Phase 2 of Pulse AI differentiation:
- Create internal/ai/baseline package for learned baselines
- Implement statistical baseline learning with mean, stddev, percentiles
- Add z-score based anomaly detection with severity classification
(low, medium, high, critical based on standard deviations)
- Integrate baseline provider into context builder
- Wire baseline store into patrol service with adapters
- Add anomaly enrichment to resource contexts
Key features:
- Learn computes baseline from historical metric data points
- IsAnomaly and CheckAnomaly detect deviations from normal
- Persists baselines to disk as JSON for durability
- Formatted anomaly descriptions for AI consumption
Example: 'Memory is high above normal (85.2% vs typical 42.1% ± 8.3%)'
The baseline store needs to be initialized and triggered to learn
from metrics history. Next step is adding the learning loop.
All tests passing.
- Add exponential backoff retry for Docker agent startup (main.go)
- Fix Docker resource/image column widths with proper truncation
- Unify IP tooltip styling across hosts and guests with detailed network info
- Improve column visibility defaults and sticky column handling
- Various component refinements for Dashboard, Storage, and Backups views
- Changed patrol schedule from preset dropdown to freeform number input
- Users can now set any interval (min 10 minutes, max 7 days, or 0 to disable)
- Added patrol_interval_minutes to API request/response (preset is now deprecated)
- Backend validates: min 10 minutes when enabled, max 10080 (7 days)
- Frontend shows human-readable duration next to input (e.g., '6h', '2h 30m')
Also improved Auto-Fix Mode safety:
- Removed '(recommended)' from preset options (was subjective)
- Added 'I understand the risks' acknowledgement checkbox
- Toggle is disabled until user explicitly acknowledges the risks
- Shows prominent warning when Auto-Fix is enabled
- Acknowledgement is session-based (must re-acknowledge on page reload)
- Add 'content' type to StreamDisplayEvent for tracking text chunks
- Track content events in streamEvents array for chronological display
- Update render to use Switch/Match for cleaner conditional rendering
- Interleave thinking, tool calls, and content as they stream in
- Add fallback for old messages without streamEvents for backwards compat
Previously, tool/command outputs stayed at top while AI text responses
accumulated at the bottom. Now all events appear in order like a
normal chatbot.
- Remove model references from provider labels ('OpenAI' not 'OpenAI (GPT-4)')
- Remove DEFAULT_MODELS usage in form initialization
- Use generic placeholders instead of specific model names
- Models are now fetched dynamically from each provider's API
- UI won't become outdated when new models are released
- Show number of configured providers and available models
- Display friendly model name (without provider prefix)
- Better status message: 'Ready • 1 10 models'provider
- Adds 'Refresh Models' button next to Default Model label
- Spinning icon animation during loading
- Allows manual refresh after configuring new providers
- Add clear_anthropic_key, clear_openai_key, clear_deepseek_key, clear_ollama_url flags to API
- Backend handles clearing with confirmation prompt
- Each provider accordion shows Test and Clear buttons when configured
- Clear button requires confirmation before removing credentials
- Frontend automatically refreshes settings after clearing
- Add /api/ai/test/{provider} endpoint for testing individual providers
- Add 'Test' button to each provider accordion (visible when configured)
- Shows test result inline (success/error message)
- Update help links with direct URLs to API key pages:
- Anthropic: console.anthropic.com/settings/keys
- OpenAI: platform.openai.com/api-keys
- DeepSeek: platform.deepseek.com/api_keys
- Ollama: ollama.ai
Backend:
- Add per-provider API key fields to AIConfig (AnthropicAPIKey, OpenAIAPIKey, DeepSeekAPIKey, OllamaBaseURL, OpenAIBaseURL)
- Add NewForProvider() and NewForModel() factory functions for multi-provider instantiation
- Update ListModels() to aggregate models from all configured providers with provider:model format
- Update Execute/ExecuteStream to dynamically create provider based on selected model
- Update TestConnection to use multi-provider aware provider creation
- Add helper functions: HasProvider(), GetConfiguredProviders(), GetAPIKeyForProvider(), GetBaseURLForProvider(), ParseModelString(), FormatModelString()
