fix(ci): 修复2个ruff错误 - F541多余f前缀 + B007未用循环变量

- ai_service.py
- ai_tasks.py
- test_ai_tasks.py

apps/api/app/services/ai_service.py

@@ -298,11 +298,13 @@ def _semantic_match_fallback(
         score = min(1.0, base_score * 0.8 + name_bonus)
         score = round(score, 3)
 
-        results.append({
-            **asset,
-            "match_score": score,
-            "match_reason": "fallback_keyword",
-        })
+        results.append(
+            {
+                **asset,
+                "match_score": score,
+                "match_reason": "fallback_keyword",
+            }
+        )
 
     # 按匹配度降序
     results.sort(key=lambda x: x["match_score"], reverse=True)
@@ -414,9 +416,7 @@ def semantic_match_assets(
         tags = asset.get("tags", [])
         tags_str = ",".join(str(t) for t in tags[:5])
         desc = str(asset.get("description", ""))[:80]
-        asset_summaries.append(
-            f"ID:{aid} | 名称:{name} | 标签:[{tags_str}] | 描述:{desc}"
-        )
+        asset_summaries.append(f"ID:{aid} | 名称:{name} | 标签:[{tags_str}] | 描述:{desc}")
 
     asset_ids = [str(a.get("id", "")) for a in assets[:50]]
 
@@ -434,8 +434,7 @@ def semantic_match_assets(
 
     user_prompt = (
         f"目标视频描述：{description}\n\n"
-        f"素材列表：\n" + "\n".join(asset_summaries) +
-        f"\n\n请返回每个素材的匹配分数JSON："
+        f"素材列表：\n" + "\n".join(asset_summaries) + "\n\n请返回每个素材的匹配分数JSON："
     )
 
     messages = [
@@ -457,11 +456,13 @@ def semantic_match_assets(
             for asset in assets:
                 aid = str(asset.get("id", ""))
                 score = scores.get(aid, 0.3)  # 没评分的给默认偏低分
-                matched.append({
-                    **asset,
-                    "match_score": round(score, 3),
-                    "match_reason": "doubao_semantic",
-                })
+                matched.append(
+                    {
+                        **asset,
+                        "match_score": round(score, 3),
+                        "match_reason": "doubao_semantic",
+                    }
+                )
             matched.sort(key=lambda x: x["match_score"], reverse=True)
 
             logger.info(

apps/worker/worker_app/tasks/ai_tasks.py

@@ -142,23 +142,25 @@ def _parse_recommend_response(
             return None
 
         clips: List[Dict[str, Any]] = []
-        for i, clip in enumerate(clips_data):
+        for _, clip in enumerate(clips_data):
             if not isinstance(clip, dict):
                 continue
             asset_id = str(clip.get("asset_id", ""))
             # 校验 asset_id 是否在输入列表中
             if asset_id and asset_id not in asset_ids:
                 asset_id = ""
-            clips.append({
-                "clip_type": clip.get("clip_type", "showcase"),
-                "order": clip.get("order", len(clips)),
-                "text_content": str(clip.get("text_content", "")),
-                "duration": max(1.0, min(30.0, float(clip.get("duration", 3.0)))),
-                "transition_effect": clip.get("transition_effect", "cut"),
-                "asset_id": asset_id,
-                "start_time": max(0.0, float(clip.get("start_time", 0.0))),
-                "config": clip.get("config", {}) or {},
-            })
+            clips.append(
+                {
+                    "clip_type": clip.get("clip_type", "showcase"),
+                    "order": clip.get("order", len(clips)),
+                    "text_content": str(clip.get("text_content", "")),
+                    "duration": max(1.0, min(30.0, float(clip.get("duration", 3.0)))),
+                    "transition_effect": clip.get("transition_effect", "cut"),
+                    "asset_id": asset_id,
+                    "start_time": max(0.0, float(clip.get("start_time", 0.0))),
+                    "config": clip.get("config", {}) or {},
+                }
+            )
 
         if not clips:
             return None
@@ -219,7 +221,7 @@ def _call_ai_recommend_service(
         "3. 总时长接近 target_duration，每个素材至少用一次\n"
         "4. 转场效果合理分配，不要全用cut\n"
         "5. 返回纯JSON，不要其他文字\n"
-        "返回格式：{\"clips\": [...], \"title\": \"视频标题\", \"confidence\": 0.85}"
+        '返回格式：{"clips": [...], "title": "视频标题", "confidence": 0.85}'
     )
 
     assets_desc = "\n".join([f"  - 素材ID: {aid}" for i, aid in enumerate(asset_ids[:30])])

tests/unit/test_ai_tasks.py

@@ -121,22 +121,41 @@ class TestRecommendResponseParsing(unittest.TestCase):
         """解析正常响应."""
         data = {
             "clips": [
-                {"clip_type": "intro", "order": 0, "text_content": "开场",
-                 "duration": 3.0, "transition_effect": "fade",
-                 "asset_id": "a1", "start_time": 0.0, "config": {}},
-                {"clip_type": "showcase", "order": 1, "text_content": "展示",
-                 "duration": 5.0, "transition_effect": "cut",
-                 "asset_id": "a2", "start_time": 1.0, "config": {}},
-                {"clip_type": "outro", "order": 2, "text_content": "结尾",
-                 "duration": 2.0, "transition_effect": "fade",
-                 "asset_id": "", "start_time": 0.0, "config": {}},
+                {
+                    "clip_type": "intro",
+                    "order": 0,
+                    "text_content": "开场",
+                    "duration": 3.0,
+                    "transition_effect": "fade",
+                    "asset_id": "a1",
+                    "start_time": 0.0,
+                    "config": {},
+                },
+                {
+                    "clip_type": "showcase",
+                    "order": 1,
+                    "text_content": "展示",
+                    "duration": 5.0,
+                    "transition_effect": "cut",
+                    "asset_id": "a2",
+                    "start_time": 1.0,
+                    "config": {},
+                },
+                {
+                    "clip_type": "outro",
+                    "order": 2,
+                    "text_content": "结尾",
+                    "duration": 2.0,
+                    "transition_effect": "fade",
+                    "asset_id": "",
+                    "start_time": 0.0,
+                    "config": {},
+                },
             ],
             "title": "精彩视频",
             "confidence": 0.85,
         }
-        result = _parse_recommend_response(
-            json.dumps(data), self._asset_ids(), 30.0
-        )
+        result = _parse_recommend_response(json.dumps(data), self._asset_ids(), 30.0)
         self.assertIsNotNone(result)
         self.assertEqual(len(result["clips"]), 3)
         self.assertEqual(result["clips"][0]["clip_type"], "intro")
@@ -145,11 +164,21 @@ class TestRecommendResponseParsing(unittest.TestCase):
 
     def test_parse_markdown_code_block(self):
         """解析markdown代码块."""
-        data = {"clips": [
-            {"clip_type": "showcase", "order": 0, "text_content": "t",
-             "duration": 3, "transition_effect": "cut",
-             "asset_id": "a1", "start_time": 0, "config": {}}
-        ], "confidence": 0.7}
+        data = {
+            "clips": [
+                {
+                    "clip_type": "showcase",
+                    "order": 0,
+                    "text_content": "t",
+                    "duration": 3,
+                    "transition_effect": "cut",
+                    "asset_id": "a1",
+                    "start_time": 0,
+                    "config": {},
+                }
+            ],
+            "confidence": 0.7,
+        }
         content = "```json\n" + json.dumps(data) + "\n```"
         result = _parse_recommend_response(content, self._asset_ids(), 30.0)
         self.assertIsNotNone(result)
@@ -167,51 +196,78 @@ class TestRecommendResponseParsing(unittest.TestCase):
 
     def test_parse_no_clips(self):
         """无clips字段返回None."""
-        result = _parse_recommend_response(
-            json.dumps({"title": "abc"}), self._asset_ids(), 30.0
-        )
+        result = _parse_recommend_response(json.dumps({"title": "abc"}), self._asset_ids(), 30.0)
         self.assertIsNone(result)
 
     def test_parse_filters_invalid_asset_ids(self):
         """过滤不在输入列表中的asset_id."""
-        data = {"clips": [
-            {"clip_type": "showcase", "order": 0, "text_content": "t",
-             "duration": 3, "transition_effect": "cut",
-             "asset_id": "fake-id", "start_time": 0, "config": {}}
-        ], "confidence": 0.7}
-        result = _parse_recommend_response(
-            json.dumps(data), self._asset_ids(), 30.0
-        )
+        data = {
+            "clips": [
+                {
+                    "clip_type": "showcase",
+                    "order": 0,
+                    "text_content": "t",
+                    "duration": 3,
+                    "transition_effect": "cut",
+                    "asset_id": "fake-id",
+                    "start_time": 0,
+                    "config": {},
+                }
+            ],
+            "confidence": 0.7,
+        }
+        result = _parse_recommend_response(json.dumps(data), self._asset_ids(), 30.0)
         self.assertIsNotNone(result)
         # 非法asset_id被清空
         self.assertEqual(result["clips"][0]["asset_id"], "")
 
     def test_parse_clamps_duration(self):
         """时长被限制在合理范围."""
-        data = {"clips": [
-            {"clip_type": "showcase", "order": 0, "text_content": "t",
-             "duration": 100, "transition_effect": "cut",
-             "asset_id": "a1", "start_time": 0, "config": {}}
-        ]}
-        result = _parse_recommend_response(
-            json.dumps(data), self._asset_ids(), 30.0
-        )
+        data = {
+            "clips": [
+                {
+                    "clip_type": "showcase",
+                    "order": 0,
+                    "text_content": "t",
+                    "duration": 100,
+                    "transition_effect": "cut",
+                    "asset_id": "a1",
+                    "start_time": 0,
+                    "config": {},
+                }
+            ]
+        }
+        result = _parse_recommend_response(json.dumps(data), self._asset_ids(), 30.0)
         self.assertIsNotNone(result)
         self.assertLessEqual(result["clips"][0]["duration"], 30.0)
 
     def test_parse_reorders_clips(self):
         """clips按order排序并重新编号."""
-        data = {"clips": [
-            {"clip_type": "showcase", "order": 5, "text_content": "b",
-             "duration": 3, "transition_effect": "cut",
-             "asset_id": "a2", "start_time": 0, "config": {}},
-            {"clip_type": "intro", "order": 0, "text_content": "a",
-             "duration": 3, "transition_effect": "fade",
-             "asset_id": "a1", "start_time": 0, "config": {}},
-        ]}
-        result = _parse_recommend_response(
-            json.dumps(data), self._asset_ids(), 30.0
-        )
+        data = {
+            "clips": [
+                {
+                    "clip_type": "showcase",
+                    "order": 5,
+                    "text_content": "b",
+                    "duration": 3,
+                    "transition_effect": "cut",
+                    "asset_id": "a2",
+                    "start_time": 0,
+                    "config": {},
+                },
+                {
+                    "clip_type": "intro",
+                    "order": 0,
+                    "text_content": "a",
+                    "duration": 3,
+                    "transition_effect": "fade",
+                    "asset_id": "a1",
+                    "start_time": 0,
+                    "config": {},
+                },
+            ]
+        }
+        result = _parse_recommend_response(json.dumps(data), self._asset_ids(), 30.0)
         self.assertIsNotNone(result)
         # 第一个应该是order=0的intro
         self.assertEqual(result["clips"][0]["clip_type"], "intro")
@@ -221,14 +277,22 @@ class TestRecommendResponseParsing(unittest.TestCase):
 
     def test_parse_confidence_clamped(self):
         """confidence被限制在0-1."""
-        data = {"clips": [
-            {"clip_type": "showcase", "order": 0, "text_content": "t",
-             "duration": 3, "transition_effect": "cut",
-             "asset_id": "a1", "start_time": 0, "config": {}}
-        ], "confidence": 2.5}
-        result = _parse_recommend_response(
-            json.dumps(data), self._asset_ids(), 30.0
-        )
+        data = {
+            "clips": [
+                {
+                    "clip_type": "showcase",
+                    "order": 0,
+                    "text_content": "t",
+                    "duration": 3,
+                    "transition_effect": "cut",
+                    "asset_id": "a1",
+                    "start_time": 0,
+                    "config": {},
+                }
+            ],
+            "confidence": 2.5,
+        }
+        result = _parse_recommend_response(json.dumps(data), self._asset_ids(), 30.0)
         self.assertIsNotNone(result)
         self.assertLessEqual(result["confidence"], 1.0)
 
@@ -260,12 +324,26 @@ class TestRunAIRecommend(unittest.TestCase):
         mock_client.is_available = True
         mock_response = {
             "clips": [
-                {"clip_type": "intro", "order": 0, "text_content": "开场",
-                 "duration": 3.0, "transition_effect": "fade",
-                 "asset_id": "a1", "start_time": 0.0, "config": {}},
-                {"clip_type": "outro", "order": 1, "text_content": "结尾",
-                 "duration": 2.0, "transition_effect": "fade",
-                 "asset_id": "a2", "start_time": 0.0, "config": {}},
+                {
+                    "clip_type": "intro",
+                    "order": 0,
+                    "text_content": "开场",
+                    "duration": 3.0,
+                    "transition_effect": "fade",
+                    "asset_id": "a1",
+                    "start_time": 0.0,
+                    "config": {},
+                },
+                {
+                    "clip_type": "outro",
+                    "order": 1,
+                    "text_content": "结尾",
+                    "duration": 2.0,
+                    "transition_effect": "fade",
+                    "asset_id": "a2",
+                    "start_time": 0.0,
+                    "config": {},
+                },
             ],
             "title": "AI生成标题",
             "confidence": 0.9,