			base_priority *= 1.3

		return base_priority

	def process_experience(self, experience: Dict[str, Any]) -> Dict[str, Any]:
		"""Process raw experience into training format."""
		processed = {
			"observation": experience.get("observation", {}),
			"action": experience.get("action", {}),
			"reward": experience.get("reward", 0.0),
			"next_observation": experience.get("next_observation", {}),
			"done": experience.get("done", False),
			"info": {
				"tests_passed": experience.get("tests_passed", False),
				"risk": experience.get("risk", 0.5),
				"near_miss": experience.get("near_miss", False)
			}
		}
		return processed

	def train_epoch(self, experiences: List[Dict[str, Any]], validation: bool = False) -> Dict[str, float]:
		"""Train or validate for one epoch."""
		metrics = defaultdict(float)
		n_batches = 0

		# Process all experiences in batches
		for i in range(0, len(experiences), self.config.batch_size):
			batch = experiences[i:i + self.config.batch_size]

			# Sample from replay buffer with priorities
			if not validation:
				replay_samples, indices, weights = self.replay_buffer.sample(len(batch))
				batch.extend(replay_samples)

			# Process batch
			processed_batch = [self.process_experience(exp) for exp in batch]

			# Simulate rollouts for each experience
			for exp in processed_batch:
				rollout = self.rollout_api.simulate_plan(
					exp["observation"],
					{"intent": "complete task"},  # Simplified plan
					[exp["action"]]
				)

				# Compute shaped rewards
				rewards = self.reward_shaper.compute_reward(
					action_result={
						"tests_passed": rollout.success_probability > 0.8,
						"files_changed": len(rollout.steps[-1].state_changes.get("files_changed", [])) if rollout.steps else 0,
						"lines_changed": sum(len(c.get("content", "").splitlines())
										  for c in rollout.steps[-1].state_changes.get("files_changed", []))
										  if rollout.steps else 0,
						"modified_files": [c.get("file") for c in rollout.steps[-1].state_changes.get("files_changed", [])]
										if rollout.steps else [],
						"partial_success": 0.5 < rollout.success_probability <= 0.8,
						"risk": rollout.avg_risk
					},
					intent=exp.get("intent", {}),
					world_model_prior={"risk": rollout.avg_risk, "success_prob": rollout.success_probability}
				)

				# Update metrics
				metrics["avg_risk"] += rollout.avg_risk
				metrics["success_prob"] += rollout.success_probability
				metrics["shaped_reward"] += rewards["total"]

				if not validation:
					# Update replay priorities based on shaped rewards
					new_priority = max(1e-6, rewards["total"] + 1.0)  # Shift to positive range
					self.replay_buffer.update_priorities(indices, np.array([new_priority]))

			n_batches += 1

		# Average metrics
		if n_batches > 0:
			for k in metrics:
				metrics[k] /= n_batches

		return dict(metrics)

	def train(self, train_data: List[Dict[str, Any]], val_data: List[Dict[str, Any]]) -> Dict[str, Any]:
		"""Main training loop."""
		best_val_metrics = None
		training_history = []

		# Initialize replay buffer with all experiences
		for exp in train_data:
			priority = self.compute_priority(exp)
			self.replay_buffer.add(exp, priority)

		# Training loop
		for epoch in range(self.config.num_epochs):
			# Training phase
			train_metrics = self.train_epoch(train_data)
			train_metrics["epoch"] = epoch

			# Validation phase
			val_metrics = self.train_epoch(val_data, validation=True)
			val_metrics = {f"val_{k}": v for k, v in val_metrics.items()}


train

				# Update metrics
				metrics["avg_risk"] += rollout.avg_risk
				metrics["success_prob"] += rollout.success_probability
				metrics["shaped_reward"] += rewards["total"]

				if not validation:
					# Update replay priorities based on shaped rewards
					new_priority = max(1e-6, rewards["total"] + 1.0)  # Shift to positive range
					self.replay_buffer.update_priorities(indices, np.array([new_priority]))

			n_batches += 1

		# Average metrics
		if n_batches > 0:
			for k in metrics:
				metrics[k] /= n_batches

		return dict(metrics)

	def train(self, train_data: List[Dict[str, Any]], val_data: List[Dict[str, Any]]) -> Dict[str, Any]:
		"""Main training loop."""
		best_val_metrics = None
		training_history = []

		# Initialize replay buffer with all experiences
		for exp in train_data:
			priority = self.compute_priority(exp)
			self.replay_buffer.add(exp, priority)

		# Training loop
		for epoch in range(self.config.num_epochs):
			# Training phase
			train_metrics = self.train_epoch(train_data)
			train_metrics["epoch"] = epoch

