Add AI-powered mental wellness features: Reflection Companion, Pattern Tags, Weekly Digest

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>

Shared/Services/FoundationModelsDigestService.swift

@@ -0,0 +1,155 @@
+//
+//  FoundationModelsDigestService.swift
+//  Reflect
+//
+//  Generates weekly emotional digests using Foundation Models.
+//
+
+import Foundation
+import FoundationModels
+
+@available(iOS 26, *)
+@MainActor
+class FoundationModelsDigestService {
+
+    // MARK: - Singleton
+
+    static let shared = FoundationModelsDigestService()
+
+    private let summarizer = MoodDataSummarizer()
+
+    private init() {}
+
+    // MARK: - Storage Keys
+
+    private static let digestStorageKey = "latestWeeklyDigest"
+
+    // MARK: - Digest Generation
+
+    /// Generate a weekly digest from the past 7 days of mood data
+    func generateWeeklyDigest() async throws -> WeeklyDigest {
+        let calendar = Calendar.current
+        let now = Date()
+        let weekStart = calendar.date(byAdding: .day, value: -7, to: now)!
+
+        let entries = DataController.shared.getData(
+            startDate: weekStart,
+            endDate: now,
+            includedDays: [1, 2, 3, 4, 5, 6, 7]
+        )
+
+        let validEntries = entries.filter { ![.missing, .placeholder].contains($0.mood) }
+
+        guard validEntries.count >= 3 else {
+            throw InsightGenerationError.insufficientData
+        }
+
+        let session = LanguageModelSession(instructions: systemInstructions)
+        let prompt = buildPrompt(entries: validEntries, weekStart: weekStart, weekEnd: now)
+
+        let response = try await session.respond(to: prompt, generating: AIWeeklyDigestResponse.self)
+
+        let digest = WeeklyDigest(
+            headline: response.content.headline,
+            summary: response.content.summary,
+            highlight: response.content.highlight,
+            intention: response.content.intention,
+            iconName: response.content.iconName,
+            generatedAt: Date(),
+            weekStartDate: weekStart,
+            weekEndDate: now
+        )
+
+        // Store the digest
+        saveDigest(digest)
+
+        return digest
+    }
+
+    /// Load the latest stored digest
+    func loadLatestDigest() -> WeeklyDigest? {
+        guard let data = GroupUserDefaults.groupDefaults.data(forKey: Self.digestStorageKey),
+              let digest = try? JSONDecoder().decode(WeeklyDigest.self, from: data) else {
+            return nil
+        }
+        return digest
+    }
+
+    // MARK: - Storage
+
+    private func saveDigest(_ digest: WeeklyDigest) {
+        if let data = try? JSONEncoder().encode(digest) {
+            GroupUserDefaults.groupDefaults.set(data, forKey: Self.digestStorageKey)
+        }
+    }
+
+    // MARK: - System Instructions
+
+    private var systemInstructions: String {
+        let personalityPack = UserDefaultsStore.personalityPackable()
+
+        switch personalityPack {
+        case .Default:
+            return """
+            You are a warm, supportive mood companion writing a weekly emotional digest. \
+            Summarize the week's mood journey with encouragement and specificity. \
+            Be personal, brief, and uplifting. Reference specific patterns from the data. \
+            SF Symbols: sun.max.fill, heart.fill, star.fill, leaf.fill, sparkles
+            """
+        case .MotivationalCoach:
+            return """
+            You are a HIGH ENERGY motivational coach delivering a weekly performance review! \
+            Celebrate wins, frame challenges as growth opportunities, and fire them up for next week! \
+            Use exclamations and power language! \
+            SF Symbols: trophy.fill, flame.fill, bolt.fill, figure.run, star.fill
+            """
+        case .ZenMaster:
+            return """
+            You are a calm Zen master offering a weekly reflection on the emotional journey. \
+            Use nature metaphors, gentle wisdom, and serene observations. Find meaning in all moods. \
+            SF Symbols: leaf.fill, moon.fill, drop.fill, sunrise.fill, wind
+            """
+        case .BestFriend:
+            return """
+            You are their best friend doing a weekly check-in on how they've been. \
+            Be warm, casual, validating, and conversational. Celebrate with them, commiserate together. \
+            SF Symbols: heart.fill, hand.thumbsup.fill, sparkles, face.smiling.fill, balloon.fill
+            """
+        case .DataAnalyst:
+            return """
+            You are a clinical data analyst delivering a weekly mood metrics report. \
+            Reference exact numbers, percentages, and observed trends. Be objective but constructive. \
+            SF Symbols: chart.bar.fill, chart.line.uptrend.xyaxis, number, percent, doc.text.magnifyingglass
+            """
+        }
+    }
+
+    // MARK: - Prompt Construction
+
+    private func buildPrompt(entries: [MoodEntryModel], weekStart: Date, weekEnd: Date) -> String {
+        let formatter = DateFormatter()
+        formatter.dateStyle = .medium
+
+        let moodList = entries.sorted { $0.forDate < $1.forDate }.map { entry in
+            let day = entry.forDate.formatted(.dateTime.weekday(.abbreviated))
+            let mood = entry.mood.widgetDisplayName
+            let hasNotes = entry.notes != nil && !entry.notes!.isEmpty
+            let noteSnippet = hasNotes ? " (\(String(entry.notes!.prefix(50))))" : ""
+            return "\(day): \(mood)\(noteSnippet)"
+        }.joined(separator: "\n")
+
+        let summary = summarizer.summarize(entries: entries, periodName: "this week")
+        let avgMood = String(format: "%.1f", summary.averageMoodScore)
+
+        return """
+        Generate a weekly emotional digest for \(formatter.string(from: weekStart)) - \(formatter.string(from: weekEnd)):
+
+        \(moodList)
+
+        Average mood: \(avgMood)/5, Trend: \(summary.recentTrend), Stability: \(String(format: "%.0f", summary.moodStabilityScore * 100))%
+        Current streak: \(summary.currentLoggingStreak) days
+
+        Write a warm, personalized weekly digest.
+        """
+    }
+}

