mrx-data

` docs = await run_in_threadpool(search_docs, query=query, knowledge_base_name=knowledge_base_name, top_k=top_k, score_threshold=score_threshold) # 加入reranker if USE_RERANKER: reranker_model_path = MODEL_PATH["reranker"].get(RERANKER_MODEL,"BAAI/bge-reranker-large") print("-----------------model path------------------") print(reranker_model_path) reranker_model = LangchainReranker(top_n=top_k, device=embedding_device(), max_length=RERANKER_MAX_LENGTH, model_name_or_path=reranker_model_path ) print(docs) docs = reranker_model.compress_documents(documents=docs,...