Orchestrator changes:
- Force-spawn GAMMA on iteration_limit before abort
- GAMMA.synthesize() creates emergency handoff payload
- loadRecoveryContext() logs "Resuming from {task_id} handoff"
- POST to /api/pipeline/log for resume message visibility
AgentGamma changes:
- Add synthesize() method for emergency abort synthesis
- Merges existing proposals into coherent handoff
- Stores as synthesis_type: "abort_recovery"
Server changes:
- Add POST /api/pipeline/log endpoint for orchestrator logging
- Recovery pipeline properly inherits GAMMA synthesis
Test coverage:
- test_auto_recovery.py: 6 unit tests
- test_e2e_auto_recovery.py: 5 E2E tests
- test_supervisor_recovery.py: 3 supervisor tests
- Success on attempt 2 (recovery works)
- Max failures (3 retries then FAILED)
- Success on attempt 1 (no recovery needed)
Recovery flow:
1. iteration_limit triggers
2. GAMMA force-spawned for emergency synthesis
3. Handoff dumped with GAMMA synthesis
4. Exit code 3 triggers auto-recovery
5. Recovery pipeline loads handoff
6. Logs "Resuming from {prior_pipeline} handoff"
7. Repeat up to 3 times or until success
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
487 lines
19 KiB
Python
487 lines
19 KiB
Python
#!/usr/bin/env python3
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"""
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Supervisor Recovery Test
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Tests the complete supervisor-driven auto-recovery flow:
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1. Start a pipeline
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2. Force iteration_limit to trigger abort
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3. Verify GAMMA synthesizes proposals before handoff
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4. Verify supervisor spawns recovery pipeline
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5. Verify recovery pipeline loads handoff with resume message
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6. Track all retries until success or max failures
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Run with: python3 tests/test_supervisor_recovery.py
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Requires: UI server running on localhost:3000
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"""
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import asyncio
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import json
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import time
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import subprocess
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import sys
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import os
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from datetime import datetime
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from pathlib import Path
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import redis
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import requests
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REDIS_HOST = "127.0.0.1"
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REDIS_PORT = 6379
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REDIS_PASSWORD = "governance2026"
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UI_BASE_URL = "http://127.0.0.1:3000"
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MAX_RETRIES = 3
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class SupervisorRecoveryTest:
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"""Tests the supervisor-driven recovery flow."""
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def __init__(self):
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self.redis = redis.Redis(
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host=REDIS_HOST,
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port=REDIS_PORT,
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password=REDIS_PASSWORD,
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decode_responses=True
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)
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self.pipeline_chain = [] # Track all pipelines in the recovery chain
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self.logs = [] # Collect all logs
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def log(self, msg: str, level: str = "INFO"):
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"""Log a message with timestamp."""
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ts = datetime.utcnow().strftime("%H:%M:%S.%f")[:-3]
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log_entry = f"[{ts}] [{level}] {msg}"
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print(log_entry)
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self.logs.append(log_entry)
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def simulate_orchestrator_run(self, pipeline_id: str, should_fail: bool = True) -> dict:
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"""Simulate an orchestrator run with configurable success/failure."""
