SuperSCC.rag.ConnectRAG.connect_client

ConnectRAG.connect_client(model_kwargs={'device': 'cpu'}, encode_kwargs={'normalize_embeddings': True}, timeout=1000)

Establishes a connection to the Qdrant vector store using the provided details.

Parameters:

• (dict (encode_kwargs) – Keyword arguments for loading the Hugging Face embedding model. Defaults to {“device”: “cpu”}.

• optional) – Keyword arguments for loading the Hugging Face embedding model. Defaults to {“device”: “cpu”}.

• (dict – Keyword arguments for the embedding model’s encoding process. Defaults to {“normalize_embeddings”: True}.

• optional) – Keyword arguments for the embedding model’s encoding process. Defaults to {“normalize_embeddings”: True}.

• (int (timeout) – The request timeout in seconds for the Qdrant client. Defaults to 1000.

• optional) – The request timeout in seconds for the Qdrant client. Defaults to 1000.