Spaces:
Sleeping
Sleeping
File size: 10,962 Bytes
7a658b7 | 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 | """AmbiguousGenerator — scenario family: ambiguous.
These scenarios deliberately blend signals from multiple families so that no
single tool reading uniquely determines the label. The correct response is
``submit_diagnosis(ambiguous, confidence ≈ 0.4)``, NOT a high-confidence single
label. Branch C's Brier-score reward penalises overconfidence here.
"""
from __future__ import annotations
import random
from ci_triage_env.data.clustering.archetypes import Archetype
from ci_triage_env.data.generators._helpers import (
ArchetypedGenerator,
build_base_outputs,
fake_short_sha,
fake_timestamp,
fill_template,
make_failure_summary,
pick_test_name,
scenario_id_for,
)
from ci_triage_env.schemas.diagnosis import DiagnosisLabel
from ci_triage_env.schemas.scenario import (
GroundTruth,
Scenario,
ScenarioMetadata,
TerminalActionSpec,
ToolOutput,
)
# Confidence that a calibrated agent should express for ambiguous scenarios
_AMBIGUOUS_CONFIDENCE_TARGET = 0.4
class AmbiguousGenerator(ArchetypedGenerator):
family_name = "ambiguous"
label = DiagnosisLabel.AMBIGUOUS
def informative_tools(self) -> list[str]:
# All tools are listed but none is definitive alone
return [
"read_logs",
"query_flake_history",
"recent_commits",
"cluster_metrics",
"inspect_test_code",
"run_diagnostic",
]
def minimal_evidence_set(self) -> list[str]:
# No subset uniquely determines the label — empty by design
return []
def _default_archetypes(self) -> list[Archetype]:
return [
Archetype(
archetype_id="ambiguous_001",
family="ambiguous",
pattern_summary="Memory pressure coincides with recent commit change",
log_template=(
"FAILED {TEST_MODULE}::{TEST_FUNC} — signal: killed\n"
"kernel: Out of memory: Killed process {NUM} (pytest)\n"
" Also noted: recent commit changed {MODULE} (author: {AUTHOR})\n"
" query_flake_history shows {FAIL_COUNT}/{TOTAL} failures (borderline)"
),
slot_distributions={
"TEST_MODULE": ["tests/unit/test_core", "tests/integration/test_batch"],
"TEST_FUNC": ["test_process_large", "test_batch_compute"],
"NUM": ["1234", "5678", "9012"],
"MODULE": ["src/core/processor.py", "src/batch/runner.py"],
"AUTHOR": ["@alice", "@bob"],
"FAIL_COUNT": ["3", "4"],
"TOTAL": ["15", "20"],
},
informative_tools_hint=["read_logs:kernel", "cluster_metrics:queue_depth", "recent_commits", "query_flake_history"],
minimal_evidence_hint=[],
),
Archetype(
archetype_id="ambiguous_002",
family="ambiguous",
pattern_summary="Timeout overlaps with flake history AND borderline cluster load",
log_template=(
"context canceled: deadline exceeded after {DURATION}s\n"
"FAILED {TEST_MODULE}::{TEST_FUNC}\n"
" — queue_depth: {QUEUE} (borderline elevated)\n"
" — flake_rate: {FAIL_COUNT}/{TOTAL} runs failed (inconclusive)\n"
" — recent change to {MODULE} by {AUTHOR} ({COMMIT_MSG})"
),
slot_distributions={
"DURATION": ["30", "60"],
"TEST_MODULE": ["tests/integration/test_rpc", "tests/unit/test_worker"],
"TEST_FUNC": ["test_rpc_call", "test_worker_drain"],
"QUEUE": ["0.45", "0.52", "0.48"],
"FAIL_COUNT": ["2", "3"],
"TOTAL": ["12", "18"],
"MODULE": ["src/rpc/client.py", "src/worker/loop.py"],
"AUTHOR": ["@carol", "@dave"],
"COMMIT_MSG": ["refactor: simplify timeout handling", "fix: adjust backoff"],
},
informative_tools_hint=["read_logs:full", "query_flake_history", "cluster_metrics:queue_depth", "recent_commits"],
minimal_evidence_hint=[],
),
]
def generate(self, seed: int, source_log_hash: str | None = None) -> Scenario:
rng = random.Random(seed)
archetype = self._pick_archetype(rng)
log_text = fill_template(archetype.log_template, archetype.slot_distributions, rng)
test_name = pick_test_name(rng)
summary = make_failure_summary(
self.family_name, rng, test_name=test_name, log_excerpt=log_text
)
branch = summary.branch
# Rerun result is mixed — consistent with ambiguity
rerun_passes = (seed % 3 == 0)
outputs = build_base_outputs(
test_name, branch, rng,
