ug! ddlZddlmZddlZddlmZmZmZeje Z GddeeZ GddeeZ y)N)cast) DocumentsEmbeddingFunction Embeddingsc4eZdZdZ d dedefdZdedefdZy) HuggingFaceEmbeddingFunctionz This class is used to get embeddings for a list of texts using the HuggingFace API. It requires an API key and a model name. The default model name is "sentence-transformers/all-MiniLM-L6-v2". api_key model_namecd||_tj|_|jjj dd|iy)a Initialize the HuggingFaceEmbeddingFunction. Args: api_key (str): Your API key for the HuggingFace API. model_name (str, optional): The name of the model to use for text embeddings. Defaults to "sentence-transformers/all-MiniLM-L6-v2". zAhttps://api-inference.huggingface.co/pipeline/feature-extraction/ AuthorizationzBearer N)_api_urlhttpxClient_sessionheadersupdate)selfr r s v/var/www/openai/venv/lib/python3.12/site-packages/chromadb/utils/embedding_functions/huggingface_embedding_function.py__init__z%HuggingFaceEmbeddingFunction.__init__sF\\f[gh    $$o 7J%KLinputreturnc tt|jj|j|ddidj S)a Get the embeddings for a list of texts. Args: texts (Documents): A list of texts to get embeddings for. Returns: Embeddings: The embeddings for the texts. Example: >>> hugging_face = HuggingFaceEmbeddingFunction(api_key="your_api_key") >>> texts = ["Hello, world!", "How are you?"] >>> embeddings = hugging_face(texts) wait_for_modelT)inputsoptionsjsonrrrpostr rrrs r__call__z%HuggingFaceEmbeddingFunction.__call__sI   MM   %3CT2JK  df   rN)z&sentence-transformers/all-MiniLM-L6-v2 __name__ __module__ __qualname____doc__strrrrr"rrrr s8 /W M M(+ M i J rrc,eZdZdZdefdZdedefdZy)HuggingFaceEmbeddingServerz This class is used to get embeddings for a list of texts using the HuggingFace Embedding server (https://github.com/huggingface/text-embeddings-inference). The embedding model is configured in the server. urlcF||_tj|_y)z Initialize the HuggingFaceEmbeddingServer. Args: url (str): The URL of the HuggingFace Embedding Server. N)r rrr)rr,s rrz#HuggingFaceEmbeddingServer.__init__>s%   rrrctt|jj|jd|ij S)a Get the embeddings for a list of texts. Args: texts (Documents): A list of texts to get embeddings for. Returns: Embeddings: The embeddings for the texts. Example: >>> hugging_face = HuggingFaceEmbeddingServer(url="http://localhost:8080/embed") >>> texts = ["Hello, world!", "How are you?"] >>> embeddings = hugging_face(texts) rrrr!s rr"z#HuggingFaceEmbeddingServer.__call__Hs<   **4==%?P*QVVX  rNr#r)rrr+r+8s& 'C' i J rr+) loggingtypingrrchromadb.api.typesrrr getLoggerr$loggerrr+r)rrr4sK GG   8 $* #4Y#?* Z" !29!=" r