When local LLM servers (LM Studio, llama.cpp) receive tool definitions
but the model doesn't support function calling, they output internal
control tokens like <|channel|>, <|im_start|>, etc. instead of proper
responses.
This change detects these control tokens during streaming and returns
a clear error message explaining that the model doesn't support function
calling and recommending compatible models (Llama 3.1+, Mistral, Qwen).
This is better than the previous approach of offering a "disable tools"
option, which would have crippled Pulse Assistant/Patrol functionality.
Users need to use compatible models for the AI features to work properly.
Related to #1154
Some local models (llama.cpp, LM Studio) output internal control tokens
like <|channel|>, <|constrain|>, <|message|> instead of using proper
function calling. These tokens leak into the UI creating a poor UX.
This adds sanitization to strip these control tokens from both streaming
and non-streaming responses before they reach the user.
- Discovery: classify transient errors (429, timeout, connection refused, etc.)
and return IsError:true so models stop retrying rate-limited calls
- Agentic loop: detect identical tool calls repeated >3 times and block with
LOOP_DETECTED error, forcing the model to try a different approach
- OpenAI provider: skip tool_choice for DeepSeek Reasoner which doesn't support it
- Read-only classifier: fix curl -I case sensitivity (uppercase flags lowered),
add iostat/vmstat/mpstat/sar/lxc-ls/lxc-info/nc -z to allowlist,
fix 2>&1 false positive in input redirect detection
Gemini requires that model messages with function calls must be
immediately followed by user messages with function responses.
When message pruning or errors leave orphaned function calls,
Gemini rejects the request.
Add sanitizeGeminiContents() to:
- Strip orphaned function calls (keeping text content)
- Remove orphaned function responses without preceding calls
- Log when sanitization occurs for debugging
Provider updates across all supported backends:
- Anthropic: Better tool call handling
- OpenAI: Improved response parsing
- Gemini: Enhanced compatibility
- Ollama: Local model support improvements
Includes test updates for OpenAI provider.
Major new AI capabilities for infrastructure monitoring:
Investigation System:
- Autonomous finding investigation with configurable autonomy levels
- Investigation orchestrator with rate limiting and guardrails
- Safety checks for read-only mode enforcement
- Chat-based investigation with approval workflows
Forecasting & Remediation:
- Trend forecasting for resource capacity planning
- Remediation engine for generating fix proposals
- Circuit breaker for AI operation protection
Unified Findings:
- Unified store bridging alerts and AI findings
- Correlation and root cause analysis
- Incident coordinator with metrics recording
New Frontend:
- AI Intelligence page with patrol controls
- Investigation drawer for finding details
- Unified findings panel with actions
Supporting Infrastructure:
- Learning store for user preference tracking
- Proxmox event ingestion and correlation
- Enhanced patrol with investigation triggers
- Restore 'mini' mode for StackedDiskBar.
- Restore layout fixes (fixed table layout, mobile columns) for Docker and Hosts tables.
- Remove 'Ask AI' and AI context selection features.
- Docker: Use compact 'Cube' icon for Podman pods to prevent name obstruction.
- Docker: Show concise image names (strip registry URL).
- Backend: Include pending fixes for AI providers.
- Updated AI providers and tests for context/tenant awareness
- Refactored tool executor for multi-tenant state handling
- Added new tests for Docker control and update tools
- Add comprehensive tests for internal/api/config_handlers.go (Phases 1-3)
- Improve test coverage for AI tools, chat service, and session management
- Enhance alert and notification tests (ResolvedAlert, Webhook)
- Add frontend unit tests for utils (searchHistory, tagColors, temperature, url)
- Add proximity client API tests
- Add ChatStream method to all providers (Anthropic, OpenAI, Gemini, Ollama)
for real-time streaming of AI responses with tool call support
- Add StreamingProvider interface with StreamEvent types for content,
thinking, tool_start, tool_end, done, and error events
- Add notable models feature that fetches model metadata from models.dev
to identify recent/recommended models (within last 3 months)
- Add Notable field to ModelInfo struct to flag "latest and greatest" models
- Add SupportsThinking method to check for extended reasoning capability
The streaming support enables real-time AI chat responses instead of
waiting for complete responses. The notable models feature helps users
identify which models are current and recommended.
Users providing base URLs like "https://openrouter.ai/api/v1" were
getting HTML error responses because the client used the URL directly
without appending "/chat/completions".
