mirror of
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Python: Azure chat client (#185)
* updated openai, fcc works, with sample * reduced files in openai * Add azure chat client * fix tests * Update python/packages/main/tests/unit/test_openai_chat_completion_base.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update python/packages/azure/agent_framework/azure/__init__.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update python/packages/azure/agent_framework/azure/_azure_openai_settings.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * PR comments * fix bad merge * disable tests for now * actually disable tests for azure * fix tests, align test files with merge changes * update code for new project structure * PR comments * add streaming integration tests. Fix flakiness --------- Co-authored-by: eavanvalkenburg <github@vanvalkenburg.eu> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
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@@ -10,7 +10,6 @@ except importlib.metadata.PackageNotFoundError:
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__version__ = "0.0.0" # Fallback for development mode
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_IMPORTS = {
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"get_logger": "._logging",
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"AFBaseModel": "._pydantic",
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"AFBaseSettings": "._pydantic",
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"Agent": "._agents",
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@@ -18,39 +17,41 @@ _IMPORTS = {
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"AgentRunResponseUpdate": "._types",
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"AgentThread": "._agents",
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"AITool": "._tools",
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"ai_function": "._tools",
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"AIFunction": "._tools",
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"AIContent": "._types",
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"AIContents": "._types",
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"ChatClient": "._clients",
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"ChatClientAgent": "._agents",
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"ChatClientAgentThread": "._agents",
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"ChatClientAgentThreadType": "._agents",
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"ChatClientBase": "._clients",
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"ChatFinishReason": "._types",
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"ChatMessage": "._types",
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"ChatOptions": "._types",
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"ChatResponse": "._types",
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"ChatResponseUpdate": "._types",
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"ChatRole": "._types",
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"ChatToolMode": "._types",
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"DataContent": "._types",
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"EmbeddingGenerator": "._clients",
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"ErrorContent": "._types",
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"FunctionCallContent": "._types",
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"FunctionResultContent": "._types",
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"GeneratedEmbeddings": "._types",
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"HttpsUrl": "._pydantic",
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"InputGuardrail": ".guard_rails",
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"OutputGuardrail": ".guard_rails",
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"SpeechToTextOptions": "._types",
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"StructuredResponse": "._types",
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"TextContent": "._types",
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"TextReasoningContent": "._types",
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"DataContent": "._types",
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"TextToSpeechOptions": "._types",
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"UriContent": "._types",
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"UsageContent": "._types",
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"UsageDetails": "._types",
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"FunctionCallContent": "._types",
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"FunctionResultContent": "._types",
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"ChatFinishReason": "._types",
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"ChatMessage": "._types",
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"ChatResponse": "._types",
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"StructuredResponse": "._types",
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"ChatResponseUpdate": "._types",
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"ChatRole": "._types",
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"ErrorContent": "._types",
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"GeneratedEmbeddings": "._types",
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"ChatOptions": "._types",
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"ChatToolMode": "._types",
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"ChatClient": "._clients",
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"ChatClientBase": "._clients",
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"ai_function": "._tools",
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"get_logger": "._logging",
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"use_tool_calling": "._clients",
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"EmbeddingGenerator": "._clients",
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"InputGuardrail": ".guard_rails",
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"OutputGuardrail": ".guard_rails",
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"TextToSpeechOptions": "._types",
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"SpeechToTextOptions": "._types",
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}
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@@ -4,7 +4,7 @@ from . import __version__ # type: ignore[attr-defined]
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from ._agents import Agent, AgentThread, ChatClientAgent, ChatClientAgentThread, ChatClientAgentThreadType
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from ._clients import ChatClient, ChatClientBase, EmbeddingGenerator, use_tool_calling
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from ._logging import get_logger
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from ._pydantic import AFBaseModel, AFBaseSettings
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from ._pydantic import AFBaseModel, AFBaseSettings, HttpsUrl
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from ._tools import AIFunction, AITool, ai_function
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from ._types import (
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AgentRunResponse,
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@@ -63,6 +63,7 @@ __all__ = [
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"FunctionCallContent",
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"FunctionResultContent",
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"GeneratedEmbeddings",
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"HttpsUrl",
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"InputGuardrail",
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"OutputGuardrail",
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"SpeechToTextOptions",
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@@ -112,7 +112,14 @@ def _tool_call_non_streaming(func: TInnerGetResponse) -> TInnerGetResponse:
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for attempt_idx in range(getattr(self, "__maximum_iterations_per_request", 10)):
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response = await func(self, messages=messages, chat_options=chat_options)
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# if there are function calls, we will handle them first
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function_calls = [it for it in response.messages[0].contents if isinstance(it, FunctionCallContent)]
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function_results = {
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it.call_id for it in response.messages[0].contents if isinstance(it, FunctionResultContent)
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}
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function_calls = [
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it
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for it in response.messages[0].contents
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if isinstance(it, FunctionCallContent) and it.call_id not in function_results
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]
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if function_calls:
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# Run all function calls concurrently
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results = await asyncio.gather(*[
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@@ -1,11 +1,14 @@
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# Copyright (c) Microsoft. All rights reserved.
