tj%ddlZddlmZddlmZddlmZddlmZddl m Z ddd d d d d dddd Z de fdZ de dee e ffdZddde de dzdee e ffdZejee de ddfdZedddd ddde de dzd!edee eeefzfd"Zd#d$gZdS)%N)util)Any) deprecated) Embeddings)Runnablelangchain_azure_ailangchain_openai langchain_awslangchain_coherelangchain_google_genailangchain_google_vertexailangchain_huggingfacelangchain_mistralailangchain_ollama) azure_ai azure_openaibedrockcohere google_genaigoogle_vertexai huggingface mistralaiollamaopenaireturncnddtDS)z3Get formatted list of providers and their packages. c3TK|]#\}}d|d|ddV$dS)z - z: _-N)replace).0ppkgs _/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/langchain_classic/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_namecrd|vrt}d|d|}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) ```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<s2 *(  0Z 0 0 %.  0 0 oo &&sA..OHe~~%%''H KKMME+++ & & &!## & & oo *oo U?r'r:r;r:c|sd}t||d|vrt|\}}n|}|st}d|}t||tvr#d|dt }t|||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;r:r9r-r8s r%_infer_model_and_providerr?Us ;;==*ooC5LL2599**  (      oo+++ & & &!## & & oo Z r')maxsizer$ctj|s.|dd}d|d|d}t|dS)z Check if a package is installed.rr zCould not import z5 python package. Please install it with `pip install `N)r find_specr! ImportError)r$pip_namer9s r% _check_pkgrFwsk >#  ;;sC(( ? ? ?3; ? ? ? # r'z1.0.5z2.0.0z$langchain.embeddings.init_embeddingszfMaintained in `langchain`; `langchain-classic` retains this entry point for import-compatibility only.)sinceremoval alternativeaddendumkwargsc |s@t}dd|}t|t ||\}}t|}t ||dkrddlm}|dd|i|S|dkrdd lm }|dd|i|S|d krdd lm } | 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|S|dkrddlm}|dd|i|S|dkrddlm}|dd|i|Sd|dt3}t|) a 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_ai` -> [`langchain-azure-ai`](https://docs.langchain.com/oss/python/integrations/providers/microsoft) - `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)AzureAIOpenAIApiEmbeddingsModelr;r)AzureOpenAIEmbeddingsr)OpenAIEmbeddingsr)BedrockEmbeddingsmodel_idr)GoogleGenerativeAIEmbeddingsr)VertexAIEmbeddingsr)CohereEmbeddingsr)MistralAIEmbeddingsr)HuggingFaceEmbeddingsr-r)OllamaEmbeddingsr1r2Nr+)r)keysr(r4r?rFlangchain_azure_ai.embeddingsrMr rNrOr rPr rRr rSr rTrrUrrVrrWr,)r;r:rKr8r9r-r$rMrNrOrPrRrSrTrUrVrWs r%init_embeddingsrZsV (--// W9AUAU W W oo4UXNNNHj x (CsOOO:QQQQQQ..JJZJ6JJJ>!!::::::$$@@:@@@@8555555;;j;F;;;9333333  ??*????>!!GGGGGG++GG*GGGG$$$@@@@@@!!== =f===8555555;;j;F;;;;;;;;;;"">>>v>>>=  ??????$$EE EfEEE8555555;;j;F;;; "X " "    " " S//r'rrZ) functools importlibrtypingrlangchain_core._apirlangchain_core.embeddingsrlangchain_core.runnablesrr)strr,tupler<r? lru_cachelenrFlistfloatrZ__all__r+r'r%rhs ******000000------%& ,2*&    C4C4E#s(O4444t     Dj  38_     DSS!566777CD87   6 )  zzz zDjz z (3U +,, zzzz| r'