WiFddlZddlmZddlmZddlmZGddeZy)N)List) TextEmbedding) BaseEmbeddercZeZdZdZddeffd Zd deededejfdZ xZ S) FastEmbedBackendaFastEmbed embedding model. The FastEmbed embedding model used for generating sentence embeddings. Arguments: embedding_model: A FastEmbed embedding model Examples: To create a model, you can load in a string pointing to a supported FastEmbed model: ```python from bertopic.backend import FastEmbedBackend sentence_model = FastEmbedBackend("BAAI/bge-small-en-v1.5") ``` embedding_modelct|tjDcgc]}|d }}t |t r||vrt||_ytdcc}w)Nmodel) model_namezPlease select a correct FasteEmbed model: the model must be a string and must be supported. The supported TextEmbedding model list is here: https://qdrant.github.io/fastembed/examples/Supported_Models/)super__init__rlist_supported_models isinstancestrr ValueError)selfrmsupported_models __class__s g/home/sietch6/trending-topics-pipeline/venv/lib/python3.12/site-packages/bertopic/backend/_fastembed.pyr zFastEmbedBackend.__init__sg 0=0S0S0UV1AgJVV os +CS0S#0O#LD @  Ws A% documentsverbosereturncxtjt|jj ||}|S)aEmbed a list of n documents/words into an n-dimensional matrix of embeddings. Arguments: documents: A list of documents or words to be embedded verbose: Controls the verbosity of the process Returns: Document/words embeddings with shape (n, m) with `n` documents/words that each have an embeddings size of `m` )show_progress_bar)nparraylistrembed)rrr embeddingss rrzFastEmbedBackend.embed)s4XXd4#7#7#=#=i[b#=#cde )zBAAI/bge-small-en-v1.5)F) __name__ __module__ __qualname____doc__rr rboolrndarrayr __classcell__)rs@rrrs6$   tCy 4 BJJ r!r) numpyrtypingr fastembedrbertopic.backendrrr!rr.s#).|.r!