HealthLog/src/lib/insights/mood-status.ts

import { prisma } from "@/lib/db";
import { resolveProvider } from "@/lib/ai/provider";
import { getMoodSystemPrompt, getMoodUserPrompt } from "@/lib/ai/prompts/mood";
import { getNoKeyMoodStatusText } from "@/lib/insights/no-key-fallbacks";
import {
  formatPreviousContextForPrompt,
  getPreviousInsightContext,
} from "@/lib/insights/memory";
import {
  pearsonCorrelation,
  type PairedPoint,
} from "@/lib/analytics/correlations";
import {
  applyPayloadBudget,
  dayOffsetToBerlinDayKey,
  type DailyBucket,
} from "@/lib/insights/bucket-series";
import { stripChartTokens } from "@/lib/insights/chart-tokens";
import { annotate } from "@/lib/logging/context";

const BERLIN_DAY_FORMATTER = new Intl.DateTimeFormat("en-US", {
  timeZone: "Europe/Berlin",
  year: "numeric",
  month: "2-digit",
  day: "2-digit",
});

type SupportedLocale = "de" | "en";

function toBerlinDayKey(date: Date): string {
  const parts = BERLIN_DAY_FORMATTER.formatToParts(date);
  const year = parts.find((part) => part.type === "year")?.value;
  const month = parts.find((part) => part.type === "month")?.value;
  const day = parts.find((part) => part.type === "day")?.value;

  if (!year || !month || !day) {
    throw new Error("Could not derive Berlin day key");
  }

  return `${year}-${month}-${day}`;
}

function round(value: number, digits = 1): number {
  const factor = 10 ** digits;
  return Math.round(value * factor) / factor;
}

function average(values: number[]): number {
  if (values.length === 0) return 0;
  return values.reduce((sum, value) => sum + value, 0) / values.length;
}

function normalizeSummaryText(value: string): string {
  return stripChartTokens(value).replace(/\s+/g, " ").trim();
}

function normalizeLocale(value: string | null | undefined): SupportedLocale {
  return value === "en" ? "en" : "de";
}

function summarizeSeries(series: Array<{ value: number }>) {
  if (series.length === 0) return null;
  const first = series[0].value;
  const last = series[series.length - 1].value;
  return {
    points: series.length,
    start: round(first, 2),
    end: round(last, 2),
    delta: round(last - first, 2),
    mean: round(average(series.map((entry) => entry.value)), 2),
    min: round(Math.min(...series.map((entry) => entry.value)), 2),
    max: round(Math.max(...series.map((entry) => entry.value)), 2),
  };
}

/**
 * Pair two daily-bucket series on `dayOffset`. The synthesised `date`
 * field is anchored at the UTC midnight of the Berlin calendar day —
 * `dayOffsetToBerlinDayKey()` is the source of truth so DST boundaries
 * don't slip the day-key by one. Each pair also carries `dayKey`
 * directly so callers can label points without re-formatting.
 */
function pairDailyBuckets(
  seriesA: DailyBucket[],
  seriesB: DailyBucket[],
  now: Date,
): Array<PairedPoint & { dayKey: string }> {
  const mapB = new Map(seriesB.map((entry) => [entry.dayOffset, entry.value]));

  return seriesA
    .map((entry) => {
      const b = mapB.get(entry.dayOffset);
      if (b == null) return null;
      const dayKey = dayOffsetToBerlinDayKey(now, entry.dayOffset);
      const [y, m, d] = dayKey.split("-").map(Number);
      return {
        a: entry.value,
        b,
        date: new Date(Date.UTC(y, m - 1, d)),
        dayKey,
      };
    })
    .filter(
      (entry): entry is PairedPoint & { dayKey: string } => entry !== null,
    );
}

export async function generateMoodStatusForUser(
  userId: string,
  options?: {
    locale?: string | null;
    force?: boolean;
  },
): Promise<{
  hasProvider: boolean;
  text: string | null;
  cached: boolean;
  updatedAt: string | null;
}> {
  const locale = normalizeLocale(options?.locale);
  const force = options?.force === true;
  const cacheAction = `insights.mood-status.${locale}`;
  const todayKey = toBerlinDayKey(new Date());

  const provider = await resolveProvider(userId);
  if (provider.type === "none") {
    return {
      hasProvider: false,
      text: getNoKeyMoodStatusText(locale),
      cached: true,
      updatedAt: null,
    };
  }

  const latestCache = await prisma.auditLog.findFirst({
    where: { userId, action: cacheAction },
    orderBy: { createdAt: "desc" },
    select: { createdAt: true, details: true },
  });

