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update:vector store config
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@ -268,10 +268,8 @@ def http_bot(state, mode, sql_mode, db_selector, temperature, max_new_tokens, re
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if mode == conversation_types["custome"] and not db_selector:
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print("vector store name: ", vector_store_name["vs_name"])
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vector_store_config = []
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vector_store_config["vector_store_name"] = vector_store_name["vs_name"]
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vector_store_config["text_field"] = "content"
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vector_store_config["vector_store_path"] = KNOWLEDGE_UPLOAD_ROOT_PATH
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vector_store_config = {"vector_store_name": vector_store_name["vs_name"], "text_field": "content",
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"vector_store_path": KNOWLEDGE_UPLOAD_ROOT_PATH}
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knowledge_embedding_client = KnowledgeEmbedding(file_path="", model_name=LLM_MODEL_CONFIG["text2vec"],
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local_persist=False,
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vector_store_config=vector_store_config)
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