chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
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# Copyright (c) Microsoft. All rights reserved.
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import logging
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from enum import Enum
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from html import unescape
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from typing import Annotated, Any, ClassVar, Literal, overload
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from xml.etree.ElementTree import Element # nosec
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from defusedxml import ElementTree
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from pydantic import Field
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from semantic_kernel.contents.annotation_content import AnnotationContent
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from semantic_kernel.contents.audio_content import AudioContent
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from semantic_kernel.contents.binary_content import BinaryContent
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from semantic_kernel.contents.const import (
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ANNOTATION_CONTENT_TAG,
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CHAT_MESSAGE_CONTENT_TAG,
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DISCRIMINATOR_FIELD,
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FILE_REFERENCE_CONTENT_TAG,
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FUNCTION_CALL_CONTENT_TAG,
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FUNCTION_RESULT_CONTENT_TAG,
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IMAGE_CONTENT_TAG,
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REASONING_CONTENT_TAG,
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STREAMING_ANNOTATION_CONTENT_TAG,
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STREAMING_FILE_REFERENCE_CONTENT_TAG,
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TEXT_CONTENT_TAG,
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ContentTypes,
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)
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from semantic_kernel.contents.file_reference_content import FileReferenceContent
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from semantic_kernel.contents.function_call_content import FunctionCallContent
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from semantic_kernel.contents.function_result_content import FunctionResultContent
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from semantic_kernel.contents.image_content import ImageContent
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from semantic_kernel.contents.kernel_content import KernelContent
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from semantic_kernel.contents.reasoning_content import ReasoningContent
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from semantic_kernel.contents.streaming_annotation_content import StreamingAnnotationContent
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from semantic_kernel.contents.streaming_file_reference_content import StreamingFileReferenceContent
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from semantic_kernel.contents.text_content import TextContent
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from semantic_kernel.contents.utils.author_role import AuthorRole
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from semantic_kernel.contents.utils.finish_reason import FinishReason
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from semantic_kernel.contents.utils.hashing import make_hashable
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from semantic_kernel.contents.utils.status import Status
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from semantic_kernel.exceptions.content_exceptions import ContentInitializationError
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TAG_CONTENT_MAP = {
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ANNOTATION_CONTENT_TAG: AnnotationContent,
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TEXT_CONTENT_TAG: TextContent,
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FILE_REFERENCE_CONTENT_TAG: FileReferenceContent,
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FUNCTION_CALL_CONTENT_TAG: FunctionCallContent,
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FUNCTION_RESULT_CONTENT_TAG: FunctionResultContent,
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IMAGE_CONTENT_TAG: ImageContent,
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REASONING_CONTENT_TAG: ReasoningContent,
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STREAMING_FILE_REFERENCE_CONTENT_TAG: StreamingFileReferenceContent,
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STREAMING_ANNOTATION_CONTENT_TAG: StreamingAnnotationContent,
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}
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CMC_ITEM_TYPES = Annotated[
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AnnotationContent
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| BinaryContent
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| ImageContent
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| TextContent
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| FunctionResultContent
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| FunctionCallContent
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| FileReferenceContent
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| ReasoningContent
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| StreamingAnnotationContent
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| StreamingFileReferenceContent
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| AudioContent,
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Field(discriminator=DISCRIMINATOR_FIELD),
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]
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logger = logging.getLogger(__name__)
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class ChatMessageContent(KernelContent):
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"""This is the class for chat message response content.
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All Chat Completion Services should return an instance of this class as response.
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Or they can implement their own subclass of this class and return an instance.
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Args:
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inner_content: Optional[Any] - The inner content of the response,
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this should hold all the information from the response so even
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when not creating a subclass a developer can leverage the full thing.
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ai_model_id: Optional[str] - The id of the AI model that generated this response.
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metadata: Dict[str, Any] - Any metadata that should be attached to the response.
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role: ChatRole - The role of the chat message.
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content: Optional[str] - The text of the response.
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encoding: Optional[str] - The encoding of the text.
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Methods:
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__str__: Returns the content of the response.