			# Validation phase
			val_metrics = self.train_epoch(val_data, validation=True)
			val_metrics = {f"val_{k}": v for k, v in val_metrics.items()}

			# Combine metrics
			epoch_metrics = {**train_metrics, **val_metrics}
			training_history.append(epoch_metrics)

			# Update best validation metrics
			if best_val_metrics is None or val_metrics["val_success_prob"] > best_val_metrics["val_success_prob"]:
				best_val_metrics = val_metrics

		return {
			"training_history": training_history,
			"best_val_metrics": best_val_metrics,
			"final_train_metrics": train_metrics,
			"final_val_metrics": val_metrics
		}

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--wm-ds", default=str(root / "data" / "skills" / "wm_ds.jsonl"))
	ap.add_argument("--replay", default=str(root / "data" / "replay" / "near_miss.jsonl"))
	ap.add_argument("--devtools", default=str(root / "data" / "devtools" / "dataset.jsonl"))
	ap.add_argument("--out", default=str(root / "models" / "wm_offpolicy"))
	ap.add_argument("--batch-size", type=int, default=32)
	ap.add_argument("--num-epochs", type=int, default=10)
	ap.add_argument("--lr", type=float, default=1e-4)
	ap.add_argument("--replay-size", type=int, default=100000)
	ap.add_argument("--priority-alpha", type=float, default=2.0)
	ap.add_argument("--seed", type=int, default=42)
	args = ap.parse_args()

	# Initialize paths
	wm_path = Path(args.wm_ds)
	rp_path = Path(args.replay)


import logging
import argparse
import json
from pathlib import Path

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--path", default=str(root / "models" / "memory"))
	ap.add_argument("--query", required=True)
	ap.add_argument("--topk", type=int, default=5)
	ap.add_argument("--recency", type=float, default=0.0)
	ap.add_argument("--quality", type=float, default=0.0, help="Quality weighting [0..1] to favor high-quality items")
	ap.add_argument("--max-age-days", type=float, default=None, help="Discard items older than this many days")
	ap.add_argument("--include-tags", nargs='*', default=[])
	ap.add_argument("--exclude-tags", nargs='*', default=[])
	args = ap.parse_args()

	from agi_dw.core.memory.episodic import EpisodicMemory  # type: ignore

	mem = EpisodicMemory.load(args.path)
	inc = list(args.include_tags or [])
	exc = list(args.exclude_tags or [])
	res = mem.query(
		args.query,
		k=max(1, int(args.topk)),
		recency_weight=float(args.recency),
		include_tags=(inc if inc else None),
		exclude_tags=(exc if exc else None),
		quality_weight=float(args.quality),
		max_age_days=(float(args.max_age_days) if args.max_age_days is not None else None),
	)
	print(json.dumps({"ok": True, "n": len(res), "hits": res}, ensure_ascii=False))
	return 0

if __name__ == "__main__":
	import sys
	sys.exit(main())

import argparse
import json
from pathlib import Path

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--mem", default=str(root / "models" / "memory"))
	ap.add_argument("--q", required=True)
	ap.add_argument("--k", type=int, default=5)
	ap.add_argument("--include", nargs='*', default=[])
	ap.add_argument("--exclude", nargs='*', default=[])
	args = ap.parse_args()

	from agi_dw.core.memory.episodic import EpisodicMemory  # type: ignore

	mem = EpisodicMemory.load(args.mem)
	res = mem.query(args.q, k=int(args.k), include_tags=list(args.include or []), exclude_tags=list(args.exclude or []))
	print(json.dumps(res, ensure_ascii=False))
	return 0

if __name__ == "__main__":
	import sys
	sys.exit(main())


main

		k=max(1, int(args.topk)),
		recency_weight=float(args.recency),
		include_tags=(inc if inc else None),
		exclude_tags=(exc if exc else None),
		quality_weight=float(args.quality),
		max_age_days=(float(args.max_age_days) if args.max_age_days is not None else None),
	)
	print(json.dumps({"ok": True, "n": len(res), "hits": res}, ensure_ascii=False))
	return 0

if __name__ == "__main__":
	import sys
	sys.exit(main())

import argparse
import json
from pathlib import Path

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--mem", default=str(root / "models" / "memory"))
	ap.add_argument("--q", required=True)
	ap.add_argument("--k", type=int, default=5)
	ap.add_argument("--include", nargs='*', default=[])
	ap.add_argument("--exclude", nargs='*', default=[])
	args = ap.parse_args()