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task_id = self.redis.hget(f"pipeline:{pipeline_id}", "task_id")
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objective = self.redis.hget(f"pipeline:{pipeline_id}", "objective")
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run_number = int(self.redis.hget(f"pipeline:{pipeline_id}", "run_number") or "1")
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self.log(f"Simulating orchestrator run for {pipeline_id} (run #{run_number})")
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# Simulate some agent proposals
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proposals = [
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{
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"agent": "ALPHA",
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"key": f"proposal_r{run_number}_1",
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"value": {"solution": f"Solution A from run {run_number}"},
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"version": 1,
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"timestamp": datetime.utcnow().isoformat()
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},
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{
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"agent": "BETA",
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"key": f"proposal_r{run_number}_1",
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"value": {"solution": f"Solution B from run {run_number}"},
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"version": 1,
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"timestamp": datetime.utcnow().isoformat()
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},
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]
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# Write proposals to blackboard
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for p in proposals:
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self.redis.hset(
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f"blackboard:{task_id}:solutions",
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f"{p['agent']}_{p['key']}",
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json.dumps(p)
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)
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if should_fail:
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# Simulate GAMMA emergency synthesis
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gamma_synthesis = {
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"merged_solution": f"Merged solution from run {run_number}",
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"key_insights": [f"Insight {i+1} from run {run_number}" for i in range(3)],
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"unresolved_issues": ["Some remaining issues"],
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"recommended_focus": "Focus on X for next run",
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"confidence": 0.7,
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"synthesis_type": "abort_recovery",
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"timestamp": datetime.utcnow().isoformat(),
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"proposals_merged": len(proposals)
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}
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self.redis.hset(
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f"blackboard:{task_id}:synthesis",
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"gamma_emergency_synthesis",
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json.dumps(gamma_synthesis)
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)
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self.log(f"GAMMA emergency synthesis simulated: {len(gamma_synthesis['key_insights'])} insights")
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# Dump handoff
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handoff_key = f"handoff:{pipeline_id}:agents"
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handoff = {
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"pipeline_id": pipeline_id,
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"task_id": task_id,
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"dump_time": datetime.utcnow().isoformat(),
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"iteration_count": 12,
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"max_iterations": 10,
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"gamma_active": True,
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"proposals": proposals,
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"synthesis_attempts": [gamma_synthesis],
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"consensus_state": [],
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"problem_analysis": [],
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"agent_states": [
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{"role": "ALPHA", "status": "WORKING", "progress": 0.8},
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{"role": "BETA", "status": "WORKING", "progress": 0.7},
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{"role": "GAMMA", "status": "COMPLETED", "progress": 1.0},
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],
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"message_summary": {
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"alpha_last_messages": [],
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"beta_last_messages": [],
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"gamma_last_messages": []
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},
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"recovery_hints": [
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f"Iteration limit (10) exceeded after 12 iterations (run {run_number})",
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"GAMMA synthesized proposals before abort",
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f"{len(proposals)} proposals generated"
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]
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}
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self.redis.set(handoff_key, json.dumps(handoff), ex=86400)
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self.redis.hset(f"pipeline:{pipeline_id}", "handoff_key", handoff_key)
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self.log(f"Handoff dumped: {handoff_key}")
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return {
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"success": False,
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"exit_code": 3,
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"abort_reason": "iteration_limit",
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"proposals": len(proposals),
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"gamma_synthesis": True
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}
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else:
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# Simulate success
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self.redis.hset(f"pipeline:{pipeline_id}", mapping={
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"status": "COMPLETED",
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"final_consensus": "true",
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"completed_at": datetime.utcnow().isoformat()
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})
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self.log(f"Pipeline {pipeline_id} completed successfully!")
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return {
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"success": True,
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"exit_code": 0,
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"proposals": len(proposals)
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}
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def trigger_recovery(self, failed_pipeline_id: str) -> dict:
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"""Trigger recovery for a failed pipeline (simulating what the server does)."""
