**GraphDetailView:** Long-hold detail popup on glucose chart#2425
Open
taylorpatterson-T1D wants to merge 231 commits intoLoopKit:devfrom
Open
**GraphDetailView:** Long-hold detail popup on glucose chart#2425taylorpatterson-T1D wants to merge 231 commits intoLoopKit:devfrom
taylorpatterson-T1D wants to merge 231 commits intoLoopKit:devfrom
Conversation
FoodFinder adds barcode scanning, AI camera analysis, voice search, and text-based food lookup to Loop's carb entry workflow. All feature code lives in dedicated FoodFinder/ subdirectories with FoodFinder_ prefixed filenames for clean isolation and portability to other Loop forks. Integration touchpoints: ~29 lines across 3 existing files (CarbEntryView, SettingsView, FavoriteFoodDetailView). Feature is controlled by a single toggle in FoodFinder_FeatureFlags.swift. New files: 34 (11 views, 3 models, 13 services, 2 view models, 1 feature flags, 1 documentation, 3 tests)
Voice search (microphone button) now uses the AI analysis pipeline instead of USDA text search, enabling natural language food descriptions like "a medium bowl of spicy ramen and a side of gyoza". Text-typed searches continue using USDA/OpenFoodFacts as before. Changes: - SearchBar: Add mic button with voice search callback - SearchRouter: Add analyzeFoodByDescription() routing through AI providers - SearchViewModel: Add performVoiceSearch() async method - EntryPoint: Wire VoiceSearchView sheet to AI analysis pipeline
Replace the separate mic button with automatic natural language detection. When the user dictates into the search field via iOS keyboard dictation, the text is analyzed: short queries (1-3 words like "apple") use USDA, while longer descriptive phrases (4+ words like "a medium bowl of spicy ramen and a side of gyoza") automatically route to the AI analysis path. Changes: - SearchBar: Remove mic button and onVoiceSearchTapped parameter - SearchViewModel: Add isNaturalLanguageQuery() heuristic, route detected natural language through performVoiceSearch in performFoodSearch - EntryPoint: Remove voice search sheet, wire onGenerativeSearchResult callback to handleAIFoodAnalysis
The Python script created group definitions but didn't properly attach all of them to their parent groups. Fixes: - Services group → now child of Loop app root (was orphaned) - Resources group → now child of Loop app root (was orphaned) - Documentation group → now child of project root (was orphaned) - ViewModels/FoodFinder → moved from Loop root to View Models group - Tests/FoodFinder → moved from project root to LoopTests group
…, analysis history - Fix triple barcode fire by consuming scan result immediately in Combine sink - Replace AsyncImage with pre-downloaded thumbnail to avoid SwiftUI rebuild issues - Use smallest OFF thumbnail (100px) with static food icon fallback for slow servers - Add secure Keychain storage for AI provider API keys - Add analysis history tracking with FoodFinder_AnalysisRecord - Consolidate AI provider settings and remove BYOTestConfig
- Remove barcode connectivity pre-check that added 3+ seconds latency per scan - Add NSCache to ImageDownloader for thumbnail deduplication (50 items, 10MB) - Remove artificial minimumSearchDuration delay from search and error paths - Merge duplicate Combine observers into single combineLatest for AI recomputation - Decode image_thumb_url from OpenFoodFacts API for smallest available thumbnail - Wrap 369 bare print() calls in #if DEBUG across 8 FoodFinder files
…eaders File consolidations (6 files removed, 2 new files created): 1. FoodFinder_ScanResult.swift + FoodFinder_VoiceResult.swift → FoodFinder_InputResults.swift 2. FoodFinder_FavoriteDetailView.swift + FoodFinder_FavoriteEditView.swift + FoodFinder_FavoritesView.swift → FoodFinder_FavoritesHelpers.swift 3. FoodFinder_AISettingsManager.swift → absorbed into FoodFinder_AIProviderConfig.swift 4. FoodFinder_FavoritesViewModel.swift → absorbed into FoodFinder_SearchViewModel.swift Other changes: - Fix long analysis titles overflowing the screen by programmatically truncating picker row names and constraining food type to 20 chars - Improve AI prompts for menu/recipe/text image analysis - Add text-only AI analysis path in AIServiceManager - Increase AI token budget for multi-item responses - Standardize all 26 FoodFinder file headers with consistent format
