File size: 11,222 Bytes
06b4790 4887b5f 06b4790 df52e99 06b4790 4887b5f 06b4790 4887b5f 06b4790 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 | #!/usr/bin/env python3
"""
validate.py — Pre-submission validation script.
Run this before submitting to confirm all checklist items pass:
python validate.py
Exit code 0 = all checks passed.
Exit code 1 = one or more checks failed.
"""
import sys
import os
import random
import traceback
sys.path.insert(0, os.path.dirname(__file__))
PASS = "\033[92m✓\033[0m"
FAIL = "\033[91m✗\033[0m"
WARN = "\033[93m!\033[0m"
failures = []
def check(name: str, fn):
try:
result = fn()
if result is True or result is None:
print(f" {PASS} {name}")
return True
else:
print(f" {FAIL} {name}: {result}")
failures.append(name)
return False
except Exception as e:
print(f" {FAIL} {name}: {e}")
traceback.print_exc()
failures.append(name)
return False
def main():
print("\n=== DevOps Incident Response — OpenEnv Validation ===\n")
# --- Imports ---
print("[ Imports ]")
def check_imports():
from env import DevOpsIncidentEnv
from models import Action, ActionType, Observation, StepResult, State
from graders.grader import grade_episode
return True
check("All modules import cleanly", check_imports)
# --- Reset returns valid Observation ---
print("\n[ reset() ]")
def check_reset_easy():
from env import DevOpsIncidentEnv
env = DevOpsIncidentEnv(task_id="easy", seed=42)
obs = env.reset()
assert obs.step == 0
assert len(obs.services) > 0
assert len(obs.active_alerts) > 0
assert obs.task_id == "easy"
return True
def check_reset_all_tasks():
from env import DevOpsIncidentEnv
for task_id in ["easy", "medium", "hard", "bonus", "security", "database", "failover"]:
env = DevOpsIncidentEnv(task_id=task_id, seed=42)
obs = env.reset()
assert obs.task_id == task_id, f"task_id mismatch for {task_id}"
assert obs.max_steps > 0
return True
def check_reset_reproducible():
from env import DevOpsIncidentEnv
from models import Action, ActionType
results = []
for _ in range(3):
env = DevOpsIncidentEnv(task_id="easy", seed=42)
obs = env.reset()
results.append(obs.services[0].memory_percent)
assert len(set(results)) == 1, f"Different results for same seed: {results}"
return True
def check_seed_variety():
from env import DevOpsIncidentEnv
roots = set()
for seed in range(10):
env = DevOpsIncidentEnv(task_id="easy", seed=seed)
env.reset()
s = env.state()
roots.add(s.ground_truth_root_cause)
assert len(roots) > 1, f"All seeds produce same scenario: {roots}"
return True
check("reset() returns valid Observation for easy task", check_reset_easy)
check("reset() works for all 7 tasks", check_reset_all_tasks)
check("Same seed always produces same episode", check_reset_reproducible)
check("Different seeds produce different scenarios", check_seed_variety)
# --- step() ---
print("\n[ step() ]")
def check_step_returns_result():
from env import DevOpsIncidentEnv
from models import Action, ActionType, StepResult
env = DevOpsIncidentEnv(task_id="easy", seed=42)
env.reset()
result = env.step(Action(action_type=ActionType.NOOP))
assert isinstance(result, StepResult)
assert isinstance(result.reward, float)
assert isinstance(result.done, bool)
assert result.observation.step == 1
return True
def check_step_reward_in_range():
from env import DevOpsIncidentEnv
from models import Action, ActionType
rng = random.Random(0)
for task_id in ["easy", "medium", "hard", "bonus", "security", "database", "failover"]:
env = DevOpsIncidentEnv(task_id=task_id, seed=42)
env.reset()
done = False
steps = 0
while not done and steps < 30:
action = Action(action_type=rng.choice(list(ActionType)))
result = env.step(action)
assert -1.0 <= result.reward <= 1.0, f"reward={result.reward} out of range"
done = result.done
steps += 1
return True
def check_max_steps_terminates():
from env import DevOpsIncidentEnv
from models import Action, ActionType
env = DevOpsIncidentEnv(task_id="easy", seed=42)
env.reset()
done = False
steps = 0
while not done:
result = env.step(Action(action_type=ActionType.NOOP))
done = result.done
steps += 1
assert steps <= 20, "Episode never terminated"
return True
check("step() returns valid StepResult", check_step_returns_result)
check("step() rewards always in [-1.0, 1.0]", check_step_reward_in_range)
check("Episode terminates at max_steps", check_max_steps_terminates)
# --- state() ---
print("\n[ state() ]")
def check_state_has_ground_truth():
from env import DevOpsIncidentEnv
from models import Action, ActionType
env = DevOpsIncidentEnv(task_id="medium", seed=42)
env.reset()
env.step(Action(action_type=ActionType.NOOP))
s = env.state()
