
||||
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 "sunny" in full_message
|
||||
|
||||
messages.clear()
|
||||
messages.append(ChatMessage(role="user", text="What is the weather in Seattle?"))
|
||||
|
||||
structured_response = azure_responses_client.get_streaming_response(
|
||||
messages=messages,
|
||||
tools=[get_weather],
|
||||
tool_choice="auto",
|
||||
response_format=OutputStruct,
|
||||
)
|
||||
full_message = ""
|
||||
async for chunk in structured_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)
|
||||
assert "Seattle" in output.location
|
||||
assert "sunny" in output.weather.lower()
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_azure_responses_client_agent_basic_run():
|
||||
"""Test Azure Responses Client agent basic run functionality with AzureOpenAIResponsesClient."""
|
||||
agent = AzureOpenAIResponsesClient(credential=AzureCliCredential()).create_agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
)
|
||||
|
||||
# Test basic run
|
||||
response = await agent.run("Hello! Please respond with 'Hello World' exactly.")
|
||||
|
||||
assert isinstance(response, AgentRunResponse)
|
||||
assert response.text is not None
|
||||
assert len(response.text) > 0
|
||||
assert "hello world" in response.text.lower()
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_azure_responses_client_agent_basic_run_streaming():
|
||||
"""Test Azure Responses Client agent basic streaming functionality with AzureOpenAIResponsesClient."""
|
||||
async with ChatAgent(
|
||||
chat_client=AzureOpenAIResponsesClient(credential=AzureCliCredential()),
|
||||
) as agent:
|
||||
# Test streaming run
|
||||
full_text = ""
|
||||
async for chunk in agent.run_stream("Please respond with exactly: 'This is a streaming response test.'"):
|
||||
assert isinstance(chunk, AgentRunResponseUpdate)
|
||||
if chunk.text:
|
||||
full_text += chunk.text
|
||||
|
||||
assert len(full_text) > 0
|
||||
assert "streaming response test" in full_text.lower()
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_azure_responses_client_agent_thread_persistence():
|
||||
"""Test Azure Responses Client agent thread persistence across runs with AzureOpenAIResponsesClient."""
|
||||
async with ChatAgent(
|
||||
chat_client=AzureOpenAIResponsesClient(credential=AzureCliCredential()),
|
||||
instructions="You are a helpful assistant with good memory.",
|
||||
) as agent:
|
||||
# Create a new thread that will be reused
|
||||
thread = agent.get_new_thread()
|
||||
|
||||
# First interaction
|
||||
first_response = await agent.run("My favorite programming language is Python. Remember this.", thread=thread)
|
||||
|
||||
assert isinstance(first_response, AgentRunResponse)
|
||||
assert first_response.text is not None
|
||||
|
||||
# Second interaction - test memory
|
||||
second_response = await agent.run("What is my favorite programming language?", thread=thread)
|
||||
|
||||
assert isinstance(second_response, AgentRunResponse)
|
||||
assert second_response.text is not None
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_azure_responses_client_agent_thread_storage_with_store_true():
|
||||
"""Test Azure Responses Client agent with store=True to verify service_thread_id is returned."""
|
||||
async with ChatAgent(
|
||||
chat_client=AzureOpenAIResponsesClient(credential=AzureCliCredential()),
|
||||
instructions="You are a helpful assistant.",
|
||||
) as agent:
|
||||
# Create a new thread
|
||||
thread = AgentThread()
|
||||
|
||||
# Initially, service_thread_id should be None
|
||||
assert thread.service_thread_id is None
|
||||
|
||||
# Run with store=True to store messages on Azure/OpenAI side
|
||||
response = await agent.run(
|
||||
"Hello! Please remember that my name is Alex.",
|
||||
thread=thread,
|
||||
store=True,
|
||||
file_id, vector_store = await create_vector_store(azure_responses_client)
|
||||
try:
|
||||
# Test that the client will use the file search tool
|
||||
response = await azure_responses_client.get_response(
|
||||
messages=[
|
||||
ChatMessage(
|
||||
role="user",
|
||||
text="What is the weather today? Do a file search to find the answer.",
|
||||
)
|
||||
],
|
||||
options={"tools": [HostedFileSearchTool(inputs=vector_store)], "tool_choice": "auto"},
|
||||
)
|
||||
|
||||
# Validate response
|
||||
assert isinstance(response, AgentRunResponse)
|
||||
assert response.text is not None
|
||||
assert len(response.text) > 0
|
||||
|
||||
# After store=True, service_thread_id should be populated
|
||||
assert thread.service_thread_id is not None
|
||||
assert isinstance(thread.service_thread_id, str)
|
||||
assert len(thread.service_thread_id) > 0
|
||||
assert "sunny" in response.text.lower()
|
||||
assert "75" in response.text
|
||||
finally:
|
||||
await delete_vector_store(azure_responses_client, file_id, vector_store.vector_store_id)
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_azure_responses_client_agent_existing_thread():
|
||||
async def test_integration_client_file_search_streaming() -> None:
|
||||
"""Test Azure responses client with file search tool and streaming."""
