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.NET: Python: OpenAI Responses Agent Completeness (#721)
* OpenAI Responses Agent Completeness * prepare options * added unit tests * azure responses test fix * resolved conflict * pre commit fix * Revert "Merge remote changes and resolve conflicts" This reverts commit56787f25a4, reversing changes made tof71a27ebfe. * Fixes * azure responses file search fix * Fix corrupted uv.lock file --------- Co-authored-by: Giles Odigwe <gilesodigwe@microsoft.com> Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com>
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Giles Odigwe
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674a514cae
commit
0715e0f8d3
@@ -14,6 +14,9 @@ from agent_framework import (
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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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ai_function,
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)
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@@ -45,6 +48,29 @@ async def get_weather(location: Annotated[str, "The location as a city name"]) -
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return f"The weather in {location} is sunny and 72°F."
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async def create_vector_store(client: AzureResponsesClient) -> tuple[str, HostedVectorStoreContent]:
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"""Create a vector store with sample documents for testing."""
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file = await client.client.files.create(
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file=("todays_weather.txt", b"The weather today is sunny with a high of 75F."), purpose="assistants"
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)
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vector_store = await client.client.vector_stores.create(
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name="knowledge_base",
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expires_after={"anchor": "last_active_at", "days": 1},
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)
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result = await client.client.vector_stores.files.create_and_poll(vector_store_id=vector_store.id, file_id=file.id)
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if result.last_error is not None:
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raise Exception(f"Vector store file processing failed with status: {result.last_error.message}")
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return file.id, HostedVectorStoreContent(vector_store_id=vector_store.id)
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async def delete_vector_store(client: AzureResponsesClient, file_id: str, vector_store_id: str) -> None:
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"""Delete the vector store after tests."""
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await client.client.vector_stores.delete(vector_store_id=vector_store_id)
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await client.client.files.delete(file_id=file_id)
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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 = AzureResponsesClient()
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@@ -459,3 +485,140 @@ async def test_azure_responses_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_azure_integration_tests_disabled
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async def test_azure_responses_client_agent_chat_options_run_level() -> None:
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"""Integration test for comprehensive ChatOptions parameter coverage with Azure Response Agent."""
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async with ChatAgent(
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chat_client=AzureResponsesClient(credential=AzureCliCredential()),
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instructions="You are a helpful assistant.",
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) as agent:
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response = await agent.run(
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"Provide a brief, helpful response.",
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max_tokens=100,
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temperature=0.7,
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top_p=0.9,
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seed=123,
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user="comprehensive-test-user",
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tools=[get_weather],
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tool_choice="auto",
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)
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assert isinstance(response, AgentRunResponse)
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assert response.text is not None
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assert len(response.text) > 0
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@skip_if_azure_integration_tests_disabled
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async def test_azure_responses_client_agent_chat_options_agent_level() -> None:
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"""Integration test for comprehensive ChatOptions parameter coverage with Azure Response Agent."""
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async with ChatAgent(
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chat_client=AzureResponsesClient(credential=AzureCliCredential()),
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instructions="You are a helpful assistant.",
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max_tokens=100,
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temperature=0.7,
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top_p=0.9,
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seed=123,
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user="comprehensive-test-user",
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tools=[get_weather],
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tool_choice="auto",
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) as agent:
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response = await agent.run(
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"Provide a brief, helpful response.",
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)
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assert isinstance(response, AgentRunResponse)
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assert response.text is not None
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assert len(response.text) > 0
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@skip_if_azure_integration_tests_disabled
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async def test_azure_responses_client_agent_hosted_mcp_tool() -> None:
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"""Integration test for HostedMCPTool with Azure Response Agent using Microsoft Learn MCP."""
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# Use the same MCP server as the Foundry example
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mcp_tool = HostedMCPTool(
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name="Microsoft Learn MCP",
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url="https://learn.microsoft.com/api/mcp",
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description="A Microsoft Learn MCP server for documentation questions",
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approval_mode="never_require",
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)
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async with ChatAgent(
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chat_client=AzureResponsesClient(credential=AzureCliCredential()),
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instructions="You are a helpful assistant that can help with microsoft documentation questions.",
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tools=[mcp_tool],
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) as agent:
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# Use the same query as the Foundry example
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response = await agent.run(
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"How to create an Azure storage account using az cli?",
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max_tokens=200,
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)
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assert isinstance(response, AgentRunResponse)
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assert response.text is not None
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assert len(response.text) > 0
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# Should contain Azure-related content since it's asking about Azure CLI
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assert any(term in response.text.lower() for term in ["azure", "storage", "account", "cli"])
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@skip_if_azure_integration_tests_disabled
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@pytest.mark.skip(reason="File search requires API key auth, subscription only allows token auth")
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async def test_azure_responses_client_file_search() -> None:
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"""Test Azure responses client with file search tool."""
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azure_responses_client = AzureResponsesClient(credential=AzureCliCredential())
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assert isinstance(azure_responses_client, ChatClientProtocol)
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file_id, vector_store = await create_vector_store(azure_responses_client)
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# Test that the client will use the web search tool
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response = await azure_responses_client.get_response(
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messages=[
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ChatMessage(
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role="user",
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text="What is the weather today? Do a file search to find the answer.",
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)
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],
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tools=[HostedFileSearchTool(inputs=vector_store)],
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tool_choice="auto",
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)
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await delete_vector_store(azure_responses_client, file_id, vector_store.vector_store_id)
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assert "sunny" in response.text.lower()
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assert "75" in response.text
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@skip_if_azure_integration_tests_disabled
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@pytest.mark.skip(reason="File search requires API key auth, subscription only allows token auth")
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async def test_azure_responses_client_file_search_streaming() -> None:
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"""Test Azure responses client with file search tool and streaming."""