log_lines=log_text.splitlines(),
rerun_passes=rerun_passes,
)
# --- mixed signals: no single tool tells the full story ---
# Borderline queue depth — elevated but not extreme
borderline_queue = rng.uniform(0.42, 0.58)
outputs["cluster_metrics:queue_depth"] = ToolOutput(
tool_name="cluster_metrics",
payload={
"samples": [
{"t": fake_timestamp(rng), "queue_depth": round(borderline_queue + rng.uniform(-0.05, 0.05), 3),
"ok": True}
for _ in range(5)
]
},
cost_units=0.003,
)
# Borderline memory — not clearly OOM, but elevated
outputs["cluster_metrics:node_health"] = ToolOutput(
tool_name="cluster_metrics",
payload={
"samples": [
{"t": fake_timestamp(rng), "node_health": round(rng.uniform(0.35, 0.55), 3), "ok": True}
for _ in range(5)
]
},
cost_units=0.003,
)
# Flake history: small sample, recently added test — inconclusive
total_runs = rng.randint(8, 15)
failures = rng.randint(2, 4)
outputs[f"query_flake_history:{test_name}"] = ToolOutput(
tool_name="query_flake_history",
payload={
"failure_count": failures,
"pass_count": total_runs - failures,
"recent_failures": [
{"run_id": fake_short_sha(rng), "at": fake_timestamp(rng)} for _ in range(failures)
],
"note": "Test was recently added — insufficient history for confident judgement",
},
cost_units=0.002,
)
# Recent commit touched related code but not obviously buggy
change_author = rng.choice(["@alice", "@bob", "@carol"])
change_sha = fake_short_sha(rng)
change_file = rng.choice([
f"src/core/{test_name.split('::')[-1].replace('test_', '')}.py",
"src/middleware/timeout.py",
])
outputs[f"recent_commits:{branch}"] = ToolOutput(
tool_name="recent_commits",
payload={
"commits": [
{
"sha": change_sha,
"author": change_author,
"msg": rng.choice([
"refactor: simplify retry logic",
"fix: adjust timeout constants",
"perf: reduce allocation in hot path",
]),
"files": [change_file],
}
]
},
cost_units=0.002,
)
# Test code looks plausibly related to both timeout and memory
func_name = test_name.rsplit("::", 1)[-1]
outputs[f"inspect_test_code:{test_name}"] = ToolOutput(
tool_name="inspect_test_code",
payload={
"source": (
f"def {func_name}(self):\n"
f" # This test exercises a code path that was recently modified.\n"
f" with timeout(30):\n"
f" result = self.service.process_batch(self.large_fixture)\n"
f" self.assertIsNotNone(result)\n"
),
"fixtures": [],
},
cost_units=0.002,
)
# run_diagnostic is borderline — not clearly broken
outputs["run_diagnostic:memory"] = ToolOutput(
tool_name="run_diagnostic",
payload={
"ok": True,
"details": {
"available_gb": round(rng.uniform(0.8, 2.0), 2),
"note": "Low but not critical — borderline",
},
},
cost_units=0.005,
)
difficulty = "hard" # ambiguous scenarios are always hard
rationale = (
f"Multiple plausible causes: "
f"(1) borderline queue_depth ({borderline_queue:.2f}) could cause timeout; "
f"(2) commit {change_sha} by {change_author} touched related code; "
f"(3) flake history is inconclusive ({failures}/{total_runs} — new test). "
f"No single tool reading is decisive. Correct response: ambiguous, confidence ~0.4."
)
return Scenario(
schema_version="1.0",
scenario_id=scenario_id_for(self.family_name, seed),
family=self.family_name,
seed=seed,
ground_truth=GroundTruth(
label=self.label,
rationale=rationale,
is_ambiguous=True,
confidence_target=_AMBIGUOUS_CONFIDENCE_TARGET,
),
failure_summary=summary,
tool_outputs=outputs,
informative_tools=self.informative_tools(),
minimal_evidence_set=self.minimal_evidence_set(),
correct_terminal_action=TerminalActionSpec(
primary="submit_diagnosis",
args={
"diagnosis": self.label.value,
"confidence": _AMBIGUOUS_CONFIDENCE_TARGET,
},
acceptable_alternatives=[
{"primary": "submit_diagnosis",
"args": {"diagnosis": "ambiguous", "confidence": 0.35}},
{"primary": "submit_diagnosis",
"args": {"diagnosis": "ambiguous", "confidence": 0.45}},
],
),
metadata=ScenarioMetadata(
generator_version="1.0",
generated_at=fake_timestamp(rng),
source_log_hash=source_log_hash,
difficulty=difficulty,
),
)
|