- Add originalAICarbs and aiConfidencePercent fields to FoodFinder_AnalysisRecord for tracking AI estimate accuracy - Add Notification.Name.foodFinderMealLogged for real-time meal event observation - Add MealDataProvider protocol with date-range query interface and AnalysisHistoryStore conformance - Add "Last 30 days" retention option to Analysis History settings
- Add originalAICarbs and aiConfidencePercent fields to FoodFinder_AnalysisRecord for tracking AI estimate accuracy - Add Notification.Name.foodFinderMealLogged for real-time meal event observation - Add MealDataProvider protocol with date-range query interface and AnalysisHistoryStore conformance - Add "Last 30 days" retention option to Analysis History settings
- Absorption time model: conservative adjustments anchored to Loop's 3-hour default. FPU adds +0/+0.5/+1.0 hr (was +1/+2.5/+4), fiber +0/+0.25/+0.5 (was +0/+1/+2), meal size +0/+0.25/+0.5 (was +0/+1/+2). Cap reduced from 8 to 5 hours. Updated AI prompt and 3 examples. - OCR routing fix: raised menu detection threshold from 1 to 5 significant lines and always include image on menu path to prevent food photo misclassification (fixes "Unidentifiable Food Item" on food photos). - Inline "Why X hrs?" pill on Absorption Time row replaces standalone DisclosureGroup row. Purple centered pill with fixed width, expands reasoning on tap. Uses AIAbsorptionTimePickerRow when AI-generated.
Add LoopInsights feature: an AI-driven therapy settings advisor that analyzes glucose, insulin, and carb data to suggest adjustments to Carb Ratios, Insulin Sensitivity Factors, and Basal Rates. Core components: - Dashboard with therapy settings overview, pattern detection, and AI suggestions - Configurable AI provider (OpenAI, Anthropic, Gemini, Grok, self-hosted) - Data aggregation pipeline with test data fixtures from Tidepool - Suggestion lifecycle: pending → applied/dismissed with full history - AI personality settings (Supportive Coach, Clinical Expert, Dry Wit, Tough Love) - Developer mode with auto-apply and test data toggles - Secure API key storage via Keychain - Safety guardrails: max 20% change per adjustment, one setting at a time - Unit tests for models, data aggregation, and suggestion store 22 new files, 4 modified files across Views, View Models, Models, Services, Managers, Resources, and Tests.
…ng, and UI refinements - Wire real therapy settings writes via LoopInsightsSettingsWriter closure - Schedule splitting: insert new entries when AI suggests times not in user's schedule - Revert feature: restore pre-apply settings from suggestion history - Settings Score (0-100) with TIR, Safety, Stability, GMI breakdown - Clinical reasoning framework: AI now understands AID-specific patterns (corrections/day, basal/bolus ratio, time-of-day analysis, cross-setting interactions) - All three settings visible in every AI prompt for cross-setting reasoning - Pre-computed red flags injected into prompt (algorithm workload, basal % alerts) - Stale-data guard: excludes manually reverted changes from recent context - Suggestion merge: consolidates split AI responses into single cards - Pre-Fill Editor: editable proposed values before applying - Auto-applied notification banner - Debug log with Copy Full Log for troubleshooting AI behavior - Temperature forced to 0.0 for deterministic analysis
… advisor UI Add Ask LoopInsights chat with AI advisor powered by therapy context and glucose data. Background monitoring with configurable frequency and notification banners. New Trends & Insights view with Daily/Weekly/Monthly/Stats/Advisor tabs. Dark gradient styling for chat and trends views. Banner now includes Ask button to open chat directly.