	from agi_dw.core.memory.episodic import EpisodicMemory  # type: ignore

	mem = EpisodicMemory.load(args.mem)
	res = mem.query(args.q, k=int(args.k), include_tags=list(args.include or []), exclude_tags=list(args.exclude or []))
	print(json.dumps(res, ensure_ascii=False))
	return 0

if __name__ == "__main__":
	import sys
	sys.exit(main())


import logging
import argparse
import json
from pathlib import Path
from typing import Dict, Iterable

def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--repairs", default=str(root / "data" / "skills" / "actuator_il_repairs.jsonl"))
	ap.add_argument("--combined", default=str(root / "data" / "skills" / "actuator_il_combined.jsonl"))
	args = ap.parse_args()

	repairs = Path(args.repairs)
	combined = Path(args.combined)
	combined.parent.mkdir(parents=True, exist_ok=True)
	count = 0
	if repairs.exists():
		with combined.open("a", encoding="utf-8") as fout:
			for obj in iter_jsonl(repairs):
				inp = obj.get("input")
				out = obj.get("output")
				if isinstance(inp, str) and isinstance(out, str) and inp and out:
					fout.write(json.dumps({"input": inp, "output": out}, ensure_ascii=False) + "\n")
					count += 1
	print(json.dumps({"promoted": count, "repairs": str(repairs), "combined": str(combined)}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


import logging
import argparse
import json
from pathlib import Path
from typing import Dict, Iterable

def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--repairs", default=str(root / "data" / "skills" / "actuator_il_repairs.jsonl"))
	ap.add_argument("--combined", default=str(root / "data" / "skills" / "actuator_il_combined.jsonl"))
	args = ap.parse_args()

	repairs = Path(args.repairs)
	combined = Path(args.combined)
	combined.parent.mkdir(parents=True, exist_ok=True)
	count = 0
	if repairs.exists():
		with combined.open("a", encoding="utf-8") as fout:
			for obj in iter_jsonl(repairs):
				inp = obj.get("input")
				out = obj.get("output")
				if isinstance(inp, str) and isinstance(out, str) and inp and out:
					fout.write(json.dumps({"input": inp, "output": out}, ensure_ascii=False) + "\n")


import argparse
import json
from pathlib import Path
from typing import Dict, Iterable

def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--repairs", default=str(root / "data" / "skills" / "actuator_il_repairs.jsonl"))
	ap.add_argument("--combined", default=str(root / "data" / "skills" / "actuator_il_combined.jsonl"))
	args = ap.parse_args()

	repairs = Path(args.repairs)
	combined = Path(args.combined)
	combined.parent.mkdir(parents=True, exist_ok=True)
	count = 0
	if repairs.exists():
		with combined.open("a", encoding="utf-8") as fout:
			for obj in iter_jsonl(repairs):
				inp = obj.get("input")
				out = obj.get("output")
				if isinstance(inp, str) and isinstance(out, str) and inp and out:
					fout.write(json.dumps({"input": inp, "output": out}, ensure_ascii=False) + "\n")
					count += 1
	print(json.dumps({"promoted": count, "repairs": str(repairs), "combined": str(combined)}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


from __future__ import annotations
import logging

import argparse
import json
from pathlib import Path
from typing import Any, Dict, List

def merge_traces(inputs: List[Path], out_path: Path, max_items: int | None = None) -> int:
	out_path.parent.mkdir(parents=True, exist_ok=True)
	n = 0
	with out_path.open("w", encoding="utf-8") as out:
		for p in inputs:
			try:
				with p.open("r", encoding="utf-8") as f:
					for line in f:
						if not line.strip():
							continue
						out.write(line)
						n += 1
						if isinstance(max_items, int) and n >= max_items:
							return n
			except Exception:
				continue
	return n

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--inputs", nargs="*", default=[str(root / "data" / "devtools" / "traces.jsonl")])
	ap.add_argument("--out", default=str(root / "data" / "devtools" / "dataset.jsonl"))
	ap.add_argument("--max-items", type=int, default=100000)
	args = ap.parse_args()

	inputs = [Path(p) for p in (args.inputs or [])]
	outp = Path(args.out)
	n = merge_traces(inputs, outp, max_items=int(args.max_items))
	print(json.dumps({"ok": True, "items": int(n), "out": str(outp)}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


def merge_traces(inputs: List[Path], out_path: Path, max_items: int | None = None) -> int:
	out_path.parent.mkdir(parents=True, exist_ok=True)
	n = 0
	with out_path.open("w", encoding="utf-8") as out:
		for p in inputs:
			try:
				with p.open("r", encoding="utf-8") as f:
					for line in f:
						if not line.strip():
							continue
						out.write(line)
						n += 1
						if isinstance(max_items, int) and n >= max_items:
							return n
			except Exception:
				continue
	return n

