langchain_community.embeddings.openvino
.OpenVINOEmbeddings¶
- class langchain_community.embeddings.openvino.OpenVINOEmbeddings[source]¶
Bases:
BaseModel
,Embeddings
OpenVINO嵌入模型。
- 示例:
from langchain_community.embeddings import OpenVINOEmbeddings model_name = "sentence-transformers/all-mpnet-base-v2" model_kwargs = {'device': 'CPU'} encode_kwargs = {'normalize_embeddings': True} ov = OpenVINOEmbeddings( model_name_or_path=model_name, model_kwargs=model_kwargs, encode_kwargs=encode_kwargs )
初始化sentence_transformer。
- param encode_kwargs: Dict[str, Any] [Optional]¶
调用模型的`encode`方法时要传递的关键字参数。
- param model_kwargs: Dict[str, Any] [Optional]¶
传递给模型的关键字参数。
- param model_name_or_path: str [Required]¶
HuggingFace模型ID。
- param ov_model: Any = None¶
OpenVINO模型对象。
- param show_progress: bool = False¶
是否显示进度条。
- param tokenizer: Any = None¶
嵌入模型的分词器。
- async aembed_documents(texts: List[str]) List[List[float]] ¶
Asynchronous 嵌入搜索文档。
- Parameters
texts (List[str]) –
- Return type
List[List[float]]
- async aembed_query(text: str) List[float] ¶
Asynchronous 嵌入查询文本。
- Parameters
text (str) –
- Return type
List[float]
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model ¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- Parameters
_fields_set (Optional[SetStr]) –
values (Any) –
- Return type
Model
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model ¶
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep (bool) – set to True to make a deep copy of the model
self (Model) –
- Returns
new model instance
- Return type
Model
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny ¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –
by_alias (bool) –
skip_defaults (Optional[bool]) –
exclude_unset (bool) –
exclude_defaults (bool) –
exclude_none (bool) –
- Return type
DictStrAny
- embed_documents(texts: List[str]) List[List[float]] [source]¶
使用HuggingFace transformer模型计算文档嵌入。
- 参数:
texts:要嵌入的文本列表。
- 返回:
嵌入列表,每个文本对应一个嵌入。
- Parameters
texts (List[str]) –
- Return type
List[List[float]]
- embed_query(text: str) List[float] [source]¶
使用HuggingFace transformer模型计算查询嵌入。
- 参数:
text:要嵌入的文本。
- 返回:
文本的嵌入。
- Parameters
text (str) –
- Return type
List[float]
- encode(sentences: Any, batch_size: int = 4, show_progress_bar: bool = False, convert_to_numpy: bool = True, convert_to_tensor: bool = False, mean_pooling: bool = False, normalize_embeddings: bool = True) Any [source]¶
计算句子嵌入。
- Parameters
sentences (Any) – 要嵌入的句子。
batch_size (int) – 用于计算的批处理大小。
show_progress_bar (bool) – 是否输出进度条。
convert_to_numpy (bool) – 输出是否应为numpy向量列表。
convert_to_tensor (bool) – 输出是否应为一个大张量。
mean_pooling (bool) – 是否对返回的向量进行池化。
normalize_embeddings (bool) – 是否对返回的向量进行归一化。
- Returns
默认情况下,形状为[num_inputs,output_dimension]的2维numpy数组。
- Return type
Any
- classmethod from_orm(obj: Any) Model ¶
- Parameters
obj (Any) –
- Return type
Model
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode ¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –
by_alias (bool) –
skip_defaults (Optional[bool]) –
exclude_unset (bool) –
exclude_defaults (bool) –
exclude_none (bool) –
encoder (Optional[Callable[[Any], Any]]) –
models_as_dict (bool) –
dumps_kwargs (Any) –
- Return type
unicode
- classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model ¶
- Parameters
path (Union[str, Path]) –
content_type (unicode) –
encoding (unicode) –
proto (Protocol) –
allow_pickle (bool) –
- Return type
Model
- classmethod parse_obj(obj: Any) Model ¶
- Parameters
obj (Any) –
- Return type
Model
- classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model ¶
- Parameters
b (Union[str, bytes]) –
content_type (unicode) –
encoding (unicode) –
proto (Protocol) –
allow_pickle (bool) –
- Return type
Model
- classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') DictStrAny ¶
- Parameters
by_alias (bool) –
ref_template (unicode) –
- Return type
DictStrAny
- classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) unicode ¶
- Parameters
by_alias (bool) –
ref_template (unicode) –
dumps_kwargs (Any) –
- Return type
unicode
- classmethod update_forward_refs(**localns: Any) None ¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
- Parameters
localns (Any) –
- Return type
None
- classmethod validate(value: Any) Model ¶
- Parameters
value (Any) –
- Return type
Model