…ports Add clinical goal tracking (TIR, A1C, below-range, custom) with progress bars, AI-powered 30-day pattern discovery with sick day and negative basal detection, timestamped reflection journal with mood tags, and HTML-to-PDF report generation with share sheet. Goals & Patterns accessible from the Dashboard navigation section.
… analysis Add HealthKit biometric data (heart rate, HRV, steps, sleep, active energy, weight) to the AI analysis and chat pipelines. Biometrics are read-only, independently authorized, and gracefully degrade when individual types are unavailable. New file: LoopInsights_HealthKitManager.swift Modified: Models, DataAggregator, AIAnalysis, ChatViewModel, Coordinator, FeatureFlags, SettingsView, DashboardView, pbxproj, Localizable.xcstrings
…nsights, Nightscout import - Ambulatory Glucose Profile (AGP) chart with percentile bands and median line - Clarity-style dashboard redesign: Glucose card, Time in Range 5-zone stacked bar, capsule period picker with exact Clarity colors (#C14F0C, #F0CA4C, #74A52E, #D36265, #7F0302) - Caffeine tracker with half-life decay modeling and glucose correlation - Meal insights with food response analysis and per-meal glucose impact - Nightscout data import support - Advanced analyzers for pattern detection - 5-zone TIR breakdown (Very High/High/In Range/Low/Very Low) replacing 3-zone model - Compact list section spacing for tighter dashboard layout - Chat view UI refinements
…card fixes P1: Parallel HealthKit queries via async let (6 concurrent fetches) P2: Single-pass TIR zone counting (5-zone) replacing multiple filter passes P3: Pre-fetch raw data in DataAggregator, cache for cross-component reuse P4: Binary search for glucose lookups in FoodResponseAnalyzer P5: Pre-sorted glucose samples with binary search in AdvancedAnalyzers P6: Pre-compute AGP data in ViewModel instead of SwiftUI view body P7: Static DateFormatter in LoopInsightsTimeBlock.formatTime P8: Pre-sort schedule items before dose loops, pre-sort in ViewModel P9: Pre-convert glucose to parallel arrays avoiding repeated doubleValue calls P10: Pass precomputed hourly averages to circadian profile builder Also: enhanced step/activity data in AI prompts with time-of-day breakdowns and activity-glucose correlation analysis (2h lag), and meal card layout cleanup. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
…y fixes Glucose chart now operates in two modes: standard Ambulatory Glucose Profile (24-hour overlay with percentile bands) for 14-day lookback, and Glucose Profile (multi-day time series) for all other periods. Both modes include an info button explaining the visualization. HealthKit glucose data supplements Loop store for longer analysis periods. Chart data clears on period change to prevent stale labels. Additional fixes across 22 files: improved HealthKit data pipeline reliability, enhanced test data provider, refined food response analysis, and minor bug fixes in background monitor, coordinator, caffeine tracker, and goals/trends views. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
…y fixes Glucose chart now operates in two modes: standard Ambulatory Glucose Profile (24-hour overlay with percentile bands) for 14-day lookback, and Glucose Profile (multi-day time series) for all other periods. Both modes include an info button explaining the visualization. HealthKit glucose data supplements Loop store for longer analysis periods. Chart data clears on period change to prevent stale labels. Additional fixes across 22 files: improved HealthKit data pipeline reliability, enhanced test data provider, refined food response analysis, and minor bug fixes in background monitor, coordinator, caffeine tracker, and goals/trends views.
Bump all body text, headers, and stat values to full white for readability on dark backgrounds. Replace .toolbarColorScheme (iOS 16+) with manual toolbar principal title for compatibility. Restore UINavigationBarAppearance approach in ChatView. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The 20-char limit was truncating food names (e.g. "Baked pastry with f…") which made them unreadable in LoopInsights Meal Insights. The RowEmojiTextField maxLength only restricts keyboard input, so longer programmatic values are safe. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Added steps for creating and using test data in developer mode for demos and feature functionality testing.
