o Zh@sddlmZddlZddlmZmZmZmZddlm Z ddl m Z m Z m Z ddlmZmZmZmZeeZGdddee ZdS) ) annotationsN)AnyDictListOptional) Embeddings)convert_to_secret_strget_from_dict_or_envpre_init) BaseModel ConfigDictField SecretStrc@seZdZUdZedddZded< edddZded< d Zd ed < edd Z d ed< dZ ded< dZ ded< ee dZ ded< ee dZded< eddZed,ddZd-d!d"Zd.d&d'Zd-d(d)Zd.d*d+ZdS)/QianfanEmbeddingsEndpointaBaidu Qianfan Embeddings embedding models. Setup: To use, you should have the ``qianfan`` python package installed, and set environment variables ``QIANFAN_AK``, ``QIANFAN_SK``. .. code-block:: bash pip install qianfan export QIANFAN_AK="your-api-key" export QIANFAN_SK="your-secret_key" Instantiate: .. code-block:: python from langchain_community.embeddings import QianfanEmbeddingsEndpoint embeddings = QianfanEmbeddingsEndpoint() Embed: .. code-block:: python # embed the documents vectors = embeddings.embed_documents([text1, text2, ...]) # embed the query vectors = embeddings.embed_query(text) # embed the documents with async vectors = await embeddings.aembed_documents([text1, text2, ...]) # embed the query with async vectors = await embeddings.aembed_query(text) NZapi_key)defaultaliaszOptional[SecretStr] qianfan_akZ secret_key qianfan_skint chunk_sizerz Optional[str]modelstrendpointrclient)default_factoryzDict[str, Any] init_kwargs model_kwargs)Zprotected_namespacesvaluesrreturncCstt|dddd|d<tt|dddd|d<zQddl}i|d id |d i}|ddkr;|d|d <|ddkrK|d|d <|d dur]|d dkr]|d |d <|jdi||d<W|Styttdw)a3 Validate whether qianfan_ak and qianfan_sk in the environment variables or configuration file are available or not. init qianfan embedding client with `ak`, `sk`, `model`, `endpoint` Args: values: a dictionary containing configuration information, must include the fields of qianfan_ak and qianfan_sk Returns: a dictionary containing configuration information. If qianfan_ak and qianfan_sk are not provided in the environment variables or configuration file,the original values will be returned; otherwise, values containing qianfan_ak and qianfan_sk will be returned. Raises: ValueError: qianfan package not found, please install it with `pip install qianfan` rZ QIANFAN_AKrrrZ QIANFAN_SKrNrrZakskrrzGqianfan package not found, please install it with `pip install qianfan`r )rr qianfangetZget_secret_valueZ Embedding ImportError)clsr!r$paramsr r l/var/www/html/lang_env/lib/python3.10/site-packages/langchain_community/embeddings/baidu_qianfan_endpoint.pyvalidate_environmentVsH    z.QianfanEmbeddingsEndpoint.validate_environmenttext List[float]cCs||g}|dSNr)embed_documents)selfr+respr r r) embed_querys z%QianfanEmbeddingsEndpoint.embed_querytexts List[str]List[List[float]]csdfddtdtjD}g}|D]}jjdd|ij}|dd|dDq|S) a_ Embeds a list of text documents using the AutoVOT algorithm. Args: texts (List[str]): A list of text documents to embed. Returns: List[List[float]]: A list of embeddings for each document in the input list. Each embedding is represented as a list of float values. cg|] }||jqSr r.0ir/r2r r) z=QianfanEmbeddingsEndpoint.embed_documents..rr2cSsg|]}|dqS) embeddingr )r8resr r r)r;sdataNr )rangelenrrdorextend)r/r2text_in_chunkslstchunkr0r r:r)r.s z)QianfanEmbeddingsEndpoint.embed_documentscs||gIdH}|dSr-)aembed_documents)r/r+Z embeddingsr r r) aembed_querysz&QianfanEmbeddingsEndpoint.aembed_querycsrfddtdtjD}g}|D] }jjdd|ijIdH}|dD] }||dgq+q|S)Ncr5r r6r7r:r r)r;r<z>QianfanEmbeddingsEndpoint.aembed_documents..rr2r?r=r )r@rArrZadorrC)r/r2rDrErFr0r>r r:r)rGs  z*QianfanEmbeddingsEndpoint.aembed_documents)r!rr"r)r+rr"r,)r2r3r"r4)__name__ __module__ __qualname____doc__r r__annotations__rrrrrdictrrr Z model_configr r*r1r.rHrGr r r r)r s2 #      <  r) __future__rloggingtypingrrrrZlangchain_core.embeddingsrZlangchain_core.utilsrr r Zpydanticr r r r getLoggerrIloggerrr r r r)s