vllm.entrypoints.chat_utils ¶
ChatCompletionContentPartParam module-attribute
¶
ChatCompletionContentPartParam: TypeAlias = Union[
ChatCompletionContentPartParam,
ChatCompletionContentPartAudioParam,
ChatCompletionContentPartInputAudioParam,
ChatCompletionContentPartVideoParam,
ChatCompletionContentPartRefusalParam,
CustomChatCompletionContentPILImageParam,
CustomChatCompletionContentSimpleImageParam,
ChatCompletionContentPartImageEmbedsParam,
CustomChatCompletionContentSimpleAudioParam,
CustomChatCompletionContentSimpleVideoParam,
str,
CustomThinkCompletionContentParam,
]
ChatCompletionMessageParam module-attribute
¶
ChatCompletionMessageParam = Union[
ChatCompletionMessageParam,
CustomChatCompletionMessageParam,
Message,
]
ChatTemplateContentFormatOption module-attribute
¶
ChatTemplateContentFormatOption = Literal[
"auto", "string", "openai"
]
MM_PARSER_MAP module-attribute
¶
MM_PARSER_MAP: dict[
str,
Callable[
[ChatCompletionContentPartParam], _ContentPart
],
] = {
"text": lambda part: get("text", None),
"thinking": lambda part: get("thinking", None),
"input_text": lambda part: get("text", None),
"input_image": lambda part: get("image_url", None),
"image_url": lambda part: get("url", None),
"image_embeds": lambda part: get("image_embeds", None),
"image_pil": lambda part: get("image_pil", None),
"audio_url": lambda part: get("url", None),
"input_audio": lambda part: get("input_audio", None),
"refusal": lambda part: get("refusal", None),
"video_url": lambda part: get("url", None),
}
MODALITY_PLACEHOLDERS_MAP module-attribute
¶
MODALITY_PLACEHOLDERS_MAP = {
"image": "<##IMAGE##>",
"audio": "<##AUDIO##>",
"video": "<##VIDEO##>",
}
PART_TYPES_TO_SKIP_NONE_CONTENT module-attribute
¶
_AssistantParser module-attribute
¶
_ChatTemplateContentFormat module-attribute
¶
_ChatTemplateContentFormat = Literal['string', 'openai']
_ContentPart module-attribute
¶
_ImageEmbedsParser module-attribute
¶
_ImageEmbedsParser = partial(
cast, ChatCompletionContentPartImageEmbedsParam
)
_InputAudioParser module-attribute
¶
_PILImageParser module-attribute
¶
_PILImageParser = partial(
cast, CustomChatCompletionContentPILImageParam
)
_PROCESSOR_CHAT_TEMPLATES module-attribute
¶
Used in _try_get_processor_chat_template
to avoid calling cached_get_processor
again if the processor fails to be loaded.
This is needed because lru_cache
does not cache when an exception happens.
_RefusalParser module-attribute
¶
_cached_load_chat_template module-attribute
¶
_cached_load_chat_template = lru_cache(_load_chat_template)
_cached_resolve_chat_template_kwargs module-attribute
¶
_cached_resolve_chat_template_kwargs = lru_cache(
_resolve_chat_template_kwargs
)
AssistantTracker ¶
Bases: Extension
Source code in vllm/entrypoints/chat_utils.py
parse ¶
Source code in vllm/entrypoints/chat_utils.py
AsyncMultiModalContentParser ¶
Bases: BaseMultiModalContentParser
Source code in vllm/entrypoints/chat_utils.py
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|
_connector instance-attribute
¶
_connector = MediaConnector(
media_io_kwargs=media_io_kwargs,
allowed_local_media_path=allowed_local_media_path,
allowed_media_domains=allowed_media_domains,
)
__init__ ¶
__init__(tracker: AsyncMultiModalItemTracker) -> None
Source code in vllm/entrypoints/chat_utils.py
parse_audio ¶
Source code in vllm/entrypoints/chat_utils.py
parse_image ¶
Source code in vllm/entrypoints/chat_utils.py
parse_image_embeds ¶
parse_image_embeds(
image_embeds: Union[str, dict[str, str], None],
uuid: Optional[str] = None,
) -> None
Source code in vllm/entrypoints/chat_utils.py
parse_image_pil ¶
Source code in vllm/entrypoints/chat_utils.py
parse_input_audio ¶
Source code in vllm/entrypoints/chat_utils.py
parse_video ¶
Source code in vllm/entrypoints/chat_utils.py
AsyncMultiModalItemTracker ¶
Bases: BaseMultiModalItemTracker[Awaitable[object]]
Source code in vllm/entrypoints/chat_utils.py
all_mm_data async
¶
all_mm_data() -> Optional[MultiModalDataDict]
Source code in vllm/entrypoints/chat_utils.py