Shared/Services/FoundationModelsReflectionService.swift

@@ -0,0 +1,128 @@
+//
+//  FoundationModelsReflectionService.swift
+//  Reflect
+//
+//  Generates personalized AI feedback after a user completes a guided reflection.
+//
+
+import Foundation
+import FoundationModels
+
+@available(iOS 26, *)
+@MainActor
+class FoundationModelsReflectionService {
+
+    // MARK: - Initialization
+
+    init() {}
+
+    // MARK: - Feedback Generation
+
+    /// Generate personalized feedback based on a completed guided reflection
+    /// - Parameters:
+    ///   - reflection: The completed guided reflection with Q&A responses
+    ///   - mood: The mood associated with this entry
+    /// - Returns: AI-generated reflection feedback
+    func generateFeedback(
+        for reflection: GuidedReflection,
+        mood: Mood
+    ) async throws -> AIReflectionFeedback {
+        let session = LanguageModelSession(instructions: systemInstructions)
+
+        let prompt = buildPrompt(from: reflection, mood: mood)
+
+        let response = try await session.respond(
+            to: prompt,
+            generating: AIReflectionFeedback.self
+        )
+
+        return response.content
+    }
+
+    // MARK: - System Instructions
+
+    private var systemInstructions: String {
+        let personalityPack = UserDefaultsStore.personalityPackable()
+
+        switch personalityPack {
+        case .Default:
+            return defaultInstructions
+        case .MotivationalCoach:
+            return coachInstructions
+        case .ZenMaster:
+            return zenInstructions
+        case .BestFriend:
+            return bestFriendInstructions
+        case .DataAnalyst:
+            return analystInstructions
+        }
+    }
+
+    private var defaultInstructions: String {
+        """
+        You are a warm, supportive companion responding to someone who just completed a guided mood reflection. \
+        Validate their effort, reflect their own words back to them, and offer a gentle takeaway. \
+        Be specific — reference what they actually wrote. Keep each field to 1 sentence. \
+        SF Symbols: sparkles, heart.fill, star.fill, sun.max.fill, leaf.fill
+        """
+    }
+
+    private var coachInstructions: String {
+        """
+        You are a HIGH ENERGY motivational coach responding to someone who just completed a guided mood reflection! \
+        Celebrate their self-awareness, pump them up about the growth they showed, and give them a power move for tomorrow. \
+        Reference what they actually wrote. Keep each field to 1 sentence. Use exclamations! \
+        SF Symbols: trophy.fill, flame.fill, bolt.fill, star.fill, figure.run
+        """
+    }
+
+    private var zenInstructions: String {
+        """
+        You are a calm, mindful guide responding to someone who just completed a guided mood reflection. \
+        Acknowledge their practice of self-awareness with gentle wisdom. Use nature metaphors. \
+        Reference what they actually wrote. Keep each field to 1 sentence. Speak with serene clarity. \
+        SF Symbols: leaf.fill, moon.fill, drop.fill, sunrise.fill, wind
+        """
+    }
+
+    private var bestFriendInstructions: String {
+        """
+        You are their supportive best friend responding after they completed a guided mood reflection. \
+        Be warm, casual, and validating. Use conversational tone. \
+        Reference what they actually wrote. Keep each field to 1 sentence. \
+        SF Symbols: heart.fill, hand.thumbsup.fill, sparkles, star.fill, face.smiling.fill
+        """
+    }
+
+    private var analystInstructions: String {
+        """
+        You are a clinical data analyst providing feedback on a completed mood reflection. \
+        Note the cognitive patterns observed, the technique application quality, and a data-informed recommendation. \
+        Reference what they actually wrote. Keep each field to 1 sentence. Be objective but encouraging. \
+        SF Symbols: chart.bar.fill, brain.head.profile, doc.text.magnifyingglass, chart.line.uptrend.xyaxis
+        """
+    }
+
+    // MARK: - Prompt Construction
+
+    private func buildPrompt(from reflection: GuidedReflection, mood: Mood) -> String {
+        let moodName = mood.widgetDisplayName
+        let technique = reflection.moodCategory.techniqueName
+
+        let qaPairs = reflection.responses
+            .filter { !$0.answer.trimmingCharacters(in: .whitespacesAndNewlines).isEmpty }
+            .map { response in
+                let chips = response.selectedChips.isEmpty ? "" : " [themes: \(response.selectedChips.joined(separator: ", "))]"
+                return "Q: \(response.question)\nA: \(response.answer)\(chips)"
+            }
+            .joined(separator: "\n\n")
+
+        return """
+        The user logged their mood as "\(moodName)" and completed a \(technique) reflection:
+
+        \(qaPairs)
+
+        Respond with personalized feedback that references their specific answers.
+        """
+    }
+}