|
||||
azure_responses_client = AzureOpenAIResponsesClient(credential=AzureCliCredential())
|
||||
file_id, vector_store = await create_vector_store(azure_responses_client)
|
||||
# Test that the client will use the file search tool
|
||||
try:
|
||||
response = azure_responses_client.get_streaming_response(
|
||||
messages=[
|
||||
ChatMessage(
|
||||
role="user",
|
||||
text="What is the weather today? Do a file search to find the answer.",
|
||||
)
|
||||
],
|
||||
options={"tools": [HostedFileSearchTool(inputs=vector_store)], "tool_choice": "auto"},
|
||||
)
|
||||
|
||||
assert response is not None
|
||||
full_response = await ChatResponse.from_chat_response_generator(response)
|
||||
assert "sunny" in full_response.text.lower()
|
||||
assert "75" in full_response.text
|
||||
finally:
|
||||
await delete_vector_store(azure_responses_client, file_id, vector_store.vector_store_id)
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_integration_client_agent_hosted_mcp_tool() -> None:
|
||||
"""Integration test for HostedMCPTool with Azure Response Agent using Microsoft Learn MCP."""
|
||||
client = AzureOpenAIResponsesClient(credential=AzureCliCredential())
|
||||
response = await client.get_response(
|
||||
"How to create an Azure storage account using az cli?",
|
||||
options={
|
||||
# this needs to be high enough to handle the full MCP tool response.
|
||||
"max_tokens": 5000,
|
||||
"tools": HostedMCPTool(
|
||||
name="Microsoft Learn MCP",
|
||||
url="https://learn.microsoft.com/api/mcp",
|
||||
description="A Microsoft Learn MCP server for documentation questions",
|
||||
approval_mode="never_require",
|
||||
),
|
||||
},
|
||||
)
|
||||
assert isinstance(response, ChatResponse)
|
||||
assert response.text
|
||||
# Should contain Azure-related content since it's asking about Azure CLI
|
||||
assert any(term in response.text.lower() for term in ["azure", "storage", "account", "cli"])
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_integration_client_agent_hosted_code_interpreter_tool():
|
||||
"""Test Azure Responses Client agent with HostedCodeInterpreterTool through AzureOpenAIResponsesClient."""
|
||||
client = AzureOpenAIResponsesClient(credential=AzureCliCredential())
|
||||
|
||||
response = await client.get_response(
|
||||
"Calculate the sum of numbers from 1 to 10 using Python code.",
|
||||
options={
|
||||
"tools": [HostedCodeInterpreterTool()],
|
||||
},
|
||||
)
|
||||
# Should contain calculation result (sum of 1-10 = 55) or code execution content
|
||||
contains_relevant_content = any(
|
||||
term in response.text.lower() for term in ["55", "sum", "code", "python", "calculate", "10"]
|
||||
)
|
||||
assert contains_relevant_content or len(response.text.strip()) > 10
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_integration_client_agent_existing_thread():
|
||||
"""Test Azure Responses Client agent with existing thread to continue conversations across agent instances."""