  if (!force && latestCache?.details) {
    try {
      const parsed = JSON.parse(latestCache.details) as {
        dateKey?: string;
        text?: string;
      };
      if (
        parsed.dateKey === todayKey &&
        typeof parsed.text === "string" &&
        parsed.text.trim().length > 0
      ) {
        return {
          hasProvider: true,
          text: parsed.text,
          cached: true,
          updatedAt: latestCache.createdAt.toISOString(),
        };
      }
    } catch {
      // ignore invalid cache payload
    }
  }

  const entries = await prisma.moodEntry.findMany({
    where: {
      userId,
    },
    orderBy: { date: "asc" },
    select: {
      date: true,
      score: true,
      tags: true,
      moodLoggedAt: true,
    },
  });

  const now = new Date();

  const moodSeries = applyPayloadBudget(
    entries.map((entry) => ({
      measuredAt: entry.moodLoggedAt,
      value: entry.score,
    })),
    { now },
  );
  const moodSummary = summarizeSeries(
    moodSeries.daily.map((bucket) => ({ value: bucket.value })),
  );

  const greenMin = 3.5;
  const greenMax = 5;
  const orangeMin = 2;
  const orangeMax = 3.5;

  // "Last 30 daily points" = the newest 30 daily buckets (offsets 0..29).
  const recentMoodDaily = moodSeries.daily.filter(
    (bucket) => bucket.dayOffset < 30,
  );
  const inTargetPctLast30DailyPoints =
    recentMoodDaily.length === 0
      ? null
      : round(
          (recentMoodDaily.filter(
            (entry) => entry.value >= greenMin && entry.value <= greenMax,
          ).length /
            recentMoodDaily.length) *
            100,
          1,
        );

  // daily[0] = newest bucket (lowest dayOffset).
  const latestMood = moodSeries.daily[0] ?? null;
  const previousMood = moodSeries.daily[1] ?? null;

  const oldestEntry = entries.length > 0 ? entries[0].moodLoggedAt : null;
  const newestEntry =
    entries.length > 0 ? entries[entries.length - 1].moodLoggedAt : null;
  const totalSpanDays =
    oldestEntry && newestEntry
      ? Math.round(
          (newestEntry.getTime() - oldestEntry.getTime()) /
            (24 * 60 * 60 * 1000),
        )
      : 0;
  const newestEntryDaysAgo = newestEntry
    ? Math.round((Date.now() - newestEntry.getTime()) / (24 * 60 * 60 * 1000))
    : null;

  // Fetch cross-metric context for enrichment
  const measurements = await prisma.measurement.findMany({
    where: {
      userId,
      type: { in: ["WEIGHT", "BLOOD_PRESSURE_SYS", "PULSE"] },
    },
    orderBy: { measuredAt: "asc" },
    select: { type: true, value: true, measuredAt: true },
  });

  const weightSeries = applyPayloadBudget(
    measurements
      .filter((m) => m.type === "WEIGHT")
      .map((m) => ({ measuredAt: m.measuredAt, value: m.value })),
    { now },
  );

  const sysSeries = applyPayloadBudget(
    measurements
      .filter((m) => m.type === "BLOOD_PRESSURE_SYS")
      .map((m) => ({ measuredAt: m.measuredAt, value: m.value })),
    { now },
  );

  const pulseSeries = applyPayloadBudget(
    measurements
      .filter((m) => m.type === "PULSE")
      .map((m) => ({ measuredAt: m.measuredAt, value: m.value })),
    { now },
  );

  // Correlations between mood and other metrics — pair on dayOffset so
  // the bucketed daily window aligns across metrics.
  const moodVsWeightPairs = pairDailyBuckets(
    moodSeries.daily,
    weightSeries.daily,
    now,
  );
  const moodVsWeightCorrelation = pearsonCorrelation(moodVsWeightPairs);

  const moodVsSysPairs = pairDailyBuckets(
    moodSeries.daily,
    sysSeries.daily,
    now,
  );
  const moodVsSysCorrelation = pearsonCorrelation(moodVsSysPairs);

  const moodVsPulsePairs = pairDailyBuckets(
    moodSeries.daily,
    pulseSeries.daily,
    now,
  );
  const moodVsPulseCorrelation = pearsonCorrelation(moodVsPulsePairs);

