Feature/wellness checkin

backend/app/api/checkins.py

@@ -18,6 +18,9 @@ class CheckinReq(BaseModel):
 @router.post("")
 async def insert_checkin(req: CheckinReq, user_id: str = Depends(get_current_user)):
     db = get_db()
+    thirty_days_ago = datetime.datetime.utcnow() - datetime.timedelta(days=30)
+    await db.checkin_logs.delete_many({"user_id": user_id, "created_at": {"$lt": thirty_days_ago}})
+
     log_id = str(uuid.uuid4())
     gap_hours = req.gap_hours if req.gap_hours is not None else req.food_gap_hours
     await db.checkin_logs.insert_one({

backend/app/api/insights.py

@@ -346,284 +346,16 @@ async def get_runway_forecast(user_id: str = Depends(get_current_user)):
 @router.get("/wellness")
 async def get_wellness_insights(user_id: str = Depends(get_current_user)):
     db = get_db()
-    now = datetime.datetime.utcnow()
-
-    # Fetch last 60 days of transactions
-    since = now - datetime.timedelta(days=60)
-    cursor = db.transactions.find({"user_id": user_id, "created_at": {"$gte": since}}).sort("created_at", -1)
-    txns = await cursor.to_list(length=2000)
-
-    # Fetch user profile
-    profile = await db.profiles.find_one({"_id": user_id})
-    if not profile:
-        profile = {}
-
-    # 1. Late-night activity (last 7 days, hours 0 to 4)
-    since_7 = now - datetime.timedelta(days=7)
-    late_txns_7d = [
-        t for t in txns
-        if t.get("created_at") and t["created_at"] >= since_7 and (
-            0 <= t["created_at"].hour < 5
-        )
-    ]
-    late_night_spend_7d = len(late_txns_7d)
-
-    # 2. Meal regularity: avg_food_gap_hours_7d
-    food_txns_7d = [
-        t for t in txns
-        if t.get("category") == "food" and t.get("created_at") and t["created_at"] >= since_7
-    ]
-    food_txns_7d.sort(key=lambda t: t["created_at"])
-
-    gaps_7d = []
-    if len(food_txns_7d) > 0:
-        for i in range(1, len(food_txns_7d)):
-            gap = (food_txns_7d[i]["created_at"] - food_txns_7d[i-1]["created_at"]).total_seconds() / 3600.0
-            gaps_7d.append(gap)
-        current_gap = (now - food_txns_7d[-1]["created_at"]).total_seconds() / 3600.0
-        gaps_7d.append(current_gap)
-        avg_food_gap_hours_7d = sum(gaps_7d) / len(gaps_7d)
-    else:
-        avg_food_gap_hours_7d = 168.0
-
-    # Calculate unpaid pool debts (committed spend runway impact)
-    unpaid_pool_debt_paise = 0
-    user_doc = await db.users.find_one({"_id": user_id})
-    full_name = user_doc.get("full_name", "") if user_doc else ""
-    if full_name and profile and profile.get("wing_label"):
-        wing_label = profile["wing_label"]
-        def local_name_key(v):
-            return " ".join((v or "").strip().split()).casefold()
-
-        async for p in db.cart_pools.find({"wing_label": wing_label, "status": "completed", "host_id": {"$ne": user_id}}):
-            pool_id = p["_id"]
-            items_cursor = db.cart_pool_items.find({"pool_id": pool_id})
-            items = await items_cursor.to_list(length=1000)
-
-            participants = list(set(it["added_by_name"] for it in items if it.get("is_purchased", True)))
-            user_items = [it for it in items if it.get("is_purchased", True) and local_name_key(it["added_by_name"]) == local_name_key(full_name)]
-            if user_items:
-                payments = p.get("payments", [])
-                user_payment = next((pay for pay in payments if local_name_key(pay["name"]) == local_name_key(full_name)), None)
-                if not user_payment or user_payment.get("status") != "verified":
-                    p_items_total = sum(it["estimated_price"] for it in user_items)
-                    final_overhead = p.get("final_overhead", 0)
-                    final_discount = p.get("final_discount", 0)
-                    net_overhead = final_overhead - final_discount
-                    num_people = len(participants)
-                    overhead_share = int(net_overhead / num_people) if num_people > 0 else 0
-                    unpaid_pool_debt_paise += (p_items_total + overhead_share)
-
-    # 3. Financial runway & safe daily limit
-    cycle_start_day = profile.get("cycle_start_day") or 1