|
||||
# First conversation - capture the thread
|
||||
preserved_thread = None
|
||||
@@ -428,7 +430,7 @@ async def test_azure_responses_client_agent_existing_thread():
|
||||
) as first_agent:
|
||||
# Start a conversation and capture the thread
|
||||
thread = first_agent.get_new_thread()
|
||||
first_response = await first_agent.run("My hobby is photography. Remember this.", thread=thread)
|
||||
first_response = await first_agent.run("My hobby is photography. Remember this.", thread=thread, store=True)
|
||||
|
||||
assert isinstance(first_response, AgentRunResponse)
|
||||
assert first_response.text is not None
|
||||
@@ -448,189 +450,3 @@ async def test_azure_responses_client_agent_existing_thread():
|
||||
assert isinstance(second_response, AgentRunResponse)
|
||||
assert second_response.text is not None
|
||||
assert "photography" in second_response.text.lower()
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_azure_responses_client_agent_hosted_code_interpreter_tool():
|
||||
"""Test Azure Responses Client agent with HostedCodeInterpreterTool through AzureOpenAIResponsesClient."""
|
||||
async with ChatAgent(
|
||||
chat_client=AzureOpenAIResponsesClient(credential=AzureCliCredential()),
|
||||
instructions="You are a helpful assistant that can execute Python code.",
|
||||
tools=[HostedCodeInterpreterTool()],
|
||||
) as agent:
|
||||
# Test code interpreter functionality
|
||||
response = await agent.run("Calculate the sum of numbers from 1 to 10 using Python code.")
|
||||
|
||||
assert isinstance(response, AgentRunResponse)
|
||||
assert response.text is not None
|
||||
assert len(response.text) > 0
|
||||
# Should contain calculation result (sum of 1-10 = 55) or code execution content
|
||||
contains_relevant_content = any(
|
||||
term in response.text.lower() for term in ["55", "sum", "code", "python", "calculate", "10"]
|
||||
)
|
||||
assert contains_relevant_content or len(response.text.strip()) > 10
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_azure_responses_client_agent_level_tool_persistence():
|
||||
"""Test that agent-level tools persist across multiple runs with Azure Responses Client."""
|
||||
|
||||
async with ChatAgent(
|
||||
chat_client=AzureOpenAIResponsesClient(credential=AzureCliCredential()),
|
||||
instructions="You are a helpful assistant that uses available tools.",
|
||||
tools=[get_weather], # Agent-level tool
|
||||
) as agent:
|
||||
# First run - agent-level tool should be available
|
||||
first_response = await agent.run("What's the weather like in Chicago?")
|
||||
|
||||
assert isinstance(first_response, AgentRunResponse)
|
||||
assert first_response.text is not None
|
||||
# Should use the agent-level weather tool
|
||||
assert any(term in first_response.text.lower() for term in ["chicago", "sunny", "72"])
|
||||
|
||||
# Second run - agent-level tool should still be available (persistence test)
|
||||
second_response = await agent.run("What's the weather in Miami?")
|
||||
|
||||
assert isinstance(second_response, AgentRunResponse)
|
||||
assert second_response.text is not None
|
||||
# Should use the agent-level weather tool again
|
||||
assert any(term in second_response.text.lower() for term in ["miami", "sunny", "72"])
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_azure_responses_client_agent_chat_options_run_level() -> None:
|
||||
"""Integration test for comprehensive ChatOptions parameter coverage with Azure Response Agent."""
|
||||
async with ChatAgent(
|
||||
chat_client=AzureOpenAIResponsesClient(credential=AzureCliCredential()),
|
||||
instructions="You are a helpful assistant.",
|
||||
) as agent:
|
||||
response = await agent.run(
|
||||
"Provide a brief, helpful response.",
|
||||
max_tokens=100,
|
||||
temperature=0.7,
|
||||
top_p=0.9,
|
||||
seed=123,
|
||||
user="comprehensive-test-user",
|
||||
tools=[get_weather],
|
||||
tool_choice="auto",
|
||||
)
|
||||
|
||||
assert isinstance(response, AgentRunResponse)
|
||||
assert response.text is not None
|
||||
assert len(response.text) > 0
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_azure_responses_client_agent_chat_options_agent_level() -> None:
|
||||
"""Integration test for comprehensive ChatOptions parameter coverage with Azure Response Agent."""
