langchain_community.embeddings.deepinfra
.DeepInfraEmbeddings¶
- class langchain_community.embeddings.deepinfra.DeepInfraEmbeddings[source]¶
Bases:
BaseModel
,Embeddings
Deep Infra的嵌入推理服务。
要使用,您应该设置环境变量``DEEPINFRA_API_TOKEN``为您的API令牌,或将其作为构造函数的命名参数传递。 有多个可用的嵌入模型,请参见https://deepinfra.com/models?type=embeddings。
- 示例:
from langchain_community.embeddings import DeepInfraEmbeddings deepinfra_emb = DeepInfraEmbeddings( model_id="sentence-transformers/clip-ViT-B-32", deepinfra_api_token="my-api-key" ) r1 = deepinfra_emb.embed_documents( [ "Alpha is the first letter of Greek alphabet", "Beta is the second letter of Greek alphabet", ] ) r2 = deepinfra_emb.embed_query( "What is the second letter of Greek alphabet" )
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- param batch_size: int = 1024¶
嵌入请求的批量大小。
- param deepinfra_api_token: Optional[str] = None¶
Deep Infra的API令牌。如果未提供,则从环境变量’DEEPINFRA_API_TOKEN’中获取令牌。
- param embed_instruction: str = 'passage: '¶
用于嵌入文档的指令。
- param model_id: str = 'sentence-transformers/clip-ViT-B-32'¶
要使用的嵌入模型。
- param model_kwargs: Optional[dict] = None¶
其他模型关键字参数
- param normalize: bool = False¶
是否规范化计算出的嵌入向量
- param query_instruction: str = 'query: '¶
用于嵌入查询的指令。
- 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Deep Infra部署的嵌入模型嵌入文档。 对于较大的批次,输入文本列表被分成较小的批次,以避免超过最大请求大小。
- 参数:
texts:要嵌入的文本列表。
- 返回:
每个文本的嵌入列表。
- Parameters
texts (List[str]) –
- Return type
List[List[float]]
- embed_query(text: str) List[float] [source]¶
使用Deep Infra部署的嵌入模型嵌入一个查询。
- 参数:
text: 要嵌入的文本。
- 返回:
文本的嵌入。
- Parameters
text (str) –
- Return type
List[float]
- 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