…ivity CoreMotion-based activity detection that automatically applies user-selected override presets when walking or running is detected. 7 new files, 2 modified. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Safety guardrails (3 layers of defense against dangerous therapy values): - LoopInsights_SafetyGuardrails struct with clinical bounds mirroring LoopKit (CR 4-28 recommended/2-150 absolute, ISF 16-400/10-500, Basal 0.05-10/0.05-30) - Post-parse validation rejects values outside absolute bounds and >25% changes - AI prompt now includes absolute bounds with clamping instructions - confirmApply() hard-blocks absolute violations - applyEditedSuggestion() validates edited blocks against absolute bounds - autoApplySuggestion() blocks anything outside recommended range (stricter) - SuggestionDetailView shows orange warning banner and color-coded values - DashboardView alert changes to "Safety Warning" with specific warnings - Suggestion cards show orange triangle badge for guardrail warnings Data-first AI prompts (all 4 AI interaction points): - Chat, Analysis, Goals/Patterns, and Trends prompts now require every answer to cite the user's specific numbers — no generic diabetes advice - Added "#1 RULE" blocks emphasizing real data over textbook answers Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Safety guardrails (3 layers of defense against dangerous therapy values): - LoopInsights_SafetyGuardrails struct with clinical bounds mirroring LoopKit (CR 4-28 recommended/2-150 absolute, ISF 16-400/10-500, Basal 0.05-10/0.05-30) - Post-parse validation rejects values outside absolute bounds and >25% changes - AI prompt now includes absolute bounds with clamping instructions - confirmApply() hard-blocks absolute violations - applyEditedSuggestion() validates edited blocks against absolute bounds - autoApplySuggestion() blocks anything outside recommended range (stricter) - SuggestionDetailView shows orange warning banner and color-coded values - DashboardView alert changes to "Safety Warning" with specific warnings - Suggestion cards show orange triangle badge for guardrail warnings Data-first AI prompts (all 4 AI interaction points): - Chat, Analysis, Goals/Patterns, and Trends prompts now require every answer to cite the user's specific numbers — no generic diabetes advice - Added "#1 RULE" blocks emphasizing real data over textbook answers
Combines FoodFinder (34 files) with LoopInsights (18 files) on a shared history rooted in feat/LoopInsights. Resolves pbxproj, SettingsView, and Localizable.xcstrings merge conflicts — both features coexist. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
…ivity CoreMotion-based activity detection that automatically applies user-selected override presets when walking or running is detected. 7 new files, 2 modified.
Root cause: servings was computed as the SUM of per-item USDA serving multipliers (e.g. salmon=2 + egg=1 + potatoes=3 = 6+ servings) instead of representing 1 plate/meal. This inflated numberOfServings to 10+ and scaled all nutrition values up accordingly. Fix: AI analysis = 1 serving = 1 plate as photographed. The per-item USDA multipliers are internal to the item-level breakdown, not the user-facing serving count. originalServings is now always 1.0, and convertAIResultToFoodProduct no longer divides by the aggregate USDA serving count.