Frontend:
- Remove legacy single-provider UI (provider grid, single API key input, single base URL)
- Add accordion-style UI for configuring all providers independently
- Add model grouping by provider in selectors using optgroup
- Update AIChat model dropdown with grouped provider sections
- Add helper functions for parsing provider from model ID and grouping models
API:
- Add multi-provider fields to AISettingsResponse and AISettingsUpdateRequest
- Add /api/ai/models endpoint for dynamic model listing
- Update settings handlers for per-provider credential management
Users can now:
1. View all active suppression rules in a collapsible section
2. Add new rules manually with resource ID, category, and description
3. Delete rules to re-enable alerts
4. See whether rules came from dismissed findings or were manually created
The UI shows:
- 🔇 Suppression Rules (N active) header with expand/collapse
- + Add Rule button to open the form
- Each rule shows resource, category, origin (Manual/From Finding), and description
- Delete button to remove rules
Users can now:
1. View all suppression rules (both from dismissed findings and manually created)
2. Create manual rules like 'ignore performance issues on debian-go'
3. Delete rules when they want alerts to come back
Backend:
- Added SuppressionRule type for user-defined rules
- Added suppressionRules storage to FindingsStore
- Added AddSuppressionRule/GetSuppressionRules/DeleteSuppressionRule methods
- Added isSuppressedInternal check for manual rules
- Added API handlers and routes for /api/ai/patrol/suppressions
Frontend:
- Added SuppressionRule interface
- Added getSuppressionRules/addSuppressionRule/deleteSuppressionRule API functions
- Added getDismissedFindings for viewing dismissed findings
Example usage:
POST /api/ai/patrol/suppressions
{
'resource_id': 'debian-go',
'category': 'performance',
'description': 'Dev container runs hot - expected'
}
The ForcePatrol() function was using the HTTP request context, which gets
cancelled immediately when the API response is sent. This caused LLM analysis
to fail with 'context canceled' before it could complete.
Now uses context.Background() so the goroutine runs independently of the
HTTP request lifecycle.
Also fixed dropdown hover gap issue in the dismiss menu.
Implements a comprehensive feedback system that allows the LLM to 'remember'
user decisions about findings, preventing repetitive/annoying alerts.
Backend changes:
- Extended Finding struct with dismissed_reason, user_note, times_raised, suppressed
- Added Dismiss(), Suppress(), SetUserNote(), IsSuppressed() methods to FindingsStore
- Added GetDismissedForContext() to format dismissed findings for LLM context
- Enhanced buildPatrolPrompt() to inject user feedback context
- Added POST /api/ai/patrol/dismiss and /api/ai/patrol/suppress endpoints
- Updated IsActive() to exclude suppressed findings
Frontend changes:
- Added Dismiss dropdown with options: Not an Issue, Expected Behavior, Will Fix Later
- Added Never Alert Again option for permanent suppression
- Expected Behavior prompts for optional note to help LLM understand context
- Added visual badges: recurrence count (×N), dismissed status, suppressed indicator
- Display user notes in expanded finding view
Also fixes:
- Fixed 403 error on Run Patrol (compilation errors from partial refactoring)
- Removed non-LLM patrol checks - patrol now uses LLM analysis only
- Fixed function signature mismatches in alert_triggered.go
The LLM now receives context about previously dismissed findings and is
instructed not to re-raise them unless severity has significantly worsened.
- Add alert-triggered AI analysis for real-time incident response
- Implement patrol history persistence across restarts
- Add patrol schedule configuration UI in AI Settings
- Enhance AIChat with patrol status and manual trigger controls
- Add resource store improvements for AI context building
- Expand Alerts page with AI-powered analysis integration
- Add Vite proxy config for AI API endpoints
- Support both Anthropic and OpenAI providers with streaming
Keep only the simple AI-powered approach:
- set_resource_url tool lets AI save discovered URLs
- Users ask AI directly: 'Find URLs for my containers'
- AI uses its intelligence to discover and set URLs
Removed:
- URLDiscoveryService (rigid port scanning)
- Bulk discovery API endpoints
- Frontend discovery button
The AI itself is smart enough to iterate through resources
and discover URLs when asked.
