tjxdZddlmZmZmZddlZddlmZddlm Z m Z m Z ddl m Z mZmZGdde eZdS) 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 eefdZdS)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)extravaluesreturncLtt|dd}||d<|S)z,Validate that api key exists in environment.rLLM_RAILS_API_KEY)rr)clsrrs f/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/langchain_community/embeddings/llm_rails.pyvalidate_environmentz'LLMRailsEmbeddings.validate_environment's4( 4G H H  $y textsctjdd|ji||jdd}d|dDS)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<)headersjsontimeoutcg|] }|d S) embedding).0items r z6LLMRailsEmbeddings.embed_documents..?sFFFd[!FFFrdata)requestspostrget_secret_valuerr )selfrresponses rembed_documentsz"LLMRailsEmbeddings.embed_documents0sg= 4 $,"?"?"A"AB 4:66     GFhmmoof.EFFFFrtextc:||gdS)zCall out to Cohere's embedding endpoint. Args: text: The text to embed. Returns: Embeddings for the text. r)r.)r,r/s r embed_queryzLLMRailsEmbeddings.embed_queryAs##TF++A..r)__name__ __module__ __qualname____doc__rstr__annotations__rrr r model_configr rrrfloatr.r1r$rrrr s"(E3'''#'GXi ''':L$4XGT#YG4U 3DGGGG" / /U / / / / / /rr)r5typingrrrr)langchain_core.embeddingsrlangchain_core.utilsrrr pydanticr r r rr$rrr>s))''''''''''000000VVVVVVVVVV5555555555?/?/?/?/?/J?/?/?/?/?/r