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025490a1bd
This PR refactored `AgentEvent` and `ChatMessage` union types to abstract base classes. This allows for user-defined message types that subclass one of the base classes to be used in AgentChat. To support a unified interface for working with the messages, the base classes added abstract methods for: - Convert content to string - Convert content to a `UserMessage` for model client - Convert content for rendering in console. - Dump into a dictionary - Load and create a new instance from a dictionary This way, all agents such as `AssistantAgent` and `SocietyOfMindAgent` can utilize the unified interface to work with any built-in and user-defined message type. This PR also introduces a new message type, `StructuredMessage` for AgentChat (Resolves #5131), which is a generic type that requires a user-specified content type. You can create a `StructuredMessage` as follow: ```python class MessageType(BaseModel): data: str references: List[str] message = StructuredMessage[MessageType](content=MessageType(data="data", references=["a", "b"]), source="user") # message.content is of type `MessageType`. ``` This PR addresses the receving side of this message type. To produce this message type from `AssistantAgent`, the work continue in #5934. Added unit tests to verify this message type works with agents and teams.
45 lines
1.5 KiB
Python
45 lines
1.5 KiB
Python
from typing import List, Union
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from autogen_core import FunctionCall, Image
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from autogen_core.models import FunctionExecutionResult, LLMMessage, UserMessage
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from pydantic import BaseModel
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# Type aliases for convenience
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_StructuredContent = BaseModel
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_UserContent = Union[str, List[Union[str, Image]]]
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_AssistantContent = Union[str, List[FunctionCall]]
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_FunctionExecutionContent = List[FunctionExecutionResult]
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_SystemContent = str
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def content_to_str(
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content: _UserContent | _AssistantContent | _FunctionExecutionContent | _SystemContent | _StructuredContent,
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) -> str:
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"""Convert the content of an LLMMessage to a string."""
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if isinstance(content, str):
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return content
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elif isinstance(content, BaseModel):
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return content.model_dump_json()
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else:
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result: List[str] = []
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for c in content:
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if isinstance(c, str):
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result.append(c)
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elif isinstance(c, Image):
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result.append("<image>")
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else:
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result.append(str(c))
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return "\n".join(result)
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def remove_images(messages: List[LLMMessage]) -> List[LLMMessage]:
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"""Remove images from a list of LLMMessages"""
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str_messages: List[LLMMessage] = []
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for message in messages:
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if isinstance(message, UserMessage) and isinstance(message.content, list):
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str_messages.append(UserMessage(content=content_to_str(message.content), source=message.source))
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else:
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str_messages.append(message)
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return str_messages
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