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pipeline_data = self.redis.hgetall(f"pipeline:{failed_pipeline_id}")
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task_id = pipeline_data.get("task_id")
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objective = pipeline_data.get("objective", "").replace("[RECOVERY", "").replace("[FORCE GAMMA]", "").strip()
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run_number = int(pipeline_data.get("run_number", "1"))
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if run_number >= MAX_RETRIES:
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self.log(f"Max retries ({MAX_RETRIES}) reached for {failed_pipeline_id}", "WARN")
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self.redis.hset(f"pipeline:{failed_pipeline_id}", mapping={
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"status": "FAILED",
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"failure_reason": "max_retries_exceeded",
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"completed_at": datetime.utcnow().isoformat()
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})
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return {"success": False, "reason": "max_retries_exceeded"}
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# Create recovery pipeline
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new_run = run_number + 1
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recovery_id = f"pipeline-recovery-{int(time.time() * 1000)}-r{new_run}"
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# Get handoff from failed pipeline
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handoff_key = f"handoff:{failed_pipeline_id}:agents"
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handoff_data = self.redis.get(handoff_key)
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inherited = json.loads(handoff_data) if handoff_data else {}
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# Create inherited handoff
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inherited_key = f"handoff:{recovery_id}:inherited"
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self.redis.set(inherited_key, json.dumps({
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"from_pipeline": failed_pipeline_id,
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"from_handoff": handoff_key,
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"inherited_at": datetime.utcnow().isoformat(),
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"proposals": inherited.get("proposals", []),
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"synthesis_attempts": inherited.get("synthesis_attempts", []),
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"recovery_hints": inherited.get("recovery_hints", [])
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}), ex=86400)
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# Create recovery pipeline
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self.redis.hset(f"pipeline:{recovery_id}", mapping={
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"task_id": task_id,
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"objective": f"[RECOVERY ATTEMPT {new_run}] [FORCE GAMMA] {objective}",
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"status": "STARTING",
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"created_at": datetime.utcnow().isoformat(),
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"agents": json.dumps([]),
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"parent_pipeline": failed_pipeline_id,
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"is_recovery": "true",
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"recovery_attempt": str(new_run),
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"run_number": str(new_run),
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"inherited_handoff": inherited_key,
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"force_gamma": "true",
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"model": "anthropic/claude-sonnet-4",
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"timeout": "60",
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"auto_continue": "true"
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})
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# Update original pipeline
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self.redis.hset(f"pipeline:{failed_pipeline_id}", mapping={
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"status": "REBOOTING",
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"recovery_pipeline": recovery_id
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})
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# Track recovery metrics
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self.redis.hset(f"recovery:{failed_pipeline_id}", mapping={
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"retry_count": str(new_run),
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"abort_reason": "iteration_limit",
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"latest_recovery": recovery_id,
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"handoff_ref": handoff_key,
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"last_attempt": datetime.utcnow().isoformat()
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})
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self.log(f"Recovery triggered: {failed_pipeline_id} -> {recovery_id} (attempt {new_run})")
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self.pipeline_chain.append(recovery_id)
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return {
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"success": True,
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"recovery_pipeline_id": recovery_id,
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"attempt": new_run,
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"inherited_proposals": len(inherited.get("proposals", []))
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}
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def verify_resume_message(self, pipeline_id: str) -> dict:
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"""Verify the pipeline logged the 'Resuming from handoff' message."""
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pipeline_data = self.redis.hgetall(f"pipeline:{pipeline_id}")
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if pipeline_data.get("is_recovery") != "true":
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return {"checked": False, "reason": "not_a_recovery_pipeline"}
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inherited_key = pipeline_data.get("inherited_handoff")
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if not inherited_key:
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return {"checked": True, "has_resume": False, "reason": "no_inherited_handoff"}
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inherited_data = self.redis.get(inherited_key)
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if not inherited_data:
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return {"checked": True, "has_resume": False, "reason": "inherited_data_missing"}
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inherited = json.loads(inherited_data)
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from_pipeline = inherited.get("from_pipeline", "unknown")
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# The resume message would be logged by the orchestrator
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# Since we're simulating, we'll verify the data is there
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has_proposals = len(inherited.get("proposals", [])) > 0
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return {
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"checked": True,
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"has_resume": True,
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"from_pipeline": from_pipeline,
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"inherited_proposals": len(inherited.get("proposals", [])),
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"expected_message": f"Resuming from {from_pipeline} handoff"
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}
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def create_initial_pipeline(self) -> str:
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"""Create the initial test pipeline."""