assert s.ground_truth_root_cause != ""
assert s.ground_truth_fix != ""
assert len(s.action_history) == 1
return True
check("state() returns ground truth and action history", check_state_has_ground_truth)
# --- Graders ---
print("\n[ Graders ]")
def check_graders_in_range():
from env import DevOpsIncidentEnv
from models import Action, ActionType
from graders.grader import grade_episode
rng = random.Random(99)
for task_id in ["easy", "medium", "hard", "bonus", "security", "database", "failover"]:
env = DevOpsIncidentEnv(task_id=task_id, seed=42)
env.reset()
done = False
steps = 0
while not done and steps < 30:
action = Action(action_type=rng.choice(list(ActionType)))
result = env.step(action)
done = result.done
steps += 1
s = env.state()
score = grade_episode(
task_id, s.action_history, s.ground_truth_root_cause,
s.ground_truth_fix, s.incident_resolved, s.total_reward,
)
assert 0.0 <= score <= 1.0, f"{task_id} score={score} out of [0,1]"
return True
def check_graders_not_constant():
from env import DevOpsIncidentEnv
from models import Action, ActionType
from graders.grader import grade_episode
scores = []
for seed in [1, 2, 3, 42, 99]:
rng = random.Random(seed * 7)
env = DevOpsIncidentEnv(task_id="easy", seed=seed)
env.reset()
done = False
steps = 0
while not done and steps < 15:
action = Action(action_type=rng.choice(list(ActionType)))
result = env.step(action)
done = result.done
steps += 1
s = env.state()
score = grade_episode(
"easy", s.action_history, s.ground_truth_root_cause,
s.ground_truth_fix, s.incident_resolved, s.total_reward,
)
scores.append(score)
assert len(set(scores)) > 1, f"Grader returns constant score: {scores}"
return True
def check_optimal_agent_scores_high():
from env import DevOpsIncidentEnv
from models import Action, ActionType
from graders.grader import grade_episode
# Easy task optimal sequence
env = DevOpsIncidentEnv(task_id="easy", seed=42)
env.reset()
s0 = env.state()
failing = s0.ground_truth_root_cause.replace("memory_leak_", "").replace("_", "-")
for act in [
Action(action_type=ActionType.READ_LOGS, service=failing),
Action(action_type=ActionType.READ_METRICS, service=failing),
Action(action_type=ActionType.DIAGNOSE, root_cause=f"memory leak {failing}"),
Action(action_type=ActionType.RESTART_SERVICE, service=failing),
]:
result = env.step(act)
if result.done:
break
s = env.state()
score = grade_episode(
"easy", s.action_history, s.ground_truth_root_cause,
s.ground_truth_fix, s.incident_resolved, s.total_reward,
)
assert score >= 0.85, f"Optimal agent scored only {score:.3f} on easy"
return True
check("All graders return scores in [0.0, 1.0]", check_graders_in_range)
check("Grader does not return constant scores across episodes", check_graders_not_constant)
check("Optimal agent scores >= 0.85 on easy task", check_optimal_agent_scores_high)
# --- Collateral damage penalty ---
print("\n[ Reward shaping ]")
def check_collateral_damage_penalty():
from env import DevOpsIncidentEnv
from models import Action, ActionType
env = DevOpsIncidentEnv(task_id="easy", seed=42)
env.reset()
s0 = env.state()
healthy = [svc for svc in s0.current_observation.services
if svc.status == "healthy"]
assert len(healthy) > 0, "No healthy services to test with"
result = env.step(Action(action_type=ActionType.RESTART_SERVICE,
service=healthy[0].name))
assert result.reward < 0, f"Expected negative reward for healthy restart, got {result.reward}"
return True
def check_info_gathering_rewarded():
from env import DevOpsIncidentEnv
from models import Action, ActionType
env = DevOpsIncidentEnv(task_id="easy", seed=42)
env.reset()
s0 = env.state()
failing = s0.ground_truth_root_cause.replace("memory_leak_", "").replace("_", "-")
result = env.step(Action(action_type=ActionType.READ_LOGS, service=failing))
assert result.reward > 0, f"Expected positive reward for reading failing service logs, got {result.reward}"
return True
check("Restarting healthy service gives negative reward", check_collateral_damage_penalty)
check("Reading failing service logs gives positive reward", check_info_gathering_rewarded)
# --- Files present ---
print("\n[ Required files ]")
for fname in ["openenv.yaml", "Dockerfile", "requirements.txt",
"inference.py", "README.md", "env.py", "api.py"]:
path = os.path.join(os.path.dirname(__file__), fname)
check(f"{fname} exists", lambda p=path: os.path.exists(p) or f"Missing: {p}")
# --- Summary ---
print()
if not failures:
print(f"{PASS} All checks passed! Ready to submit.\n")
sys.exit(0)
else:
print(f"{FAIL} {len(failures)} check(s) failed: {failures}\n")
sys.exit(1)
if __name__ == "__main__":
main()
|