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azure_responses_client = AzureResponsesClient(credential=AzureCliCredential())
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assert isinstance(azure_responses_client, ChatClientProtocol)
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file_id, vector_store = await create_vector_store(azure_responses_client)
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# Test that the client will use the web search tool
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response = azure_responses_client.get_streaming_response(
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messages=[
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ChatMessage(
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role="user",
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text="What is the weather today? Do a file search to find the answer.",
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)
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],
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tools=[HostedFileSearchTool(inputs=vector_store)],
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tool_choice="auto",
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)
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assert response is not None
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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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await delete_vector_store(azure_responses_client, file_id, vector_store.vector_store_id)
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assert "sunny" in full_message.lower()
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assert "75" in full_message
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@@ -162,7 +162,7 @@ class OpenAIAssistantsClient(OpenAIConfigMixin, BaseChatClient):
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**kwargs: Any,
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) -> AsyncIterable[ChatResponseUpdate]:
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# Extract necessary state from messages and options
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run_options, tool_results = self._create_run_options(messages, chat_options, **kwargs)
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run_options, tool_results = self._prepare_options(messages, chat_options, **kwargs)
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# Get the thread ID
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thread_id: str | None = (
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@@ -349,7 +349,7 @@ class OpenAIAssistantsClient(OpenAIConfigMixin, BaseChatClient):
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return contents
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def _create_run_options(
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def _prepare_options(
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self,
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messages: MutableSequence[ChatMessage],
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chat_options: ChatOptions | None,
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@@ -1,10 +1,9 @@
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# Copyright (c) Microsoft. All rights reserved.
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import sys
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from collections.abc import AsyncIterable, Callable, Mapping, MutableMapping, MutableSequence, Sequence
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from collections.abc import AsyncIterable, Mapping, MutableMapping, MutableSequence, Sequence
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from datetime import datetime
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from itertools import chain
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from typing import TYPE_CHECKING, Any, Literal, TypeVar
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from typing import Any, TypeVar
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from openai import AsyncOpenAI, BadRequestError
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from openai.types.responses.file_search_tool_param import FileSearchToolParam
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@@ -67,17 +66,6 @@ from ..telemetry import use_telemetry
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from ._exceptions import OpenAIContentFilterException
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from ._shared import OpenAIBase, OpenAIConfigMixin, OpenAISettings, prepare_function_call_results
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if sys.version_info >= (3, 12):
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from typing import override # type: ignore # pragma: no cover
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else:
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from typing_extensions import override # type: ignore[import] # pragma: no cover
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if TYPE_CHECKING:
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from openai.types.responses.response_includable import ResponseIncludable
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from .._types import ChatToolMode
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logger = get_logger("agent_framework.openai")
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__all__ = ["OpenAIResponsesClient"]
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@@ -90,192 +78,6 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient):
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FILE_SEARCH_MAX_RESULTS: int = 50
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def _filter_options(self, **kwargs: Any) -> dict[str, Any]:
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"""Filter options for the responses call."""
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# The responses call does not support all the options that the chat completion call does.
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# We filter out the unsupported options.
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return {key: value for key, value in kwargs.items() if value is not None}
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@override
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async def get_response(
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self,
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messages: str | ChatMessage | list[str] | list[ChatMessage],
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*,
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include: list["ResponseIncludable"] | None = None,
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instructions: str | None = None,
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max_tokens: int | None = None,
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parallel_tool_calls: bool | None = None,
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model: str | None = None,
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previous_response_id: str | None = None,
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reasoning: dict[str, str] | None = None,
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service_tier: str | None = None,
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response_format: type[BaseModel] | None = None,
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seed: int | None = None,
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store: bool | None = None,
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temperature: float | None = None,
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tool_choice: "ChatToolMode" | Literal["auto", "required", "none"] | dict[str, Any] | None = "auto",
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tools: ToolProtocol
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| Callable[..., Any]
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| MutableMapping[str, Any]
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| list[ToolProtocol | Callable[..., Any] | MutableMapping[str, Any]]
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| None = None,
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top_p: float | None = None,
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user: str | None = None,
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truncation: str | None = None,
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timeout: float | None = None,
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additional_properties: dict[str, Any] | None = None,
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**kwargs: Any,
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) -> ChatResponse:
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"""Get a response from the OpenAI API.
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Args:
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messages: the message or messages to send to the model
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include: additional output data to include in the model response.
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instructions: a system (or developer) message inserted into the model's context.
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max_tokens: The maximum number of tokens to generate.
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parallel_tool_calls: Whether to enable parallel tool calls.
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model: The model to use for the agent.
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previous_response_id: The ID of the previous response.
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reasoning: The reasoning to use for the response.
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service_tier: The service tier to use for the response.
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response_format: The format of the response.
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seed: The random seed to use for the response.
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store: whether to store the response.
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temperature: the sampling temperature to use.
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tool_choice: the tool choice for the request.
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tools: the tools to use for the request.
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top_p: the nucleus sampling probability to use.
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user: the user to associate with the request.
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truncation: the truncation strategy to use.
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timeout: the timeout for the request.
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additional_properties: additional properties to include in the request.
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kwargs: any additional keyword arguments,
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will only be passed to functions that are called.
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Returns:
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A chat response from the model.
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"""
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additional_properties = additional_properties or {}
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additional_properties.update(
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self._filter_options(
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include=include,
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instructions=instructions,
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parallel_tool_calls=parallel_tool_calls,
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model=model,
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previous_response_id=previous_response_id,
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reasoning=reasoning,
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service_tier=service_tier,
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truncation=truncation,
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timeout=timeout,
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)
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)
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return await super().get_response(
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messages=messages,
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max_tokens=max_tokens,
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response_format=response_format,
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seed=seed,
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store=store,
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temperature=temperature,
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tool_choice=tool_choice,
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tools=tools, # type: ignore
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top_p=top_p,
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user=user,
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additional_properties=additional_properties,
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**kwargs,
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)
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@override
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async def get_streaming_response(
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self,
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messages: str | ChatMessage | list[str] | list[ChatMessage],
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*,
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# TODO(peterychang): enable this option. background: bool | None = None,
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include: list["ResponseIncludable"] | None = None,
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instructions: str | None = None,
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max_tokens: int | None = None,
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parallel_tool_calls: bool | None = None,
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model: str | None = None,
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previous_response_id: str | None = None,
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reasoning: dict[str, str] | None = None,
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service_tier: str | None = None,
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response_format: type[BaseModel] | None = None,
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seed: int | None = None,
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store: bool | None = None,
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temperature: float | None = None,
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tool_choice: "ChatToolMode" | Literal["auto", "required", "none"] | dict[str, Any] | None = "auto",
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tools: ToolProtocol
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| Callable[..., Any]
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| MutableMapping[str, Any]
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| list[ToolProtocol | Callable[..., Any] | MutableMapping[str, Any]]
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| None = None,
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top_p: float | None = None,
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user: str | None = None,
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truncation: str | None = None,
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timeout: float | None = None,
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additional_properties: dict[str, Any] | None = None,
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**kwargs: Any,
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) -> AsyncIterable[ChatResponseUpdate]:
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"""Get a streaming response from the OpenAI API.
