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Python: [Breaking] removed pydantic from types and workflows (#917)
* removed pydantic from types * fix test * fix test * fix tests * fix assistants client * Remove Pydantic usage from workflow code. * updated pydantic removal * updated lock and test fixes * fix mypy * updated build system * updated chat client parsing * fix broken test --------- Co-authored-by: Evan Mattson <evan.mattson@microsoft.com>
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co-authored by
Evan Mattson
parent
647db9635a
commit
b4ebafa9b1
@@ -14,7 +14,6 @@ from agent_framework import (
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ChatOptions,
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ChatResponse,
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ChatResponseUpdate,
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ChatToolMode,
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Contents,
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DataContent,
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FunctionApprovalRequestContent,
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@@ -29,6 +28,7 @@ from agent_framework import (
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HostedWebSearchTool,
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Role,
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TextContent,
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ToolMode,
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ToolProtocol,
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UriContent,
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UsageContent,
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@@ -483,7 +483,7 @@ class AzureAIAgentClient(BaseChatClient):
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raw_representation=event_data,
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response_id=response_id,
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role=Role.ASSISTANT,
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ai_model_id=event_data.model,
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model_id=event_data.model,
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)
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case RunStep():
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@@ -628,7 +628,7 @@ class AzureAIAgentClient(BaseChatClient):
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if chat_options is not None:
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run_options["max_completion_tokens"] = chat_options.max_tokens
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run_options["model"] = chat_options.ai_model_id
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run_options["model"] = chat_options.model_id
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run_options["top_p"] = chat_options.top_p
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run_options["temperature"] = chat_options.temperature
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run_options["parallel_tool_calls"] = chat_options.allow_multiple_tool_calls
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@@ -644,7 +644,7 @@ class AzureAIAgentClient(BaseChatClient):
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elif chat_options.tool_choice == "auto":
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run_options["tool_choice"] = AgentsToolChoiceOptionMode.AUTO
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elif (
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isinstance(chat_options.tool_choice, ChatToolMode)
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isinstance(chat_options.tool_choice, ToolMode)
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and chat_options.tool_choice == "required"
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and chat_options.tool_choice.required_function_name is not None
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):
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@@ -864,7 +864,11 @@ class AzureAIAgentClient(BaseChatClient):
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)
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results: list[Any] = []
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for item in result_contents:
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if isinstance(item, BaseModel):
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if isinstance(item, Contents):
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results.append(
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json.dumps(item.to_dict(exclude={"raw_representation", "additional_properties"}))
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)
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elif isinstance(item, BaseModel):
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results.append(item.model_dump_json())
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else:
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results.append(json.dumps(item))
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