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from typing import Any, ClassVar, TypeVar
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from typing import Annotated, Any, ClassVar, TypeVar
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from pydantic import BaseModel, ConfigDict, Field
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from pydantic import BaseModel, ConfigDict, Field, UrlConstraints
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from pydantic.networks import AnyUrl
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from pydantic_settings import BaseSettings, SettingsConfigDict
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HttpsUrl = Annotated[AnyUrl, UrlConstraints(max_length=2083, allowed_schemes=["https"])]
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class AFBaseModel(BaseModel):
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"""Base class for all pydantic models in the Agent Framework."""
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@@ -16,7 +16,16 @@ from collections.abc import (
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)
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from typing import Annotated, Any, ClassVar, Generic, Literal, TypeVar, overload
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from pydantic import BaseModel, ConfigDict, Field, PrivateAttr, ValidationError, field_validator, model_validator
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from pydantic import (
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BaseModel,
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ConfigDict,
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Field,
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PrivateAttr,
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ValidationError,
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field_validator,
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model_serializer,
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model_validator,
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)
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from ._pydantic import AFBaseModel
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from ._tools import AITool, ai_function
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@@ -1398,6 +1407,11 @@ class ChatToolMode(AFBaseModel):
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return self.mode == other.mode and self.required_function_name == other.required_function_name
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return False
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@model_serializer
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def serialize_model(self) -> str:
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"""Serializes the ChatToolMode to just the mode string."""
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return self.mode
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ChatToolMode.AUTO = ChatToolMode(mode="auto") # type: ignore[assignment]
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ChatToolMode.REQUIRED_ANY = ChatToolMode(mode="required") # type: ignore[assignment]
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@@ -1496,10 +1510,13 @@ class ChatOptions(AFBaseModel):
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Dictionary of settings for provider.
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"""
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default_exclude = {"additional_properties"}
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# No tool choice if no tools are defined
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if self.tools is None or len(self.tools) == 0:
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default_exclude.add("tool_choice")
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merged_exclude = default_exclude if exclude is None else default_exclude | set(exclude)
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settings = self.model_dump(exclude_none=True, by_alias=by_alias, exclude=merged_exclude)
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settings = {k: v for k, v in settings.items() if v and not isinstance(v, dict)}
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settings = {k: v for k, v in settings.items() if v}
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settings.update(self.additional_properties)
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for key in merged_exclude:
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settings.pop(key, None)
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@@ -7,6 +7,8 @@ PACKAGE_EXTRA = "azure"
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_IMPORTS = {
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"__version__": "agent_framework_azure",
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"AzureChatClient": "agent_framework_azure",
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"get_entra_auth_token": "agent_framework_azure",
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}
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@@ -46,6 +46,12 @@ class ServiceContentFilterException(ServiceResponseException):
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pass
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class ServiceInvalidAuthError(ServiceException):
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"""An error occurred while authenticating the service."""
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pass
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class ServiceInvalidExecutionSettingsError(ServiceResponseException):
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"""An error occurred while validating the execution settings of the service."""
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@@ -2,9 +2,11 @@
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from ._chat_client import OpenAIChatClient
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from ._shared import OpenAISettings
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from ._shared import OpenAIHandler, OpenAIModelTypes, OpenAISettings
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__all__ = [
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"OpenAIChatClient",
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"OpenAIHandler",
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"OpenAIModelTypes",
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"OpenAISettings",
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]
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@@ -239,11 +239,11 @@ class OpenAIChatClientBase(OpenAIHandler, ChatClientBase):
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function_call = self._openai_content_parser(content)
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if "tool_calls" not in args:
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args["tool_calls"] = []
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args["tool_calls"].append(function_call)
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args["tool_calls"].append(function_call) # type: ignore
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case _:
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if "content" not in args:
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args["content"] = []
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args["content"].append(self._openai_content_parser(content))
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args["content"].append(self._openai_content_parser(content)) # type: ignore
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if "content" in args or "tool_calls" in args:
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all_messages.append(args)
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return all_messages
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