  // Extract tag frequencies from recent entries — keep the v1.4.5
  // ~90-day window so the model still gets a recency-weighted view of
  // tag patterns. The mood DB query already pulls 3 years (no where
  // filter); we slice by date here, not by record count.
  const tagWindowCutoff = new Date(now.getTime() - 90 * 24 * 60 * 60 * 1000);
  const recentEntries = entries.filter(
    (entry) => entry.moodLoggedAt.getTime() >= tagWindowCutoff.getTime(),
  );
  const tagCounts = new Map<string, { count: number; scoreSum: number }>();
  for (const entry of recentEntries) {
    if (entry.tags && Array.isArray(entry.tags)) {
      for (const tag of entry.tags as string[]) {
        const current = tagCounts.get(tag) ?? { count: 0, scoreSum: 0 };
        current.count += 1;
        current.scoreSum += entry.score;
        tagCounts.set(tag, current);
      }
    }
  }
  const tagSummary = Array.from(tagCounts.entries())
    .filter(([, stats]) => stats.count >= 2)
    .sort((a, b) => b[1].count - a[1].count)
    .slice(0, 10)
    .map(([tag, stats]) => ({
      tag,
      count: stats.count,
      avgScore: round(stats.scoreSum / stats.count, 2),
    }));

  const snapshot = {
    locale,
    generatedForDay: todayKey,
    focus: "mood",
    dataCoverage: {
      totalEntries: entries.length,
      totalSpanDays,
      newestEntryDaysAgo,
    },
    mood: {
      summary: moodSummary,
      series: moodSeries,
      latestDayFocus: latestMood
        ? {
            dayOffset: latestMood.dayOffset,
            value: latestMood.value,
            deltaToPreviousDailyPoint:
              previousMood == null
                ? null
                : round(latestMood.value - previousMood.value, 2),
          }
        : null,
      target: {
        greenMin,
        greenMax,
        orangeMin,
        orangeMax,
        inTargetPctLast30DailyPoints,
      },
      tags: tagSummary.length > 0 ? tagSummary : null,
    },
    crossMetricContext:
      weightSeries.daily.length >= 3 ||
      sysSeries.daily.length >= 3 ||
      pulseSeries.daily.length >= 3
        ? {
            weight:
              weightSeries.daily.length >= 3
                ? {
                    summary: summarizeSeries(
                      weightSeries.daily.map((bucket) => ({
                        value: bucket.value,
                      })),
                    ),
                    correlation: moodVsWeightCorrelation,
                  }
                : null,
            bloodPressureSystolic:
              sysSeries.daily.length >= 3
                ? {
                    summary: summarizeSeries(
                      sysSeries.daily.map((bucket) => ({
                        value: bucket.value,
                      })),
                    ),
                    correlation: moodVsSysCorrelation,
                  }
                : null,
            pulse:
              pulseSeries.daily.length >= 3
                ? {
                    summary: summarizeSeries(
                      pulseSeries.daily.map((bucket) => ({
                        value: bucket.value,
                      })),
                    ),
                    correlation: moodVsPulseCorrelation,
                  }
                : null,
          }
        : null,
  };

  const snapshotJson = JSON.stringify(snapshot, null, 2);

  annotate({
    action: { name: cacheAction },
    meta: { payload_size_bytes: snapshotJson.length },
  });

  const previousContext = await getPreviousInsightContext(
    userId,
    "mood-status",
    locale,
    12,
  );
  const previousContextBlock = formatPreviousContextForPrompt(
    previousContext,
    locale,
  );

  const result = await provider.generateCompletion({
    systemPrompt: getMoodSystemPrompt(locale),
    userPrompt: getMoodUserPrompt(
      snapshotJson,
      todayKey,
      locale,
      previousContextBlock,
    ),
    temperature: 0.3,
    maxTokens: 1000,
  });

  const content = result.content;
  if (typeof content !== "string" || content.trim().length === 0) {
    throw new Error("AI returned empty content for mood-status");
  }

  let summary = "";
  try {
    const parsed = JSON.parse(content) as { summary?: string };
    if (typeof parsed.summary === "string") {
      summary = parsed.summary;
    } else {
      summary = content;
    }
  } catch {
    summary = content;
  }

  summary = normalizeSummaryText(summary);
  if (!summary) {
    throw new Error("Mood-status summary was empty after normalization");
  }

  const created = await prisma.auditLog.create({
    data: {
      userId,
      action: cacheAction,
      details: JSON.stringify({
        dateKey: todayKey,
        locale,
        text: summary,
        providerType: provider.type,
        model: result.model ?? "unknown",
        tokensUsed: result.tokensUsed ?? null,
      }),
    },
    select: { createdAt: true },
  });

  return {
    hasProvider: true,
    text: summary,
    cached: false,
    updatedAt: created.createdAt.toISOString(),
  };
}

export function resolveMoodStatusLocale(
  locale: string | null | undefined,
): SupportedLocale {
  return normalizeLocale(locale);
}