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pipeline_id = f"test-supervisor-{int(time.time())}"
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task_id = f"task-supervisor-{int(time.time())}"
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self.redis.hset(f"pipeline:{pipeline_id}", mapping={
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"task_id": task_id,
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"objective": "Test supervisor recovery flow",
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"status": "RUNNING",
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"created_at": datetime.utcnow().isoformat(),
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"agents": json.dumps(["ALPHA", "BETA"]),
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"run_number": "1",
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"model": "anthropic/claude-sonnet-4",
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"timeout": "30"
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})
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self.pipeline_chain.append(pipeline_id)
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self.log(f"Created initial pipeline: {pipeline_id}")
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return pipeline_id
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def cleanup(self):
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"""Clean up all test pipelines."""
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for pid in self.pipeline_chain:
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try:
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keys = self.redis.keys(f"*{pid}*")
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if keys:
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self.redis.delete(*keys)
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except Exception:
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pass
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# Also clean up task-related keys
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for pid in self.pipeline_chain:
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try:
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task_id = f"task-supervisor-{pid.split('-')[-1]}"
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keys = self.redis.keys(f"*{task_id}*")
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if keys:
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self.redis.delete(*keys)
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except Exception:
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pass
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def run_full_test(self, succeed_on_attempt: int = 2) -> dict:
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"""
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Run the full supervisor recovery test.
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Args:
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succeed_on_attempt: Which attempt should succeed (1-3, or 0 for never)
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"""
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print("\n" + "=" * 70)
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print("SUPERVISOR RECOVERY TEST")
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print(f"Success planned on attempt: {succeed_on_attempt if succeed_on_attempt else 'NEVER (test max failures)'}")
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print("=" * 70 + "\n")
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results = {
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"phases": [],
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"final_status": None,
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"total_attempts": 0,
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"pipeline_chain": []
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}
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try:
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# Phase 1: Create initial pipeline
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self.log("PHASE 1: Creating initial pipeline...")
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pipeline_id = self.create_initial_pipeline()
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results["phases"].append({"phase": 1, "action": "create", "pipeline": pipeline_id})
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current_pipeline = pipeline_id
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attempt = 1
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while attempt <= MAX_RETRIES:
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self.log(f"\n--- ATTEMPT {attempt} ---")
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# Should this attempt succeed?
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should_fail = (attempt != succeed_on_attempt)
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# Phase 2: Run orchestrator
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self.log(f"PHASE 2.{attempt}: Running orchestrator...")
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run_result = self.simulate_orchestrator_run(current_pipeline, should_fail=should_fail)
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results["phases"].append({
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"phase": f"2.{attempt}",
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"action": "orchestrate",
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"pipeline": current_pipeline,
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"result": run_result
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})
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if run_result["success"]:
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self.log(f"SUCCESS on attempt {attempt}!")
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results["final_status"] = "SUCCESS"
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results["total_attempts"] = attempt
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break
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# Phase 3: Verify GAMMA synthesis
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self.log(f"PHASE 3.{attempt}: Verifying GAMMA synthesis...")
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if run_result.get("gamma_synthesis"):
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self.log("+ GAMMA emergency synthesis confirmed")
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else:
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self.log("- GAMMA synthesis not found", "WARN")
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# Phase 4: Trigger recovery
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self.log(f"PHASE 4.{attempt}: Triggering recovery...")
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recovery_result = self.trigger_recovery(current_pipeline)
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results["phases"].append({
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"phase": f"4.{attempt}",
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"action": "recovery",
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"from_pipeline": current_pipeline,
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"result": recovery_result
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})
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if not recovery_result["success"]:
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self.log(f"Recovery failed: {recovery_result.get('reason')}", "ERROR")
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results["final_status"] = "FAILED"
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results["total_attempts"] = attempt
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break
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# Phase 5: Verify resume message
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recovery_pipeline = recovery_result["recovery_pipeline_id"]
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self.log(f"PHASE 5.{attempt}: Verifying resume message...")
