o ZhA@sddlmZmZmZmZddlmZddlmZddl m Z ddl m Z m Z mZddlmZdgZGddde eZGd d d Zd S) )AnyDictListOptional) Embeddingsget_from_dict_or_env)parse) BaseModel ConfigDictmodel_validator)SelfGradientEmbeddingsc@seZdZUdZeed< dZeeed< dZeeed< dZ eed< dZ eeed< dZ e ed < e d d Zed d edede fddZedd defddZdeedeeefddZdeedeeefddZdedeefddZdedeefddZdS)raGradient.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_retrievalclientZforbid)extrabefore)modevaluesreturncCs8t|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)clsrra/var/www/html/lang_env/lib/python3.10/site-packages/langchain_community/embeddings/gradient_ai.pyvalidate_environment:s z'GradientEmbeddings.validate_environmentaftercCshzddl}Wn tytdwt|jtdkrtd|j|j|j|jd}|j|j d|_ |S)NrzAGradientEmbeddings requires `pip install -U "gradientai>=1.4.0"`.z1.4.0)Z access_tokenZ workspace_idhost)Zslug) gradientai ImportErrorr __version__ZGradientrrrZget_embeddings_modelrr)selfr"Zgradientrrr post_initNs$  zGradientEmbeddings.post_inittextscCs,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. cSg|]}d|iqSinputr.0textrrr mz6GradientEmbeddings.embed_documents..inputscSg|]}|jqSrZ embeddingr,errrr.q)rZembed embeddingsr%r'r1resultrrrembed_documentsds z"GradientEmbeddings.embed_documentscs4dd|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. cSr(r)rr+rrrr.|r/z7GradientEmbeddings.aembed_documents..r0NcSr2rr3r4rrrr.r6)rZaembedr7r8rrraembed_documentsss z#GradientEmbeddings.aembed_documentsr-cCs*|jr |jd|n|}||gdS)zCall out to Gradient's embedding endpoint. Args: text: The text to embed. Returns: Embeddings for the text.  r)rr:)r%r-queryrrr embed_querys  zGradientEmbeddings.embed_querycs6|jr |jd|n|}||gIdH}|dS)zAsync call out to Gradient's embedding endpoint. Args: text: The text to embed. Returns: Embeddings for the text. r<Nr)rr;)r%r-r=r7rrr aembed_querys zGradientEmbeddings.aembed_query)__name__ __module__ __qualname____doc__str__annotations__rrrrrrrr Z model_configr classmethodrrr r&rfloatr:r;r>r?rrrrr s4   c@seZdZdZdddZdS) 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. rNcOstd)Nz8Deprecated,TinyAsyncGradientEmbeddingClient was removed.) ValueError)r%argskwargsrrr__init__sz)TinyAsyncGradientEmbeddingClient.__init__)rN)r@rArBrCrLrrrrrHsrHN)typingrrrrZlangchain_core.embeddingsrZlangchain_core.utilsrZpackaging.versionr Zpydanticr r r Ztyping_extensionsr __all__rrHrrrrs