- Add host metadata API for custom URL editing on hosts page
- Enhance AI routing with unified resource provider lookup
- Add encryption key watcher script for debugging key issues
- Improve AI service with better command timeout handling
- Update dev environment workflow with key monitoring docs
- Fix resource store deduplication logic
- Add Claude OAuth authentication support with hybrid API key/OAuth flow
- Implement Docker container historical metrics in backend and charts API
- Add CEPH cluster data collection and new Ceph page
- Enhance RAID status display with detailed tooltips and visual indicators
- Fix host deduplication logic with Docker bridge IP filtering
- Fix NVMe temperature collection in host agent
- Add comprehensive test coverage for new features
- Improve frontend sparklines and metrics history handling
- Fix navigation issues and frontend reload loops
Replaced 18+ console.log statements in AI-related files with
logger.debug/warn/error calls. This ensures debug output only
appears in development mode, keeping production logs clean.
Files updated:
- frontend-modern/src/api/ai.ts (15 statements)
- frontend-modern/src/components/AI/AIChat.tsx (4 statements)
These were internal planning/architecture docs not meant for end users:
- .gemini/docs/unified-resource-architecture.md (design doc)
- .gemini/tasks/persistent-metrics-storage.md (implementation plan)
- frontend-modern/PLAN-column-visibility.md (implementation plan)
This cleanup addresses transition debt from the unified resources migration:
Frontend cleanup:
- Move all Resource→Legacy type conversions to useResourcesAsLegacy() hook
- Add asNodes() and asDockerHosts() adapter functions to the hook
- Simplify DockerRoute, HostsRoute, DashboardView to use the centralized hook
- Remove ~300 lines of duplicated adapter code from App.tsx
- Remove debug console.log statements from Dashboard.tsx
- Fix CPU value conversion (divide by 100) for Dashboard compatibility
Backend fixes (from previous session):
- Fix parentID format in converters (VM, Container, Storage) to match Node.ID
- Format changed from 'instance/node/nodename' to 'instance-nodename'
- Update tests to match new parentID format
This consolidates all legacy type conversion logic in one place,
making future cleanup easier when components are migrated to use
unified resources directly.
The Dashboard grouping was broken because:
- node was set to r.parentId (full resource ID)
- instance was set to r.platformId
Fixed to read from platformData which contains the correct values:
- node = platformData.node (e.g., 'minipc')
- instance = platformData.instance (e.g., 'https://pve:8006')
This matches the legacy data format and fixes the grouped/list toggle.
BREAKING: Route components no longer fall back to legacy state arrays.
All data now flows through the unified resource model:
- DockerRoute: uses state.resources filtered for docker-host/docker-container
- HostsRoute: uses state.resources filtered for host
- DashboardView: uses state.resources filtered for node/vm/container
The legacy arrays (state.nodes, state.vms, etc.) are still broadcast
by the backend for API compatibility, but the main UI routes no longer
use them.
If resources array is empty, pages will show no data rather than
falling back to legacy data. This ensures a clean data model with
no hidden fallback behavior.
Backend:
- Call SetMonitor after router creation to inject resource store
- Add debug logging for resource population and broadcast
Frontend:
- Add resources array to WebSocket store initial state
- Handle resources in WebSocket message processing
- Use reconcile for efficient state updates
The unified resources are now properly:
1. Populated from StateSnapshot on each broadcast cycle
2. Converted to frontend format (ResourceFrontend)
3. Included in WebSocket state messages
4. Received and stored in frontend state
5. Consumed by migrated route components
Console now shows '[DashboardView] Using unified resources: VMs: X'
confirming the migration is working end-to-end.
Temporary logging to verify which code path is being used:
- DockerRoute: logs docker-host and docker-container counts
- HostsRoute: logs host count
- DashboardView: logs VM count
Check browser console to confirm unified resources are being received.
These logs can be removed once migration is verified.
Docker page:
- DockerRoute now uses unified resources with fallback to legacy data
- Reconstructs container hierarchy from flat resource list
- Maps docker-host and docker-container resources to DockerHost type
Dashboard page:
- DashboardView now uses unified resources with fallback
- Converts vm, container, and node resources to legacy types
- Maintains full backward compatibility with existing components
Both pages use resource type filtering and platform data extraction
to adapt the unified model to existing component interfaces.