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Args:
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messages: the message or messages to send to the model
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include: additional output data to include in the model response.
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instructions: a system (or developer) message inserted into the model's context.
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max_tokens: The maximum number of tokens to generate.
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parallel_tool_calls: Whether to enable parallel tool calls.
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model: The model to use for the agent.
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previous_response_id: The ID of the previous response.
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reasoning: The reasoning to use for the response.
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service_tier: The service tier to use for the response.
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response_format: The format of the response.
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seed: The random seed to use for the response.
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store: whether to store the response.
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temperature: the sampling temperature to use.
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tool_choice: the tool choice for the request.
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tools: the tools to use for the request.
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top_p: the nucleus sampling probability to use.
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user: the user to associate with the request.
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truncation: the truncation strategy to use.
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timeout: the timeout for the request.
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additional_properties: additional properties to include in the request.
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kwargs: any additional keyword arguments,
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will only be passed to functions that are called.
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Returns:
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A stream representing the response(s) from the LLM.
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"""
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additional_properties = additional_properties or {}
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additional_properties.update(
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self._filter_options(
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include=include,
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instructions=instructions,
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parallel_tool_calls=parallel_tool_calls,
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model=model,
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previous_response_id=previous_response_id,
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reasoning=reasoning,
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service_tier=service_tier,
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truncation=truncation,
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timeout=timeout,
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)
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)
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async for update in super().get_streaming_response(
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messages=messages,
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max_tokens=max_tokens,
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response_format=response_format,
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seed=seed,
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store=store,
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temperature=temperature,
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tool_choice=tool_choice,
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tools=tools, # type: ignore
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top_p=top_p,
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user=user,
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additional_properties=additional_properties,
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**kwargs,
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):
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yield update
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# region Inner Methods
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async def _inner_get_response(
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@@ -474,18 +276,33 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient):
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return response_tools
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def _prepare_options(self, messages: MutableSequence[ChatMessage], chat_options: ChatOptions) -> dict[str, Any]:
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"""Take ChatOptions and create the specific options for Responses."""
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options_dict = chat_options.to_provider_settings(exclude={"response_format"})
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"""Take ChatOptions and create the specific options for Responses API."""
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options_dict: dict[str, Any] = {}
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if chat_options.max_tokens is not None:
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options_dict["max_output_tokens"] = chat_options.max_tokens
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if chat_options.temperature is not None:
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options_dict["temperature"] = chat_options.temperature
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if chat_options.top_p is not None:
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options_dict["top_p"] = chat_options.top_p
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if chat_options.user is not None:
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options_dict["user"] = chat_options.user
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# messages
|
||||
request_input = self._prepare_chat_messages_for_request(messages)
|
||||
if not request_input:
|
||||
raise ServiceInvalidRequestError("Messages are required for chat completions")
|
||||
options_dict["input"] = request_input
|
||||
|
||||
# tools
|
||||
if chat_options.tools is None:
|
||||
options_dict.pop("parallel_tool_calls", None)
|
||||
else:
|
||||
options_dict["tools"] = self._tools_to_response_tools(chat_options.tools)
|
||||
|
||||
# other settings
|
||||
if "store" not in options_dict:
|
||||
options_dict["store"] = False
|
||||
|
||||
@@ -620,8 +620,8 @@ def test_openai_assistants_client_create_function_call_contents_basic(mock_async
|
||||
assert contents[0].arguments == {"location": "Seattle"}
|
||||
|
||||
|
||||
def test_openai_assistants_client_create_run_options_basic(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _create_run_options with basic chat options."""
|
||||
def test_openai_assistants_client_prepare_options_basic(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _prepare_options with basic chat options."""
|
||||
chat_client = create_test_openai_assistants_client(mock_async_openai)
|
||||
|
||||
# Create basic chat options
|
||||
@@ -635,7 +635,7 @@ def test_openai_assistants_client_create_run_options_basic(mock_async_openai: Ma
|
||||
messages = [ChatMessage(role=Role.USER, text="Hello")]
|
||||
|
||||
# Call the method
|
||||
run_options, tool_results = chat_client._create_run_options(messages, chat_options) # type: ignore
|
||||
run_options, tool_results = chat_client._prepare_options(messages, chat_options) # type: ignore
|
||||
|
||||
# Check basic options were set
|
||||
assert run_options["max_completion_tokens"] == 100
|
||||
@@ -645,8 +645,8 @@ def test_openai_assistants_client_create_run_options_basic(mock_async_openai: Ma
|
||||
assert tool_results is None
|
||||
|
||||
|
||||
def test_openai_assistants_client_create_run_options_with_ai_function_tool(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _create_run_options with AIFunction tool."""
|
||||
def test_openai_assistants_client_prepare_options_with_ai_function_tool(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _prepare_options with AIFunction tool."""
|
||||
|
||||
chat_client = create_test_openai_assistants_client(mock_async_openai)
|
||||
|
||||
@@ -664,7 +664,7 @@ def test_openai_assistants_client_create_run_options_with_ai_function_tool(mock_
|
||||
messages = [ChatMessage(role=Role.USER, text="Hello")]
|
||||
|
||||
# Call the method
|
||||
run_options, tool_results = chat_client._create_run_options(messages, chat_options) # type: ignore
|
||||
run_options, tool_results = chat_client._prepare_options(messages, chat_options) # type: ignore
|
||||
|
||||
# Check tools were set correctly
|
||||
assert "tools" in run_options
|
||||
@@ -674,8 +674,8 @@ def test_openai_assistants_client_create_run_options_with_ai_function_tool(mock_
|
||||
assert run_options["tool_choice"] == "auto"
|
||||
|
||||
|
||||
def test_openai_assistants_client_create_run_options_with_code_interpreter(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _create_run_options with HostedCodeInterpreterTool."""
|
||||
def test_openai_assistants_client_prepare_options_with_code_interpreter(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _prepare_options with HostedCodeInterpreterTool."""
