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feature:knowledge embedding update
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@@ -19,7 +19,7 @@ from langchain import PromptTemplate
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ROOT_PATH = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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sys.path.append(ROOT_PATH)
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from pilot.configs.model_config import KNOWLEDGE_UPLOAD_ROOT_PATH, LLM_MODEL_CONFIG
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from pilot.configs.model_config import DB_SETTINGS, KNOWLEDGE_UPLOAD_ROOT_PATH, LLM_MODEL_CONFIG, TOP_RETURN_SIZE
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from pilot.server.vectordb_qa import KnownLedgeBaseQA
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from pilot.connections.mysql import MySQLOperator
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from pilot.source_embedding.knowledge_embedding import KnowledgeEmbedding
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@@ -256,11 +256,13 @@ 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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persist_dir = os.path.join(KNOWLEDGE_UPLOAD_ROOT_PATH, vector_store_name["vs_name"] + ".vectordb")
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print("向量数据库持久化地址: ", persist_dir)
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knowledge_embedding_client = KnowledgeEmbedding(file_path="", model_name=LLM_MODEL_CONFIG["text2vec"], vector_store_config={"vector_store_name": vector_store_name["vs_name"],
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print("vector store path: ", persist_dir)
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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_name": vector_store_name["vs_name"],
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"vector_store_path": KNOWLEDGE_UPLOAD_ROOT_PATH})
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query = state.messages[-2][1]
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docs = knowledge_embedding_client.similar_search(query, 10)
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docs = knowledge_embedding_client.similar_search(query, TOP_RETURN_SIZE)
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context = [d.page_content for d in docs]
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prompt_template = PromptTemplate(
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template=conv_qa_prompt_template,
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@@ -600,6 +602,7 @@ def knowledge_embedding_store(vs_id, files):
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knowledge_embedding_client = KnowledgeEmbedding(
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file_path=os.path.join(KNOWLEDGE_UPLOAD_ROOT_PATH, vs_id, filename),
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model_name=LLM_MODEL_CONFIG["text2vec"],
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local_persist=False,
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vector_store_config={
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"vector_store_name": vector_store_name["vs_name"],
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"vector_store_path": KNOWLEDGE_UPLOAD_ROOT_PATH})
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@@ -624,7 +627,7 @@ if __name__ == "__main__":
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# 配置初始化
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cfg = Config()
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dbs = get_database_list()
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# dbs = get_database_list()
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cfg.set_plugins(scan_plugins(cfg, cfg.debug_mode))
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