style: auto-format with black + isort + ruff + prettier [skip ci-format-check]

staging E2E实测：
- 3图总耗时39.79s，1/3 fast+pro双超时全失败（fast 14.7s超时/pro 25.1s超时）
- 8图总耗时30.50s，7/8 fast命中，1张fast超时pro兜底成功
- fast单图普遍6-8s（之前本地2.6-4.2s），12s/25s超时设置边缘擦挂

调整：
- fast_json _DEFAULT_TIMEOUT 12→15s
- fast_path _FAST_TIMEOUT/_FAST_JSON_TIMEOUT 12→15s
- pro fallback _DEFAULT_TIMEOUT 25→30s，外层_PRO_TIMEOUT 25→30s
- 保留环境变量覆盖能力

apps/worker/worker_app/tasks/vision/_prompt.py

@@ -2,6 +2,7 @@
 """V2 prompt 解析：优先读后台 viral_video_prompt_templates 配置，30s TTL 热加载；
 DB 不可用/读到默认XML模板时，fallback 到硬编码 JSON schema prompt。
 """
+
 from __future__ import annotations
 
 import logging
@@ -80,6 +81,7 @@ def _load_template() -> Any | None:
     """从DB读image_analysis模板，失败返回None。"""
     try:
         from packages.application.viral_video.prompt_loader import get_template
+
         return get_template("image_analysis")
     except Exception as e:
         logger.warning("[vision.v2] 读取后台prompt配置失败: %s", e)
@@ -131,15 +133,15 @@ def _resolve(kind: str) -> tuple[str, str]:
                 sys_prompt = custom_sys + tail
             if custom_user_tpl:
                 # V2 是单图调用，简单替换几个常用占位符；缺键原样保留
-                usr_prompt = (custom_user_tpl
-                              .replace("{image_count}", "1")
-                              .replace("{industry}", "通用")
-                              .replace("{image_urls}", "")
-                              .strip())
+                usr_prompt = (
+                    custom_user_tpl.replace("{image_count}", "1")
+                    .replace("{industry}", "通用")
+                    .replace("{image_urls}", "")
+                    .strip()
+                )
                 if not usr_prompt:
                     usr_prompt = default_user
-            logger.info("[vision.v2] 使用后台自定义prompt (kind=%s version=%s)",
-                        kind, getattr(tpl, "version", "?"))
+            logger.info("[vision.v2] 使用后台自定义prompt (kind=%s version=%s)", kind, getattr(tpl, "version", "?"))
     except Exception as e:
         logger.warning("[vision.v2] 解析后台prompt失败，使用默认: %s", e)
 

apps/worker/worker_app/tasks/vision/fast_path.py

@@ -23,10 +23,10 @@ logger = logging.getLogger(__name__)
 
 # 超时（可通过环境变量覆盖）
 _IMG_WORKERS = int(os.environ.get("VISION_V2_IMG_WORKERS", "8"))
-_FAST_TIMEOUT = float(os.environ.get("VISION_V2_FAST_TIMEOUT", "12"))
-_FAST_JSON_TIMEOUT = float(os.environ.get("VISION_V2_FAST_JSON_TIMEOUT", "12"))
+_FAST_TIMEOUT = float(os.environ.get("VISION_V2_FAST_TIMEOUT", "15"))
+_FAST_JSON_TIMEOUT = float(os.environ.get("VISION_V2_FAST_JSON_TIMEOUT", "15"))
 _OCR_TIMEOUT = float(os.environ.get("VISION_V2_OCR_TIMEOUT", "6"))
-_PRO_TIMEOUT = float(os.environ.get("VISION_V2_PRO_TIMEOUT", "25"))
+_PRO_TIMEOUT = float(os.environ.get("VISION_V2_PRO_TIMEOUT", "30"))
 
 _FALLBACK_RESULT = {
     "name": "未识别",

apps/worker/worker_app/tasks/vision/vlm_fallback.py

@@ -25,7 +25,7 @@ logger = logging.getLogger(__name__)
 
