feat: 老板台2.0 + 手机端适配 + 专家库 + 智囊入口
- 老板台: AI执行摘要卡 + 待办优先级排序 + 时间线视图 + 环形健康度 - 手机端: 事项看板折叠列表 + 7个页面响应式修复 + 底部安全边距 - 专家库: 新增用户端专家浏览页(参考管理端卡片风格) - 智囊入口: 底部Tab加"智囊" + 4个智囊页场景切换栏 + "我"页分组入口 - FAB弹窗: 场景快速入口 + 指令卡片优化 + 输入区sticky - 后端: /dashboard/summary + /dashboard/timeline API - 后端: life场景事实维度扩充(2→5) + 17个生活关键词优先级 - 前端: 抑制React DevTools startTime噪音错误 Generated with [Devin](https://devin.ai) Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
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selfrelease
@@ -2410,6 +2410,172 @@ def dashboard_today(authorization: str | None = Header(default=None)):
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conn.close()
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@app.get("/dashboard/summary")
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def dashboard_summary(authorization: str | None = Header(default=None)):
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"""老板台执行摘要:AI 用一句话总结当前状态和建议行动。
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降级策略:Kimi 不可用时返回规则摘要。
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"""
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phone = get_current_phone(authorization)
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if not phone:
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raise HTTPException(401, "未登录")
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conn = _matter_dsn()
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try:
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cur = conn.cursor()
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cur.execute(
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"SELECT id, title, risk_level, scene, status FROM matters "
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"WHERE user_phone = %s AND status != 'closed' ORDER BY updated_at DESC LIMIT 10",
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(phone,),
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)
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rows = cur.fetchall()
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open_matters = [{"id": r[0], "title": r[1], "risk_level": r[2], "scene": r[3], "status": r[4]} for r in rows]
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cur.execute(
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"SELECT COUNT(*) FROM matters WHERE user_phone = %s AND status = 'pending_confirm'",
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(phone,),
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)
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pending_count = cur.fetchone()[0]
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cur.execute(
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"SELECT COUNT(*) FROM expert_consultations WHERE user_phone = %s AND status = 'replied'",
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(phone,),
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)
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reply_count = cur.fetchone()[0]
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finally:
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conn.close()
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red_count = sum(1 for m in open_matters if m["risk_level"] == "red")
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orange_count = sum(1 for m in open_matters if m["risk_level"] == "orange")
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# 规则摘要(兜底)
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parts = []
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if red_count > 0:
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parts.append(f"有 {red_count} 项高风险事项需立即处理")
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if orange_count > 0:
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parts.append(f"{orange_count} 项中风险事项需关注")
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if pending_count > 0:
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parts.append(f"{pending_count} 个事项待你确认")
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if reply_count > 0:
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parts.append(f"{reply_count} 条专家回复待查看")
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if not parts:
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rule_summary = "当前无待办事项,经营状况良好。可主动发起咨询或查看经营健康度。"
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rule_action = "浏览智囊或查看事项看板"
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else:
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rule_summary = "、".join(parts) + "。"
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if red_count > 0:
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rule_action = "建议优先处理高风险事项"
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elif pending_count > 0:
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rule_action = "建议先确认待办事项"
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elif reply_count > 0:
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rule_action = "建议查看专家回复"
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else:
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rule_action = "建议关注中风险事项"
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# 尝试 AI 生成更自然的摘要
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try:
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if kimi and open_matters:
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matter_desc = "\n".join(
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f"- {m['title']}(风险:{m['risk_level']},场景:{m['scene']},状态:{m['status']})"
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for m in open_matters[:5]
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)
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prompt = (
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f"你是中小企业老板的AI助手。请根据以下数据,用一句话(不超过50字)总结当前经营状态,"
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f"并给出一个最优先的行动建议(不超过20字)。\n\n"
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f"待办事项:\n{matter_desc}\n"
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f"待确认:{pending_count}个,专家回复:{reply_count}条\n\n"
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f"返回 JSON 格式:{{\"summary\": \"...\", \"action\": \"...\"}}"
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)
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answer = kimi.chat(
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[{"role": "system", "content": "你是经营顾问助手,只返回JSON。"},
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{"role": "user", "content": prompt}],
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temperature=0.3, timeout=15,
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)
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answer = answer.strip()
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if answer.startswith("```"):
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answer = answer.split("\n", 1)[1] if "\n" in answer else answer[3:]
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if answer.endswith("```"):
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answer = answer[:-3]
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answer = answer.replace("\u201c", '"').replace("\u201d", '"').strip()
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start = answer.find("{")
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end = answer.rfind("}")
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if start != -1 and end != -1:
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import json as _json
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parsed = _json.loads(answer[start:end + 1])
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return {
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"summary": parsed.get("summary", rule_summary),
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"action": parsed.get("action", rule_action),
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"ai_generated": True,
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}
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except Exception:
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pass
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return {"summary": rule_summary, "action": rule_action, "ai_generated": False}
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@app.get("/dashboard/timeline")
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def dashboard_timeline(authorization: str | None = Header(default=None)):
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"""老板台时间线:按时间倒序聚合最近活动(案卡变更、专家回复、风险推送)。"""
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phone = get_current_phone(authorization)
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if not phone:
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raise HTTPException(401, "未登录")
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conn = _matter_dsn()
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try:
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cur = conn.cursor()
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items = []
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# 案卡最近更新
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cur.execute(
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"SELECT id, title, scene, status, risk_level, updated_at "
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"FROM matters WHERE user_phone = %s ORDER BY updated_at DESC LIMIT 8",
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(phone,),
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)
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for r in cur.fetchall():
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items.append({
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"type": "matter",
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"id": r[0],
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"title": r[1],
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"scene": r[2],
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"status": r[3],
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"risk_level": r[4],
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"time": r[5].isoformat() if r[5] else None,
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})
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# 专家回复
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cur.execute(
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"SELECT c.id, e.name, e.title, c.reply, c.replied_at "
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"FROM expert_consultations c JOIN experts e ON c.expert_id = e.id "
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"WHERE c.user_phone = %s AND c.status = 'replied' "
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"ORDER BY c.replied_at DESC LIMIT 5",
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(phone,),
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)
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for r in cur.fetchall():
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items.append({
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"type": "expert_reply",
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"id": r[0],
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"expert_name": r[1],
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"expert_title": r[2],
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"snippet": (r[3] or "")[:60],
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"time": r[4].isoformat() if r[4] else None,
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})
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# 风险推送
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try:
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cur.execute(
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"SELECT id, title, level, created_at FROM risk_alerts "
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"WHERE user_phone = %s ORDER BY created_at DESC LIMIT 5",
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(phone,),
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)
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for r in cur.fetchall():
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items.append({
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"type": "risk_alert",
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"id": r[0],
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"title": r[1],
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"level": r[2],
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"time": r[3].isoformat() if r[3] else None,
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})
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except Exception:
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pass # risk_alerts 表可能不存在
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# 按时间倒序
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items.sort(key=lambda x: x.get("time") or "", reverse=True)
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return {"results": items[:15]}
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finally:
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conn.close()
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@app.get("/team")
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def my_team(authorization: str | None = Header(default=None)):
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"""我的团队:咨询过的专家自动沉淀"""
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