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--inputs", nargs="*", default=[str(root / "data" / "devtools" / "traces.jsonl")])
	ap.add_argument("--out", default=str(root / "data" / "devtools" / "dataset.jsonl"))
	ap.add_argument("--max-items", type=int, default=100000)
	args = ap.parse_args()

	inputs = [Path(p) for p in (args.inputs or [])]
	outp = Path(args.out)
	n = merge_traces(inputs, outp, max_items=int(args.max_items))
	print(json.dumps({"ok": True, "items": int(n), "out": str(outp)}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


from __future__ import annotations
import logging

import argparse
import json
from pathlib import Path
from typing import Any, Dict, List

def _safe(obj: Any) -> Any:
	try:
		json.dumps(obj, ensure_ascii=False)
		return obj
	except Exception:
		return str(obj)

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--in", dest="inp", default=str(root / "data" / "devtools" / "traces.jsonl"))
	ap.add_argument("--out", dest="out", default=str(root / "data" / "traces" / "coder_ds.jsonl"))
	ap.add_argument("--skills-out", dest="skills_out", default=str(root / "data" / "skills" / "coder_ds.jsonl"))
	# SC-NTP style control-tag text alongside JSON rows
	ap.add_argument("--text-out", dest="text_out", default=str(root / "data" / "traces" / "coder_ds.txt"))
	ap.add_argument("--skills-text-out", dest="skills_text_out", default=str(root / "data" / "skills" / "coder_ds.txt"))
	args = ap.parse_args()

	inp = Path(args.inp)
	out = Path(args.out)
	skills_out = Path(args.skills_out)
	text_out = Path(args.text_out)
	skills_text_out = Path(args.skills_text_out)
	out.parent.mkdir(parents=True, exist_ok=True)
	skills_out.parent.mkdir(parents=True, exist_ok=True)
	text_out.parent.mkdir(parents=True, exist_ok=True)
	skills_text_out.parent.mkdir(parents=True, exist_ok=True)

	written = 0
	if not inp.exists():
		print(json.dumps({"ok": False, "error": f"input not found: {str(inp)}"}, ensure_ascii=False))
		return 2
	with inp.open("r", encoding="utf-8") as f, out.open("w", encoding="utf-8") as g, skills_out.open("w", encoding="utf-8") as gs, text_out.open("w", encoding="utf-8") as gt, skills_text_out.open("w", encoding="utf-8") as gts:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				rec: Dict[str, Any] = json.loads(line)
			except Exception:
				continue

			# Core fields
			obs = rec.get("obs", {}) if isinstance(rec.get("obs"), dict) else {}
			plan = rec.get("plan", {}) if isinstance(rec.get("plan"), dict) else {}
			result = rec.get("result", {}) if isinstance(rec.get("result"), dict) else {}
			action = rec.get("action", {}) if isinstance(rec.get("action"), dict) else {}
			critique = rec.get("critique", {}) if isinstance(rec.get("critique"), dict) else {}

			# Failures/context
			failures: List[Dict[str, Any]] = []
			try:
				failures = list(obs.get("failures") or [])
			except Exception:
				failures = []
			failure_summary = "\n".join([f"- {str(f.get('path',''))}::{str(f.get('test',''))}" for f in failures]) if failures else ""

			# Derived source candidates from tests
			def _derive_sources(paths: List[str]) -> List[str]:
				out: List[str] = []
				try:
					for p in paths:
						name = str(p).split("/")[-1]
						stem = name
						if name.startswith("test_"):
							stem = name[len("test_"):]
						cand = stem
						if cand and cand not in out:
							out.append(cand)
				except Exception:
					pass
				return out
			first_fail_paths = [str(f.get("path","")) for f in failures if f.get("path")] if failures else []
			src_candidates = _derive_sources(first_fail_paths)

			# Intent and rails
			intent_summary = str(plan.get("intent_summary", "")) if isinstance(plan, dict) else ""
			primary_path = plan.get("primary_path") if isinstance(plan, dict) else None
			allow_paths = plan.get("allow_paths") if isinstance(plan, dict) else None
			block_paths = plan.get("block_paths") if isinstance(plan, dict) else None
			budgets = plan.get("budgets") if isinstance(plan, dict) else None
			target_symbols = plan.get("target_symbols") if isinstance(plan, dict) else None

