langchain_community.embeddings.baidu_qianfan_endpoint.QianfanEmbeddingsEndpoint¶
- class langchain_community.embeddings.baidu_qianfan_endpoint.QianfanEmbeddingsEndpoint[source]¶
Bases:
BaseModel,Embeddings百度千帆嵌入 嵌入模型。
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 chunk_size: int = 16¶
多个文本输入时的块大小
- param client: Any = None¶
千帆客户端
- param endpoint: str = ''¶
Qianfan嵌入的端点，如果使用自定义模型则需要。
- param init_kwargs: Dict[str, Any] [Optional]¶
初始化qianfan客户端的kwargs，例如`query_per_second`，它与qianfan资源对象相关联，用于限制QPS。
- param model: str = 'Embedding-V1'¶
模型名称 您可以从 https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Nlks5zkzu 获取
目前，我们支持 Embedding-V1 和 - Embedding-V1 （默认模型） - bge-large-en - bge-large-zh
预设模型将映射到一个端点。 如果设置了 endpoint，则 model 将被忽略。
- param model_kwargs: Dict[str, Any] [Optional]¶
使用`do`时调用模型的额外参数。
- param qianfan_ak: Optional[str] = None¶
前方应用程序 API 密钥
- param qianfan_sk: Optional[str] = None¶
Qianfan应用程序的秘钥
- async aembed_documents(texts: List[str]) List[List[float]][source]¶
Asynchronous 嵌入搜索文档。
- Parameters
texts (List[str]) –
- Return type
List[List[float]]
- async aembed_query(text: str) List[float][source]¶
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AutoVOT算法嵌入文本文档列表。
- 参数：
texts（List[str]）：要嵌入的文本文档列表。
- 返回：
- List[List[float]]：输入列表中每个文档的嵌入列表。
每个嵌入都表示为一组浮点值。
- Parameters
texts (List[str]) –
- Return type
List[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