U h5@svddlmZmZmZmZddlmZddlmZm Z ddl m Z ddl m Z dgZGdddeeZGdd d Zd S) )AnyDictListOptional) Embeddings) BaseModelroot_validatorget_from_dict_or_env)parseGradientEmbeddingsc@seZdZUdZeed<dZeeed<dZeeed<dZ eed<dZ eeed<dZ e ed <Gd d d Z ed d eedddZedd deedddZeeeeedddZeeeeedddZeeedddZeeedddZdS)r aGradient.ai Embedding models. GradientLLM is a class to interact with Embedding Models on gradient.ai To use, set the environment variable ``GRADIENT_ACCESS_TOKEN`` with your API token and ``GRADIENT_WORKSPACE_ID`` for your gradient workspace, or alternatively provide them as keywords to the constructor of this class. Example: .. code-block:: python from langchain_community.embeddings import GradientEmbeddings GradientEmbeddings( model="bge-large", gradient_workspace_id="12345614fc0_workspace", gradient_access_token="gradientai-access_token", ) modelNgradient_workspace_idgradient_access_tokenhttps://api.gradient.ai/apigradient_api_urlquery_prompt_for_retrievalclientc@seZdZdZdS)zGradientEmbeddings.ConfigZforbidN)__name__ __module__ __qualname__extrarrN/tmp/pip-unpacked-wheel-9gdii04g/langchain_community/embeddings/gradient_ai.pyConfig5srT)pre)valuesreturncCs8t|dd|d<t|dd|d<t|dddd|d<|S) z?Validate that api key and python package exists in environment.rZGRADIENT_ACCESS_TOKENrZGRADIENT_WORKSPACE_IDrZGRADIENT_API_URLr)defaultr )clsrrrrvalidate_environment8s" z'GradientEmbeddings.validate_environmentF)rZskip_on_failurecCsxz ddl}Wntk r(tdYnXt|jtdkrDtd|j|d|d|dd}|j|dd |d <|S) NrzAGradientEmbeddings requires `pip install -U "gradientai>=1.4.0"`.z1.4.0rrr)Z access_tokenZ workspace_idhostr )Zslugr) gradientai ImportErrorr __version__ZGradientZget_embeddings_model)rrr"Zgradientrrr post_initKs"  zGradientEmbeddings.post_init)textsrcCs,dd|D}|jj|dj}dd|DS)zCall out to Gradient's embedding endpoint. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. cSsg|] }d|iqSinputr.0textrrr jsz6GradientEmbeddings.embed_documents..inputscSsg|] }|jqSrZ embeddingr*errrr,ns)rembed embeddingsselfr&r.resultrrrembed_documentsas z"GradientEmbeddings.embed_documentscs2dd|D}|jj|dIdHj}dd|DS)zAsync call out to Gradient's embedding endpoint. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. cSsg|] }d|iqSr'rr)rrrr,ysz7GradientEmbeddings.aembed_documents..r-NcSsg|] }|jqSrr/r0rrrr,}s)rZaembedr3r4rrraembed_documentsps z#GradientEmbeddings.aembed_documents)r+rcCs*|jr|jd|n|}||gdS)zCall out to Gradient's embedding endpoint. Args: text: The text to embed. Returns: Embeddings for the text.  r)rr7)r5r+queryrrr embed_querys zGradientEmbeddings.embed_querycs4|jr|jd|n|}||gIdH}|dS)zAsync call out to Gradient's embedding endpoint. Args: text: The text to embed. Returns: Embeddings for the text. r9Nr)rr8)r5r+r:r3rrr aembed_querys zGradientEmbeddings.aembed_query)rrr__doc__str__annotations__rrrrrrrrrrr r%rfloatr7r8r;r<rrrrr s    c@seZdZdZddddZdS) TinyAsyncGradientEmbeddingClientzDeprecated, TinyAsyncGradientEmbeddingClient was removed. This class is just for backwards compatibility with older versions of langchain_community. It might be entirely removed in the future. N)rcOs tddS)Nz8Deprecated,TinyAsyncGradientEmbeddingClient was removed.) ValueError)r5argskwargsrrr__init__sz)TinyAsyncGradientEmbeddingClient.__init__)rrrr=rErrrrrAsrAN)typingrrrrZlangchain_core.embeddingsrZlangchain_core.pydantic_v1rrZlangchain_core.utilsr Zpackaging.versionr __all__r rArrrrs