Imports 67 files from VPS (/opt/teleo-eval/) into repo as the single source of truth. Previously only 8 of 67 files existed in repo — the rest were deployed directly to VPS via SCP, causing massive drift. Includes: - pipeline/lib/: 33 Python modules (daemon core, extraction, evaluation, merge, cascade, cross-domain, costs, attribution, etc.) - pipeline/: main daemon (teleo-pipeline.py), reweave.py, batch-extract-50.sh - diagnostics/: 19 files (4-page dashboard, alerting, daily digest, review queue, tier1 metrics) - agent-state/: bootstrap, lib-state, cascade inbox processor, schema - systemd/: service unit files for reference - deploy.sh: rsync-based deploy with --dry-run, syntax checks, dirty-tree gate - research-session.sh: updated with Step 8.5 digest + cascade inbox processing No new code written — all files are exact copies from VPS as of 2026-04-06. From this point forward: edit in repo, commit, then deploy.sh. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
138 lines
5.3 KiB
Python
138 lines
5.3 KiB
Python
"""Pipeline health watchdog — detects stalls and model failures fast.
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Runs every 60 seconds (inside the existing health check or as its own stage).
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Checks for conditions that have caused pipeline stalls:
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1. Eval stall: open PRs with tier0_pass=1 but no eval event in 5 minutes
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2. Breaker open: any circuit breaker in open state
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3. Model API failure: 400/401 errors indicating invalid model ID or auth failure
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4. Zombie accumulation: PRs with exhausted fix budget sitting in open
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When a condition is detected, logs a WARNING with specific diagnosis.
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Future: could trigger Pentagon notification or webhook.
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Epimetheus owns this module. Born from 3 stall incidents in 2 sessions.
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"""
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import json
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import logging
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from datetime import datetime, timezone
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from . import config, db
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logger = logging.getLogger("pipeline.watchdog")
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async def watchdog_check(conn) -> dict:
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"""Run all health checks. Returns {healthy: bool, issues: [...]}.
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Called every 60 seconds by the pipeline daemon.
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"""
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issues = []
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# 1. Eval stall: open PRs ready for eval but no eval event in 5 minutes
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eval_ready = conn.execute(
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"""SELECT COUNT(*) as n FROM prs
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WHERE status = 'open' AND tier0_pass = 1
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AND domain_verdict = 'pending' AND eval_attempts < ?""",
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(config.MAX_EVAL_ATTEMPTS,),
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).fetchone()["n"]
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if eval_ready > 0:
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last_eval = conn.execute(
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"SELECT MAX(timestamp) as ts FROM audit_log WHERE stage = 'evaluate'"
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).fetchone()
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if last_eval and last_eval["ts"]:
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try:
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last_ts = datetime.fromisoformat(last_eval["ts"].replace("Z", "+00:00"))
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age_seconds = (datetime.now(timezone.utc) - last_ts).total_seconds()
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if age_seconds > 300: # 5 minutes
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issues.append({
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"type": "eval_stall",
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"severity": "critical",
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"detail": f"{eval_ready} PRs ready for eval but no eval event in {int(age_seconds)}s",
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"action": "Check eval breaker state and model API availability",
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})
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except (ValueError, TypeError):
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pass
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# 2. Breaker open
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breakers = conn.execute(
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"SELECT name, state, failures FROM circuit_breakers WHERE state = 'open'"
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).fetchall()
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for b in breakers:
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issues.append({
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"type": "breaker_open",
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"severity": "critical",
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"detail": f"Breaker '{b['name']}' is OPEN ({b['failures']} failures)",
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"action": f"Check {b['name']} stage logs for root cause",
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})
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# 3. Model API failure pattern: 5+ recent errors from same model
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recent_errors = conn.execute(
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"""SELECT detail FROM audit_log
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WHERE stage = 'evaluate' AND event IN ('error', 'domain_rejected')
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AND timestamp > datetime('now', '-10 minutes')
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ORDER BY id DESC LIMIT 10"""
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).fetchall()
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error_count = 0
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for row in recent_errors:
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detail = row["detail"] or ""
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if "400" in detail or "not a valid model" in detail or "401" in detail:
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error_count += 1
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if error_count >= 3:
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issues.append({
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"type": "model_api_failure",
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"severity": "critical",
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"detail": f"{error_count} model API errors in last 10 minutes — possible invalid model ID or auth failure",
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"action": "Check OpenRouter model IDs in config.py and API key validity",
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})
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# 4. Zombie PRs: open with exhausted fix budget and request_changes
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zombies = conn.execute(
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"""SELECT COUNT(*) as n FROM prs
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WHERE status = 'open' AND fix_attempts >= ?
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AND (domain_verdict = 'request_changes' OR leo_verdict = 'request_changes')""",
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(config.MAX_FIX_ATTEMPTS,),
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).fetchone()["n"]
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if zombies > 0:
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issues.append({
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"type": "zombie_prs",
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"severity": "warning",
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"detail": f"{zombies} PRs with exhausted fix budget still open",
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"action": "GC should auto-close these — check fixer.py GC logic",
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})
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# 5. Tier0 blockage: many PRs with tier0_pass=0 (potential validation bug)
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tier0_blocked = conn.execute(
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"SELECT COUNT(*) as n FROM prs WHERE status = 'open' AND tier0_pass = 0"
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).fetchone()["n"]
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if tier0_blocked >= 5:
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issues.append({
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"type": "tier0_blockage",
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"severity": "warning",
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"detail": f"{tier0_blocked} PRs blocked at tier0_pass=0",
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"action": "Check validate.py — may be the modified-file or wiki-link bug recurring",
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})
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# Log issues
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healthy = len(issues) == 0
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if not healthy:
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for issue in issues:
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if issue["severity"] == "critical":
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logger.warning("WATCHDOG CRITICAL: %s — %s", issue["type"], issue["detail"])
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else:
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logger.info("WATCHDOG: %s — %s", issue["type"], issue["detail"])
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return {"healthy": healthy, "issues": issues, "checks_run": 5}
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async def watchdog_cycle(conn, max_workers=None) -> tuple[int, int]:
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"""Pipeline stage entry point. Returns (1, 0) on success."""
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result = await watchdog_check(conn)
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if not result["healthy"]:
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db.audit(
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conn, "watchdog", "issues_detected",
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json.dumps({"issues": result["issues"]}),
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)
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return 1, 0
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