ghDlddlZddlmZddlmZmZmZddlmZddl m Z dddd d d d dd Z de fdZ de dee e ffdZddde dee dee e ffdZejee de ddfdZddde dee dedeee eeefffdZddgZdS)N)util)AnyOptionalUnion) Embeddings)Runnablelangchain_openai langchain_awslangchain_coherelangchain_google_vertexailangchain_huggingfacelangchain_mistralailangchain_ollama) azure_openaibedrockcoheregoogle_vertexai huggingface mistralaiollamaopenaireturncnddtDS)z3Get formatted list of providers and their packages. c3TK|]#\}}d|d|ddV$dS)z - z: _-N)replace).0ppkgs V/var/www/FlaskApp/flask-venv/lib/python3.11/site-packages/langchain/embeddings/base.py z%_get_provider_list..sV063+q++CKKS))++)join_SUPPORTED_PROVIDERSitemsr$r"_get_provider_listr)s@ 99:N:T:T:V:V  r$ model_namecfd|vrt}td|d||dd\}}|}|}|tvr!td|dt |std||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_stringr8s0 *(  0Z 0 0 %.  0 0   !&&sA..OHe~~%%''H KKMME+++ & & &!## & &   75666 U?r$r6r7r6c|std|d|vrt|\}}n|}|}|st}td||tvr!td|dt ||fS)Nr0r,zMust specify either: 1. A model string in format 'provider:model-name' Example: 'openai:text-embedding-3-small' 2. Or explicitly set provider from: r.r/)r4r1r8r&r))r7r6r*r5s r"_infer_model_and_providerr;Ns ;;==75666C5LL2599**  (        +++ & & &!## & &   Z r$)maxsizer!cZtj|std|d|ddS)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_pkgrAlsU >#    : : :36 : : :     r$kwargsc |s>t}tdd|t ||\}}t|}t ||dkrddlm}|dd|i|S|dkrdd lm}|dd|i|S|d krdd l m }|dd|i|S|d krdd l m } | dd|i|S|dkrddl m} | dd|i|S|dkrddlm} | dd|i|S|dkrddlm} | dd|i|S|dkrddlm} | 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, r9rr)OpenAIEmbeddingsr7r)AzureOpenAIEmbeddingsr)VertexAIEmbeddingsr)BedrockEmbeddingsmodel_idr)CohereEmbeddingsr)MistralAIEmbeddingsr)HuggingFaceEmbeddingsr*r)OllamaEmbeddingsr.r/Nr()r&keysr1r%r;rAr rDrEr rFr rGr rIrrJr rKrrLr))r7r6rBr5r*r!rDrErFrGrIrJrKrLs r"init_embeddingsrNvstn  (--//  W9AUAU W W   5UXNNNHj x (CsOOO8555555;;j;F;;; ^ # #::::::$$@@:@@@@ & & &@@@@@@!!== =f=== Y  333333  ??*???? X  555555;;j;F;;; [ ;;;;;;"">>>v>>> ] " "??????$$EE EfEEE X  555555;;j;F;;; & & &!## & &   r$rNr) functools importlibrtypingrrrlangchain_core.embeddingsrlangchain_core.runnablesrr&strr)tupler8r; lru_cachelenrAlistfloatrN__all__r(r$r"r[s''''''''''000000------' 2*&    C0C0E#s(O0000h.2    %c]  38_    <SS!566777 C D   87 #f f f f smf  f  :xT%[ 01 12 f f f f T r$