Ah@SSKrSSKJr SSKJrJrJr SSKJr SSK J r SSSS S S S SS .r S\ 4Sjr S\ S\\ \ 44SjrSS.S\ S\\ S\\ \ 44Sjjr\R""\"\ 5S9S\ SS4Sj5rSS.S\ S\\ S\S\\\ \\\444SjjrSS/rg)N)util)AnyOptionalUnion) Embeddings)Runnablelangchain_openai langchain_awslangchain_coherelangchain_google_vertexailangchain_huggingfacelangchain_mistralailangchain_ollama) azure_openaibedrockcoheregoogle_vertexai huggingface mistralaiollamaopenaireturncVSRS[R555$)z3Get formatted list of providers and their packages. c3T# UHupSUSURSS53v M! g7f)z - z: _-N)replace).0ppkgs Q/var/www/html/shao/venv/lib/python3.13/site-packages/langchain/embeddings/base.py %_get_provider_list..s/:V$qcCKKS)*+:Vs&()join_SUPPORTED_PROVIDERSitemsr"_get_provider_listr*s) 99:N:T:T:V r) model_namec<SU;a[nSUSU3n[U5eURSS5up4UR5R 5nUR 5nU[;aSUS[ 53n[U5eU(d Sn[U5eX44$)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+ providersmsgprovidermodels r"_parse_model_stringr:s0 *( $ZL1$ %.;  0 o &&sA.OH~~%%'H KKME++ #A!#$ & o *o ?r)r8r9r8cUR5(d Sn[U5eUcSU;a[U5upOUnU(d[nSU3n[U5eU[;aSUS[ 53n[U5eX4$)Nr1r-zMust specify either: 1. A model string in format 'provider:model-name' Example: 'openai:text-embedding-3-small' 2. Or explicitly set provider from: r/r0)r5r2r:r&r*)r9r8r7r+r6s r"_infer_model_and_providerr=Qs ;;==*oC5L259* (  3k   o++ #A!#$ & o  r))maxsizer!cb[R"U5(dSUSUS3n[U5eg)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!r7s r" _check_pkgrCssB >>#  u%336%q : # r)kwargsc JU(d3[R5nSSRU53n[U5e[ XS9up[Un[ U5 US:XaSSKJn U"SSU0UD6$US:XaSS KJn U"SSU0UD6$US :XaSS K J n U "SSU0UD6$US :XaSS K J n U "SSU0UD6$US:XaSSK Jn U "SSU0UD6$US:XaSSKJn U "SSU0UD6$US:XaSSKJn U "SSU0UD6$US:XaSSKJn U"SSU0UD6$SUS[+53n[U5e)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)OpenAIEmbeddingsr9r)AzureOpenAIEmbeddingsr)VertexAIEmbeddingsr)BedrockEmbeddingsmodel_idr)CohereEmbeddingsr)MistralAIEmbeddingsr)HuggingFaceEmbeddingsr+r)OllamaEmbeddingsr/r0r()r&keysr%r2r=rCr rFrGr rHr rIr rKrrLr rMrrNr*)r9r8rDr6r7r+r!rFrGrHrIrKrLrMrNs r"init_embeddingsrP~sun (--/ @9AU@V W o4UNH x (CsO85;j;F;;>!:$@:@@@$$@!= =f==93 ?*???85;j;F;;;;">>v>>= ?$E EfEE85;j;F;; XJ=    " S/r)rrP) functools importlibrtypingrrrlangchain_core.embeddingsrlangchain_core.runnablesrr&strr*tupler:r= lru_cachelenrClistfloatrP__all__r(r)r"r]s(''0-' 2*&   C3C3E#s(O3r#  sm  38_  D S!567CD8#g gsmg g  :xT%[ 01 12 gV r)