ugxddlZddlmZmZddlZddlmZmZmZeje Z GddeeZ y)N)Unioncast) DocumentsEmbeddingFunction Embeddingsc>eZdZdZdededdfdZdeeefdefdZ y) OllamaEmbeddingFunctionz This class is used to generate embeddings for a list of texts using the Ollama Embedding API (https://github.com/ollama/ollama/blob/main/docs/api.md#generate-embeddings). url model_namereturnNcT||_||_tj|_y)a Initialize the Ollama Embedding Function. Args: url (str): The URL of the Ollama Server. model_name (str): The name of the model to use for text embeddings. E.g. "nomic-embed-text" (see https://ollama.com/library for available models). N)_api_url _model_namehttpxClient_session)selfr r s q/var/www/openai/venv/lib/python3.12/site-packages/chromadb/utils/embedding_functions/ollama_embedding_function.py__init__z OllamaEmbeddingFunction.__init__s"% %  inputc (t|tr|n|g}|Dcgc]D}|jj|j|j |dj F}}tt|Dcgc] }d|vr|d c}Scc}wcc}w)a Get the embeddings for a list of texts. Args: input (Documents): A list of texts to get embeddings for. Returns: Embeddings: The embeddings for the texts. Example: >>> ollama_ef = OllamaEmbeddingFunction(url="http://localhost:11434/api/embeddings", model_name="nomic-embed-text") >>> texts = ["Hello, world!", "How are you?"] >>> embeddings = ollama_ef(texts) )modelprompt)json embedding) isinstancelistrpostrrrrr)rrtextstext embeddingsrs r__call__z OllamaEmbeddingFunction.__call__s $E40ug    MM   d.>.>$$O  df    ", !+I)++&!+     s A B 3B ) __name__ __module__ __qualname____doc__strrrrrr#rrr r s= 'C 'S 'T ' eIsN3  rr ) loggingtypingrrrchromadb.api.typesrrr getLoggerr$loggerr r)rrr/s8 GG   8 $/ / :/ r