9|h~`ddlZddlmZddlmZmZmZmZmZddl m Z ddl m Z ddl mZddd d d d d ddZdefdZdedeeeffdZdddedeedeeeffdZej(eededdfdZe dddedeededee eeeefffdZddgZy)N)util)AnyListOptionalTupleUnion)beta) Embeddings)Runnablelangchain_openai langchain_awslangchain_coherelangchain_google_vertexailangchain_huggingfacelangchain_mistralailangchain_ollama) azure_openaibedrockcoheregoogle_vertexai huggingface mistralaiollamaopenaireturncVdjdtjDS)z3Get formatted list of providers and their packages. c3RK|]\}}d|d|jdd!yw)z - z: _-N)replace).0ppkgs X/var/www/html/test/engine/venv/lib/python3.12/site-packages/langchain/embeddings/base.py z%_get_provider_list..s2063$qcCKKS)*+s%')join_SUPPORTED_PROVIDERSitemsr%_get_provider_listr,s) 99:N:T:T:V r+ model_namec"d|vrt}td|d||jdd\}}|jj }|j }|tvrtd|dt |s td||fS)aParse a model string into provider and model name components. The model string should be in the format 'provider:model-name', where provider is one of the supported providers. Args: model_name: A model string in the format 'provider:model-name' Returns: A tuple of (provider, model_name) .. code-block:: python _parse_model_string("openai:text-embedding-3-small") # Returns: ("openai", "text-embedding-3-small") _parse_model_string("bedrock:amazon.titan-embed-text-v1") # Returns: ("bedrock", "amazon.titan-embed-text-v1") Raises: ValueError: If the model string is not in the correct format or the provider is unsupported :zInvalid model format 'z'. Model name must be in format 'provider:model-name' Example valid model strings: - openai:text-embedding-3-small - bedrock:amazon.titan-embed-text-v1 - cohere:embed-english-v3.0 Supported providers:  Provider 'E' is not supported. Supported providers and their required packages: Model name cannot be empty)r( ValueErrorsplitlowerstripr,)r- providersprovidermodels r%_parse_model_stringr;s0 *( $ZL1$ %.;  0  !&&sA.OHe~~%%'H KKME++ #A!#$ &  566 U?r+r9r:r9c|js td|d|vrt|\}}n|}|}|st}td||tvrtd|dt ||fS)Nr3r/zMust specify either: 1. A model string in format 'provider:model-name' Example: 'openai:text-embedding-3-small' 2. Or explicitly set provider from: r1r2)r7r4r;r(r,)r:r9r-r8s r%_infer_model_and_providerr>Os ;;=566C5L259* (  3k    ++ #A!#$ &  Z r+)maxsizer$cRtj|std|d|dy)z Check if a package is installed.zCould not import z5 python package. Please install it with `pip install `N)r find_spec ImportError)r$s r% _check_pkgrDms: >># u%336%q :   r+kwargsc 2|s1tj}tddj|t ||\}}t|}t ||dk(rddlm}|dd|i|S|dk(rdd lm}|dd|i|S|d k(rdd l m }|dd|i|S|d k(rdd l m } | dd|i|S|dk(rddl m} | dd|i|S|dk(rddlm} | dd|i|S|dk(rddlm} | dd|i|S|dk(rddlm} | dd|i|Std|dt+)aInitialize an embeddings model from a model name and optional provider. **Note:** Must have the integration package corresponding to the model provider installed. Args: model: Name of the model to use. Can be either: - A model string like "openai:text-embedding-3-small" - Just the model name if provider is specified provider: Optional explicit provider name. If not specified, will attempt to parse from the model string. Supported providers and their required packages: {_get_provider_list()} **kwargs: Additional model-specific parameters passed to the embedding model. These vary by provider, see the provider-specific documentation for details. Returns: An Embeddings instance that can generate embeddings for text. Raises: ValueError: If the model provider is not supported or cannot be determined ImportError: If the required provider package is not installed .. dropdown:: Example Usage :open: .. code-block:: python # Using a model string model = init_embeddings("openai:text-embedding-3-small") model.embed_query("Hello, world!") # Using explicit provider model = init_embeddings( model="text-embedding-3-small", provider="openai" ) model.embed_documents(["Hello, world!", "Goodbye, world!"]) # With additional parameters model = init_embeddings( "openai:text-embedding-3-small", api_key="sk-..." ) .. versionadded:: 0.3.9 z2Must specify model name. Supported providers are: z, r<rr)OpenAIEmbeddingsr:r)AzureOpenAIEmbeddingsr)VertexAIEmbeddingsr)BedrockEmbeddingsmodel_idr)CohereEmbeddingsr)MistralAIEmbeddingsr)HuggingFaceEmbeddingsr-r)OllamaEmbeddingsr1r2r*)r(keysr4r'r>rDr rGrHrrIr rJrrLrrMrrNrrOr,)r:r9rEr8r-r$rGrHrIrJrLrMrNrOs r%init_embeddingsrQwstp (--/ @9AU@V W  5UXNHj x (CsO85;j;F;; ^ #:$@:@@@ & &@!= =f== Y 3 ?*??? X 5;j;F;; [ ;">>v>> ] "?$E EfEE X 5;j;F;; #A!#$ &  r+rQr ) functools importlibrtypingrrrrrlangchain_core._apir langchain_core.embeddingsr langchain_core.runnablesr r(strr,r;r> lru_cachelenrDfloatrQ__all__r*r+r%r]s:44$0-' 2*&   C0C0E#s(O0h.2  %c]  38_ <S!567 C D 8 #f f smf  f  :xT%[ 01 12 f f T r+