|
||||
chat_client = create_test_openai_assistants_client(mock_async_openai)
|
||||
|
||||
# Create a real HostedCodeInterpreterTool
|
||||
@@ -689,7 +689,7 @@ def test_openai_assistants_client_create_run_options_with_code_interpreter(mock_
|
||||
messages = [ChatMessage(role=Role.USER, text="Calculate something")]
|
||||
|
||||
# Call the method
|
||||
run_options, tool_results = chat_client._create_run_options(messages, chat_options) # type: ignore
|
||||
run_options, tool_results = chat_client._prepare_options(messages, chat_options) # type: ignore
|
||||
|
||||
# Check code interpreter tool was set correctly
|
||||
assert "tools" in run_options
|
||||
@@ -698,8 +698,8 @@ def test_openai_assistants_client_create_run_options_with_code_interpreter(mock_
|
||||
assert run_options["tool_choice"] == "auto"
|
||||
|
||||
|
||||
def test_openai_assistants_client_create_run_options_tool_choice_none(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _create_run_options with tool_choice set to 'none'."""
|
||||
def test_openai_assistants_client_prepare_options_tool_choice_none(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _prepare_options with tool_choice set to 'none'."""
|
||||
chat_client = create_test_openai_assistants_client(mock_async_openai)
|
||||
|
||||
chat_options = ChatOptions(
|
||||
@@ -709,15 +709,15 @@ def test_openai_assistants_client_create_run_options_tool_choice_none(mock_async
|
||||
messages = [ChatMessage(role=Role.USER, text="Hello")]
|
||||
|
||||
# Call the method
|
||||
run_options, tool_results = chat_client._create_run_options(messages, chat_options) # type: ignore
|
||||
run_options, tool_results = chat_client._prepare_options(messages, chat_options) # type: ignore
|
||||
|
||||
# Should set tool_choice to none and not include tools
|
||||
assert run_options["tool_choice"] == "none"
|
||||
assert "tools" not in run_options
|
||||
|
||||
|
||||
def test_openai_assistants_client_create_run_options_required_function(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _create_run_options with required function tool choice."""
|
||||
def test_openai_assistants_client_prepare_options_required_function(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _prepare_options with required function tool choice."""
|
||||
chat_client = create_test_openai_assistants_client(mock_async_openai)
|
||||
|
||||
# Create a required function tool choice
|
||||
@@ -730,7 +730,7 @@ def test_openai_assistants_client_create_run_options_required_function(mock_asyn
|
||||
messages = [ChatMessage(role=Role.USER, text="Hello")]
|
||||
|
||||
# Call the method
|
||||
run_options, tool_results = chat_client._create_run_options(messages, chat_options) # type: ignore
|
||||
run_options, tool_results = chat_client._prepare_options(messages, chat_options) # type: ignore
|
||||
|
||||
# Check required function tool choice was set correctly
|
||||
expected_tool_choice = {
|
||||
@@ -740,8 +740,8 @@ def test_openai_assistants_client_create_run_options_required_function(mock_asyn
|
||||
assert run_options["tool_choice"] == expected_tool_choice
|
||||
|
||||
|
||||
def test_openai_assistants_client_create_run_options_with_file_search_tool(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _create_run_options with HostedFileSearchTool."""
|
||||
def test_openai_assistants_client_prepare_options_with_file_search_tool(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _prepare_options with HostedFileSearchTool."""
|
||||
|
||||
chat_client = create_test_openai_assistants_client(mock_async_openai)
|
||||
|
||||
@@ -756,7 +756,7 @@ def test_openai_assistants_client_create_run_options_with_file_search_tool(mock_
|
||||
messages = [ChatMessage(role=Role.USER, text="Search for information")]
|
||||
|
||||
# Call the method
|
||||
run_options, tool_results = chat_client._create_run_options(messages, chat_options) # type: ignore
|
||||
run_options, tool_results = chat_client._prepare_options(messages, chat_options) # type: ignore
|
||||
|
||||
# Check file search tool was set correctly
|
||||
assert "tools" in run_options
|
||||
@@ -766,8 +766,8 @@ def test_openai_assistants_client_create_run_options_with_file_search_tool(mock_
|
||||
assert run_options["tool_choice"] == "auto"
|
||||
|
||||
|
||||
def test_openai_assistants_client_create_run_options_with_mapping_tool(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _create_run_options with MutableMapping tool."""
|
||||
def test_openai_assistants_client_prepare_options_with_mapping_tool(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _prepare_options with MutableMapping tool."""
|
||||
chat_client = create_test_openai_assistants_client(mock_async_openai)
|
||||
|
||||
# Create a tool as a MutableMapping (dict)
|
||||
@@ -781,7 +781,7 @@ def test_openai_assistants_client_create_run_options_with_mapping_tool(mock_asyn
|
||||
messages = [ChatMessage(role=Role.USER, text="Use custom tool")]
|
||||
|
||||
# Call the method
|
||||
run_options, tool_results = chat_client._create_run_options(messages, chat_options) # type: ignore
|
||||
run_options, tool_results = chat_client._prepare_options(messages, chat_options) # type: ignore
|
||||
|
||||
# Check mapping tool was set correctly
|
||||
assert "tools" in run_options
|
||||
@@ -790,8 +790,8 @@ def test_openai_assistants_client_create_run_options_with_mapping_tool(mock_asyn
|
||||
assert run_options["tool_choice"] == "auto"
|
||||
|
||||
|
||||
def test_openai_assistants_client_create_run_options_with_system_message(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _create_run_options with system message converted to instructions."""
|
||||
def test_openai_assistants_client_prepare_options_with_system_message(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _prepare_options with system message converted to instructions."""
|
||||
chat_client = create_test_openai_assistants_client(mock_async_openai)
|
||||
|
||||
messages = [
|
||||
@@ -800,7 +800,7 @@ def test_openai_assistants_client_create_run_options_with_system_message(mock_as
|
||||
]
|
||||
|
||||
# Call the method
|
||||
run_options, tool_results = chat_client._create_run_options(messages, None) # type: ignore
|
||||
run_options, tool_results = chat_client._prepare_options(messages, None) # type: ignore
|
||||
|
||||
# Check that additional_messages only contains the user message
|
||||
# System message should be converted to instructions (though this is handled internally)
|
||||
@@ -809,8 +809,8 @@ def test_openai_assistants_client_create_run_options_with_system_message(mock_as
|
||||
assert run_options["additional_messages"][0]["role"] == "user"
|
||||
|
||||
|
||||
def test_openai_assistants_client_create_run_options_with_image_content(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _create_run_options with image content."""
