j TddlmZmZmZmZddlmZddlmZm Z m Z GddeeZ y))AnyDictListOptional) Embeddings) BaseModel ConfigDictmodel_validatorceZdZUdZdZeeed<dZee ed<dZ eeed<iZ ee ed<e ed<ed Zed ed ede fdZdeedeeefdZdedeefdZy)GPT4AllEmbeddingsaGPT4All embedding models. To use, you should have the gpt4all python package installed Example: .. code-block:: python from langchain_community.embeddings import GPT4AllEmbeddings model_name = "all-MiniLM-L6-v2.gguf2.f16.gguf" gpt4all_kwargs = {'allow_download': 'True'} embeddings = GPT4AllEmbeddings( model_name=model_name, gpt4all_kwargs=gpt4all_kwargs ) N model_name n_threadscpudevicegpt4all_kwargsclient)protected_namespacesbefore)modevaluesreturnc ddlm}|d |jd|jd|jdd|jdxsi|d<|S#t$r td wxYw) z+Validate that GPT4All library is installed.r) Embed4Allr rr)r rrrrzuCould not import gpt4all library. Please install the gpt4all library to use this embedding model: pip install gpt4allr)gpt4allrget ImportError)clsrrs p/var/www/html/Fitness-lenito-AI-main/venv/lib/python3.12/site-packages/langchain_community/embeddings/gpt4all.pyvalidate_environmentz&GPT4AllEmbeddings.validate_environment!s  )( !::l3 **[1zz(+ ::./52  F8   @  s AAA.textsc |Dcgc]}|jj|}}|Dcgc]}ttt|c}Scc}wcc}w)zEmbed a list of documents using GPT4All. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. )rembedlistmapfloat)selfr!text embeddingses rembed_documentsz!GPT4AllEmbeddings.embed_documents6sQ;@@%$dkk''-% @-78ZS]#Z88A8s "A Ar(c,|j|gdS)zEmbed a query using GPT4All. Args: text: The text to embed. Returns: Embeddings for the text. r)r+)r'r(s r embed_queryzGPT4AllEmbeddings.embed_queryCs##TF+A..)__name__ __module__ __qualname____doc__r rstr__annotations__rintrrdictrr model_configr classmethodrr rr&r+r-rr.rr r s"!%J $#Ix}#!FHSM!%'NHTN' K26L(#$3$& 9T#Y 94U 3D 9 / /U /r.r N) typingrrrrlangchain_core.embeddingsrpydanticrr r r rr.rr<s$,,0;;E/ :E/r.