feat(ai): AI 教练 —— 晨间简报、运动处方、趋势归因与 Copilot

数值全部在服务端算好再交给模型，模型只做解读。让模型从 CSV 里自己推
z 分数，它算错的次数足以让简报引用图表反驳它的数字。

- services/insights.py：z 分数（28 天个人基线，且**排除当天**——用一个
  值参与算出来的均值去衡量它自己，会把真实离群点摊平）、13 个月趋势斜率
  （按序数日期最小二乘，手表放充电器上一周不会压缩 x 轴）、近 7 天活动量
  对比。
- services/coach.py：三套提示词 + 回复解析，每套都配一个规则引擎版本。
  网关一次生成要几分钟，上游被限流时给一个朴素的答案，好过给一张空卡片。
- services/ai.py：多轮 chat()、SSE stream()、complete()/stream_chat()，
  以及 extract_json()——上游是推理模型，可见输出以思维链开头，所以从末尾
  倒着找最后一个配平的 JSON（字符串感知，扛得住引号里的 } 和转义引号）。
- 接口 briefing / trend-insight / copilot(SSE)，缓存表 ai_insights。
- 前端：今日页晨报卡（后台生成 + 轮询升级）、全局 Copilot 浮窗、指标详情
  页归因面板。features.ai 打开。

实测（对着自建 ai-gateway）：晨报一次 273 秒，缓存命中 18 毫秒——所以简报
绝不能同步阻塞首屏。网关的流式通道比阻塞通道更不可靠：同一条提示词流式
139 秒后返回「所有模型均不可用」，阻塞则成功，因此 stream_chat() 在流式零
输出时对同一模型退回非流式重试。Copilot 实测 TTFB 9ms、全程 40 秒。

顺带修两处：refresh 原来只跳过缓存读、不删行，导致「重新生成」后的轮询读
到旧行、看到 cached 就停了，用户一直盯着他刚要求替换掉的那段字；基线零方差
时原来返回 z=0.0，把「和每一条观测都不同」标成「完全正常」，改为 z=null。

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

backend/routes/analysis.py

@@ -1,9 +1,12 @@
-"""Analysis routes: trends + recommendations."""
-from flask import Blueprint, request, g, jsonify
+"""Analysis routes: trends, recommendations, and the AI coach."""
+import json
+
+from flask import Blueprint, Response, request, g, jsonify
 
 from auth import require_auth
 from services import analysis as analysis_svc
 from services import ai as ai_svc
+from services import insights
 
 bp = Blueprint("analysis", __name__)
 
@@ -47,3 +50,88 @@ def ai_recommendations():
     return jsonify(
         analysis_svc.get_ai_recommendations(g.user_id, model, days, refresh)
     )
+
+
+def _flag(name):
+    return request.args.get(name) in ("1", "true", "yes")
+
+
+@bp.route("/briefing", methods=["GET"])
+@require_auth
+def briefing():
+    """AI 晨间简报 + 今日运动处方, plus the computed context behind it.
+
+    Answers immediately. When no cached model answer matches the current data
+    the rule-based briefing is returned with `meta.pending`, and a generation
+    runs in the background — a model round-trip costs minutes, which cannot
+    sit in the first paint of the 今日 screen. Poll the same URL to pick up
+    the model's version.
+
+    `?wait=1` blocks for the model instead, for a deliberate regenerate.
+    """
+    return jsonify(analysis_svc.get_briefing(
+        g.user_id,
+        date=request.args.get("date"),
+        model=request.args.get("model") or None,
+        refresh=_flag("refresh"),
+        wait=_flag("wait"),
+    ))
+
+
+@bp.route("/trend-insight", methods=["GET"])
+@require_auth
+def trend_insight():
+    """Attribution for one metric over a selected span (chart brush)."""
+    metric = request.args.get("metric")
+    start = request.args.get("startDate")
+    end = request.args.get("endDate")
+    if not (metric and start and end):
+        return jsonify({"error": "缺少 metric / startDate / endDate 参数"}), 400
+    if metric not in insights.METRICS:
+        return jsonify({
+            "error": f"不支持的指标: {metric}",
+            "supported": sorted(insights.METRICS),
+        }), 400
+    return jsonify(analysis_svc.get_trend_insight(
+        g.user_id, metric, start, end,
+        model=request.args.get("model") or None,
+        refresh=_flag("refresh"),
+    ))
+
+
+@bp.route("/copilot", methods=["POST"])
+@require_auth
+def copilot():
+    """Health Copilot, streamed as server-sent events.
+
+    Streaming is about keeping the connection honest as much as about speed:
+    the upstream can think for minutes before its first token, and a plain
+    JSON request that long is indistinguishable from a hang — to the user, to
+    a proxy, and to Gunicorn's worker timeout.
+    """
+    body = request.get_json(silent=True) or {}
+    question = (body.get("question") or "").strip()
+    if not question:
+        return jsonify({"error": "缺少 question"}), 400
+
+    history = body.get("history")
+    history = history if isinstance(history, list) else []
+    # Read off `g` here, not inside the generator: the request context is torn
+    # down before the first chunk is pulled, and touching g there raises.
+    user_id = g.user_id
+    date = body.get("date")
+    model = body.get("model") or None
+
+    def events():
+        for event, data in analysis_svc.copilot_stream(
+            user_id, question, history, date, model
+        ):
+            yield f"event: {event}\ndata: {json.dumps(data, ensure_ascii=False)}\n\n"
+
+    return Response(
+        events(),
+        mimetype="text/event-stream",
+        # X-Accel-Buffering stops nginx-style proxies from holding the stream
+        # until it completes, which would undo the point of streaming it.
+        headers={"Cache-Control": "no-cache", "X-Accel-Buffering": "no"},
+    )