|
||||
def test_openai_assistants_client_prepare_options_with_image_content(mock_async_openai: MagicMock) -> None:
|
||||
"""Test _prepare_options with image content."""
|
||||
|
||||
chat_client = create_test_openai_assistants_client(mock_async_openai)
|
||||
|
||||
@@ -819,7 +819,7 @@ def test_openai_assistants_client_create_run_options_with_image_content(mock_asy
|
||||
messages = [ChatMessage(role=Role.USER, contents=[image_content])]
|
||||
|
||||
# Call the method
|
||||
run_options, tool_results = chat_client._create_run_options(messages, None) # type: ignore
|
||||
run_options, tool_results = chat_client._prepare_options(messages, None) # type: ignore
|
||||
|
||||
# Check that image content was processed
|
||||
assert "additional_messages" in run_options
|
||||
|
||||
@@ -186,37 +186,6 @@ def test_serialize_with_org_id(openai_unit_test_env: dict[str, str]) -> None:
|
||||
assert "User-Agent" not in dumped_settings["default_headers"]
|
||||
|
||||
|
||||
def test_filter_options_method(openai_unit_test_env: dict[str, str]) -> None:
|
||||
"""Test that the _filter_options method filters out None values correctly."""
|
||||
client = OpenAIResponsesClient()
|
||||
|
||||
# Test with a mix of None and non-None values
|
||||
filtered = client._filter_options( # type: ignore
|
||||
include=["usage"],
|
||||
instructions="Test instruction",
|
||||
max_tokens=None,
|
||||
temperature=0.7,
|
||||
seed=None,
|
||||
model="test-model",
|
||||
store=True,
|
||||
top_p=None,
|
||||
)
|
||||
|
||||
# Should only contain non-None values
|
||||
expected = {
|
||||
"include": ["usage"],
|
||||
"instructions": "Test instruction",
|
||||
"temperature": 0.7,
|
||||
"model": "test-model",
|
||||
"store": True,
|
||||
}
|
||||
|
||||
assert filtered == expected
|
||||
assert "max_tokens" not in filtered
|
||||
assert "seed" not in filtered
|
||||
assert "top_p" not in filtered
|
||||
|
||||
|
||||
def test_get_response_with_invalid_input() -> None:
|
||||
"""Test get_response with invalid inputs to trigger exception handling."""
|
||||
|
||||
@@ -977,7 +946,7 @@ async def test_openai_responses_client_response_tools() -> None:
|
||||
|
||||
@skip_if_openai_integration_tests_disabled
|
||||
async def test_openai_responses_client_streaming() -> None:
|
||||
"""Test Azure OpenAI chat completion responses."""
|
||||
"""Test OpenAI chat completion responses."""
|
||||
openai_responses_client = OpenAIResponsesClient()
|
||||
|
||||
assert isinstance(openai_responses_client, ChatClientProtocol)
|
||||
@@ -1161,7 +1130,6 @@ async def test_openai_responses_client_web_search_streaming() -> None:
|
||||
|
||||
|
||||
@skip_if_openai_integration_tests_disabled
|
||||
@pytest.mark.skip(reason="OpenAI file search functionality is currently broken - tracked in GitHub issue")
|
||||
async def test_openai_responses_client_file_search() -> None:
|
||||
openai_responses_client = OpenAIResponsesClient()
|
||||
|
||||
@@ -1186,7 +1154,6 @@ async def test_openai_responses_client_file_search() -> None:
|
||||
|
||||
|
||||
@skip_if_openai_integration_tests_disabled
|
||||
@pytest.mark.skip(reason="OpenAI file search functionality is currently broken - tracked in GitHub issue")
|
||||
async def test_openai_responses_client_streaming_file_search() -> None:
|
||||
openai_responses_client = OpenAIResponsesClient()
|
||||
|
||||
@@ -1427,6 +1394,81 @@ async def test_openai_responses_client_run_level_tool_isolation():
|
||||
assert call_count == 1
|
||||
|
||||
|
||||
@skip_if_openai_integration_tests_disabled
|
||||
async def test_openai_responses_client_agent_chat_options_run_level() -> None:
|
||||
"""Integration test for comprehensive ChatOptions parameter coverage with OpenAI Response Agent."""
|
||||
async with ChatAgent(
|
||||
chat_client=OpenAIResponsesClient(),
|
||||
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
|
||||
|
||||
|
||||
@skip_if_openai_integration_tests_disabled
|
||||
async def test_openai_responses_client_agent_chat_options_agent_level() -> None:
|
||||
"""Integration test for comprehensive ChatOptions parameter coverage with OpenAI Response Agent."""
|
||||
async with ChatAgent(
|
||||
chat_client=OpenAIResponsesClient(),
|
||||
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
|
||||
|
||||
|
||||
@skip_if_openai_integration_tests_disabled
|
||||
async def test_openai_responses_client_agent_hosted_mcp_tool() -> None:
|
||||
"""Integration test for HostedMCPTool with OpenAI Response Agent using Microsoft Learn MCP."""
|
||||
# Use the same MCP server as the Foundry example
|
||||
mcp_tool = 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",
|
||||
)
|
||||
|
||||
async with ChatAgent(
|
||||
chat_client=OpenAIResponsesClient(),
|
||||
instructions="You are a helpful assistant that can help with microsoft documentation questions.",
|
||||
tools=[mcp_tool],
|
||||
) as agent:
|
||||
# Use the same query as the Foundry example
|
||||
response = await agent.run(
|
||||
"How to create an Azure storage account using az cli?",
|
||||
max_tokens=200,
|
||||
)
|
||||
|
||||
assert isinstance(response, AgentRunResponse)
|
||||
assert response.text is not None
|
||||
assert len(response.text) > 0
|
||||
# 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"])
|
||||
|
||||
|
||||
def test_service_response_exception_includes_original_error_details() -> None:
|
||||
"""Test that ServiceResponseException messages include original error details in the new format."""
|
||||
client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key")
|
||||
@@ -1452,6 +1494,148 @@ def test_service_response_exception_includes_original_error_details() -> None:
|
||||
assert original_error_message in exception_message
|
||||
|
||||
|
||||
def test_get_streaming_response_with_response_format() -> None:
|
||||
"""Test get_streaming_response with response_format."""
