openvino_genai.VLMPipeline#

class openvino_genai.VLMPipeline#

Bases: pybind11_object

This class is used for generation with VLMs

__init__(self: openvino_genai.py_openvino_genai.VLMPipeline, models_path: os.PathLike, device: str, **kwargs) → None#
device on which inference will be done

VLMPipeline class constructor. models_path (str): Path to the folder with exported model files. device (str): Device to run the model on (e.g., CPU, GPU). Default is ‘CPU’. kwargs: Device properties

Methods

__delattr__(name, /)

Implement delattr(self, name).

__dir__()

Default dir() implementation.

__eq__(value, /)

Return self==value.

__format__(format_spec, /)

Default object formatter.

__ge__(value, /)

Return self>=value.

__getattribute__(name, /)

Return getattr(self, name).

__gt__(value, /)

Return self>value.

__hash__()

Return hash(self).

__init__(self, models_path, device, **kwargs)

device on which inference will be done

__init_subclass__

This method is called when a class is subclassed.

__le__(value, /)

Return self<=value.

__lt__(value, /)

Return self<value.

__ne__(value, /)

Return self!=value.

__new__(**kwargs)

__reduce__()

Helper for pickle.

__reduce_ex__(protocol, /)

Helper for pickle.

__repr__()

Return repr(self).

__setattr__(name, value, /)

Implement setattr(self, name, value).

__sizeof__()

Size of object in memory, in bytes.

__str__()

Return str(self).

__subclasshook__

Abstract classes can override this to customize issubclass().

finish_chat(self)

generate(*args, **kwargs)

Overloaded function.

get_generation_config(self)

get_tokenizer(self)

set_chat_template(self, arg0)

set_generation_config(self, arg0)

start_chat(self[, system_message])

__class__#

alias of pybind11_type

__delattr__(name, /)#

Implement delattr(self, name).

__dir__()#

Default dir() implementation.

__eq__(value, /)#

Return self==value.

__format__(format_spec, /)#

Default object formatter.

__ge__(value, /)#

Return self>=value.

__getattribute__(name, /)#

Return getattr(self, name).

__gt__(value, /)#

Return self>value.

__hash__()#

Return hash(self).

__init__(self: openvino_genai.py_openvino_genai.VLMPipeline, models_path: os.PathLike, device: str, **kwargs) → None#
device on which inference will be done

VLMPipeline class constructor. models_path (str): Path to the folder with exported model files. device (str): Device to run the model on (e.g., CPU, GPU). Default is ‘CPU’. kwargs: Device properties

__init_subclass__()#

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__(value, /)#

Return self<=value.

__lt__(value, /)#

Return self<value.

__ne__(value, /)#

Return self!=value.

__new__(**kwargs)#
__reduce__()#

Helper for pickle.

__reduce_ex__(protocol, /)#

Helper for pickle.

__repr__()#

Return repr(self).

__setattr__(name, value, /)#

Implement setattr(self, name, value).

__sizeof__()#

Size of object in memory, in bytes.

__str__()#

Return str(self).

__subclasshook__()#

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

finish_chat(self: openvino_genai.py_openvino_genai.VLMPipeline) → None#
generate(*args, **kwargs)#

Overloaded function.

  1. generate(self: openvino_genai.py_openvino_genai.VLMPipeline, prompt: str, images: list[openvino._pyopenvino.Tensor], generation_config: openvino_genai.py_openvino_genai.GenerationConfig = None, streamer: Union[Callable[[str], bool], openvino_genai.py_openvino_genai.StreamerBase, None] = None, **kwargs) -> object

    Generates sequences for VLMs.

    param prompt:

    input prompt

    type prompt:

    str

    param images:

    list of images

    type inputs:

    List[ov.Tensor]

    param generation_config:

    generation_config

    type generation_config:

    GenerationConfig or a Dict

    param streamer:

    streamer either as a lambda with a boolean returning flag whether generation should be stopped

    :type : Callable[[str], bool], ov.genai.StreamerBase

    param kwargs:

    arbitrary keyword arguments with keys corresponding to GenerationConfig fields.

    :type : Dict

    return:

    return results in decoded form

    rtype:

    DecodedResults

  2. generate(self: openvino_genai.py_openvino_genai.VLMPipeline, prompt: str, **kwargs) -> object

    Generates sequences for VLMs.

    param prompt:

    input prompt

    type prompt:

    str

    param kwargs:

    arbitrary keyword arguments with keys corresponding to generate params.

    Expected parameters list: image: ov.Tensor - input image, images: List[ov.Tensor] - input images, generation_config: GenerationConfig, streamer: Callable[[str], bool], ov.genai.StreamerBase - streamer either as a lambda with a boolean returning flag whether generation should be stopped

    return:

    return results in decoded form

    rtype:

    DecodedResults

get_generation_config(self: openvino_genai.py_openvino_genai.VLMPipeline) → openvino_genai.py_openvino_genai.GenerationConfig#
get_tokenizer(self: openvino_genai.py_openvino_genai.VLMPipeline) → openvino_genai.py_openvino_genai.Tokenizer#
set_chat_template(self: openvino_genai.py_openvino_genai.VLMPipeline, arg0: str) → None#
set_generation_config(self: openvino_genai.py_openvino_genai.VLMPipeline, arg0: openvino_genai.py_openvino_genai.GenerationConfig) → None#
start_chat(self: openvino_genai.py_openvino_genai.VLMPipeline, system_message: str = '') → None#