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resume_result = self.verify_resume_message(recovery_pipeline)
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results["phases"].append({
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"phase": f"5.{attempt}",
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"action": "verify_resume",
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"pipeline": recovery_pipeline,
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"result": resume_result
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})
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if resume_result.get("has_resume"):
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self.log(f"+ Resume message verified: '{resume_result['expected_message']}'")
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self.log(f" Inherited {resume_result['inherited_proposals']} proposals")
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current_pipeline = recovery_pipeline
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attempt += 1
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# Set final status if we exhausted retries
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if results["final_status"] is None:
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results["final_status"] = "FAILED"
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results["total_attempts"] = MAX_RETRIES
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results["pipeline_chain"] = self.pipeline_chain
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# Print summary
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print("\n" + "=" * 70)
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print("TEST SUMMARY")
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print("=" * 70)
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print(f" Final Status: {results['final_status']}")
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print(f" Total Attempts: {results['total_attempts']}")
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print(f" Pipeline Chain:")
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for i, pid in enumerate(self.pipeline_chain):
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status = self.redis.hget(f"pipeline:{pid}", "status") or "UNKNOWN"
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print(f" {i+1}. {pid} -> {status}")
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print("=" * 70)
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# Verify Redis tracking
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if len(self.pipeline_chain) > 1:
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original = self.pipeline_chain[0]
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recovery_data = self.redis.hgetall(f"recovery:{original}")
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print("\nRECOVERY TRACKING (in Redis):")
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print(f" retry_count: {recovery_data.get('retry_count', 'N/A')}")
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print(f" abort_reason: {recovery_data.get('abort_reason', 'N/A')}")
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print(f" latest_recovery: {recovery_data.get('latest_recovery', 'N/A')}")
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print(f" handoff_ref: {recovery_data.get('handoff_ref', 'N/A')}")
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return results
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finally:
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# Cleanup
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self.log("\nCleaning up test data...")
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self.cleanup()
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def main():
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"""Run supervisor recovery tests."""
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print("\n" + "=" * 70)
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print("RUNNING SUPERVISOR RECOVERY TESTS")
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print("=" * 70 + "\n")
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# Test 1: Success on second attempt
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print("\n[TEST 1] Success on second attempt\n")
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tester1 = SupervisorRecoveryTest()
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result1 = tester1.run_full_test(succeed_on_attempt=2)
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test1_pass = result1["final_status"] == "SUCCESS" and result1["total_attempts"] == 2
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# Test 2: Max failures (all 3 attempts fail)
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print("\n[TEST 2] Max failures (all attempts fail)\n")
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tester2 = SupervisorRecoveryTest()
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result2 = tester2.run_full_test(succeed_on_attempt=0)
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test2_pass = result2["final_status"] == "FAILED" and result2["total_attempts"] == 3
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|
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# Test 3: Success on first attempt (no recovery needed)
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print("\n[TEST 3] Success on first attempt\n")
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tester3 = SupervisorRecoveryTest()
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|
result3 = tester3.run_full_test(succeed_on_attempt=1)
|
|
test3_pass = result3["final_status"] == "SUCCESS" and result3["total_attempts"] == 1
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|
|
# Final results
|
|
print("\n" + "=" * 70)
|
|
print("FINAL TEST RESULTS")
|
|
print("=" * 70)
|
|
print(f" Test 1 (success on attempt 2): {'PASS' if test1_pass else 'FAIL'}")
|
|
print(f" Test 2 (max failures): {'PASS' if test2_pass else 'FAIL'}")
|
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print(f" Test 3 (success on attempt 1): {'PASS' if test3_pass else 'FAIL'}")
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|
|
|
all_pass = test1_pass and test2_pass and test3_pass
|
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print(f"\n OVERALL: {'ALL TESTS PASSED' if all_pass else 'SOME TESTS FAILED'}")
|
|
print("=" * 70 + "\n")
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|
|
|
return 0 if all_pass else 1
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|
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|
|
|
if __name__ == "__main__":
|
|
sys.exit(main())
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