|
||||
client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key")
|
||||
messages = [ChatMessage(role="user", text="Test streaming with format")]
|
||||
|
||||
# It will fail due to invalid API key, but exercises the code path
|
||||
with pytest.raises(ServiceResponseException):
|
||||
|
||||
async def run_streaming():
|
||||
async for _ in client.get_streaming_response(messages=messages, response_format=OutputStruct):
|
||||
pass
|
||||
|
||||
asyncio.run(run_streaming())
|
||||
|
||||
|
||||
def test_openai_content_parser_image_content() -> None:
|
||||
"""Test _openai_content_parser with image content variations."""
|
||||
client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key")
|
||||
|
||||
# Test image content with detail parameter and file_id
|
||||
image_content_with_detail = UriContent(
|
||||
uri="https://example.com/image.jpg",
|
||||
media_type="image/jpeg",
|
||||
additional_properties={"detail": "high", "file_id": "file_123"},
|
||||
)
|
||||
result = client._openai_content_parser(Role.USER, image_content_with_detail, {}) # type: ignore
|
||||
assert result["type"] == "input_image"
|
||||
assert result["image_url"] == "https://example.com/image.jpg"
|
||||
assert result["detail"] == "high"
|
||||
assert result["file_id"] == "file_123"
|
||||
|
||||
# Test image content without additional properties (defaults)
|
||||
image_content_basic = UriContent(uri="https://example.com/basic.png", media_type="image/png")
|
||||
result = client._openai_content_parser(Role.USER, image_content_basic, {}) # type: ignore
|
||||
assert result["type"] == "input_image"
|
||||
assert result["detail"] == "auto"
|
||||
assert result["file_id"] is None
|
||||
|
||||
|
||||
def test_openai_content_parser_audio_content() -> None:
|
||||
"""Test _openai_content_parser with audio content variations."""
|
||||
client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key")
|
||||
|
||||
# Test WAV audio content
|
||||
wav_content = UriContent(uri="data:audio/wav;base64,abc123", media_type="audio/wav")
|
||||
result = client._openai_content_parser(Role.USER, wav_content, {}) # type: ignore
|
||||
assert result["type"] == "input_audio"
|
||||
assert result["input_audio"]["data"] == "data:audio/wav;base64,abc123"
|
||||
assert result["input_audio"]["format"] == "wav"
|
||||
|
||||
# Test MP3 audio content
|
||||
mp3_content = UriContent(uri="data:audio/mp3;base64,def456", media_type="audio/mp3")
|
||||
result = client._openai_content_parser(Role.USER, mp3_content, {}) # type: ignore
|
||||
assert result["type"] == "input_audio"
|
||||
assert result["input_audio"]["format"] == "mp3"
|
||||
|
||||
|
||||
def test_openai_content_parser_unsupported_content() -> None:
|
||||
"""Test _openai_content_parser with unsupported content types."""
|
||||
client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key")
|
||||
|
||||
# Test unsupported audio format
|
||||
unsupported_audio = UriContent(uri="data:audio/ogg;base64,ghi789", media_type="audio/ogg")
|
||||
result = client._openai_content_parser(Role.USER, unsupported_audio, {}) # type: ignore
|
||||
assert result == {}
|
||||
|
||||
# Test non-media content
|
||||
text_uri_content = UriContent(uri="https://example.com/document.txt", media_type="text/plain")
|
||||
result = client._openai_content_parser(Role.USER, text_uri_content, {}) # type: ignore
|
||||
assert result == {}
|
||||
|
||||
|
||||
def test_create_streaming_response_content_code_interpreter() -> None:
|
||||
"""Test _create_streaming_response_content with code_interpreter_call."""
|
||||
client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key")
|
||||
chat_options = ChatOptions()
|
||||
function_call_ids: dict[int, tuple[str, str]] = {}
|
||||
|
||||
mock_event_image = MagicMock()
|
||||
mock_event_image.type = "response.output_item.added"
|
||||
mock_item_image = MagicMock()
|
||||
mock_item_image.type = "code_interpreter_call"
|
||||
mock_image_output = MagicMock()
|
||||
mock_image_output.type = "image"
|
||||
mock_image_output.url = "https://example.com/plot.png"
|
||||
mock_item_image.outputs = [mock_image_output]
|
||||
mock_item_image.code = None
|
||||
mock_event_image.item = mock_item_image
|
||||
|
||||
result = client._create_streaming_response_content(mock_event_image, chat_options, function_call_ids) # type: ignore
|
||||
assert len(result.contents) == 1
|
||||
assert isinstance(result.contents[0], UriContent)
|
||||
assert result.contents[0].uri == "https://example.com/plot.png"
|
||||
assert result.contents[0].media_type == "image"
|
||||
|
||||
|
||||
def test_create_streaming_response_content_reasoning() -> None:
|
||||
"""Test _create_streaming_response_content with reasoning content."""
|
||||
client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key")
|
||||
chat_options = ChatOptions()
|
||||
function_call_ids: dict[int, tuple[str, str]] = {}
|
||||
|
||||
mock_event_reasoning = MagicMock()
|
||||
mock_event_reasoning.type = "response.output_item.added"
|
||||
mock_item_reasoning = MagicMock()
|
||||
mock_item_reasoning.type = "reasoning"
|
||||
mock_reasoning_content = MagicMock()
|
||||
mock_reasoning_content.text = "Analyzing the problem step by step..."
|
||||
mock_item_reasoning.content = [mock_reasoning_content]
|
||||
mock_item_reasoning.summary = ["Problem analysis summary"]
|
||||
mock_event_reasoning.item = mock_item_reasoning
|
||||
|
||||
result = client._create_streaming_response_content(mock_event_reasoning, chat_options, function_call_ids) # type: ignore
|
||||
assert len(result.contents) == 1
|
||||
assert isinstance(result.contents[0], TextReasoningContent)
|
||||
assert result.contents[0].text == "Analyzing the problem step by step..."
|
||||
if result.contents[0].additional_properties:
|
||||
assert result.contents[0].additional_properties["summary"] == "Problem analysis summary"
|
||||
|
||||
|
||||
def test_openai_content_parser_text_reasoning_comprehensive() -> None:
|
||||
"""Test _openai_content_parser with TextReasoningContent all additional properties."""
