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| import chromadb | |
| from chromadb.utils import embedding_functions | |
| def get_client(): | |
| client = chromadb.PersistentClient(path="./chromadb_linux/") | |
| MODEL_NAME: str = "mixedbread-ai/mxbai-embed-large-v1" # ~ 0.5 gb | |
| COLLECTION_NAME: str = "scheme" | |
| EMBEDDING_FUNC = embedding_functions.SentenceTransformerEmbeddingFunction( | |
| model_name=MODEL_NAME | |
| ) | |
| schemer = client.get_collection( | |
| name=COLLECTION_NAME, | |
| embedding_function=EMBEDDING_FUNC, | |
| ) | |
| return schemer | |