- Updated HostsRoute to consume unified resources with fallback to legacy data
- Added asHosts adapter to useResourcesAsLegacy hook
- Adapter converts Resource type to Host type for existing component
The Hosts page now uses resources from state.resources when available,
falling back to state.hosts for backward compatibility. This approach
allows gradual migration without breaking the existing HostsOverview
component.
- Created resource.ts with TypeScript types for unified Resource model
- ResourceType, PlatformType, SourceType, ResourceStatus enums
- Resource interface matching backend ResourceFrontend
- Helper functions: isInfrastructure, isWorkload, getDisplayName, etc.
- ResourceFilter interface for complex filtering
- Updated api.ts State interface to include optional resources array
- Created useResources hook for accessing unified resources
- Reactive access via getGlobalWebSocketStore
- Pre-computed memos for infra, workloads, statusCounts
- Filtering methods: byType, byPlatform, filtered
- Query helpers: get, children, topByCpu, topByMemory
- Created useResourcesAsLegacy helper for migration
- Converts resources to legacy VM/Container formats
- Enables gradual component migration
This provides the foundation for migrating frontend pages to use
the unified resource model.
- Removed /resources page and associated frontend components
- Removed ResourcesOverview.tsx, UnifiedResourceRow.tsx, columns.ts
- Removed frontend types/resource.ts
- Updated unified-resource-architecture.md to mark Phase 4 as ABANDONED
- Removed unified-view-migration-plan.md
- Backend unified resource model remains for AI context
This is a checkpoint before attempting full frontend migration to unified model.
This implements Phase 4 of the Unified Resource Architecture - the frontend
unified resources view.
New Features:
- Unified resources page at /resources route
- Fetches from /api/resources REST endpoint
- Auto-refreshes every 10 seconds
- Filtering by search, type, platform, status
- Grouping by type, platform, or parent
- Status indicators with alert badges
- CPU/Memory/Disk progress bars
Files Added:
- frontend-modern/src/types/resource.ts - TypeScript types matching Go backend
- frontend-modern/src/components/Resources/ResourcesOverview.tsx - Main component
Files Modified:
- frontend-modern/src/App.tsx - Added lazy import and route for ResourcesOverview
- .gemini/docs/unified-resource-architecture.md - Updated Phase 4 status
Access the unified view by navigating to /resources directly.
The route is not yet in the main navigation (power user feature).
- Extended AI context selection to host rows in HostsOverview
- Added resourceId prop to StackedMemoryBar for sparkline support
- Relocated guest URL editing from GuestRow name click
- Added GuestNotes component with URL field in AI sidebar
- Refined host routing in AI service backend
- Minor animation and styling improvements
- Implement 'Show Problems Only' toggle combining degraded status, high CPU/memory alerts, and needs backup filters
- Add 'Investigate with AI' button to filter bar for problematic guests
- Fix dashboard column sizing inconsistencies between bars and sparklines view modes
- Fix PBS backups display and polling
- Refine AI prompt for general-purpose usage
- Fix frontend flickering and reload loops during initial load
- Integrate persistent SQLite metrics store with Monitor
- Fortify AI command routing with improved validation and logging
- Fix CSRF token handling for note deletion
- Debug and fix AI command execution issues
- Various AI reliability improvements and command safety enhancements
Simplified OS display to plain "Windows" and "Linux" text labels.
Previous icon attempts were rejected as too complex or unclear.
Text labels are cleaner and more universally recognizable.
- Extract ostype from LXC container config (debian, ubuntu, alpine, etc.)
- Map ostype values to human-readable names (e.g., "debian" -> "Debian")
- Add OSName field to Container model and ContainerFrontend
- Add icons for NixOS, openSUSE, and Gentoo in frontend
- LXC containers now show OS icons alongside VMs in the dashboard
Supported LXC OS types: alpine, archlinux, centos, debian, devuan,
fedora, gentoo, nixos, opensuse, ubuntu, unmanaged
- Add OSInfoCell component with OS-specific icons (Windows, Ubuntu,
Debian, Alpine, CentOS/RHEL, Fedora, Arch, FreeBSD, generic Linux)
- Each OS type has a distinct color for quick visual identification
- Portal tooltip shows full OS name, version, and guest agent version
- Much more compact than text strings like "Microsoft Windows Server 2022"