|
||||
client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key")
|
||||
|
||||
# Test TextReasoningContent with all additional properties
|
||||
comprehensive_reasoning = TextReasoningContent(
|
||||
text="Comprehensive reasoning summary",
|
||||
additional_properties={
|
||||
"status": "in_progress",
|
||||
"reasoning_text": "Step-by-step analysis",
|
||||
"encrypted_content": "secure_data_456",
|
||||
},
|
||||
)
|
||||
result = client._openai_content_parser(Role.ASSISTANT, comprehensive_reasoning, {}) # type: ignore
|
||||
assert result["type"] == "reasoning"
|
||||
assert result["summary"]["text"] == "Comprehensive reasoning summary"
|
||||
assert result["status"] == "in_progress"
|
||||
assert result["content"]["type"] == "reasoning_text"
|
||||
assert result["content"]["text"] == "Step-by-step analysis"
|
||||
assert result["encrypted_content"] == "secure_data_456"
|
||||
|
||||
|
||||
def test_streaming_reasoning_text_delta_event() -> None:
|
||||
"""Test reasoning text delta event creates TextReasoningContent."""
|
||||
client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key")
|
||||
|
||||
Generated
+167
-164
@@ -493,7 +493,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "azure-ai-projects"
|
||||
version = "1.1.0b3"
|
||||
version = "1.1.0b4"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "azure-ai-agents", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
@@ -502,23 +502,23 @@ dependencies = [
|
||||
{ name = "isodate", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
{ name = "typing-extensions", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
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]
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sdist = { url = "https://files.pythonhosted.org/packages/a7/dd/1dc533648c8cafe5b5fdf93ca2f1b681d5d718ff30b1d1aa8b90e87cbf9b/azure_ai_projects-1.1.0b3.tar.gz", hash = "sha256:f18397de1456e315c592e708a0c4af00d6b52f646f2d199b2f99554e8236d495", size = 145568, upload-time = "2025-08-26T23:16:05.836Z" }
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sdist = { url = "https://files.pythonhosted.org/packages/bc/16/7a7c978a79f545d62ab4327cd704c22b5d7ade8dcfb58ea193257aebabf9/azure_ai_projects-1.1.0b4.tar.gz", hash = "sha256:39e2f1396270b375069c2d9c82ccfe91c11384eca9f61d59adbc12fb6d6a32ca", size = 147568, upload-time = "2025-09-12T17:35:08.52Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/64/8a/92085213bdf90e6df93a4678b1ec84e2f9ef0857ab649c6034a574960ec7/azure_ai_projects-1.1.0b3-py3-none-any.whl", hash = "sha256:6149e5b17f4cbd467eec812ae9b335be48b7e856d886e49c1c0cd55385a5fa78", size = 125797, upload-time = "2025-08-26T23:16:07.866Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/db/10/8b7bd070e3cc804343dab124ce66a3b7999a72d5be0e49232cbcd1d36e18/azure_ai_projects-1.1.0b4-py3-none-any.whl", hash = "sha256:d8aab84fd7cd7c5937e78141e37ca4473dc5ed6cce2c0490c634418abe14afea", size = 126670, upload-time = "2025-09-12T17:35:10.039Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "azure-core"
|
||||
version = "1.35.0"
|
||||
version = "1.35.1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
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{ name = "requests", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
{ name = "six", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
{ name = "typing-extensions", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/ce/89/f53968635b1b2e53e4aad2dd641488929fef4ca9dfb0b97927fa7697ddf3/azure_core-1.35.0.tar.gz", hash = "sha256:c0be528489485e9ede59b6971eb63c1eaacf83ef53001bfe3904e475e972be5c", size = 339689, upload-time = "2025-07-03T00:55:23.496Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/15/6b/2653adc0f33adba8f11b1903701e6b1c10d34ce5d8e25dfa13a422f832b0/azure_core-1.35.1.tar.gz", hash = "sha256:435d05d6df0fff2f73fb3c15493bb4721ede14203f1ff1382aa6b6b2bdd7e562", size = 345290, upload-time = "2025-09-11T22:58:04.481Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/d4/78/bf94897361fdd650850f0f2e405b2293e2f12808239046232bdedf554301/azure_core-1.35.0-py3-none-any.whl", hash = "sha256:8db78c72868a58f3de8991eb4d22c4d368fae226dac1002998d6c50437e7dad1", size = 210708, upload-time = "2025-07-03T00:55:25.238Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/27/52/805980aa1ba18282077c484dba634ef0ede1e84eec8be9c92b2e162d0ed6/azure_core-1.35.1-py3-none-any.whl", hash = "sha256:12da0c9e08e48e198f9158b56ddbe33b421477e1dc98c2e1c8f9e254d92c468b", size = 211800, upload-time = "2025-09-11T22:58:06.281Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -536,7 +536,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "azure-identity"
|
||||
version = "1.24.0"
|
||||
version = "1.25.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "azure-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
@@ -545,9 +545,9 @@ dependencies = [
|
||||
{ name = "msal-extensions", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
{ name = "typing-extensions", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/b5/44/f3ee20bacb220b6b4a2b0a6cf7e742eecb383a5ccf604dd79ec27c286b7e/azure_identity-1.24.0.tar.gz", hash = "sha256:6c3a40b2a70af831e920b89e6421e8dcd4af78a0cb38b9642d86c67643d4930c", size = 271630, upload-time = "2025-08-07T22:27:36.258Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/4e/9e/4c9682a286c3c89e437579bd9f64f311020e5125c1321fd3a653166b5716/azure_identity-1.25.0.tar.gz", hash = "sha256:4177df34d684cddc026e6cf684e1abb57767aa9d84e7f2129b080ec45eee7733", size = 278507, upload-time = "2025-09-12T01:30:04.418Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/a9/74/17428cb429e8d52f6d0d69ed685f4760a545cb0156594963a9337b53b6c9/azure_identity-1.24.0-py3-none-any.whl", hash = "sha256:9e04997cde0ab02ed66422c74748548e620b7b29361c72ce622acab0267ff7c4", size = 187890, upload-time = "2025-08-07T22:27:38.033Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/75/54/81683b6756676a22e037b209695b08008258e603f7e47c56834029c5922a/azure_identity-1.25.0-py3-none-any.whl", hash = "sha256:becaec086bbdf8d1a6aa4fb080c2772a0f824a97d50c29637ec8cc4933f1e82d", size = 190861, upload-time = "2025-09-12T01:30:06.474Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -1052,7 +1052,7 @@ name = "exceptiongroup"
