i]( UdZddlZddlZddlmZddlmZddlmZde ededefd Z d d e fd d dfdde fdde fdde fdddfdde fdde fd de fd Z e e ee e edefffed< ejee  d!e dedeffd"Zde fd#Zd$e dee e ffd%Zdd&d'e d!e dzdee e ffd(Zdd&d'e d!e dzdedefd)Zd*d+gZdS),z!Factory functions for embeddings.N)Callable)Any) Embeddingsclskwargsreturnc |di|S)Nr )rrs C:\Users\Dell Inspiron 16\Desktop\tws\AgrotaPowerBi\back-agrota-powerbi\mcp-client-agrota\venv\Lib\site-packages\langchain/embeddings/base.py_callr s 3====langchain_openaiAzureOpenAIEmbeddings langchain_awsBedrockEmbeddingsc |dd|i|S)Nmodel_idr r rmodelrs r rsSS%B%B%%B6%B%Br langchain_cohereCohereEmbeddingslangchain_google_genaiGoogleGenerativeAIEmbeddingslangchain_google_vertexaiVertexAIEmbeddingslangchain_huggingfaceHuggingFaceEmbeddingsc |dd|i|S)N model_namer r rs r rrsSS%D%DE%DV%D%Dr langchain_mistralaiMistralAIEmbeddingslangchain_ollamaOllamaEmbeddingsOpenAIEmbeddings) azure_openaibedrockcohere google_genaigoogle_vertexai huggingface mistralaiollamaopenai._BUILTIN_PROVIDERS)maxsizeprovidercv|tvr#d|dt}t|t|\}}} tj|}nA#t $r4}|dd}d|d|d}t ||d}~wwxYwt||}tj || S) aLReturn a factory function that creates an embeddings model for the given provider. This function is cached to avoid repeated module imports. Args: provider: The name of the model provider (e.g., `'openai'`, `'cohere'`). Must be a key in `_BUILTIN_PROVIDERS`. Returns: A callable that accepts model kwargs and returns an `Embeddings` instance for the specified provider. Raises: ValueError: If the provider is not in `_BUILTIN_PROVIDERS`. ImportError: If the provider's integration package is not installed. Provider 'E' is not supported. Supported providers and their required packages: _-zCould not import z5 python package. Please install it with `pip install `N)r) r/_get_provider_list ValueError importlib import_module ImportErrorreplacegetattr functoolspartial) r1msg module_name class_name creator_funcmoduleepkgrs r _get_embeddings_class_creatorrH8s&))) & & &!## & & oo,>x,H)K\&(55 &&&!!#s++b#bb\_bbb#A%& &* % %C  \s 3 3 33sA B/B  BcnddtDS)z3Get formatted list of providers and their packages. c3`K|])\}}d|d|dddV*dS)z - z: rr5r6N)r=).0prGs r z%_get_provider_list..asZ391c.q..CFNN3,,..r )joinr/itemsr r r r8r8_s@ 99=O=U=U=W=W  r r cd|vr.d|dt}t||dd\}}|}|}|tvr#d|dt }t||sd}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) Example: ```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: r3r4Model name cannot be empty)r/keysr9splitlowerstripr8)r rAr1rs r _parse_model_stringrYfs4 * @Z @ @ %7$;$;$=$=  @ @ oo &&sA..OHe~~%%''H KKMME))) & & &!## & & oo *oo U?r r1rc<|sd}t||d|vrt|\}}n|}|s+dt}t||tvr#d|dt }t|||fS)NrTrRzMust specify either: 1. A model string in format 'provider:model-name' Example: 'openai:text-embedding-3-small' 2. Or explicitly set provider from: r3r4)rXr9rYr/rUr8)rr1rAr s r _infer_model_and_providerr\s ;;==*ooC5LL2599**  +"&&((  + + oo))) & & &!## & & oo Z r c |s@t}dd|}t|t ||\}}t |dd|i|S)aq Initialize an embedding model from a model name and optional provider. !!! note Requires the integration package for the chosen model provider to be installed. See the `model_provider` parameter below for specific package names (e.g., `pip install langchain-openai`). Refer to the [provider integration's API reference](https://docs.langchain.com/oss/python/integrations/providers) for supported model parameters to use as `**kwargs`. Args: model: The name of the model, e.g. `'openai:text-embedding-3-small'`. You can also specify model and model provider in a single argument using `'{model_provider}:{model}'` format, e.g. `'openai:text-embedding-3-small'`. provider: The model provider if not specified as part of the model arg (see above). Supported `provider` values and the corresponding integration package are: - `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_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. Refer to the specific model provider's [integration reference](https://reference.langchain.com/python/integrations/) for all available parameters. 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 ???+ example ```python # pip install langchain langchain-openai # 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, rZrr )r/rUrOr9r\rH)rr1r providersrAr s r init_embeddingsr_s~N &++-- Y499YCWCWYYoo4UXNNNHj 2 ( 2 2 N N Nv N NNr rr_)__doc__r?r:collections.abcrtypingrlangchain_core.embeddingsrtyper r/dictstrtuple__annotations__ lru_cachelenrHr8rYr\r___all__r r r rls'''$$$$$$000000tJ3: ()@%HBB "#5u=-/MuU35I5QDD ()>F!#5u=!#5u=#MMDeChsJ.G$GHHI&,SS!344555#4C#4HS*_4M#4#4#465#4LC4C4E#s(O4444t     Dj  38_     H MOMOMO MODjMO MO  MOMOMOMOb r