-    monthly_allowance = profile.get("monthly_allowance") or 1000000  # in paise
-    total_allowance_rs = monthly_allowance / 100
-
-    cycle_start = get_cycle_start(cycle_start_day, now)
-    cycle_end = get_cycle_end(cycle_start)
-
-    cycle_txns = [t for t in txns if t.get("created_at") and t["created_at"] >= cycle_start]
-    total_spent_rs = (sum(t.get("amount", 0) for t in cycle_txns) + unpaid_pool_debt_paise) / 100
-    remaining_rs = max(0.0, total_allowance_rs - total_spent_rs)
-
-    days_since_start = max(1, (now - cycle_start).days)
-    avg_daily_spend_rs = total_spent_rs / days_since_start
-    days_left = max(1, (cycle_end - now).days)
-
-    if avg_daily_spend_rs > 0:
-        runway_days = int(remaining_rs / avg_daily_spend_rs)
-    else:
-        runway_days = days_left
-
-    runway_days = min(runway_days, days_left + 5)
-
-    # safe_daily_limit_rs
-    safe_daily_limit_rs = remaining_rs / days_left
-
-    # 4. Spending velocity
-    spend_7_rs = sum(t.get("amount", 0) for t in txns if t.get("created_at") and t["created_at"] >= since_7) / 100.0
-    avg_daily_spend_7d_rs = spend_7_rs / 7.0
-
-    if safe_daily_limit_rs > 0:
-        spend_velocity = avg_daily_spend_7d_rs / safe_daily_limit_rs
-    else:
-        spend_velocity = 1.5 if avg_daily_spend_7d_rs > 0 else 0.0
-
-    # 5. Exam window
-    in_exam_period = False
-    if profile:
-        exam_start = profile.get("exam_start_date")
-        exam_end = profile.get("exam_end_date")
-        if exam_start and exam_end:
-            try:
-                import datetime as dt
-                es = dt.datetime.fromisoformat(str(exam_start))
-                ee = dt.datetime.fromisoformat(str(exam_end) + "T23:59:59")
-                if es <= now <= ee:
-                    in_exam_period = True
-            except Exception:
-                pass
-
-    # 6. Social signal from cart pools
-    user_doc = await db.users.find_one({"_id": user_id})
-    full_name = user_doc.get("full_name", "") if user_doc else ""
-    user_hosted_pools = await db.cart_pools.find({"host_id": user_id}).to_list(length=100)
-    participated_pool_ids = []
-    if full_name:
-        import re
-        name_regex = re.compile(f"^{re.escape(full_name)}$", re.IGNORECASE)
-        user_items = await db.cart_pool_items.find({"added_by_name": name_regex}).to_list(length=500)
-        participated_pool_ids = [item["pool_id"] for item in user_items]
-
-    all_pool_ids = list(set([p["_id"] for p in user_hosted_pools] + participated_pool_ids))
-    if all_pool_ids:
-        latest_pools = await db.cart_pools.find({"_id": {"$in": all_pool_ids}}).sort("created_at", -1).to_list(length=1)
-        if latest_pools:
-            last_pool_time = latest_pools[0].get("created_at")
-            days_since_last_pool = (now - last_pool_time).days
-        else:
-            days_since_last_pool = None
-    else:
-        days_since_last_pool = None
-
-    # Calculate Wellness Score
-    score = 100
-
-    # Sleep: late_night_spend_7d > 3 (-20), > 1 (-10)
-    if late_night_spend_7d > 3:
-        score -= 20
-    elif late_night_spend_7d > 1:
-        score -= 10
-
-    # Meal regularity: avg_food_gap_hours_7d > 10 (-20), > 6 (-10)
-    if avg_food_gap_hours_7d > 10:
-        score -= 20
-    elif avg_food_gap_hours_7d > 6:
-        score -= 10
-
-    # Runway: runway_days < 5 (-20), < 10 (-10)
-    if runway_days < 5:
-        score -= 20
-    elif runway_days < 10:
-        score -= 10
-
-    # Exam pressure: in_exam_window: -15
-    if in_exam_period:
-        score -= 15
-
-    # Spending control: spend_velocity > 1.4 (-15), > 1.2 (-8)
-    if spend_velocity > 1.4:
-        score -= 15
-    elif spend_velocity > 1.2:
-        score -= 8
-
-    # Social signal: days_since_last_pool > 7 (-10)
-    if days_since_last_pool is not None and days_since_last_pool > 7:
-        score -= 10
-
-    score = max(0, min(100, score))
-
-    # Determine status bucket and messages
-    if score >= 70:
-        status = "steady"
-        label = "Your routine looks steady"
-        message = "Your routine looks steady this week. Keep meals regular and stay within today's safe spend target."
