FLAME-operator

🔥 FLAME-operator — Operate & Maintain FLAME

Skill ID: FLAME-operator · Version: 2.0.0 · Axis: ops Load when: Probing FLAME health, checking hit-rates, recovering demoted tiers, debugging model failures. Do NOT load for: Adding paid models (constitutional boundary), changing agent cascade.

Quick Ops

# Health probe — all 12 tiers, latency + content sanity
free-llm --mode probe

# Hit-rate dashboard — calls, success rate, avg latency per model
free-llm --mode stats

# Integrity snapshot — SHA256 of hit-rate state (NOT a seal)
free-llm --mode snapshot-checksum

# S5 Auto-recovery — attempt to re-promote demoted tiers after cooldown
free-llm --mode recover
free-llm --mode recover --json   # machine-readable

# Batch inference — one prompt per line
free-llm --batch /path/to/prompts.txt

# Single inference with JSON output
free-llm "prompt" --json

Tier Architecture (12 tiers, 2026-08-04)

FLAME runs 12 tiers of free/cheap models across Groq, SEA-LION, Gemini, Cerebras, OpenRouter, and Ollama. Auto-demotion fires at 3 consecutive fails. Auto-recovery attempts re-promotion after a 30-minute cooldown.

# List all tiers
python3 -c "
import json
cfg = json.load(open('/root/A-FORGE/flame/flame_config.json'))
for t in cfg['chains']['RM0-TOOLS-FREELOOP']['tiers']:
    w = t.get('weight', 1)
    print(f'{t[\"provider\"]}/{t[\"model\"]}  (weight={w})')
"

Health Probe Interpretation

Dynamic Reordering

FLAME auto-reorders every 5 minutes based on:

1. Latency: Faster models promoted
2. Hit-rate: Higher success rate weighted higher
3. Weight: Config-defined preference multiplier

# Force immediate reorder
python3 -c "
from flame_router import FlameEngine
e = FlameEngine()
new_order = e.reorder_by_latency()
for t in new_order: print(f'{t[\"provider\"]}/{t[\"model\"]}')
"

Tier Management

Auto-Demotion (L5)

• Trigger: 3 consecutive fails on any tier
• Effect: tier marked inactive, skipped in cascade
• Escalation: 10 total fails → permanent removal (requires manual re-probe)
• S5 fix (2026-08-04): caller-fault (reasoning model with starved token budget) is detected via heuristic (>100 chars reasoning OR <think> markers) and does NOT increment consecutive_fails. Only genuine model-faults trigger demotion.

Auto-Recovery (S5 Part 2)

# Attempt recovery of all demoted tiers (30-min cooldown per tier)
free-llm --mode recover

• Cooldown: 30 minutes before re-probe attempt
• Probe: "Say OK" with 80 max_tokens, 5s timeout
• Success: tier reactivated, consecutive_fails reset, promoted_at recorded
• Failure: demoted_at reset to now (cooldown extended another 30m)
• Cron: install a 5-minute timer to auto-run recovery

  # Already installed at:
  systemctl status flame-recover.timer
  

Manual Recovery (when auto-recovery fails 3+ times)

1. Direct probe the provider: curl test the endpoint
2. If provider is dead/expired: mark in FED, update config
3. If provider is healthy but tier still failing: check model ID, key rotation, rate limits
4. Force-reactivate: edit flame_config.json → set active: true on the tier
5. Run free-llm --mode probe to verify

Hit-Rate File

2026-08-04 path correction — verified live. Doc referenced wrong directory for 9 days (state file zeroed since 2026-07-26 because no FLAME process was writing to that path). Canonical paths below. A compat symlink was created at the legacy path so old monitoring tools keep working.

Hit-Rate: /root/.local/share/flame/flame_hitrate.jsonl
State:    /root/.local/share/flame/flame_state.json     ← canonical (FLAME writes here)
Seal:     /root/A-FORGE/flame/flame_seal.txt
Compat:   /root/.local/share/arifos/flame_state.json → ../flame/flame_state.json

If you see the legacy path returning zeros or missing: it was the bug. Read the canonical path above. Do NOT edit the legacy file — it's a symlink.

Each line in hitrate.jsonl is a call record with provider, model, success, latency, timestamp.

Debugging Model Failures

# Direct model test (bypass FLAME)
curl -s "PROVIDER_BASE/chat/completions" \
  -H "Authorization: Bearer $KEY" \
  -d '{"model":"MODEL_ID","messages":[{"role":"user","content":"Reply READY"}],"max_tokens":10}'

# Check current tier state (active/inactive/demoted)
python3 -c "
from flame_router import FlameEngine
e = FlameEngine()
for k,v in e.hitrates.items():
    status = '🟢' if v.active else '🔴'
    demoted = f' (demoted {v.demoted_at})' if v.demoted_at > 0 else ''
    print(f'{status} {k}: {v.calls}c {v.hit_rate:.0%}hr {v.avg_latency_ms:.0f}ms{demoted}')
"

# Attempt recovery
free-llm --mode recover

# Force reorder
python3 -c "
from flame_router import FlameEngine
e = FlameEngine()
new_order = e.reorder_by_latency()
for t in new_order: print(f'{t[\"provider\"]}/{t[\"model\"]}')
"

Constitutional Boundary

FLAME-operator is a maintenance skill, not a governance skill. It does not:

• Change which models are in the agent cascade (arifOS kernel domain)
• Add paid models (RM0 hard gate)
• Modify F1-F13 thresholds

For governance decisions (adding providers, changing cascade order), use the agent lane with arif_judge.