| 29 | |
| 30 | |
| 31 | def load_vector_db(): |
| 32 | # 加载编码模型 |
| 33 | bce_emb_config = load_config('rag_langchain', 'bce_emb_config') |
| 34 | embeddings = HuggingFaceEmbeddings(**bce_emb_config) |
| 35 | # 加载本地索引，创建向量检索器 |
| 36 | # 除非指定使用chroma，否则默认使用faiss |
| 37 | rag_model_type = load_config('rag_langchain', 'rag_model_type') |
| 38 | if rag_model_type == "chroma": |
| 39 | vector_db_path = "../rag_langchain/chroma_db" |
| 40 | vectordb = Chroma(persist_directory=vector_db_path, embedding_function=embeddings) |
| 41 | else: |
| 42 | vector_db_path = "../rag_langchain/faiss_index" |
| 43 | vectordb = FAISS.load_local(folder_path=vector_db_path, embeddings=embeddings) |
| 44 | return vectordb |
| 45 | |
| 46 | |
| 47 | def load_retriever(): |