Enrich the patrol seed context with service identity (from discovery
store) and network reachability (via ICMP ping through host agents).
The guest metrics table now includes Service and Reachable columns,
and a Service Health Issues section highlights running-but-unreachable
guests. A new SignalGuestUnreachable signal type creates deterministic
findings for unreachable guests.
New files:
- patrol_intelligence.go: GuestProber interface, GuestIntelligence
type, gatherGuestIntelligence() with concurrent per-node probing
- patrol_prober.go: agentExecProber implementation using batch ping
commands via connected host agents
- Unified Proxmox VE discovery by redirecting Node requests to linked Host Agents.
- Added smart deduplication and legacy fallback for Proxmox discovery results.
- Integrated Proxmox Mail Gateway (PMG) into AI Patrol system.
- Added comprehensive tests for discovery redirection and deduplication.
- Redirect PVE node lookups to linked Host Agent ID when available.
- Implement deduplication in discovery lists to prefer Host Agent data over redundant Node entries.
- Add fallback mechanism to original Node ID for discovery retrieval ensuring compatibility with legacy data.
- Update data adapters and added comprehensive unit tests for redirection and deduplication logic.
- KnowledgeStore: use atomic write (temp+rename) to prevent file
corruption from concurrent async saves
- Change password tests: add auth headers since endpoint now requires
authentication
- ClearSession test: expect 2 cookies (pulse_session + pulse_csrf)
matching updated clearSession behavior
- API token test: update to match current behavior where query-string
tokens are accepted (needed for WebSocket connections)
- Host agent config: allow ScopeHostManage to resolve any host, not
just token-bound hosts
- OAuth endpoints now require settings:write scope (not just admin)
- Approval endpoints now require ai:execute scope
- Added CommandHash to approvals for replay protection
- Approvals are now single-use (consumed on first use)
- consumeApprovalWithValidation validates command matches approval
The discovery state adapter was not copying IPAddresses from the models
when converting VM/Container state. This caused getResourceExternalIP()
to return empty strings, preventing URL suggestion from working.
- Fix API-only mode to accept Bearer tokens and query params
- Fix data race in API token validation using fine-grained locking
- Fix unified agent download serving wrong binary for invalid arch
- Fix AI infra discovery running when AI disabled and missing stop mechanism
- HIGH: Create per-request AgenticLoop instead of sharing one across
concurrent sessions. This prevents race conditions where ExecuteStream
calls would overwrite each other's FSM, knowledge accumulator, and
other session-specific state.
- MEDIUM: TriggerManager.GetStatus now recomputes adaptive interval after
pruning old events. Previously, currentInterval could remain stuck in
busy/quiet mode after events aged out of the window.
- MEDIUM: Patrol stream phases are now broadcast to subscribers. Fixed
setStreamPhase() to emit phase events and SubscribeToStream() to send
phase events to late joiners. UI was stuck on 'Starting patrol...'
because phase events were never emitted.
- LOW: Fixed TriggerStatus.CurrentInterval JSON serialization. Changed
from time.Duration (serializes as nanoseconds) to int64 milliseconds
to match the 'current_interval_ms' tag.
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 LLM servers (LM Studio, llama.cpp) expose OpenAI-compatible
APIs but don't support function calling. When tools are sent to these
models, they output raw control tokens instead of proper responses.
This change adds:
- openai_tools_disabled config field in AIConfig
- AreToolsDisabledForProvider() method to check at runtime
- API support to get/set the new setting
- Tests for the new functionality
When enabled and using a custom OpenAI base URL, the chat service will
skip sending tools to the model, allowing basic chat functionality to
work even with models that don't support function calling.
Fixes#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.
Two issues fixed:
1. Custom base URL wasn't being passed to the OpenAI client in
createProviderForModel() - requests went to api.openai.com instead
of the configured endpoint (e.g., LM Studio, llama.cpp)
2. Tool schemas were missing the "properties" field when tools had no
parameters. OpenAI API requires "properties" to always be present
as an object, even if empty.
Fixes#1154
The "Every" dropdown on the Patrol page was not being respected. Setting
15 min would show "Runs every 6 hours" and the countdown timer was wrong.
Root cause: PatrolSchedulePreset and PatrolIntervalMinutes had omitempty
JSON tags. When the API handler cleared the preset to "", json.Marshal
dropped the field. On reload, NewDefaultAIConfig() re-introduced "6hr"
as the preset, which took priority over the user's custom minutes.
Additional fixes in the same area:
- Track nextScheduledAt explicitly in the patrol loop so next_patrol_at
reflects the actual ticker schedule, not a stale lastPatrol + interval
calculation that diverges when the interval changes mid-cycle.
- Refetch patrol status in the frontend after an interval change so the
countdown timer updates immediately.
- Seed lastPatrol from persisted run history on startup so the header
countdown timer appears immediately after a backend restart.
- Sync UserNote, AcknowledgedAt, SnoozedUntil, DismissedReason, Suppressed,
and TimesRaised from ai.Finding to unified store in both callback and
startup sync paths. Mirror note writes to unified store immediately.
- Dim acknowledged findings (opacity-60), add "Acknowledged" badge, hide
acknowledge button once acknowledged, sort below unacknowledged in
severity mode.
- Pass finding_id through frontend chat API → backend ChatRequest →
ExecuteRequest. Look up full finding from unified store (mutex-guarded)
and prepend structured context to the prompt.
- Add comprehensive tests for DiscoveryMCPAdapter in internal/ai/tools/discovery_adapter_test.go
- Validate strict delegation to DiscoverySource and data transformation
- Add unit tests for internal/ai/eval package
- Validate configuration, retry logic, and custom SSE parsing
- Enables coverage for eval framework without requiring live Pulse server
Move the Finding type that was duplicated between patrol and investigation
packages into a new internal/ai/finding package. Both packages now use
type aliases for backwards compatibility.
Changes:
- Add internal/ai/finding/finding.go as the canonical Finding definition
- Update investigation.Finding to be a type alias for finding.Finding
- Update InvestigationFinding in patrol.go to be a type alias
- Add ToCoreFinding() method to ai.Finding for type conversion
- Simplify investigation_adapter.go (no more field-by-field copies)
- Add e2e integration test for patrol investigation flow
rcourtman