			# Candidate/action labels
			args = action.get("args", {}) if isinstance(action.get("args"), dict) else {}
			candidate_size = int(args.get("size", 0) or 0)
			candidate_files = int(args.get("files", 0) or 0)
			# Optional pre-check flags if present in plan/action
			touches_primary = bool(plan.get("touches_primary", False)) if isinstance(plan, dict) else False
			plausible_fix = bool(plan.get("plausible_return_fix", False)) if isinstance(plan, dict) else False

			# Results and priors
			status = str(result.get("status", "")).strip()
			applied_ok = bool(status == "ok")
			wm_prior_risk = None
			try:
				wm_prior_risk = float(rec.get("meta", {}).get("wm_prior_risk"))  # type: ignore
			except Exception:
				wm_prior_risk = None

			# Lint/Index/Manifest summaries if present
			lint_summary = str(rec.get("meta", {}).get("lint_summary", "")) if isinstance(rec.get("meta"), dict) else ""
			code_index = rec.get("meta", {}).get("code_index", {}) if isinstance(rec.get("meta"), dict) else {}
			manifest_subset = rec.get("meta", {}).get("manifest", {}) if isinstance(rec.get("meta"), dict) else {}
			ctx_files_struct = rec.get("meta", {}).get("ctx_files", []) if isinstance(rec.get("meta"), dict) else []
			src_files_struct = rec.get("meta", {}).get("src_files", []) if isinstance(rec.get("meta"), dict) else []

			# Targets: diff_text (if stored; else empty placeholder)
			diff_text = str(plan.get("diff_text", "")) if isinstance(plan, dict) else ""
			# Compute churn stats from diff_text
			added_lines = 0
			deleted_lines = 0
			try:
				for ln in (diff_text or "").splitlines():
					if ln.startswith("+") and not ln.startswith("+++ "):
						added_lines += 1
					elif ln.startswith("-") and not ln.startswith("--- "):
						deleted_lines += 1
			except Exception:
				added_lines, deleted_lines = (0, 0)

			row = {
				"failure_summary": failure_summary,
				"ctx_files": [{"path": str(it.get("path", "")), "text": str(it.get("text", ""))} for it in (ctx_files_struct or [])],
				"src_candidates": src_candidates,
				"src_files": [{"path": str(it.get("path", "")), "text": str(it.get("text", ""))} for it in (src_files_struct or [])],
				"code_index": _safe(code_index),
				"lint_summary": lint_summary,
				"intent": {
					"intent_summary": intent_summary,
					"primary_path": primary_path,
					"allow_paths": allow_paths or [],
					"block_paths": block_paths or [],
					"budgets": budgets or {},
					"target_symbols": target_symbols or [],
				},
				"candidate": {
					"size": candidate_size,
					"files": candidate_files,
					"touches_primary": bool(touches_primary),
					"plausible_return_fix": bool(plausible_fix),
				},
				"wm_prior_risk": wm_prior_risk,
				"diff_text": diff_text,
				"churn": {"added": int(added_lines), "deleted": int(deleted_lines)},
				"applied_ok": bool(applied_ok),
			}
			line_out = json.dumps(row, ensure_ascii=False) + "\n"
			g.write(line_out)
			gs.write(line_out)
			# Also emit SC-NTP control-tag text for sequence models
			try:
				ctx_parts: List[str] = []
				if failure_summary:
					ctx_parts.append(f"Failures\n{failure_summary}")
				if lint_summary:
					ctx_parts.append(f"Lint\n{lint_summary}")
				# Include FILE blocks (capped)
				file_blocks = []
				try:
					cap = 3
					for it in (ctx_files_struct or [])[:cap]:
						p = str(it.get("path", ""))
						t = str(it.get("text", ""))
						file_blocks.append(f"FILE {p}\n<<CODE_START>>\n{t}\n<<CODE_END>>\n")
					if file_blocks:
						ctx_parts.append("\n".join(file_blocks))
				except Exception:
					pass
				# Compact intent context
				intent_lines: List[str] = []
				if intent_summary:
					intent_lines.append(f"intent_summary: {intent_summary}")
				if primary_path:
					intent_lines.append(f"primary_path: {primary_path}")
				if allow_paths:
					intent_lines.append(f"allow_paths: {', '.join([str(x) for x in allow_paths])}")
				if block_paths:
					intent_lines.append(f"block_paths: {', '.join([str(x) for x in block_paths])}")
				if budgets:
					try:
						intent_lines.append("budgets: " + json.dumps(budgets, ensure_ascii=False))
					except Exception:
						pass
				if target_symbols:
					intent_lines.append(f"target_symbols: {', '.join([str(x) for x in target_symbols])}")
				if intent_lines:
					ctx_parts.append("Intent\n" + "\n".join(intent_lines))
				# Candidate summary
				cand_lines = [f"size: {candidate_size}", f"files: {candidate_files}"]
				if touches_primary:
					cand_lines.append("touches_primary: true")
				if plausible_fix:
					cand_lines.append("plausible_return_fix: true")
				ctx_parts.append("Candidate\n" + "\n".join(cand_lines))
				# Add SOURCE blocks (capped)
				source_blocks = []
				try:
					cap_src = 2
					for it in (src_files_struct or [])[:cap_src]:
						p = str(it.get("path", ""))
						t = str(it.get("text", ""))
						source_blocks.append(f"SOURCE {p}\n<<CODE_START>>\n{t}\n<<CODE_END>>\n")
					if source_blocks:
						ctx_parts.append("\n".join(source_blocks))
				except Exception:
					pass
				# Build CTX/DIFF block
				ctx_text = ("\n\n".join(ctx_parts)).strip()
				diff_text_out = str(diff_text or "").strip()
				seq = "<CTX>\n" + (ctx_text + "\n" if ctx_text else "") + "<DIFF>\n" + diff_text_out + "\n\n"
				gt.write(seq)
				gts.write(seq)
			except Exception:
				pass
			written += 1
	print(json.dumps({"ok": True, "items": int(written), "out": str(out)}, ensure_ascii=False))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


