sync(server-release): 从 main 同步逻辑改动（不含 API 格式变更）

同步内容:
- knowledge/manager.py: VLM max_tokens 512→2048 + reasoning_content fallback
- services/feedback.py: FAQ max_tokens 200→512
- services/session.py: 消息排序增加 id DESC 次级排序
- knowledge/image_cleanup.py: 新增图片/VLM缓存孤儿文件清理模块
- knowledge/collection.py: 集合删除时清理孤儿文件 + list_collections 磁盘扫描策略
- knowledge/document.py: 文档删除时清理孤儿文件
- api/chat_routes.py: 新增 _rescue_bm25_divergence 函数（BM25-CE分歧救援）
- core/intent_analyzer.py: 使用 get_intent_client 专用客户端 + 移除短追问缓存跳过逻辑
- cleanup_orphans.py: 独立孤儿文件清理脚本

knowledge/manager.py

@@ -654,7 +654,7 @@ class KnowledgeBaseManager(
         try:
             from config import get_llm_client, DASHSCOPE_MODEL
             client = get_llm_client()
-            summary = call_llm(client, prompt, DASHSCOPE_MODEL, max_tokens=512)
+            summary = call_llm(client, prompt, DASHSCOPE_MODEL, max_tokens=2048)
             return summary.strip() if summary else ""
         except Exception as e:
             logger.warning(f"生成表格摘要失败: {e}")
@@ -713,13 +713,31 @@ class KnowledgeBaseManager(
                         ]
                     }
                 ],
-                max_tokens=512
+                max_tokens=2048  # mimo-v2.5 推理模型思考链消耗 ~1000 token，需留足输出空间
             )
 
             description = response.choices[0].message.content
 
+            # 推理模型兼容：content 为空时从 reasoning_content 提取
+            if not description or not description.strip():
+                reasoning = getattr(response.choices[0].message, 'reasoning_content', None)
+                if reasoning and reasoning.strip():
+                    import re
+                    # 尝试从思考链中提取有用文本（去掉 <think> 标签后的内容）
+                    cleaned = re.sub(r'', '', reasoning, flags=re.DOTALL).strip()
+                    if cleaned:
+                        logger.info(f"VLM content为空，从reasoning_content提取描述: {image_path}")
+                        description = cleaned
+                    else:
+                        description = reasoning.strip()
+
+            if not description:
+                logger.warning(f"VLM 返回空描述: {image_path}")
+                return ""
+
             # 缓存结果
             import hashlib
+            import re as _re
             img_hash = hashlib.md5(img_path.read_bytes()).hexdigest()
             cache_dir = Path('.data/cache/vlm')
             cache_dir.mkdir(parents=True, exist_ok=True)