The reporting engine's synthesis layer was reachable only through
Generate/GenerateMulti, which always rendered PDF or CSV. Pulse
Assistant needs the same retrospective synthesis (per-resource
summary, fleet outliers, period comparison) in a form it can present
in chat, not as a downloaded artifact.
Add two non-rendering entry points to the Engine interface:
NarrativeFor(req MetricReportRequest) (*Narrative, error)
FleetNarrativeFor(req MultiReportRequest) (*FleetNarrative, error)
Both run the same query path and the same narrator resolution as their
rendering counterparts (heuristic by default, AI when the request
supplies a narrator, fail-closed-to-heuristic on any narrator error)
and return the structured narrative without invoking the fpdf/csv
output stage. Test stubs in pkg/reporting and internal/api are
updated to implement the extended interface.
These are the seams the upcoming pulse_summarize Assistant tools wrap
to answer questions like "what's hot on pve1 this week" or "where
should I look across my fleet" without round-tripping through report
generation. Same synthesis layer, no PDF involved.
Also fixes a pre-existing flake in TestEngineGenerate_UsesSuppliedNarrator
(metrics writes are async; the first Generate sometimes ran before
the raw tier flushed). Wrapped in the same eventually-pattern used by
the prior-period and findings-provider tests.
The single-resource AI narrative landed in b2bd9d114 but multi-resource
fleet reports stayed heuristic-only. That left a gap on the exact axis
where AI helps most: a 50-resource fleet PDF is where synthesis is the
difference between useful and unread.
Introduce FleetNarrator as a separate interface from Narrator. The
input shapes are different — single-resource takes one set of metric
stats with a prior window, fleet takes a denormalised cross-resource
view with per-resource summaries plus a fleet aggregate.
HeuristicFleetNarrator owns the deterministic fallback: ranks
resources by severity (critical alerts > unhealthy disks > storage
pressure > memory > CPU > non-critical alerts), picks up to 5
outliers, derives cross-cutting patterns by counting how many of N
resources share a hot signal, and emits fleet-scoped recommendations.
internal/ai.Service implements FleetNarrator through
report_fleet_narrator.go. Distinct use-case label
(report_narrative_fleet) so fleet vs single-resource spend is
separable in the cost ledger and budget gate. The fleet payload is
denormalised through buildReportFleetPayload so prompt cost scales
linearly with fleet size. Same fail-closed invariant — nil provider,
parse failure, or context cancellation falls through to the heuristic.
Single-resource Narrator is intentionally NOT propagated through
engine.GenerateMulti: a 50-resource fleet report performs one AI call
(fleet narrator), not 51. The router resolver returns the AI service
for all three roles (Narrator, FleetNarrator, FindingsProvider).
The fleet PDF renders the FleetNarrative in the fleet summary cover
when present: executive prose, named outliers with severity-coloured
bullets, cross-cutting patterns, recommendations, optional period
comparison, and an AI provenance footer. The deterministic resource
summary table is preserved above so every named outlier is verifiable
against the table immediately below it. Legacy "Highest CPU / Most
alerts" bullets remain as the fallback when no FleetNarrative is
attached.
Performance reports rendered the Executive Summary, Observations, and
Recommendations sections from inline threshold rules in pdf.go. That
narrative looked intelligent but was static templating against alert
counts and metric percentiles, which felt off-brand alongside Patrol
and Pulse Assistant.
Introduce a Narrator interface in pkg/reporting and a FindingsProvider
counterpart that the engine consults at report time. The heuristic
rules are lifted into HeuristicNarrator unchanged so the deterministic
fallback still produces the same observations and recommendations.
The engine now also queries the comparable prior period and threads
its aggregate stats through the narrator so deltas can be expressed.
internal/ai.Service implements both interfaces via report_narrator.go
(single-turn JSON call grounded in the structured ReportData payload,
falling back to the heuristic on any error/timeout) and
report_findings.go (Patrol findings whose lifecycle overlaps the
report window). The reporting handler resolves the per-tenant AI
service when it is configured and supplies it in the request; absent
configuration, reports look identical to the prior heuristic output.
Charts, stats tables, alert lists, storage and disk sections stay
deterministic — sysadmins can verify every AI claim against the data
tables next to it. The PDF renders the AI prose between the health
card and Quick Stats, adds a Period-over-period section after
Recommendations, and prints a provenance footer when the narrative
came from the assistant.
ai-runtime.md and api-contracts.md updates land in a follow-up commit
on this branch; agent-lifecycle / performance-and-scalability /
storage-recovery have no contract delta from this change (router.go
is referenced in their Extension Points but their semantics are
unchanged).
The reporting engine held a direct pointer to the metrics store, which
becomes invalid after a monitor reload (settings change, node config
save, etc.) closes and recreates the store. Use a dynamic getter closure
that always resolves to the current monitor's active store.
Also adds diagnostic logging when report queries return zero metrics,
and integration tests covering the full metrics-to-report pipeline
including reload scenarios.
Fixes#1186
Replace manual resource ID entry with a searchable, filterable resource
picker that uses live WebSocket state. Support selecting multiple
resources (up to 50) for combined fleet reports.
Multi-resource PDFs include a cover page, fleet summary table with
aggregate health status, and condensed per-resource detail pages with
overlaid CPU/memory charts. Multi-resource CSVs include a summary
section followed by interleaved time-series data with resource columns.
New POST /api/admin/reports/generate-multi endpoint handles multi-resource
requests while the existing single-resource GET endpoint remains unchanged.
Also fixes resource ID validation regex to allow colons used in
VM/container IDs (e.g., "instance:node:vmid").
rcourtman