from __future__ import annotations
import logging

import argparse
import json
from pathlib import Path
from typing import Any, Dict, List

def _safe(obj: Any) -> Any:
	try:
		json.dumps(obj, ensure_ascii=False)
		return obj
	except Exception:
		return str(obj)

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--in", dest="inp", default=str(root / "data" / "devtools" / "traces.jsonl"))
	ap.add_argument("--out", dest="out", default=str(root / "data" / "traces" / "coder_ds.jsonl"))
	ap.add_argument("--skills-out", dest="skills_out", default=str(root / "data" / "skills" / "coder_ds.jsonl"))
	# SC-NTP style control-tag text alongside JSON rows
	ap.add_argument("--text-out", dest="text_out", default=str(root / "data" / "traces" / "coder_ds.txt"))
	ap.add_argument("--skills-text-out", dest="skills_text_out", default=str(root / "data" / "skills" / "coder_ds.txt"))
	args = ap.parse_args()

	inp = Path(args.inp)
	out = Path(args.out)
	skills_out = Path(args.skills_out)
	text_out = Path(args.text_out)
	skills_text_out = Path(args.skills_text_out)
	out.parent.mkdir(parents=True, exist_ok=True)
	skills_out.parent.mkdir(parents=True, exist_ok=True)


				rec: Dict[str, Any] = json.loads(line)
			except Exception:
				continue

			# Core fields
			obs = rec.get("obs", {}) if isinstance(rec.get("obs"), dict) else {}
			plan = rec.get("plan", {}) if isinstance(rec.get("plan"), dict) else {}
			result = rec.get("result", {}) if isinstance(rec.get("result"), dict) else {}
			action = rec.get("action", {}) if isinstance(rec.get("action"), dict) else {}
			critique = rec.get("critique", {}) if isinstance(rec.get("critique"), dict) else {}

			# Failures/context
			failures: List[Dict[str, Any]] = []
			try:
				failures = list(obs.get("failures") or [])
			except Exception:
				failures = []
			failure_summary = "\n".join([f"- {str(f.get('path',''))}::{str(f.get('test',''))}" for f in failures]) if failures else ""

			# Derived source candidates from tests
			def _derive_sources(paths: List[str]) -> List[str]:
				out: List[str] = []
				try:
					for p in paths:
						name = str(p).split("/")[-1]
						stem = name
						if name.startswith("test_"):
							stem = name[len("test_"):]
						cand = stem
						if cand and cand not in out:
							out.append(cand)
				except Exception:
					pass
				return out
			first_fail_paths = [str(f.get("path","")) for f in failures if f.get("path")] if failures else []
			src_candidates = _derive_sources(first_fail_paths)

			# Intent and rails
			intent_summary = str(plan.get("intent_summary", "")) if isinstance(plan, dict) else ""
			primary_path = plan.get("primary_path") if isinstance(plan, dict) else None
			allow_paths = plan.get("allow_paths") if isinstance(plan, dict) else None
			block_paths = plan.get("block_paths") if isinstance(plan, dict) else None
			budgets = plan.get("budgets") if isinstance(plan, dict) else None
			target_symbols = plan.get("target_symbols") if isinstance(plan, dict) else None

