a bg@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<eddZedddddZdddd d!Zd"d#d$d%d&Zdddd'd(Zd"d#d$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_namespacesr)valuesreturncCstt|dddd|d<tt|dddd|d<zddl}i|d id |d i}|ddkrv|d|d <|ddkr|d|d <|d dur|d dkr|d |d <|jfi||d<WntytdYn0|S)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`)rr qianfangetZget_secret_valueZ Embedding ImportError)clsr!r$paramsr r /var/www/html/cobodadashboardai.evdpl.com/venv/lib/python3.9/site-packages/langchain_community/embeddings/baidu_qianfan_endpoint.pyvalidate_environmentVsF     z.QianfanEmbeddingsEndpoint.validate_environmentz List[float])textr"cCs||g}|dSNr)embed_documents)selfr+respr r r) embed_querys z%QianfanEmbeddingsEndpoint.embed_queryz List[str]zList[List[float]])textsr"csdfddtdtjD}g}|D]4}jjfd|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. csg|]}||jqSr r.0ir.r1r r) sz=QianfanEmbeddingsEndpoint.embed_documents..rr1cSsg|] }|dqS) embeddingr )r4resr r r)r7data)rangelenrrdorextend)r.r1text_in_chunkslstchunkr/r r6r)r-s z)QianfanEmbeddingsEndpoint.embed_documentscs||gIdH}|dSr,)aembed_documents)r.r+Z embeddingsr r r) aembed_querysz&QianfanEmbeddingsEndpoint.aembed_querycspfddtdtjD}g}|D]@}jjfd|ijIdH}|dD]}||dgqTq*|S)Ncsg|]}||jqSr r2r3r6r r)r7sz>QianfanEmbeddingsEndpoint.aembed_documents..rr1r;r8)r<r=rrZadorr?)r.r1r@rArBr/r9r r6r)rCs  z*QianfanEmbeddingsEndpoint.aembed_documents)__name__ __module__ __qualname____doc__r r__annotations__rrrrrdictrrr Z model_configr r*r0r-rDrCr r r r)r s #    <r) __future__rloggingtypingrrrrZlangchain_core.embeddingsrZlangchain_core.utilsrr r Zpydanticr r r r getLoggerrEloggerrr r r r)s