-    elif score >= 50:
-        status = "watch"
-        label = "A few patterns need attention"
-        message = "A few patterns need attention: your food timing, spending pace, or exam pressure is starting to stack up. Pick one reset today: a proper meal, a low-spend window, or a short break."
-    else:
-        status = "stressed"
-        label = "Pattern suggests high stress"
-        message = "Your recent pattern suggests you may be stretched thin. You do not need to fix everything today; start with one meal and one planned spend decision, then check in again."
-
-    # Construct signals list
-    signals = []
-
-    # Food gap signal
-    food_gap_severity = "ok"
-    if avg_food_gap_hours_7d > 10:
-        food_gap_severity = "stressed"
-    elif avg_food_gap_hours_7d > 6:
-        food_gap_severity = "watch"
-    signals.append({
-        "key": "food_gap",
-        "label": "Avg Food gap",
-        "value": f"{avg_food_gap_hours_7d:.1f}h" if avg_food_gap_hours_7d < 168.0 else "—",
-        "severity": food_gap_severity,
-        "detail": "Long gaps between meals detected" if food_gap_severity != "ok" else "Regular meal timing"
-    })
-
-    # Runway signal
-    runway_severity = "ok"
-    if runway_days < 5:
-        runway_severity = "stressed"
-    elif runway_days < 10:
-        runway_severity = "watch"
-    signals.append({
-        "key": "runway",
-        "label": "Runway",
-        "value": f"{runway_days} days" if runway_days is not None else "—",
-        "severity": runway_severity,
-        "detail": "Allowance may not last the cycle" if runway_severity != "ok" else "Runway looks stable"
-    })
-
-    # Late night signal
-    late_night_severity = "ok"
-    if late_night_spend_7d > 3:
-        late_night_severity = "stressed"
-    elif late_night_spend_7d > 1:
-        late_night_severity = "watch"
-    signals.append({
-        "key": "late_night",
-        "label": "Late-night spending",
-        "value": f"{late_night_spend_7d} txns",
-        "severity": late_night_severity,
-        "detail": "Frequent late-night activity" if late_night_severity != "ok" else "Healthy nighttime routine"
-    })
-
-    # Velocity signal
-    velocity_severity = "ok"
-    if spend_velocity > 1.4:
-        velocity_severity = "stressed"
-    elif spend_velocity > 1.2:
-        velocity_severity = "watch"
-    signals.append({
-        "key": "velocity",
-        "label": "Spend velocity",
-        "value": f"{spend_velocity:.2f}x",
-        "severity": velocity_severity,
-        "detail": "Spending is accelerating rapidly" if velocity_severity == "stressed" else "Spending is slightly elevated" if velocity_severity == "watch" else "Spending velocity is stable"
-    })
-
-    # Exam signal
-    exam_severity = "stressed" if in_exam_period else "ok"
-    signals.append({
-        "key": "exam",
-        "label": "Exam period",
-        "value": "Active" if in_exam_period else "No",
-        "severity": exam_severity,
-        "detail": "Active exam schedule" if in_exam_period else "No exams active"
-    })
-
-    # Social signal from cart pools
-    pool_severity = "stressed" if (days_since_last_pool is not None and days_since_last_pool > 7) else "ok"
-    signals.append({
-        "key": "cart_pool",
-        "label": "Social index",
-        "value": f"{days_since_last_pool}d idle" if days_since_last_pool is not None else "None",
-        "severity": pool_severity,
-        "detail": "Low cart pool participation recently (possible social withdrawal)" if pool_severity == "stressed" else "Active in cart pools"
-    })
-
+    from app.services.wellness import compute_wellness
+    package = await compute_wellness(db, user_id)
     return {
-        "score": score,
-        "status": status,
-        "label": label,
-        "message": message,
-        "signals": signals,
-        "generated_by": "local_rules",
-        "avg_food_gap_hours_7d": round(avg_food_gap_hours_7d, 1)
+        "score": package["score"],
+        "status": package["status"],
+        "label": package["label"],
+        "message": package["message"],
+        "signals": package["signals"],
+        "generated_by": package["generated_by"],
+        "avg_food_gap_hours_7d": package["avg_food_gap_hours_7d"]
     }