- Normalize baseURL in NewOpenAIClient to ensure it ends with /chat/completions
- Fix modelsEndpoint() to derive /models from the normalized baseURL
- Add tests for URL normalization with various endpoint formats
The DisableDockerUpdateActions setting was being saved to disk but not
updated in h.config, causing the UI toggle to appear to revert on page
refresh since the API returned the stale runtime value.
Related to #1023
This update integrates learned baselines into the heuristic analysis to detect abnormal behavior and records significant events (migrations, restarts, spikes) for correlation analysis. Also fixed syntax errors in Ollama integration tests.
- Add persistent volume mounts for Go/npm caches (faster rebuilds)
- Add shell config with helpful aliases and custom prompt
- Add comprehensive devcontainer documentation
- Add pre-commit hooks for Go formatting and linting
- Use go-version-file in CI workflows instead of hardcoded versions
- Simplify docker compose commands with --wait flag
- Add gitignore entries for devcontainer auth files
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Adds RequestTimeoutSeconds to AI config (default 300s / 5 min).
Users with low-power hardware running Ollama can increase this
value in Settings to prevent timeouts on slower inference.
The issue was a SolidJS reactivity problem in the Dashboard component.
When guestMetadata signal was accessed inside a For loop callback and
assigned to a plain variable, SolidJS lost reactive tracking.
Changed from:
const metadata = guestMetadata()[guestId] || ...
customUrl={metadata?.customUrl}
To:
const getMetadata = () => guestMetadata()[guestId] || ...
customUrl={getMetadata()?.customUrl}
This ensures SolidJS properly tracks the signal dependency when the
getter function is called directly in JSX props.
Fixes issue where Ollama users get 'I'm a large language model, I can't do XYZ'
responses when trying to use the AI assistant. The problem was that the
Ollama provider was not passing tool definitions to the API.
Changes:
- Add Tools field to ollamaRequest struct
- Add ollamaTool, ollamaToolFunction, ollamaToolCall structs
- Convert tools from ChatRequest to Ollama format in Chat()
- Parse tool_calls from Ollama response
- Set StopReason to 'tool_use' when model requests tool execution
- Handle tool results in multi-turn conversations
Requires Ollama v0.3.0+ and a tool-capable model (llama3.1+, mistral-nemo, etc.)
Closes: Discussion #845 comment by misterlegend
- Add integration tests for Ollama provider (17 tests against real API)
- Add unit tests for baseline, correlation, patterns, memory, knowledge, cost packages
- Add context formatter and builder tests
- Add factory tests for provider initialization
- Add Makefile targets: test-integration, test-all
- Clean up test theatre (removed struct field tests)
Integration tests require Ollama at OLLAMA_URL (default: 192.168.0.124:11434)
Run with: make test-integration
- Replace verbose info banner with streamlined layout
- Add collapsible 'Advanced Model Selection' accordion for Chat/Patrol models
- Make AI Patrol Settings section collapsible with inline summary badges
- Compact Cost Controls into single-row inline layout
- Reduce form spacing for tighter presentation
- Remove unused formHelpText import
Also includes:
- OpenAI provider fixes for max_tokens parameters
- Security setup CSRF and 401 fixes
- Minor UI tweaks
Backend fixes:
- Strip provider prefix (anthropic:, openai:, deepseek:, ollama:) in all
provider Chat methods and constructors for robust handling
- Models are now correctly parsed regardless of caller format
Frontend fixes:
- Tool cards now persist in AI chat after approval execution by adding
to streamEvents array
- Dashboard now listens for pulse:metadata-changed custom event
- AI Chat emits this event when set_resource_url tool completes
- Guest URL icons now update instantly when AI sets them
- Add setup modal that appears when enabling AI without configured provider
- Modal allows selecting provider (Anthropic, OpenAI, DeepSeek, Ollama)
- Enter API key/URL and enable AI in one smooth flow
- Reorder backend to apply API keys before enabled check
- Fix Ollama to strip 'ollama:' prefix from model names
- Simplify backend error message for unconfigured providers
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
- 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
- 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
- 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
- Add AI service with Anthropic, OpenAI, and Ollama providers
- Add AI chat UI component with streaming responses
- Add AI settings page for configuration
- Add agent exec framework for command execution
- Add API endpoints for AI chat and configuration
