Three new Foundation Models features to deepen user engagement with mental wellness: 1. AI Reflection Companion — personalized feedback after completing guided reflections, referencing the user's actual words with personality-pack-adapted tone 2. Mood Pattern Tags — auto-extracts theme tags (work, family, stress, etc.) from notes and reflections, displayed as colored pills on entries 3. Weekly Emotional Digest — BGTask-scheduled Sunday digest with headline, summary, highlight, and intention; shown as card in Insights tab with notification All features: on-device (zero cost), premium-gated, iOS 26+ with graceful degradation. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
156 lines
5.7 KiB
Swift
156 lines
5.7 KiB
Swift
//
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// FoundationModelsDigestService.swift
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// Reflect
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//
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// Generates weekly emotional digests using Foundation Models.
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//
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import Foundation
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import FoundationModels
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@available(iOS 26, *)
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@MainActor
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class FoundationModelsDigestService {
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// MARK: - Singleton
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static let shared = FoundationModelsDigestService()
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private let summarizer = MoodDataSummarizer()
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private init() {}
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// MARK: - Storage Keys
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private static let digestStorageKey = "latestWeeklyDigest"
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// MARK: - Digest Generation
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/// Generate a weekly digest from the past 7 days of mood data
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func generateWeeklyDigest() async throws -> WeeklyDigest {
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let calendar = Calendar.current
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let now = Date()
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let weekStart = calendar.date(byAdding: .day, value: -7, to: now)!
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let entries = DataController.shared.getData(
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startDate: weekStart,
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endDate: now,
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includedDays: [1, 2, 3, 4, 5, 6, 7]
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)
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let validEntries = entries.filter { ![.missing, .placeholder].contains($0.mood) }
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guard validEntries.count >= 3 else {
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throw InsightGenerationError.insufficientData
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}
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let session = LanguageModelSession(instructions: systemInstructions)
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let prompt = buildPrompt(entries: validEntries, weekStart: weekStart, weekEnd: now)
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let response = try await session.respond(to: prompt, generating: AIWeeklyDigestResponse.self)
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let digest = WeeklyDigest(
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headline: response.content.headline,
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summary: response.content.summary,
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highlight: response.content.highlight,
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intention: response.content.intention,
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iconName: response.content.iconName,
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generatedAt: Date(),
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weekStartDate: weekStart,
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weekEndDate: now
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)
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// Store the digest
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saveDigest(digest)
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return digest
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}
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/// Load the latest stored digest
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func loadLatestDigest() -> WeeklyDigest? {
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guard let data = GroupUserDefaults.groupDefaults.data(forKey: Self.digestStorageKey),
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let digest = try? JSONDecoder().decode(WeeklyDigest.self, from: data) else {
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return nil
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}
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return digest
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}
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// MARK: - Storage
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private func saveDigest(_ digest: WeeklyDigest) {
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if let data = try? JSONEncoder().encode(digest) {
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GroupUserDefaults.groupDefaults.set(data, forKey: Self.digestStorageKey)
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}
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}
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// MARK: - System Instructions
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private var systemInstructions: String {
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let personalityPack = UserDefaultsStore.personalityPackable()
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switch personalityPack {
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case .Default:
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return """
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You are a warm, supportive mood companion writing a weekly emotional digest. \
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Summarize the week's mood journey with encouragement and specificity. \
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Be personal, brief, and uplifting. Reference specific patterns from the data. \
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SF Symbols: sun.max.fill, heart.fill, star.fill, leaf.fill, sparkles
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"""
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case .MotivationalCoach:
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return """
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You are a HIGH ENERGY motivational coach delivering a weekly performance review! \
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Celebrate wins, frame challenges as growth opportunities, and fire them up for next week! \
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Use exclamations and power language! \
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SF Symbols: trophy.fill, flame.fill, bolt.fill, figure.run, star.fill
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"""
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case .ZenMaster:
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return """
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You are a calm Zen master offering a weekly reflection on the emotional journey. \
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Use nature metaphors, gentle wisdom, and serene observations. Find meaning in all moods. \
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SF Symbols: leaf.fill, moon.fill, drop.fill, sunrise.fill, wind
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"""
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case .BestFriend:
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return """
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You are their best friend doing a weekly check-in on how they've been. \
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Be warm, casual, validating, and conversational. Celebrate with them, commiserate together. \
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SF Symbols: heart.fill, hand.thumbsup.fill, sparkles, face.smiling.fill, balloon.fill
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"""
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case .DataAnalyst:
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return """
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You are a clinical data analyst delivering a weekly mood metrics report. \
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Reference exact numbers, percentages, and observed trends. Be objective but constructive. \
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SF Symbols: chart.bar.fill, chart.line.uptrend.xyaxis, number, percent, doc.text.magnifyingglass
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"""
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}
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}
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// MARK: - Prompt Construction
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private func buildPrompt(entries: [MoodEntryModel], weekStart: Date, weekEnd: Date) -> String {
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let formatter = DateFormatter()
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formatter.dateStyle = .medium
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let moodList = entries.sorted { $0.forDate < $1.forDate }.map { entry in
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let day = entry.forDate.formatted(.dateTime.weekday(.abbreviated))
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let mood = entry.mood.widgetDisplayName
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let hasNotes = entry.notes != nil && !entry.notes!.isEmpty
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let noteSnippet = hasNotes ? " (\(String(entry.notes!.prefix(50))))" : ""
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return "\(day): \(mood)\(noteSnippet)"
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}.joined(separator: "\n")
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let summary = summarizer.summarize(entries: entries, periodName: "this week")
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let avgMood = String(format: "%.1f", summary.averageMoodScore)
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return """
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Generate a weekly emotional digest for \(formatter.string(from: weekStart)) - \(formatter.string(from: weekEnd)):
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\(moodList)
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Average mood: \(avgMood)/5, Trend: \(summary.recentTrend), Stability: \(String(format: "%.0f", summary.moodStabilityScore * 100))%
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Current streak: \(summary.currentLoggingStreak) days
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Write a warm, personalized weekly digest.
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"""
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}
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}
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