			# Candidate/action labels
			args = action.get("args", {}) if isinstance(action.get("args"), dict) else {}
			candidate_size = int(args.get("size", 0) or 0)
			candidate_files = int(args.get("files", 0) or 0)
			# Optional pre-check flags if present in plan/action
			touches_primary = bool(plan.get("touches_primary", False)) if isinstance(plan, dict) else False
			plausible_fix = bool(plan.get("plausible_return_fix", False)) if isinstance(plan, dict) else False

			# Results and priors


from __future__ import annotations
import logging

import argparse
import json
from pathlib import Path
from typing import Any, Dict, Iterable, Tuple

def iter_jsonl(path: Path) -> Iterable[Dict[str, Any]]:
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			s = line.strip()
			if not s:
				continue
			try:
				yield json.loads(s)
			except Exception:
				continue

def signature(trace: Dict[str, Any]) -> Tuple[str, str]:
	repo = str((trace.get("obs", {}) or {}).get("repo", ""))
	test = ""
	try:
		fails = (trace.get("obs", {}) or {}).get("failures", [])
		if isinstance(fails, list) and fails:
			test = f"{fails[0].get('path','')}::{fails[0].get('test','')}"
	except Exception:
		test = ""
	return repo, test

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--in", default=str(root / "data" / "traces" / "near_miss.jsonl"))
	ap.add_argument("--out", default=str(root / "data" / "traces" / "hardcase.jsonl"))
	args = ap.parse_args()

	inp = Path(args.in)
	out = Path(args.out)
	out.parent.mkdir(parents=True, exist_ok=True)

	seen = set()
	written = 0
	with out.open("w", encoding="utf-8") as g:
		for tr in iter_jsonl(inp):
			repo, test = signature(tr)
			if not repo or not test:
				continue
			sig = (repo, test)
			if sig in seen:
				continue
			seen.add(sig)
			g.write(json.dumps(tr, ensure_ascii=False) + "\n")
			written += 1

	print(json.dumps({"ok": True, "items": int(written), "out": str(out)}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())

import argparse
import json
from pathlib import Path
from typing import Any, Dict, Tuple, Set

def _iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			s = line.strip()
			if not s:
				continue
			try:
				yield json.loads(s)
			except Exception:
				continue

def _is_near_miss(rec: Dict[str, Any]) -> bool:
	plan = rec.get("plan", {}) if isinstance(rec.get("plan"), dict) else {}
	touches = bool(plan.get("touches_primary"))
	plausible = bool(plan.get("plausible_return_fix"))
	result = rec.get("result", {}) if isinstance(rec.get("result"), dict) else {}
	status = str(result.get("status", "")).lower()
	return bool(touches and plausible and status != "ok")

def _id_keys(rec: Dict[str, Any]) -> Tuple[str, str]:
	repo = str(rec.get("obs", {}).get("repo", "")) if isinstance(rec.get("obs"), dict) else str(rec.get("repo", ""))
	# Use first failure path::test if available
	test_id = ""
	try:
		fails = rec.get("obs", {}).get("failures") if isinstance(rec.get("obs"), dict) else rec.get("failures")
		if isinstance(fails, list) and fails:
			f0 = fails[0]
			test_id = f"{f0.get('path','')}::{f0.get('test','')}"
	except Exception:
		test_id = ""
	return repo, test_id

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--traces", nargs="*", default=[str(root / "data" / "traces" / "dev_loop.ci.jsonl"), str(root / "data" / "traces" / "dev_loop.jsonl")])
	ap.add_argument("--out", default=str(root / "data" / "traces" / "hardcase.jsonl"))
	ap.add_argument("--per-repo-cap", type=int, default=100)
	args = ap.parse_args()

	caps: Dict[str, int] = {}
	seen: Set[Tuple[str, str]] = set()

	outp = Path(args.out)
	outp.parent.mkdir(parents=True, exist_ok=True)
	n = 0
	with outp.open("w", encoding="utf-8") as w:
		for p in [Path(x) for x in (args.traces or [])]:
			if not p.exists():
				continue
			for rec in _iter_jsonl(p):
				if not isinstance(rec, dict):
					continue
				if not _is_near_miss(rec):
					continue
				repo, test_id = _id_keys(rec)
				key = (repo, test_id)
				if key in seen:
					continue
				if caps.get(repo, 0) >= int(args.per_repo_cap or 0):
					continue
				try:
					w.write(json.dumps(rec, ensure_ascii=False) + "\n")
					seen.add(key)
					caps[repo] = caps.get(repo, 0) + 1
					n += 1
				except Exception:
					continue

	print(json.dumps({"ok": True, "items": int(n), "out": str(outp), "repos": {k: int(v) for k, v in caps.items()}}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


import logging
import argparse
import hashlib
import json
from pathlib import Path
from typing import Dict, Tuple

