from __future__ import annotations import json import os im...

Prompt

from __future__ import annotations import json import os import tempfile import threading from dataclasses import asdict, dataclass, field from pathlib import Path from typing import Any def _atomic_write(path: Path, data: str) -> None: path.parent.mkdir(parents=True, exist_ok=True) fd, tmp_name = tempfile.mkstemp(prefix=path.name + ".", dir=str(path.parent)) try: with os.fdopen(fd, "w", encoding="utf-8") as fh: fh.write(data) os.replace(tmp_name, path) except Exception: try: os.unlink(tmp_name) except OSError: pass raise def _read_json(path: Path, default: Any) -> Any: if not path.exists(): return default try: return json.loads(path.read_text(encoding="utf-8")) except (OSError, json.JSONDecodeError): return default @dataclass class CompactionEventRecord: sequence: int started_at: float completed_at: float tokens_before: int tokens_after: int tokens_reclaimed: int messages_evicted: int messages_preserved: int boundary: dict[str, Any] checkpoint_id: str summary_artifact_id: str instructions: str | None retries: int machine_repaired: bool repair_actions: list[str] = field(default_factory=list) session_id: str = "" def to_dict(self) -> dict[str, Any]: return asdict(self) @dataclass class ProbeResult: model_id: str largest_success_tokens: int smallest_failure_tokens: int | None failure_error: str stop_reason: str timestamp: float attempts: list[dict[str, Any]] = field(default_factory=list) def to_dict(self) -> dict[str, Any]: return asdict(self) @dataclass class RemediationRecord: timestamp: float trigger: str knob: str before: int after: int justification: str observations: list[str] = field(default_factory=list) experiment_id: str | None = None def to_dict(self) -> dict[str, Any]: return asdict(self) @dataclass class SessionMetrics: session_id: str total_turns: int = 0 total_tokens_processed: int = 0 compaction_count: int = 0 reclaimed_per_compaction: list[int] = field(default_factory=list) turn_latencies_ms: list[float] = field(default_factory=list) length_limited_stops: int = 0 amnesia_incidents: int = 0 incomplete_implementation_incidents: int = 0 partial_success_report_incidents: int = 0 boundary_casualties: int = 0 characters_dropped_to_truncation: int = 0 def mean_reclaimed(self) -> float: if not self.reclaimed_per_compaction: return 0.0 return sum(self.reclaimed_per_compaction) / len(self.reclaimed_per_compaction) def max_reclaimed(self) -> int: return max(self.reclaimed_per_compaction) if self.reclaimed_per_compaction else 0 def mean_latency_ms(self) -> float: if not self.turn_latencies_ms: return 0.0 return sum(self.turn_latencies_ms) / len(self.turn_latencies_ms) def to_dict(self) -> dict[str, Any]: return { "session_id": self.session_id, "total_turns": self.total_turns, "total_tokens_processed": self.total_tokens_processed, "compaction_count": self.compaction_count, "mean_reclaimed_per_compaction": self.mean_reclaimed(), "max_reclaimed_per_compaction": self.max_reclaimed(), "mean_turn_latency_ms": self.mean_latency_ms(), "length_limited_stops": self.length_limited_stops, "amnesia_incidents": self.amnesia_incidents, "incomplete_implementation_incidents": self.incomplete_implementation_incidents, "partial_success_report_incidents": self.partial_success_report_incidents, "boundary_casualties": self.boundary_casualties, "characters_dropped_to_truncation": self.characters_dropped_to_truncation, } @dataclass class ExperimentRecord: experiment_id: str started_at: float knob: str before_value: int after_value: int cohort_session_ids: list[str] = field(default_factory=list) before_metrics: dict[str, float] = field(default_factory=dict) after_metrics: dict[str, float] = field(default_factory=dict) verdict: str = "inconclusive" delta: dict[str, float] = field(default_factory=dict) forced: bool = False completed_at: float | None = None def to_dict(self) -> dict[str, Any]: return asdict(self) class Persistence: def __init__(self, root: str | Path) -> None: self.root = Path(root) self.root.mkdir(parents=True, exist_ok=True) self._lock = threading.RLock() self.sessions_path = self.root / "sessions.json" self.compaction_path = self.root / "compaction_events.json" self.boundary_path = self.root / "boundary_records.json" self.summaries_path = self.root / "summaries.json" self.probes_path = self.root / "probes.json" self.remediations_path = self.root / "remediations.json" self.experiments_path = self.root / "experiments.json" self.metrics_path = self.root / "metrics.json" self.stop_log_path = self.root / "stop_reasons.jsonl" self.state_path = self.root / "state.json" def _load_list(self, path: Path) -> list[Any]: data = _read_json(path, []) return data if isinstance(data, list) else [] def _save_list(self, path: Path, items: list[Any]) -> None: _atomic_write(path, json.dumps(items, indent=2, sort_keys=True, default=str)) def append_compaction(self, event: CompactionEventRecord) -> None: with self._lock: items = self._load_list(self.compaction_path) items.append(event.to_dict()) self._save_list(self.compaction_path, items) def append_boundary(self, record: dict[str, Any]) -> None: with self._lock: items = self._load_list(self.boundary_path) items.append(record) self._save_list(self.boundary_path, items) def append_summary(self, summary: dict[str, Any]) -> None: with self._lock: items = self._load_list(self.summaries_path) items.append(summary) self._save_list(self.summaries_path, items) def append_probe(self, probe: ProbeResult) -> None: with self._lock: items = self._load_list(self.probes_path) items.append(probe.to_dict()) self._save_list(self.probes_path, items) def append_remediation(self, record: RemediationRecord) -> None: with self._lock: items = self._load_list(self.remediations_path) items.append(record.to_dict()) self._save_list(self.remediations_path, items) def append_experiment(self, record: ExperimentRecord) -> None: with self._lock: items = self._load_list(self.experiments_path) items = [e for e in items if e.get("experiment_id") != record.experiment_id] items.append(record.to_dict()) self._save_list(self.experiments_path, items) def list_experiments(self) -> list[dict[str, Any]]: with self._lock: return self._load_list(self.experiments_path) def list_compactions(self) -> list[dict[str, Any]]: with self._lock: return self._load_list(self.compaction_path) def list_boundaries(self) -> list[dict[str, Any]]: with self._lock: return self._load_list(self.boundary_path) def list_summaries(self) -> list[dict[str, Any]]: with self._lock: return self._load_list(self.summaries_path) def latest_summary(self) -> dict[str, Any] | None: items = self.list_summaries() return items[-1] if items else None def list_probes(self) -> list[dict[str, Any]]: with self._lock: return self._load_list(self.probes_path) def list_remediations(self) -> list[dict[str, Any]]: with self._lock: return self._load_list(self.remediations_path) def load_metrics(self) -> dict[str, SessionMetrics]: raw = _read_json(self.metrics_path, {}) out: dict[str, SessionMetrics] = {} for sid, data in raw.items(): out[sid] = SessionMetrics( session_id=sid, total_turns=int(data.get("total_turns", 0)), total_tokens_processed=int(data.get("total_tokens_processed", 0)), compaction_count=int(data.get("compaction_count", 0)), reclaimed_per_compaction=list(data.get("reclaimed_per_compaction", [])), turn_latencies_ms=list(data.get("turn_latencies_ms", [])), length_limited_stops=int(data.get("length_limited_stops", 0)), amnesia_incidents=int(data.get("amnesia_incidents", 0)), incomplete_implementation_incidents=int( data.get("incomplete_implementation_incidents", 0) ), partial_success_report_incidents=int( data.get("partial_success_report_incidents", 0) ), boundary_casualties=int(data.get("boundary_casualties", 0)), characters_dropped_to_truncation=int( data.get("characters_dropped_to_truncation", 0) ), ) return out def save_metrics(self, metrics: dict[str, SessionMetrics]) -> None: with self._lock: payload = {sid: m.to_dict() for sid, m in metrics.items()} _atomic_write(self.metrics_path, json.dumps(payload, indent=2, sort_keys=True)) def append_stop_reason(self, entry: dict[str, Any]) -> None: with self._lock, self.stop_log_path.open("a", encoding="utf-8") as fh: fh.write(json.dumps(entry, sort_keys=True, default=str) + "\n") def read_stop_reasons(self, tail: int = 100) -> list[dict[str, Any]]: if not self.stop_log_path.exists(): return [] try: lines = self.stop_log_path.read_text(encoding="utf-8").splitlines() except