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"""
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content_type: Literal[ContentTypes.CHAT_MESSAGE_CONTENT] = Field(default=CHAT_MESSAGE_CONTENT_TAG, init=False) # type: ignore
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tag: ClassVar[str] = CHAT_MESSAGE_CONTENT_TAG
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role: AuthorRole
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name: str | None = None
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items: list[CMC_ITEM_TYPES] = Field(default_factory=list)
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encoding: str | None = None
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finish_reason: FinishReason | None = None
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status: Status | None = None
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@overload
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def __init__(
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self,
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role: AuthorRole,
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items: list[CMC_ITEM_TYPES],
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name: str | None = None,
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inner_content: Any | None = None,
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encoding: str | None = None,
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finish_reason: FinishReason | None = None,
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status: Status | None = None,
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ai_model_id: str | None = None,
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metadata: dict[str, Any] | None = None,
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**kwargs: Any,
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) -> None: ...
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@overload
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def __init__(
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self,
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role: AuthorRole,
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content: str,
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name: str | None = None,
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inner_content: Any | None = None,
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encoding: str | None = None,
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finish_reason: FinishReason | None = None,
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status: Status | None = None,
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ai_model_id: str | None = None,
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metadata: dict[str, Any] | None = None,
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**kwargs: Any,
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) -> None: ...
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def __init__( # type: ignore
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self,
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role: AuthorRole,
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items: list[CMC_ITEM_TYPES] | None = None,
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content: str | None = None,
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inner_content: Any | None = None,
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name: str | None = None,
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encoding: str | None = None,
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finish_reason: FinishReason | None = None,
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status: Status | None = None,
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ai_model_id: str | None = None,
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metadata: dict[str, Any] | None = None,
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**kwargs: Any,
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):
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"""Create a ChatMessageContent instance.
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Args:
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role: AuthorRole - The role of the chat message.
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items: list[TextContent, StreamingTextContent, FunctionCallContent, FunctionResultContent, ImageContent]
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- The content.
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content: str - The text of the response.
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inner_content: Optional[Any] - The inner content of the response,
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this should hold all the information from the response so even
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when not creating a subclass a developer can leverage the full thing.
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name: Optional[str] - The name of the response.
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encoding: Optional[str] - The encoding of the text.
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finish_reason: Optional[FinishReason] - The reason the response was finished.
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status: Optional[Status] - The status of the response for the Responses API.
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ai_model_id: Optional[str] - The id of the AI model that generated this response.
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metadata: Dict[str, Any] - Any metadata that should be attached to the response.
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**kwargs: Any - Any additional fields to set on the instance.
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"""
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kwargs["role"] = role
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if encoding:
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kwargs["encoding"] = encoding
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if finish_reason:
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kwargs["finish_reason"] = finish_reason
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if status:
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kwargs["status"] = status
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if name:
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kwargs["name"] = name
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if content:
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item = TextContent(
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ai_model_id=ai_model_id,
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inner_content=inner_content,
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metadata=metadata or {},
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text=content,
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encoding=encoding,
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)
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if items:
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items.append(item)
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else:
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items = [item]
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if items:
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kwargs["items"] = items
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if inner_content:
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kwargs["inner_content"] = inner_content
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if metadata:
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kwargs["metadata"] = metadata
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if ai_model_id:
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kwargs["ai_model_id"] = ai_model_id
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super().__init__(
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**kwargs,
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)
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@property
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def content(self) -> str:
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"""Get the content of the response, will find the first TextContent's text."""
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for item in self.items:
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if isinstance(item, TextContent):
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return item.text
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return ""
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@content.setter
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def content(self, value: str):
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"""Set the content of the response."""
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if not value:
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logger.warning(
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"Setting empty content on ChatMessageContent does not work, "
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"you can do this through the underlying items if needed, ignoring."
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)
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return
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for item in self.items:
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if isinstance(item, TextContent):
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item.text = value
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item.encoding = self.encoding
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return
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self.items.append(
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TextContent(
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ai_model_id=self.ai_model_id,
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inner_content=self.inner_content,
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metadata=self.metadata,
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text=value,
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encoding=self.encoding,
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)
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)
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def __str__(self) -> str:
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"""Get the content of the response as a string."""