 _BASE_URL = "https://dashscope.aliyuncs.com/compatible-mode/v1"
 _PRO_MODEL = "qwen3.7-plus"
-_DEFAULT_TIMEOUT = 25
+_DEFAULT_TIMEOUT = 30
 _DEFAULT_MAX_TOKENS = 800
 
 
@@ -131,10 +131,13 @@ def call_pro_vlm(
         "model": _PRO_MODEL,
         "messages": [
             {"role": "system", "content": system_prompt},
-            {"role": "user", "content": [
-                {"type": "image_url", "image_url": {"url": img_url}},
-                {"type": "text", "text": user_prompt},
-            ]},
+            {
+                "role": "user",
+                "content": [
+                    {"type": "image_url", "image_url": {"url": img_url}},
+                    {"type": "text", "text": user_prompt},
+                ],
+            },
         ],
         "temperature": 0.3,
         "max_tokens": _DEFAULT_MAX_TOKENS,
@@ -165,8 +168,11 @@ def call_pro_vlm(
             reasoning_tokens = ctd.get("reasoning_tokens", 0)
         logger.info(
             "[vision.v2] pro 完成 model=%s elapsed=%.1fs in=%d out=%d reasoning=%d",
-            _PRO_MODEL, elapsed,
-            usage.get("prompt_tokens", 0), usage.get("completion_tokens", 0), reasoning_tokens,
+            _PRO_MODEL,
+            elapsed,
+            usage.get("prompt_tokens", 0),
+            usage.get("completion_tokens", 0),
+            reasoning_tokens,
         )
         s = raw.strip()
         if s.startswith("```"):

apps/worker/worker_app/tasks/vision/vlm_fast_json.py

@@ -27,7 +27,7 @@ logger = logging.getLogger(__name__)
 # DashScope OpenAI 兼容 endpoint
 _BASE_URL = "https://dashscope.aliyuncs.com/compatible-mode/v1"
 _FAST_MODEL = "qwen3.8-flash"
-_DEFAULT_TIMEOUT = 12
+_DEFAULT_TIMEOUT = 15
 _DEFAULT_MAX_TOKENS = 350
 
 
@@ -102,7 +102,9 @@ def call_fast_json(
             )
             elapsed = time.time() - t0
         if resp.status_code != 200:
-            logger.warning("[vision.v2] fast_json HTTP %d elapsed=%.1fs body=%s", resp.status_code, elapsed, resp.text[:200])
+            logger.warning(
+                "[vision.v2] fast_json HTTP %d elapsed=%.1fs body=%s", resp.status_code, elapsed, resp.text[:200]
+            )
             return None
         data = resp.json()
         raw = (data.get("choices") or [{}])[0].get("message", {}).get("content")
@@ -116,8 +118,11 @@ def call_fast_json(
             reasoning_tokens = ctd.get("reasoning_tokens", 0)
         logger.info(
             "[vision.v2] fast_json 完成 model=%s elapsed=%.1fs in=%d out=%d reasoning=%d",
-            _FAST_MODEL, elapsed,
-            usage.get("prompt_tokens", 0), usage.get("completion_tokens", 0), reasoning_tokens,
+            _FAST_MODEL,
+            elapsed,
+            usage.get("prompt_tokens", 0),
+            usage.get("completion_tokens", 0),
+            reasoning_tokens,
         )
         text = _strip_code_fence(raw)
         lpos, r = text.find("{"), text.rfind("}")
@@ -133,7 +138,10 @@ def call_fast_json(
             return None
         logger.info(
             "[vision.v2] fast_json 完成 elapsed=%.1fs has_person=%s has_product=%s category=%s",
-            elapsed, obj.get("has_person"), obj.get("has_product"), obj.get("category"),
+            elapsed,
+            obj.get("has_person"),
+            obj.get("has_product"),
+            obj.get("category"),
         )
         return obj
     except Exception as e: