feat(market): 技能/MCP 分类改为面向用户的业务场景(人群->场景)，AI验证期按场景归类

backend/python/app/api/market.py

@@ -18,7 +18,7 @@ from ..models import (
 )
 from ..auth import get_current_user, get_current_user_id, get_current_user_id_optional
 from ..middleware.log_service import LogService
-from ..capability_registry import CAPABILITY_TYPES, resolve_auto_model as _resolve_auto_model
+from ..capability_registry import resolve_auto_model as _resolve_auto_model
 from app.api.admin.mcp_admin import _test_mcp_server, parse_mcp_config
 
 router = APIRouter()
@@ -207,9 +207,48 @@ def verify_agent_connectivity(platform: str, endpoint: str, api_key: str) -> dic
         return {"ok": False, "verified": False, "detail": f"地址不可达：{_short_err(e)}"}
 
 
-# ===== 能力分类（AI 自动归类，任何失败都返回 None，不阻断导入） =====
-def _classify_capability(name: str, description: Optional[str], content: Optional[str], db: Session) -> Optional[str]:
-    """用平台文本模型把应用归类到 11 种能力之一；失败返回 None（不阻断导入）。"""
+# ===== 业务场景分类（面向用户的技能/MCP 分类，与后端模型路由的 capability_registry 解耦） =====
+# 注意：MarketApp.capability 列在此存放「业务场景 id」（见 MARKET_SCENES），不再是 text/vision 等模型能力。
+MARKET_SCENES: list = [
+    # 自由职业者
+    {"id": "freelance_content", "label": "内容创作/自媒体", "color": "#F59E0B", "group": "freelance"},
+    {"id": "freelance_client",  "label": "客户沟通/提案",  "color": "#F97316", "group": "freelance"},
+    {"id": "freelance_finance", "label": "报价合同/记账",  "color": "#FBBF24", "group": "freelance"},
+    # 上班从业者
+    {"id": "office_doc",   "label": "文档/会议纪要",  "color": "#3B82F6", "group": "office"},
+    {"id": "office_data",  "label": "数据/报表分析", "color": "#6366F1", "group": "office"},
+    {"id": "office_email", "label": "邮件/协作",     "color": "#0EA5E9", "group": "office"},
+    {"id": "office_pm",    "label": "项目/周报",     "color": "#8B5CF6", "group": "office"},
+    # 育人教育者
+    {"id": "edu_prepare", "label": "备课/课件",     "color": "#10B981", "group": "educator"},
+    {"id": "edu_grade",   "label": "作业批改/测评", "color": "#14B8A6", "group": "educator"},
+    {"id": "edu_tutor",   "label": "学情辅导/答疑", "color": "#22C55E", "group": "educator"},
+    {"id": "edu_home",    "label": "家校沟通",      "color": "#84CC16", "group": "educator"},
+    # 电商创业
+    {"id": "biz_product", "label": "商品/营销文案", "color": "#EC4899", "group": "commerce"},
+    {"id": "biz_service", "label": "客服/转化",     "color": "#F43F5E", "group": "commerce"},
+    {"id": "biz_ops",     "label": "运营/投放",     "color": "#D946EF", "group": "commerce"},
+    # 通用提效
+    {"id": "general_write",    "label": "通用写作",      "color": "#64748B", "group": "general"},
+    {"id": "general_research", "label": "资料/调研",     "color": "#06B6D4", "group": "general"},
+    {"id": "general_agent",    "label": "智能体/自动化", "color": "#A855F7", "group": "general"},
+]
+SCENE_GROUPS: list = [
+    {"id": "freelance", "label": "自由职业者"},
+    {"id": "office",    "label": "上班从业者"},
+    {"id": "educator",  "label": "育人教育者"},
+    {"id": "commerce",  "label": "电商创业"},
+    {"id": "general",   "label": "通用提效"},
+]
+_VALID_SCENE_IDS = {s["id"] for s in MARKET_SCENES}
+
+
+def _scene_label(scene_id):
+    return next((s["label"] for s in MARKET_SCENES if s["id"] == scene_id), None)
+
+
+def _classify_scene(name: str, description: Optional[str], content: Optional[str], db: Session) -> Optional[str]:
+    """用平台文本模型把应用归类到面向用户的业务场景之一；失败返回 None（不阻断导入）。"""
     try:
         text_model = _resolve_auto_model("text", db)
         if not text_model:
@@ -225,9 +264,10 @@ def _classify_capability(name: str, description: Optional[str], content: Optiona
         )
         if not api_url:
             return None
-        options = "、".join(f"{c['id']}({c['label']})" for c in CAPABILITY_TYPES)
+        options = "、".join(f"{s['id']}({s['label']})" for s in MARKET_SCENES)
         sys_prompt = (
-            "你是应用市场的能力分类器。根据应用名称、描述与内容，把它精确归类到下列能力之一："
+            "你是 AI 应用市场的『业务场景分类器』。请站在使用者视角，根据应用名称、描述与内容，"
+            "判断它最常被哪一类【人群 / 岗位 / 业务场景】的用户使用，并归类到下列场景之一："
             f"{options}。\n只返回一个 JSON 对象：{{\"capability\": \"<id>\"}}，不要任何额外解释或 Markdown。"
         )
         user_text = f"名称：{name}\n描述：{description or ''}\n内容摘要：{(content or '')[:2000]}"
@@ -247,7 +287,7 @@ def _classify_capability(name: str, description: Optional[str], content: Optiona
         data = r.json()
         text_out = data.get("choices", [{}])[0].get("message", {}).get("content", "")
         m = re.search(r'"capability"\s*:\s*"([a-z_]+)"', text_out)
-        if m and m.group(1) in {c["id"] for c in CAPABILITY_TYPES}:
+        if m and m.group(1) in _VALID_SCENE_IDS:
             return m.group(1)
         return None
     except Exception:
@@ -283,9 +323,9 @@ def detect_capability(
     db: Session = Depends(get_db),
     current_user: User = Depends(get_current_user),
 ):
-    """导入前 AI 验证阶段：根据名称/描述/内容识别能力分类，供前台预填并允许用户修改。"""
-    cap = _classify_capability(req.name, req.description, req.skill_content, db)
-    label = next((c["label"] for c in CAPABILITY_TYPES if c["id"] == cap), None)
+    """导入前 AI 验证阶段：根据名称/描述/内容识别业务场景分类，供前台预填并允许用户修改。"""
+    cap = _classify_scene(req.name, req.description, req.skill_content, db)
+    label = _scene_label(cap)
     return {"code": 0, "data": {"capability": cap, "label": label}, "message": "ok"}
 
 
@@ -528,7 +568,7 @@ def upload_app(
     )
     # 能力分类：前端显式指定优先；否则导入阶段由 AI 自动归类；都不行则留空（不阻断导入）
     _classify_content = req.skill_content or req.download_url or ""
-    app.capability = req.capability or _classify_capability(req.name, req.description, _classify_content, db) or None
+    app.capability = req.capability or _classify_scene(req.name, req.description, _classify_content, db) or None
     db.add(app)
     db.commit()
     db.refresh(app)