|
||||
async with ChatAgent(
|
||||
chat_client=AzureOpenAIResponsesClient(credential=AzureCliCredential()),
|
||||
instructions="You are a helpful assistant.",
|
||||
max_tokens=100,
|
||||
temperature=0.7,
|
||||
top_p=0.9,
|
||||
seed=123,
|
||||
user="comprehensive-test-user",
|
||||
tools=[get_weather],
|
||||
tool_choice="auto",
|
||||
) as agent:
|
||||
response = await agent.run(
|
||||
"Provide a brief, helpful response.",
|
||||
)
|
||||
|
||||
assert isinstance(response, AgentRunResponse)
|
||||
assert response.text is not None
|
||||
assert len(response.text) > 0
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_azure_responses_client_agent_hosted_mcp_tool() -> None:
|
||||
"""Integration test for HostedMCPTool with Azure Response Agent using Microsoft Learn MCP."""
|
||||
|
||||
async with ChatAgent(
|
||||
chat_client=AzureOpenAIResponsesClient(credential=AzureCliCredential()),
|
||||
instructions="You are a helpful assistant that can help with microsoft documentation questions.",
|
||||
tools=HostedMCPTool(
|
||||
name="Microsoft Learn MCP",
|
||||
url="https://learn.microsoft.com/api/mcp",
|
||||
description="A Microsoft Learn MCP server for documentation questions",
|
||||
approval_mode="never_require",
|
||||
),
|
||||
) as agent:
|
||||
response = await agent.run(
|
||||
"How to create an Azure storage account using az cli?",
|
||||
# this needs to be high enough to handle the full MCP tool response.
|
||||
max_tokens=5000,
|
||||
)
|
||||
|
||||
assert isinstance(response, AgentRunResponse)
|
||||
assert response.text
|
||||
# Should contain Azure-related content since it's asking about Azure CLI
|
||||
assert any(term in response.text.lower() for term in ["azure", "storage", "account", "cli"])
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_azure_responses_client_file_search() -> None:
|
||||
"""Test Azure responses client with file search tool."""
|
||||
azure_responses_client = AzureOpenAIResponsesClient(credential=AzureCliCredential())
|
||||
|
||||
assert isinstance(azure_responses_client, ChatClientProtocol)
|
||||
|
||||
file_id, vector_store = await create_vector_store(azure_responses_client)
|
||||
# Test that the client will use the file search tool
|
||||
response = await azure_responses_client.get_response(
|
||||
messages=[
|
||||
ChatMessage(
|
||||
role="user",
|
||||
text="What is the weather today? Do a file search to find the answer.",
|
||||
)
|
||||
],
|
||||
tools=[HostedFileSearchTool(inputs=vector_store)],
|
||||
tool_choice="auto",
|
||||
)
|
||||
|
||||
await delete_vector_store(azure_responses_client, file_id, vector_store.vector_store_id)
|
||||
assert "sunny" in response.text.lower()
|
||||
assert "75" in response.text
|
||||
|
||||
|
||||
@pytest.mark.flaky
|
||||
@skip_if_azure_integration_tests_disabled
|
||||
async def test_azure_responses_client_file_search_streaming() -> None:
|
||||
"""Test Azure responses client with file search tool and streaming."""
|
||||
azure_responses_client = AzureOpenAIResponsesClient(credential=AzureCliCredential())
|
||||
|
||||
assert isinstance(azure_responses_client, ChatClientProtocol)
|
||||
|
||||
file_id, vector_store = await create_vector_store(azure_responses_client)
|
||||
# Test that the client will use the file search tool
|
||||
response = azure_responses_client.get_streaming_response(
|
||||
messages=[
|
||||
ChatMessage(
|
||||
role="user",
|
||||
text="What is the weather today? Do a file search to find the answer.",
|
||||
)
|
||||
],
|
||||
tools=[HostedFileSearchTool(inputs=vector_store)],
|
||||
tool_choice="auto",
|
||||
)
|
||||
|
||||
assert response is not None
|
||||
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
|
||||
|
||||
await delete_vector_store(azure_responses_client, file_id, vector_store.vector_store_id)
|
||||
|
||||
assert "sunny" in full_message.lower()
|
||||
assert "75" in full_message
|
||||
|
||||
Reference in New Issue
Block a user