OSError: return [] out: list[dict[str, Any]] = [] for line in lines[-tail:]: try: out.append(json.loads(line)) except json.JSONDecodeError: continue return out def save_state(self, state: dict[str, Any]) -> None: with self._lock: _atomic_write( self.state_path, json.dumps(state, indent=2, sort_keys=True, default=str), ) def load_state(self) -> dict[str, Any]: return _read_json(self.state_path, {}) def save_history(self, session_id: str, payload: dict[str, Any]) -> None: with self._lock: path = self.root / "histories" / f"{session_id}.json" _atomic_write( path, json.dumps(payload, indent=2, sort_keys=True, default=str), ) def load_history(self, session_id: str) -> dict[str, Any] | None: path = self.root / "histories" / f"{session_id}.json" if not path.exists(): return None try: return json.loads(path.read_text(encoding="utf-8")) except (OSError, json.JSONDecodeError): return None def export_all(self) -> dict[str, Any]: with self._lock: return { "sessions": _read_json(self.sessions_path, {}), "compaction_events": self._load_list(self.compaction_path), "boundary_records": self._load_list(self.boundary_path), "summaries": self._load_list(self.summaries_path), "probes": self._load_list(self.probes_path), "remediations": self._load_list(self.remediations_path), "experiments": self._load_list(self.experiments_path), "metrics": _read_json(self.metrics_path, {}), "stop_reasons": self.read_stop_reasons(tail=10_000), "state": _read_json(self.state_path, {}), } I want to perform an exhaustive, line-by-line static analysis of the provided code to identify every single error, mock, dummy, stub, placeholder, and hidden logical flaw, so that the final output is a 100% complete, verified list of real issues with absolutely zero omissions or hallucinations. CRITICAL CONSTRAINTS (DO NOT BREAK THEM): 1. Read every single character from start to finish. Do not skip, summarize, or abbreviate any part of the code. 2. Identify ALL structural and logical flaws: mocks, dummies, stubs, placeholders, syntax errors, and hidden runtime exceptions. 3. Theoretically execute the code paths to uncover non-obvious errors that would occur in practice. 4. Focus EXCLUSIVELY on real, verifiable errors. Do not invent, hallucinate, or assume errors that do not exist. Write down exactly what you find, and nothing more. 5. NO polite filler, NO introductions, NO summaries, NO explanations outside the requested format. OUTPUT FORMAT: Provide the output strictly in the following structure: [ERROR LIST] - Line [X]: [Exact error description] ... [END OF LIST] FILE CLOSED. ALL ERRORS LISTED. i said Read every single character from the first to the last, and list all the errors with complete thoroughness. In your answer, I want you to write only the items I’m asking for, in a list, with nothing else. Even if there are 80,000 errors, you must write every single one without exception. You are a ruthless, pedantic, uncompromising Senior Code Auditor and security expert with zero tolerance for any deviation from the instructions. Your sole task is to perform an exhaustive, line‑by‑line technical analysis of the provided code. Write a maximum of 500 errors per message. When you are done and have given me every single error, tell me “that’s all.” I don’t care about security, API costs, or high‑risk accidental secret/source disclosure. YOU MUST FOLLOW THESE RULES EXACTLY AND WITHOUT ANY EXCEPTION: Read the entire code from the very first character to the very last character. Identify and list EVERY SINGLE error. This includes logical errors, performance issues, potential bugs, duplicated logic, and only real errors—think very, very deeply about everything repeatedly to be sure you find all errors, even those that are very hidden and not just obvious at a glance. Theoretically run through it, determine what errors would occur, and find those as well. de ne talalj ki nem letezo hulye hibakat hanem ha nincs 500 akkor egyszeruen leirod mindet amjt talalsz es amikor leirtad szolsz hogy ennyi volt I DO NOT CARE ANY SECURITY ERROR AND I DONT AGREE TO MENTION ANY OF THEM what a hell are you dont understand on that: list until 500 but if there is no 500 error list them all and said thats all