jpdZddlmZmZmZddlZddlmZddlm Z m Z m Z ddl m Z mZmZGdde eZy) z#This file is for LLMRails Embedding)DictListOptionalN) Embeddings)convert_to_secret_strget_from_dict_or_envpre_init) BaseModel ConfigDict SecretStrceZdZUdZdZeed< dZee ed< e dZ e de d e fd Zd eed eeefd Zd ed eefdZy)LLMRailsEmbeddingsaLLMRails embedding models. To use, you should have the environment variable ``LLM_RAILS_API_KEY`` set with your API key or pass it as a named parameter to the constructor. Model can be one of ["embedding-english-v1","embedding-multi-v1"] Example: .. code-block:: python from langchain_community.embeddings import LLMRailsEmbeddings cohere = LLMRailsEmbeddings( model="embedding-english-v1", api_key="my-api-key" ) zembedding-english-v1modelNapi_keyforbid)extravaluesreturnc<tt|dd}||d<|S)z,Validate that api key exists in environment.rLLM_RAILS_API_KEY)rr)clsrrs r/var/www/html/Fitness-lenito-AI-main/venv/lib/python3.12/site-packages/langchain_community/embeddings/llm_rails.pyvalidate_environmentz'LLMRailsEmbeddings.validate_environment's,( 4G H $y textsctjdd|jji||jdd}|j dDcgc]}|d c}Scc}w)zCall out to Cohere's embedding endpoint. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. z&https://api.llmrails.com/v1/embeddingsz X-API-KEY)inputr<)headersjsontimeoutdata embedding)requestspostrget_secret_valuerr )selfrresponseitems rembed_documentsz"LLMRailsEmbeddings.embed_documents0se== 4 $,,"?"?"AB 4::6   /7mmof.EF.Ed[!.EFFFs A%textc,|j|gdS)zCall out to Cohere's embedding endpoint. Args: text: The text to embed. Returns: Embeddings for the text. r)r*)r'r+s r embed_queryzLLMRailsEmbeddings.embed_queryAs##TF+A..r)__name__ __module__ __qualname____doc__rstr__annotations__rrr r model_configr rrrfloatr*r-rrrr s"(E3'#'GXi 'L$4GT#YG4U 3DG" / /U /rr)r1typingrrrr$langchain_core.embeddingsrlangchain_core.utilsrrr pydanticr r r rr6rrr;s.)''0VV55?/J?/r