Shared/Services/FoundationModelsTagService.swift

@@ -0,0 +1,99 @@
+//
+//  FoundationModelsTagService.swift
+//  Reflect
+//
+//  Extracts theme tags from mood entry notes and guided reflections using Foundation Models.
+//
+
+import Foundation
+import FoundationModels
+
+@available(iOS 26, *)
+@MainActor
+class FoundationModelsTagService {
+
+    // MARK: - Singleton
+
+    static let shared = FoundationModelsTagService()
+
+    private init() {}
+
+    // MARK: - Tag Extraction
+
+    /// Extract theme tags from an entry's note and/or reflection content
+    /// - Parameters:
+    ///   - entry: The mood entry to extract tags from
+    /// - Returns: Array of tag label strings, or nil if extraction fails
+    func extractTags(for entry: MoodEntryModel) async -> [String]? {
+        // Need at least some text content to extract from
+        let noteText = entry.notes?.trimmingCharacters(in: .whitespacesAndNewlines) ?? ""
+        let reflectionText = extractReflectionText(from: entry)
+
+        guard !noteText.isEmpty || !reflectionText.isEmpty else {
+            return nil
+        }
+
+        let session = LanguageModelSession(instructions: systemInstructions)
+        let prompt = buildPrompt(noteText: noteText, reflectionText: reflectionText, mood: entry.mood)
+
+        do {
+            let response = try await session.respond(to: prompt, generating: AIEntryTags.self)
+            return response.content.tags.map { $0.label.lowercased() }
+        } catch {
+            print("Tag extraction failed: \(error.localizedDescription)")
+            return nil
+        }
+    }
+
+    /// Extract tags and save them to the entry via DataController
+    func extractAndSaveTags(for entry: MoodEntryModel) async {
+        guard let tags = await extractTags(for: entry), !tags.isEmpty else { return }
+
+        if let data = try? JSONEncoder().encode(tags),
+           let json = String(data: data, encoding: .utf8) {
+            DataController.shared.updateTags(forDate: entry.forDate, tagsJSON: json)
+        }
+    }
+
+    // MARK: - System Instructions
+
+    private var systemInstructions: String {
+        """
+        You are a theme extractor for a mood journal. Extract 1-4 theme tags from the user's journal text. \
+        Only use tags from this list: work, family, social, health, sleep, exercise, stress, gratitude, \
+        growth, creative, nature, self-care, finances, relationships, loneliness, motivation. \
+        Only extract tags clearly present in the text. Do not guess or infer themes not mentioned.
+        """
+    }
+
+    // MARK: - Prompt Construction
+
+    private func buildPrompt(noteText: String, reflectionText: String, mood: Mood) -> String {
+        var content = "Mood: \(mood.widgetDisplayName)\n"
+
+        if !noteText.isEmpty {
+            content += "\nJournal note:\n\(String(noteText.prefix(500)))\n"
+        }
+
+        if !reflectionText.isEmpty {
+            content += "\nReflection responses:\n\(String(reflectionText.prefix(800)))\n"
+        }
+
+        content += "\nExtract theme tags from the text above."
+        return content
+    }
+
+    // MARK: - Helpers
+
+    private func extractReflectionText(from entry: MoodEntryModel) -> String {
+        guard let json = entry.reflectionJSON,
+              let reflection = GuidedReflection.decode(from: json) else {
+            return ""
+        }
+
+        return reflection.responses
+            .filter { !$0.answer.trimmingCharacters(in: .whitespacesAndNewlines).isEmpty }
+            .map { "Q: \($0.question)\nA: \($0.answer)" }
+            .joined(separator: "\n")
+    }
+}