fix: 改进知识库初始化和重排序错误处理，增强日志记录

Author: piexian

astrbot/core/knowledge_base/kb_helper.py

@@ -150,21 +150,28 @@ async def get_ep(self) -> EmbeddingProvider:
     async def get_rp(self) -> RerankProvider | None:
         if not self.kb.rerank_provider_id:
             return None
-        rp: RerankProvider = await self.prov_mgr.get_provider_by_id(
+        rp: RerankProvider | None = await self.prov_mgr.get_provider_by_id(
             self.kb.rerank_provider_id,
         )  # type: ignore
         if not rp:
-            raise ValueError(
-                f"无法找到 ID 为 {self.kb.rerank_provider_id} 的 Rerank Provider",
+            logger.warning(
+                f"知识库 {self.kb.kb_name}({self.kb.kb_id}) 的 Rerank Provider({self.kb.rerank_provider_id}) 不可用，将跳过重排序。",
             )
+            return None
         return rp
 
     async def _ensure_vec_db(self) -> FaissVecDB:
         if not self.kb.embedding_provider_id:
             raise ValueError(f"知识库 {self.kb.kb_name} 未配置 Embedding Provider")
 
         ep = await self.get_ep()
-        rp = await self.get_rp()
+        rp: RerankProvider | None = None
+        try:
+            rp = await self.get_rp()
+        except Exception as e:
+            logger.warning(
+                f"知识库 {self.kb.kb_name}({self.kb.kb_id}) 初始化重排序能力失败，将跳过重排序: {e}",
+            )
 
         vec_db = FaissVecDB(
             doc_store_path=str(self.kb_dir / "doc.db"),

astrbot/core/knowledge_base/kb_mgr.py

@@ -232,10 +232,10 @@ async def retrieve(
         for kb_name in kb_names:
             if kb_helper := await self.get_kb_by_name(kb_name):
                 if kb_helper.init_error:
-                    logger.warning(
-                        f"跳过初始化失败的知识库 {kb_name}: {kb_helper.init_error}"
+                    logger.error(f"知识库 {kb_name} 不可用: {kb_helper.init_error}")
+                    raise ValueError(
+                        f"知识库 {kb_name} 不可用: {kb_helper.init_error}",
                     )
-                    continue
                 kb_ids.append(kb_helper.kb.kb_id)
                 kb_id_helper_map[kb_helper.kb.kb_id] = kb_helper
 

astrbot/core/knowledge_base/retrieval/manager.py

@@ -184,12 +184,15 @@ async def retrieve(
                 first_rerank = vec_db.rerank_provider
                 break
         if first_rerank and retrieval_results:
-            retrieval_results = await self._rerank(
-                query=query,
-                results=retrieval_results,
-                top_k=top_m_final,
-                rerank_provider=first_rerank,
-            )
+            try:
+                retrieval_results = await self._rerank(
+                    query=query,
+                    results=retrieval_results,
+                    top_k=top_m_final,
+                    rerank_provider=first_rerank,
+                )
+            except Exception as e:
+                logger.warning(f"Rerank 执行失败，已跳过重排序并使用融合结果: {e}")
 
         return retrieval_results[:top_m_final]
 
@@ -229,10 +232,8 @@ async def _dense_retrieve(
 
                 all_results.extend(vec_results)
             except Exception as e:
-                from astrbot.core import logger
-
-                logger.warning(f"知识库 {kb_id} 稠密检索失败: {e}")
-                continue
+                logger.error(f"知识库 {kb_id} 稠密检索失败: {e}")
+                raise RuntimeError(f"知识库 {kb_id} 稠密检索失败: {e}") from e
 
         # 按相似度排序并返回 top_k
         all_results.sort(key=lambda x: x.similarity, reverse=True)