Implements three programmatic safeguards from Street (2026) "Frontier LLMs require explicit clinical context to avoid training-data anchoring for insulin pump settings" (https://www.diabettech.com/wp-content/uploads/2026/04/diabettech_preprint-3.pdf): 1. Bounds clamping (recommendation #2): Values exceeding the max change % by up to 1.5x are clamped to the limit instead of hard-rejected, with a logged validation note. 2. Citation verification (recommendation LoopKit#3): Glucose values cited in AI reasoning are cross-checked against the actual hourly averages sent to the model (±2 mg/dL tolerance). Misattribution rate is reported as a validation note. 3. Confidence adjustment by data availability: CR analysis with <5 meals or ISF analysis with <3 corrections is capped at Low confidence with an explicit warning about anchor substitution risk. Basal (the most data- driven setting per Street's anchoring spectrum) is not capped. All changes are in the response parsing layer — no prompt modifications: - LoopInsights_AIAnalysis.swift: parseResponse() + extractCitedGlucoseValues() - LoopInsights_Models.swift: validationNotes field on LoopInsightsAnalysisResponse - LoopInsights_DashboardView.swift: validation notes display in UI
Additional safeguards addressing Street (2026) findings that LLMs cannot distinguish "I have evidence" from "I should generate something plausible": 1. Stronger refusal mandate in system prompt: Model MUST return empty suggestions when data is insufficient to validate a setting. Explicitly forbids echoing current values with medium/high confidence when no supporting data pattern exists. 2. Explicit AID system context in user prompt: States "Loop (oref-based)" with DIA prominently positioned and marked as DO NOT CHANGE. Prevents catastrophic DIA collapse to 4-5h textbook values (Street 2026 found 100% of models defaulted to textbook DIA without this context). 3. Contradiction detection (validation pass LoopKit#4): Scans reasoning for admissions like "cannot be derived", "insufficient data", "no meal data" while confidence is medium/high. If found, suppresses the suggestion entirely — the model was filling gaps with training priors. All changes in LoopInsights_AIAnalysis.swift (system prompt, user prompt, and parseResponse validation layer). Reference: Street T. "Frontier LLMs require explicit clinical context to avoid training-data anchoring for insulin pump settings." April 2026. https://www.diabettech.com/wp-content/uploads/2026/04/diabettech_preprint-3.pdf
…ency with FoodFinder
…tering - Replace CarbQuantityRow with inline slider when AI analysis is active (Amount Consumed | slider | editable text field | g) - Slider turns grey and centers when user manually types a value - Locale-aware AI prompts: metric users get cm/mm, imperial get inches - Location service only includes venue name when a restaurant/POI is confirmed; bare street addresses are filtered out
- Teal "LI" circle on glucose chart opens dashboard directly - Red badge dot appears when pending suggestions exist - Only visible when LoopInsights feature is enabled - Made DashboardContainer and wrapper internal for reuse
…rtion control DataLayer: wire barcodeScanned, chatMessage, mealDebrief, therapySettingsChanged, overrideActivated/Deactivated, activityDetected, biometricSnapshot events. FoodFinder: fix location race condition — request GPS on camera button tap and wait up to 1.5s for reverse geocode before AI analysis. Restructure food detail cards with per-item USDA serving steppers so users can fine-tune portion estimates independently. Nutrition circles and totals update live with stepper changes. AI prompt: clarify serving_multiplier = visible portion / USDA serving with examples.
…rompt - Remove 500ms cosmetic delays after analysis success/error in AICameraView - Add fast VNDetectTextRectanglesRequest gate before expensive OCR — skips full text recognition when <5 text regions detected (most food photos) - Consolidate mandatory prompt rules (43 → 13) and remove 2 of 3 worked examples, keeping the high-GI Teriyaki example most relevant for diabetes
Shows relative timestamps ("2 hours ago", "in 4 hours") so the user
can verify background monitoring is actually running on schedule.
- Remove unused extractNumericConfidence(), shouldUseParallelProcessing, and createPlaceholderImage() from FoodFinder services/view models - Add onDisappear to clear cached location when FoodFinder is dismissed
Defer prediction snapshot capture to next .LoopDataUpdated instead of capturing immediately on .foodFinderMealLogged. StatusExtensionContext predictions are stale until the Loop algorithm re-runs with the new carbs — capturing immediately was the primary cause of "no prediction data captured" failures in Meal Insights.
A1: Extend AutoPresets Stop Delay slider from 10min max to 2hr max with dedicated value steps (10s, 20s, 30s, 1m, 2m, 3m, 5m, 10m, 15m, 20m, 30m, 45m, 1hr, 1.5hr, 2hr) for post-exercise recovery. F5: Add mandatory pre-bolus timing advisory to FoodFinder AI prompt for all analyses (not just advanced mode). Recommends bolus timing based on GI category, meal composition, and current glucose. N5: Add user engagement/burnout awareness to LoopInsights AI system. Teaches AI to interpret low carb logging, declining corrections, and high suggestion reversion as possible disengagement signals. Computes engagement metrics in supplemental context for every analysis.