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return self.content or ""
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def to_element(self) -> "Element":
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"""Convert the ChatMessageContent to an XML Element.
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Args:
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root_key: str - The key to use for the root of the XML Element.
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Returns:
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Element - The XML Element representing the ChatMessageContent.
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"""
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root = Element(self.tag)
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for field in self.model_fields_set:
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if field not in ["role", "name", "encoding", "finish_reason", "ai_model_id"]:
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continue
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value = getattr(self, field)
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if isinstance(value, Enum):
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value = value.value
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root.set(field, value)
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for index, item in enumerate(self.items):
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root.insert(index, item.to_element())
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return root
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@classmethod
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def from_element(cls, element: Element) -> "ChatMessageContent":
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"""Create a new instance of ChatMessageContent from an XML element.
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Args:
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element: Element - The XML Element to create the ChatMessageContent from.
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Returns:
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ChatMessageContent - The new instance of ChatMessageContent or a subclass.
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"""
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if element.tag != cls.tag:
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raise ContentInitializationError(f"Element tag is not {cls.tag}") # pragma: no cover
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kwargs: dict[str, Any] = {key: value for key, value in element.items()}
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items: list[KernelContent] = []
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if element.text:
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items.append(TextContent(text=unescape(element.text)))
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for child in element:
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if child.tag not in TAG_CONTENT_MAP:
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logger.warning('Unknown tag "%s" in ChatMessageContent, treating as text', child.tag)
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text = ElementTree.tostring(child, encoding="unicode", short_empty_elements=False)
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items.append(TextContent(text=unescape(text) or ""))
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else:
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items.append(TAG_CONTENT_MAP[child.tag].from_element(child)) # type: ignore
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if len(items) == 1 and isinstance(items[0], TextContent):
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kwargs["content"] = items[0].text
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elif all(isinstance(item, TextContent) for item in items):
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kwargs["content"] = "".join(item.text for item in items) # type: ignore
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else:
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kwargs["items"] = items
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if "choice_index" in kwargs and cls is ChatMessageContent:
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logger.info(
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"Seems like you are trying to create a StreamingChatMessageContent, "
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"use StreamingChatMessageContent.from_element instead, ignoring that field "
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"and creating a ChatMessageContent instance."
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)
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kwargs.pop("choice_index")
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return cls(**kwargs)
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def to_prompt(self) -> str:
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"""Convert the ChatMessageContent to a prompt.
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Returns:
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str - The prompt from the ChatMessageContent.
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"""
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root = self.to_element()
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return ElementTree.tostring(root, encoding=self.encoding or "unicode", short_empty_elements=False)
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def to_dict(self, role_key: str = "role", content_key: str = "content") -> dict[str, Any]:
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"""Serialize the ChatMessageContent to a dictionary.
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Returns:
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dict - The dictionary representing the ChatMessageContent.
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"""
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ret: dict[str, Any] = {
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role_key: self.role.value,
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}
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if self.role == AuthorRole.ASSISTANT and any(isinstance(item, FunctionCallContent) for item in self.items):
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ret["tool_calls"] = [item.to_dict() for item in self.items if isinstance(item, FunctionCallContent)]
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else:
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ret[content_key] = self._parse_items()
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if self.role == AuthorRole.TOOL:
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assert isinstance(self.items[0], FunctionResultContent) # nosec
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ret["tool_call_id"] = self.items[0].id or ""
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if self.role != AuthorRole.TOOL and self.name:
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ret["name"] = self.name
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return ret
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def _parse_items(self) -> str | list[dict[str, Any]]:
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"""Parse the items of the ChatMessageContent.
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Returns:
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str | list of dicts - The parsed items.
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"""
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if len(self.items) == 1 and isinstance(self.items[0], TextContent):
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return self.items[0].text
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if len(self.items) == 1 and isinstance(self.items[0], FunctionResultContent):
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return str(self.items[0].result)
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return [item.to_dict() for item in self.items]
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def __hash__(self) -> int:
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"""Return the hash of the chat message content."""
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hashable_items = [make_hashable(item) for item in self.items] if self.items else []
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return hash((self.tag, self.role, self.content, self.encoding, self.finish_reason, *hashable_items))
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