tj^) UdZddlZddlZddlmZddlmZddlmZde ededefd Z d d e fd d e fdddfdde fdde fdde fdddfdde fdde fd de fd Z e e ee e ed efffed!< ejee "d#e ded effd$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 W/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/langchain/embeddings/base.py_callr s 3====zlangchain_azure_ai.embeddingsAzureAIOpenAIApiEmbeddingsModellangchain_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_ai azure_openaibedrockcohere google_genaigoogle_vertexai huggingface mistralaiollamaopenai._BUILTIN_PROVIDERS)maxsizeproviderc|tvr#d|dt}t|t|\}}} tj|}n\#t $rO}|ddddd}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: .)maxsplitr_-zCould not import z5 python package. Please install it with `pip install `N)r) r1_get_provider_list ValueError importlib import_module ImportErrorsplitreplacegetattr functoolspartial) r3msg module_name class_name creator_funcmoduleepkgrs r _get_embeddings_class_creatorrN9s &))) & & &!## & & oo,>x,H)K\&(55 &&&a003;;CEEb#bb\_bbb#A%& &* % %C  \s 3 3 33sA B-A B((B-cnddtDS)z3Get formatted list of providers and their packages. c3`K|])\}}d|d|dddV*dS)z - z: rr:r;N)rC).0prMs r z%_get_provider_list..bsZ391c.q..CFNN3,,..r )joinr1itemsr r r r=r=`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: r8r5r6Model name cannot be empty)r1keysr>rBlowerstripr=)r!rGr3rs r _parse_model_stringr]gs4 * @Z @ @ %7$;$;$=$=  @ @ oo &&sA..OHe~~%%''H KKMME))) & & &!## & & oo *oo U?r r3rc<|sd}t||d|vrt|\}}n|}|s+dt}t||tvr#d|dt }t|||fS)NrYrXzMust specify either: 1. A model string in format 'provider:model-name' Example: 'openai:text-embedding-3-small' 2. Or explicitly set provider from: r5r6)r\r>r]r1rZr=)rr3rGr!s r _infer_model_and_providerr`s ;;==*ooC5LL2599**  +"&&((  + + oo))) & & &!## & & oo Z r c |s@t}dd|}t|t ||\}}t |dd|i|S)a 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_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_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, r^rr )r1rZrUr>r`rN)rr3r providersrGr!s r init_embeddingsrcs~P &++-- Y499YCWCWYYoo4UXNNNHj 2 ( 2 2 N N Nv N NNr rrc)__doc__rEr?collections.abcrtypingrlangchain_core.embeddingsrtyper r1dictstrtuple__annotations__ lru_cachelenrNr=r]r`rc__all__r r r rps'''$$$$$$000000tJ3: 12SUZ[')@%HBB "#5u=-/MuU35I5QDD ()>F!#5u=!#5u=%MMDeChsJ.G$GHHI(,SS!344555#4C#4HS*_4M#4#4#465#4LC4C4E#s(O4444t     Dj  38_     H NONONO NODjNO NO  NONONONOd r