create_parser ¶
create_parser() -> BaseMultiModalContentParser
BaseMultiModalContentParser ¶
Bases: ABC
Source code in vllm/entrypoints/chat_utils.py
__init__ ¶
Source code in vllm/entrypoints/chat_utils.py
_add_placeholder ¶
_add_placeholder(
modality: ModalityStr, placeholder: Optional[str]
)
mm_placeholder_storage ¶
parse_audio abstractmethod
¶
parse_image abstractmethod
¶
parse_image_embeds abstractmethod
¶
parse_image_pil abstractmethod
¶
parse_input_audio abstractmethod
¶
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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_items_by_modality instance-attribute
¶
_uuids_by_modality instance-attribute
¶
__init__ ¶
__init__(
model_config: ModelConfig, tokenizer: AnyTokenizer
)
Source code in vllm/entrypoints/chat_utils.py
add ¶
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
all_mm_uuids ¶
all_mm_uuids() -> Optional[MultiModalUUIDDict]
Source code in vllm/entrypoints/chat_utils.py
create_parser abstractmethod
¶
create_parser() -> BaseMultiModalContentParser
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
ConversationMessage ¶
Bases: TypedDict
Source code in vllm/entrypoints/chat_utils.py
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
¶
content: Union[str, list[ChatCompletionContentPartParam]]
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.
tool_call_id instance-attribute
¶
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
MultiModalContentParser ¶
Bases: BaseMultiModalContentParser
Source code in vllm/entrypoints/chat_utils.py
_connector instance-attribute
¶
_connector = MediaConnector(
media_io_kwargs=media_io_kwargs,
allowed_local_media_path=allowed_local_media_path,
allowed_media_domains=allowed_media_domains,
)
__init__ ¶
__init__(tracker: MultiModalItemTracker) -> None
Source code in vllm/entrypoints/chat_utils.py
parse_audio ¶
Source code in vllm/entrypoints/chat_utils.py
parse_image ¶
Source code in vllm/entrypoints/chat_utils.py
parse_image_embeds ¶
parse_image_embeds(
image_embeds: Union[str, dict[str, str], None],
uuid: Optional[str] = None,
) -> None
Source code in vllm/entrypoints/chat_utils.py
parse_image_pil ¶
parse_input_audio ¶
Source code in vllm/entrypoints/chat_utils.py
parse_video ¶
Source code in vllm/entrypoints/chat_utils.py
MultiModalItemTracker ¶
Bases: BaseMultiModalItemTracker[object]
Source code in vllm/entrypoints/chat_utils.py
all_mm_data ¶
all_mm_data() -> Optional[MultiModalDataDict]
Source code in vllm/entrypoints/chat_utils.py
create_parser ¶
create_parser() -> BaseMultiModalContentParser
PILImage ¶
Bases: BaseModel
A PIL.Image.Image object.
Source code in vllm/entrypoints/chat_utils.py
_detect_content_format cached
¶
_detect_content_format(
chat_template: str,
*,
default: _ChatTemplateContentFormat,
) -> _ChatTemplateContentFormat
Source code in vllm/entrypoints/chat_utils.py
_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
_get_interleaved_text_prompt ¶
Source code in vllm/entrypoints/chat_utils.py
_is_attr_access ¶
Source code in vllm/entrypoints/chat_utils.py
_is_var_access ¶
_is_var_or_elems_access ¶
Source code in vllm/entrypoints/chat_utils.py
_iter_nodes_assign_content_item ¶
Source code in vllm/entrypoints/chat_utils.py
_iter_nodes_assign_messages_item ¶
Source code in vllm/entrypoints/chat_utils.py
_iter_nodes_assign_var_or_elems ¶
_iter_nodes_assign_var_or_elems(root: Node, varname: str)
Source code in vllm/entrypoints/chat_utils.py
_load_chat_template ¶
_load_chat_template(
chat_template: Optional[Union[Path, str]],
*,
is_literal: bool = False,
) -> Optional[str]
Source code in vllm/entrypoints/chat_utils.py
_log_chat_template_content_format cached
¶
_log_chat_template_content_format(
chat_template: Optional[str],
given_format: ChatTemplateContentFormatOption,
detected_format: ChatTemplateContentFormatOption,
)
Source code in vllm/entrypoints/chat_utils.py
_parse_chat_message_content ¶
_parse_chat_message_content(
message: ChatCompletionMessageParam,