Remove advanced-mode gate on absorption time recalculation so fat/ protein adjustments always apply when items are removed. Increase high-FPU adjustment from +1.0h to +1.5h and raise total cap from 5h to 6h to better handle pizza/nachos/high-fat meals that cause delayed glucose rises.
Capture glucose stats (TIR, avg, below-range, CV) at suggestion apply time via new LoopInsightsGlucoseStatsSnapshot. Show "Settings Impact" section on dashboard with recently applied suggestions, days-since, outcome verdict, key metrics at time of change, and AI reasoning.
…data Analyzes FoodFinder meal history for systematic user corrections by food type, location, time of day, and AI confidence level. Surfaces patterns as alerts on the dashboard and in a dedicated Behavior Insights view. Injects patterns into AI supplemental context and Post-Meal debrief prompts for richer recommendations. Also makes Settings Impact section collapsible via DisclosureGroup.
…ights Adds one-tap PDF report for endocrinologist appointments with branded LoopInsights teal header, toggleable sections, vertical Dexcom Clarity-style Time in Range bar, detected glucose/insulin patterns, behavior correction patterns, and custom email subject line. Report covers glucose, insulin, nutrition, settings changes, biometrics, engagement, caffeine/alcohol, and pump suspensions.
…very Configurable digest for caregivers with recipient email/phone storage, delivery method picker (Email or iMessage), frequency (daily/weekly), and personalized greeting. Send Now generates summary and opens pre-filled compose view — recipient just taps Send. Includes TIR, glucose stats, insulin delivery, and meal data.
Automatically activate presets when arriving at or leaving saved locations (gym, office, park) using iOS region monitoring. Battery-efficient — no continuous GPS tracking. Includes map picker, radius config, trigger type selection, and full integration with existing AutoPresets activity log.
EventKit integration that scans calendars for keyword-matched events and auto-activates presets with configurable lead time. Supports all calendar providers, per-calendar filtering, and deactivation on event end.
Replaces the existing minimal chart touch highlight with a rich detail popup showing glucose, IOB, COB, bolus, basal, preset, AutoPreset, and heart rate data at any point on the glucose chart. Supports scrubbing left/right with haptic feedback, auto-fades after 5 seconds, respects safe areas in both orientations, and works standalone with optional enhanced data when other features (AutoPresets, etc.) are enabled.
taylorpatterson-T1D
changed the title
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Summary
Long-press anywhere on the glucose chart to see a detailed popup of everything happening at that moment — glucose, insulin, carbs, presets, heart rate and more. Scrub left and right to explore the timeline. Replaces the existing minimal touch highlight with a richer, more informative experience. Part of the Loop AI PowerPack.
Inspired by Issue #2257 and similar functionality seen in Trio.
The Problem We're Solving
Loop's glucose chart currently shows a minimal touch highlight when you long-press — just the glucose value at that point. Users frequently want to understand what was happening at a specific moment: Was a bolus delivered? What was IOB? Was a preset active? Was my heart rate elevated? Today, answering these questions requires navigating to multiple screens and mentally correlating timestamps.
This is especially frustrating when reviewing post-meal spikes, unexpected lows, or activity-related patterns. The data exists in Loop — it's just not accessible in context.
New Feature's Impact
GraphDetailView adds an interactive detail popup directly on the glucose chart. Long-press to see data at a point in time, then scrub left/right to explore the timeline without lifting your finger. The popup shows all relevant data at that moment in a clean, color-coded layout.
What it does
Data shown at each point
Behavior details
Standalone design
GraphDetailDataandGraphDetailViewModelArchitecture
StatusTableViewController.swift— gesture handling, popup presentation/dismissal (~225 lines in a dedicated MARK section)project.pbxproj— file references for new filesNew files
GraphDetailView.swiftViews/GraphDetailViewModel.swiftManagers/Integration points into Loop (2 files modified)
StatusTableViewController.swiftproject.pbxprojScreenshots
Portrait Mode
Landscape Mode
Installation
Option A — Merge branch directly
Option B — Cherry-pick the commit