|
||||
version = "1.3.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "typing-extensions", marker = "(python_full_version < '3.11' and sys_platform == 'darwin') or (python_full_version < '3.11' and sys_platform == 'linux') or (python_full_version < '3.11' and sys_platform == 'win32')" },
|
||||
{ name = "typing-extensions", marker = "(python_full_version < '3.13' and sys_platform == 'darwin') or (python_full_version < '3.13' and sys_platform == 'linux') or (python_full_version < '3.13' and sys_platform == 'win32')" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/0b/9f/a65090624ecf468cdca03533906e7c69ed7588582240cfe7cc9e770b50eb/exceptiongroup-1.3.0.tar.gz", hash = "sha256:b241f5885f560bc56a59ee63ca4c6a8bfa46ae4ad651af316d4e81817bb9fd88", size = 29749, upload-time = "2025-05-10T17:42:51.123Z" }
|
||||
wheels = [
|
||||
@@ -1580,74 +1580,75 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "jiter"
|
||||
version = "0.10.0"
|
||||
version = "0.11.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/ee/9d/ae7ddb4b8ab3fb1b51faf4deb36cb48a4fbbd7cb36bad6a5fca4741306f7/jiter-0.10.0.tar.gz", hash = "sha256:07a7142c38aacc85194391108dc91b5b57093c978a9932bd86a36862759d9500", size = 162759, upload-time = "2025-05-18T19:04:59.73Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/9d/c0/a3bb4cc13aced219dd18191ea66e874266bd8aa7b96744e495e1c733aa2d/jiter-0.11.0.tar.gz", hash = "sha256:1d9637eaf8c1d6a63d6562f2a6e5ab3af946c66037eb1b894e8fad75422266e4", size = 167094, upload-time = "2025-09-15T09:20:38.212Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/be/7e/4011b5c77bec97cb2b572f566220364e3e21b51c48c5bd9c4a9c26b41b67/jiter-0.10.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:cd2fb72b02478f06a900a5782de2ef47e0396b3e1f7d5aba30daeb1fce66f303", size = 317215, upload-time = "2025-05-18T19:03:04.303Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/8a/4f/144c1b57c39692efc7ea7d8e247acf28e47d0912800b34d0ad815f6b2824/jiter-0.10.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:32bb468e3af278f095d3fa5b90314728a6916d89ba3d0ffb726dd9bf7367285e", size = 322814, upload-time = "2025-05-18T19:03:06.433Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/63/1f/db977336d332a9406c0b1f0b82be6f71f72526a806cbb2281baf201d38e3/jiter-0.10.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:aa8b3e0068c26ddedc7abc6fac37da2d0af16b921e288a5a613f4b86f050354f", size = 345237, upload-time = "2025-05-18T19:03:07.833Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/d7/1c/aa30a4a775e8a672ad7f21532bdbfb269f0706b39c6ff14e1f86bdd9e5ff/jiter-0.10.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:286299b74cc49e25cd42eea19b72aa82c515d2f2ee12d11392c56d8701f52224", size = 370999, upload-time = "2025-05-18T19:03:09.338Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/35/df/f8257abc4207830cb18880781b5f5b716bad5b2a22fb4330cfd357407c5b/jiter-0.10.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6ed5649ceeaeffc28d87fb012d25a4cd356dcd53eff5acff1f0466b831dda2a7", size = 491109, upload-time = "2025-05-18T19:03:11.13Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/06/76/9e1516fd7b4278aa13a2cc7f159e56befbea9aa65c71586305e7afa8b0b3/jiter-0.10.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b2ab0051160cb758a70716448908ef14ad476c3774bd03ddce075f3c1f90a3d6", size = 388608, upload-time = "2025-05-18T19:03:12.911Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/6d/64/67750672b4354ca20ca18d3d1ccf2c62a072e8a2d452ac3cf8ced73571ef/jiter-0.10.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:03997d2f37f6b67d2f5c475da4412be584e1cec273c1cfc03d642c46db43f8cf", size = 352454, upload-time = "2025-05-18T19:03:14.741Z" },
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{ url = "https://files.pythonhosted.org/packages/96/4d/5c4e36d48f169a54b53a305114be3efa2bbffd33b648cd1478a688f639c1/jiter-0.10.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c404a99352d839fed80d6afd6c1d66071f3bacaaa5c4268983fc10f769112e90", size = 391833, upload-time = "2025-05-18T19:03:16.426Z" },
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{ url = "https://files.pythonhosted.org/packages/0b/de/ce4a6166a78810bd83763d2fa13f85f73cbd3743a325469a4a9289af6dae/jiter-0.10.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:66e989410b6666d3ddb27a74c7e50d0829704ede652fd4c858e91f8d64b403d0", size = 523646, upload-time = "2025-05-18T19:03:17.704Z" },
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{ url = "https://files.pythonhosted.org/packages/a2/a6/3bc9acce53466972964cf4ad85efecb94f9244539ab6da1107f7aed82934/jiter-0.10.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:b532d3af9ef4f6374609a3bcb5e05a1951d3bf6190dc6b176fdb277c9bbf15ee", size = 514735, upload-time = "2025-05-18T19:03:19.44Z" },
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{ url = "https://files.pythonhosted.org/packages/b4/d8/243c2ab8426a2a4dea85ba2a2ba43df379ccece2145320dfd4799b9633c5/jiter-0.10.0-cp310-cp310-win32.whl", hash = "sha256:da9be20b333970e28b72edc4dff63d4fec3398e05770fb3205f7fb460eb48dd4", size = 210747, upload-time = "2025-05-18T19:03:21.184Z" },
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{ url = "https://files.pythonhosted.org/packages/37/7a/8021bd615ef7788b98fc76ff533eaac846322c170e93cbffa01979197a45/jiter-0.10.0-cp310-cp310-win_amd64.whl", hash = "sha256:f59e533afed0c5b0ac3eba20d2548c4a550336d8282ee69eb07b37ea526ee4e5", size = 207484, upload-time = "2025-05-18T19:03:23.046Z" },
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{ url = "https://files.pythonhosted.org/packages/1b/dd/6cefc6bd68b1c3c979cecfa7029ab582b57690a31cd2f346c4d0ce7951b6/jiter-0.10.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:3bebe0c558e19902c96e99217e0b8e8b17d570906e72ed8a87170bc290b1e978", size = 317473, upload-time = "2025-05-18T19:03:25.942Z" },
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[[package]]
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Reference in New Issue
Block a user