3fi # .ddlZddlmZddlmZddlmZddlmZdddd d d d d dd Z de fdZ de de e e ffdZ ddde de dzde e e ffdZejee de ddfdZddde de dzdedeeeeefzfdZddgZy)N)util)Any) Embeddings)Runnablelangchain_openai langchain_awslangchain_coherelangchain_google_genailangchain_google_vertexailangchain_huggingfacelangchain_mistralailangchain_ollama) azure_openaibedrockcohere google_genaigoogle_vertexai huggingface mistralaiollamaopenaireturncVdjdtjDS)z3Get formatted list of providers and their packages. c3RK|]\}}d|d|jdd!yw)z - z: _-N)replace).0ppkgs _/var/www/auto_recruiter/arenv/lib/python3.12/site-packages/langchain_classic/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}d|d|}t||jdd\}}|jj }|j }|tvrd|dt }t||s d}t|||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) ```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_stringr9s2 *( $ZL1$ %.;  0 o &&sA.OHe~~%%'H KKME++ #A!#$ & o *o U?r(r7r8r7c|js d}t||d|vrt|\}}n|}|st}d|}t||tvrd|dt }t|||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/)r4r1r9r%r))r8r7r6r*r5s r"_infer_model_and_providerr<Ss ;;=*oC5L259* (  3k   o++ #A!#$ & o Z r()maxsizer!cVtj|sd|d|d}t|y)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!r6s r" _check_pkgrBus? >># u%336%q : # r(kwargsc d|s3tj}ddj|}t|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|S|dk(rddlm}|dd|i|Sd|dt/}t|)aa Initialize 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 the provider is specified separately or can be inferred. See supported providers under the `provider` arg description. provider: Optional explicit provider name. If not specified, will attempt to parse from the model string in the `model` arg. Supported providers: - `openai` -> [`langchain-openai`](https://docs.langchain.com/oss/python/integrations/providers/openai) - `azure_openai` -> [`langchain-openai`](https://docs.langchain.com/oss/python/integrations/providers/openai) - `bedrock` -> [`langchain-aws`](https://docs.langchain.com/oss/python/integrations/providers/aws) - `cohere` -> [`langchain-cohere`](https://docs.langchain.com/oss/python/integrations/providers/cohere) - `google_genai` -> [`langchain-google-genai`](https://docs.langchain.com/oss/python/integrations/providers/google) - `google_vertexai` -> [`langchain-google-vertexai`](https://docs.langchain.com/oss/python/integrations/providers/google) - `huggingface` -> [`langchain-huggingface`](https://docs.langchain.com/oss/python/integrations/providers/huggingface) - `mistralai` -> [`langchain-mistralai`](https://docs.langchain.com/oss/python/integrations/providers/mistralai) - `ollama` -> [`langchain-ollama`](https://docs.langchain.com/oss/python/integrations/providers/ollama) **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 ???+ note "Example Usage" ```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-...") ``` !!! version-added "Added in `langchain` 0.3.9" z2Must specify model name. Supported providers are: z, r:rr)OpenAIEmbeddingsr8r)AzureOpenAIEmbeddingsr)GoogleGenerativeAIEmbeddingsr)VertexAIEmbeddingsr)BedrockEmbeddingsmodel_idr)CohereEmbeddingsr)MistralAIEmbeddingsr)HuggingFaceEmbeddingsr*r)OllamaEmbeddingsr.r/r')r%keysr$r1r<rBrrErFr rGr rHrrIr rKr rLr rMrrNr))r8r7rCr5r6r*r!rErFrGrHrIrKrLrMrNs r"init_embeddingsrPsB (--/ @9AU@V W o4UXNHj x (CsO85;j;F;;>!:$@:@@@>!G+G*GGG$$@!= =f==93 ?*???85;j;F;;;;">>v>>= ?$E EfEE85;j;F;; XJ=    " S/r(rrP) functools importlibrtypingrlangchain_core.embeddingsrlangchain_core.runnablesrr%strr)tupler9r< lru_cachelenrBlistfloatrP__all__r'r(r"r]s%0-' ,2*&   C4C4E#s(O4t   Dj  38_  DS!567CD8 u uDju u (3U +,, ur r(