Adds patterns/telemetry.yaml with 6 rule groups (samsung, belkin, roku, lg, amazon, advertising).
Adds app/services/blocklist.py with TelemetryRule and BlocklistCandidate dataclasses, load_telemetry_rules(), and matches_telemetry() with exact and subdomain matching.
6 new TestTelemetry tests pass; 199 total passing.
The relative-time regex only matched digits between 'last/past' and
the unit, so 'last few hours' fell through to dateparser which then
found the bare word 'hours' and resolved it as midnight local time.
Extended the regex to capture 'few', 'couple of', 'several', 'a few'
as approximate quantifiers, mapped to 3 units each. Numeric expressions
and bare 'last hour' still work as before.
- Add context_block param to summarize() and thread it into _PROMPT_TEMPLATE
- Wire retrieve_context/format_context_block into diagnose_stream() before
log search; emit context SSE event (facts + chunks) to the client
- 3 new tests covering prompt injection and SSE event emission (155 total, all pass)
POST /api/inference/task with product=turnstone task=log_analysis routes to
the security reasoning model assigned in cf-orch. Falls back to the OpenAI-
compat /v1/chat/completions path on 404 (no assignment) or if the task
endpoint is absent (local instances, example-node).
- Diagnose: add source_filter param threaded through entries_in_window,
search, _diagnose, and DiagnoseRequest — clicking diagnose on a
dashboard source now scopes both keyword and window hits to that source
- QuickCapture: read route.query.source; show scope badge with clear ✕;
auto-run when source param is present without a query
- DashboardView: pass source= (not q=) when navigating to diagnose
- collect_cluster_logs.sh: auto-discover Docker containers on all nodes
(Heimdall non-watched, Navi, Strahl via SSH); collect Cass Plex logs
via SSH; write to per-node dirs for directory-mode ingest
- turnstone-cluster.service: add --reload for hot-reload during dev
Turnstone now calls /v1/chat/completions instead of Ollama's /api/generate.
This format works with both local Ollama (>=0.1.24) and a remote cf-orch
coordinator, enabling GPU-less nodes like Contributor2's to route diagnoses through
the cluster without any local model.
- llm.py: OpenAI-compat messages format, optional Bearer auth header
- diagnose.py: thread llm_api_key through the call chain
- rest.py: llm_api_key pref (default empty), SettingsBody field, passed to diagnose
- SettingsView.vue: API Key field, label updated from "Ollama URL" to "LLM Endpoint URL"
- tests: updated mocks for new response shape; added bearer token assertion test
Turnstone incidents now carry an issue_type tag (free-text with datalist
suggestions) used to categorize patterns for signature building.
Backend:
- Incident model gains issue_type; additive ALTER TABLE migration keeps
existing DBs working without a full schema rebuild
- New received_bundles table stores incoming JSON bundles with indexes on
bundled_at and issue_type
- build_bundle() assembles incident + related log entries into a versioned
bundle dict; store_bundle()/list_bundles()/get_bundle() for the receiver
- POST /api/incidents/{id}/send — pushes bundle to TURNSTONE_BUNDLE_ENDPOINT
- GET /api/incidents/{id}/bundle — export without sending
- POST /api/bundles — receive and store an incoming bundle
- GET /api/bundles — list all received bundles
- TURNSTONE_SOURCE_HOST and TURNSTONE_BUNDLE_ENDPOINT env vars; auto-set
source host from hostname in podman-standalone.sh
Frontend:
- Incidents form: issue_type field with datalist suggestions; Type column
in the table; Send Bundle button + status feedback in the detail drawer
- New BundlesView: collapsible bundle rows, inline JSON parse (no extra
round-trip), Export JSON download button
- Router and nav updated with /bundles route
- Add GET /api/stats endpoint with 24h windowed aggregation (criticals,
errors, per-source health, recent criticals list)
- Fix timestamp format bug: strftime('%Y-%m-%dT%H:%M:%S', ...) to match
stored ISO-8601 T-separated timestamps (datetime('now') uses space)
- Add composite index idx_ts_repeat(timestamp_iso, repeat_count) — drops
stats query from 3.5 s to <1 ms by resolving both WHERE conditions
from the index without table row fetches
- New DashboardView: 3 stat cards, source health table with health dots,
diagnose-per-source button, recent criticals panel, zero-state card
- Router default / → /dashboard; Dashboard first in nav
- DiagnoseView: reads ?q= query param on mount and auto-runs; shows
formatted LLM summary block
- LogEntryRow: expand/collapse for long entries (>200 chars or multiline)
When diagnose() auto-detects a source name, FTS keyword scoring can
bury real errors whose text doesn't match the symptom query. Add
recent_source_errors() — a plain-SQL scan ordered by timestamp — so
the most recent errors from a known service always surface regardless
of keyword overlap.
- Add `incidents` table to SQLite schema (id, label, started_at, ended_at,
notes, created_at, severity)
- Extract `ensure_schema()` from ingest pipeline so tables are always
created at startup, not only during ingest
- New `app/services/incidents.py`: create/list/get/delete + time-window
entry association (FTS keyword search + raw window fallback)
- New `entries_in_window()` in search.py: plain SQL scan for incident
detail when keyword FTS returns nothing
- REST endpoints: POST/GET /api/incidents, GET/DELETE /api/incidents/{id}
- Incident detail returns up to 100 associated log entries sorted by
timestamp, prioritising FTS keyword hits then ERROR/CRITICAL then all
Ingest pipeline (journald / Caddy / Docker-wrapped formats) with
per-source state tracking (repeat dedup, out-of-order detection),
named pattern tagging at ingest time, and idempotent SHA1-keyed writes.
FTS5 search layer with porter stemmer, severity/source/pattern/time
filters, and BM25 ranking. MCP server (FastMCP stdio) with three tools:
search_logs, diagnose, list_log_sources — compatible with both
Claude Code and Copilot CLI.
WAL mode enabled on all connections. FTS index auto-built after ingest.
MCP configs included for Claude Code (.mcp.json) and Copilot CLI
(.github/copilot/mcp.json).
