vllm.entrypoints.chat_utils ¶
BaseMultiModalItemTracker ¶
Tracks multi-modal items in a given request and ensures that the number of multi-modal items in a given request does not exceed the configured maximum per prompt.
Source code in vllm/entrypoints/chat_utils.py
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use_unified_vision_chunk_modality cached property ¶
use_unified_vision_chunk_modality: bool
Check if model uses unified vision_chunk modality for images/videos.
add ¶
add(modality: ModalityStr, item: _T) -> str | None
Add a multi-modal item to the current prompt and returns the placeholder string to use, if any.
An optional uuid can be added which serves as a unique identifier of the media.
Source code in vllm/entrypoints/chat_utils.py
ChatCompletionContentPartAudioEmbedsParam ¶
Bases: TypedDict
Source code in vllm/entrypoints/chat_utils.py
audio_embeds instance-attribute ¶
The audio embeddings. It can be either: - A single base64 string representing a serialized torch tensor. - A dictionary where each value is a base64 string.
ChatCompletionContentPartAudioParam ¶
Bases: TypedDict
Source code in vllm/entrypoints/chat_utils.py
ChatCompletionContentPartImageEmbedsParam ¶
Bases: TypedDict
Source code in vllm/entrypoints/chat_utils.py
image_embeds instance-attribute ¶
The image embeddings. It can be either: - A single base64 string. - A dictionary where each value is a base64 string.
ChatCompletionContentPartVideoParam ¶
Bases: TypedDict
Source code in vllm/entrypoints/chat_utils.py
ChatTemplateResolutionError ¶
Bases: ValueError
Raised when chat template resolution fails.
This is a subclass of ValueError for backward compatibility with existing exception handlers.
ConversationMessage ¶
Bases: TypedDict
Source code in vllm/entrypoints/chat_utils.py
reasoning instance-attribute ¶
reasoning: str | None
The reasoning content for interleaved thinking.
reasoning_content instance-attribute ¶
reasoning_content: str | None
Deprecated: The reasoning content for interleaved thinking.
tool_call_id instance-attribute ¶
tool_call_id: str | None
Tool call that this message is responding to.
CustomChatCompletionContentPILImageParam ¶
Bases: TypedDict
A simpler version of the param that only accepts a PIL image.
Example: { "image_pil": ImageAsset('cherry_blossom').pil_image }
Source code in vllm/entrypoints/chat_utils.py
CustomChatCompletionContentSimpleAudioParam ¶
Bases: TypedDict
A simpler version of the param that only accepts a plain audio_url.
Example: { "audio_url": "https://example.com/audio.mp3" }
Source code in vllm/entrypoints/chat_utils.py
CustomChatCompletionContentSimpleImageParam ¶
Bases: TypedDict
A simpler version of the param that only accepts a plain image_url. This is supported by OpenAI API, although it is not documented.
Example: { "image_url": "https://example.com/image.jpg" }
Source code in vllm/entrypoints/chat_utils.py
CustomChatCompletionContentSimpleVideoParam ¶
Bases: TypedDict
A simpler version of the param that only accepts a plain audio_url.
Example: { "video_url": "https://example.com/video.mp4" }
Source code in vllm/entrypoints/chat_utils.py
CustomChatCompletionMessageParam ¶
Bases: TypedDict
Enables custom roles in the Chat Completion API.
Source code in vllm/entrypoints/chat_utils.py
content instance-attribute ¶
The contents of the message.
name instance-attribute ¶
name: str
An optional name for the participant.
Provides the model information to differentiate between participants of the same role.
reasoning instance-attribute ¶
reasoning: str | None
The reasoning content for interleaved thinking.
tool_call_id instance-attribute ¶
tool_call_id: str | None
Tool call that this message is responding to.
CustomThinkCompletionContentParam ¶
Bases: TypedDict
A Think Completion Content Param that accepts a plain text and a boolean.
Example: { "thinking": "I am thinking about the answer", "closed": True, "type": "thinking" }
Source code in vllm/entrypoints/chat_utils.py
PILImage ¶
_get_full_multimodal_text_prompt ¶
_get_full_multimodal_text_prompt(
placeholder_storage: dict[str, list],
texts: list[str],
interleave_strings: bool,
) -> str
Combine multimodal prompts for a multimodal language model.
Source code in vllm/entrypoints/chat_utils.py
_parse_chat_message_content_mm_part ¶
_parse_chat_message_content_mm_part(
part: ChatCompletionContentPartParam,
) -> tuple[str, _ContentPart]
Parses a given multi-modal content part based on its type.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
part | ChatCompletionContentPartParam | A dict containing the content part, with a potential 'type' field. | required |
Returns:
| Type | Description |
|---|---|
str | A tuple (part_type, content) where: |
_ContentPart |
|
tuple[str, _ContentPart] |
|
Raises:
| Type | Description |
|---|---|
ValueError | If the 'type' field is missing and no direct URL is found. |
Source code in vllm/entrypoints/chat_utils.py
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_parse_chat_message_content_part ¶
_parse_chat_message_content_part(
part: ChatCompletionContentPartParam,
mm_parser: BaseMultiModalContentParser,
*,
wrap_dicts: bool,
interleave_strings: bool,
) -> _ContentPart | None
Parses a single part of a conversation. If wrap_dicts is True, structured dictionary pieces for texts and images will be wrapped in dictionaries, i.e., {"type": "text", "text", ...} and {"type": "image"}, respectively. Otherwise multimodal data will be handled by mm_parser, and texts will be returned as strings to be joined with multimodal placeholders.
Source code in vllm/entrypoints/chat_utils.py
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validate_chat_template ¶
Raises if the provided chat template appears invalid.