mm_tracker: BaseMultiModalItemTracker,
content_format: _ChatTemplateContentFormat,
interleave_strings: bool,
) -> list[ConversationMessage]
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,
) -> Optional[_ContentPart]
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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_parse_chat_message_content_parts ¶
_parse_chat_message_content_parts(
role: str,
parts: Iterable[ChatCompletionContentPartParam],
mm_tracker: BaseMultiModalItemTracker,
*,
wrap_dicts: bool,
interleave_strings: bool,
) -> list[ConversationMessage]
Source code in vllm/entrypoints/chat_utils.py
_postprocess_messages ¶
_postprocess_messages(
messages: list[ConversationMessage],
) -> None
Source code in vllm/entrypoints/chat_utils.py
_resolve_chat_template_content_format ¶
_resolve_chat_template_content_format(
chat_template: Optional[str],
tools: Optional[list[dict[str, Any]]],
tokenizer: AnyTokenizer,
*,
model_config: ModelConfig,
) -> _ChatTemplateContentFormat
Source code in vllm/entrypoints/chat_utils.py
_resolve_chat_template_kwargs ¶
_resolve_chat_template_kwargs(chat_template: str)
Source code in vllm/entrypoints/chat_utils.py
_try_extract_ast ¶
Source code in vllm/entrypoints/chat_utils.py
_try_get_processor_chat_template ¶
_try_get_processor_chat_template(
tokenizer: Union[
PreTrainedTokenizer, PreTrainedTokenizerFast
],
model_config: ModelConfig,
) -> Optional[str]
Source code in vllm/entrypoints/chat_utils.py
apply_hf_chat_template ¶
apply_hf_chat_template(
tokenizer: Union[
PreTrainedTokenizer, PreTrainedTokenizerFast
],
conversation: list[ConversationMessage],
chat_template: Optional[str],
tools: Optional[list[dict[str, Any]]],
*,
model_config: ModelConfig,
tokenize: bool = False,
**kwargs: Any,
) -> str
Source code in vllm/entrypoints/chat_utils.py
apply_mistral_chat_template ¶
apply_mistral_chat_template(
tokenizer: MistralTokenizer,
messages: list[ChatCompletionMessageParam],
chat_template: Optional[str],
tools: Optional[list[dict[str, Any]]],
**kwargs: Any,
) -> list[int]
Source code in vllm/entrypoints/chat_utils.py
get_history_tool_calls_cnt ¶
get_history_tool_calls_cnt(
conversation: list[ConversationMessage],
)
Source code in vllm/entrypoints/chat_utils.py
load_chat_template ¶
parse_chat_messages ¶
parse_chat_messages(
messages: list[ChatCompletionMessageParam],
model_config: ModelConfig,
tokenizer: AnyTokenizer,
content_format: _ChatTemplateContentFormat,
) -> tuple[
list[ConversationMessage],
Optional[MultiModalDataDict],
Optional[MultiModalUUIDDict],
]
Source code in vllm/entrypoints/chat_utils.py
parse_chat_messages_futures ¶
parse_chat_messages_futures(
messages: list[ChatCompletionMessageParam],
model_config: ModelConfig,
tokenizer: AnyTokenizer,
content_format: _ChatTemplateContentFormat,
) -> tuple[
list[ConversationMessage],
Awaitable[Optional[MultiModalDataDict]],
Optional[MultiModalUUIDDict],
]
Source code in vllm/entrypoints/chat_utils.py
resolve_chat_template_content_format ¶
resolve_chat_template_content_format(
chat_template: Optional[str],
tools: Optional[list[dict[str, Any]]],
given_format: ChatTemplateContentFormatOption,
tokenizer: AnyTokenizer,
*,
model_config: ModelConfig,
) -> _ChatTemplateContentFormat
Source code in vllm/entrypoints/chat_utils.py
resolve_chat_template_kwargs ¶
resolve_chat_template_kwargs(
tokenizer: Union[
PreTrainedTokenizer, PreTrainedTokenizerFast
],
chat_template: str,
chat_template_kwargs: dict[str, Any],
) -> dict[str, Any]
Source code in vllm/entrypoints/chat_utils.py
resolve_hf_chat_template ¶
resolve_hf_chat_template(
tokenizer: Union[
PreTrainedTokenizer, PreTrainedTokenizerFast
],
chat_template: Optional[str],
tools: Optional[list[dict[str, Any]]],
*,
model_config: ModelConfig,
) -> Optional[str]
Source code in vllm/entrypoints/chat_utils.py
resolve_mistral_chat_template ¶
Source code in vllm/entrypoints/chat_utils.py
validate_chat_template ¶
Raises if the provided chat template appears invalid.