def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def key_for_il(obj: Dict) -> str:
	return str(obj.get("input", ""))

def write_split(src: Path, out_train: Path, out_eval: Path, ratio: float) -> Tuple[int, int]:
	out_train.parent.mkdir(parents=True, exist_ok=True)
	out_eval.parent.mkdir(parents=True, exist_ok=True)
	n_tr = 0
	n_ev = 0
	with out_train.open("w", encoding="utf-8") as ftr, out_eval.open("w", encoding="utf-8") as fev:
		for obj in iter_jsonl(src):
			h = int(hashlib.sha256(key_for_il(obj).encode("utf-8")).hexdigest(), 16)
			p = (h % 1000) / 1000.0
			line = json.dumps(obj, ensure_ascii=False) + "\n"
			if p < ratio:
				ftr.write(line)
				n_tr += 1
			else:
				fev.write(line)
				n_ev += 1
	return n_tr, n_ev

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--src", default=str(root / "data" / "skills" / "actuator_il_combined.jsonl"))
	ap.add_argument("--train", default=str(root / "data" / "splits" / "actuator_il_train.jsonl"))
	ap.add_argument("--eval", default=str(root / "data" / "splits" / "actuator_il_eval.jsonl"))
	ap.add_argument("--ratio", type=float, default=0.8)
	args = ap.parse_args()

	n_tr, n_ev = write_split(Path(args.src), Path(args.train), Path(args.eval), max(0.0, min(1.0, float(args.ratio))))
	print(json.dumps({"train": n_tr, "eval": n_ev}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


import logging
import argparse
import hashlib
import json
from pathlib import Path
from typing import Dict, Tuple

def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def key_for_il(obj: Dict) -> str:
	return str(obj.get("input", ""))

def write_split(src: Path, out_train: Path, out_eval: Path, ratio: float) -> Tuple[int, int]:
	out_train.parent.mkdir(parents=True, exist_ok=True)
	out_eval.parent.mkdir(parents=True, exist_ok=True)
	n_tr = 0
	n_ev = 0
	with out_train.open("w", encoding="utf-8") as ftr, out_eval.open("w", encoding="utf-8") as fev:
		for obj in iter_jsonl(src):
			h = int(hashlib.sha256(key_for_il(obj).encode("utf-8")).hexdigest(), 16)
			p = (h % 1000) / 1000.0
			line = json.dumps(obj, ensure_ascii=False) + "\n"
			if p < ratio:
				ftr.write(line)
				n_tr += 1
			else:


import hashlib
import json
from pathlib import Path
from typing import Dict, Tuple

def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def key_for_il(obj: Dict) -> str:
	return str(obj.get("input", ""))

def write_split(src: Path, out_train: Path, out_eval: Path, ratio: float) -> Tuple[int, int]:
	out_train.parent.mkdir(parents=True, exist_ok=True)
	out_eval.parent.mkdir(parents=True, exist_ok=True)
	n_tr = 0
	n_ev = 0
	with out_train.open("w", encoding="utf-8") as ftr, out_eval.open("w", encoding="utf-8") as fev:
		for obj in iter_jsonl(src):
			h = int(hashlib.sha256(key_for_il(obj).encode("utf-8")).hexdigest(), 16)
			p = (h % 1000) / 1000.0
			line = json.dumps(obj, ensure_ascii=False) + "\n"
			if p < ratio:
				ftr.write(line)
				n_tr += 1
			else:
				fev.write(line)
				n_ev += 1
	return n_tr, n_ev


def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def key_for_il(obj: Dict) -> str:
	return str(obj.get("input", ""))

def write_split(src: Path, out_train: Path, out_eval: Path, ratio: float) -> Tuple[int, int]:
	out_train.parent.mkdir(parents=True, exist_ok=True)
	out_eval.parent.mkdir(parents=True, exist_ok=True)
	n_tr = 0
	n_ev = 0
	with out_train.open("w", encoding="utf-8") as ftr, out_eval.open("w", encoding="utf-8") as fev:
		for obj in iter_jsonl(src):
			h = int(hashlib.sha256(key_for_il(obj).encode("utf-8")).hexdigest(), 16)
			p = (h % 1000) / 1000.0
			line = json.dumps(obj, ensure_ascii=False) + "\n"
			if p < ratio:
				ftr.write(line)
				n_tr += 1
			else:
				fev.write(line)
				n_ev += 1
	return n_tr, n_ev

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--src", default=str(root / "data" / "skills" / "actuator_il_combined.jsonl"))
	ap.add_argument("--train", default=str(root / "data" / "splits" / "actuator_il_train.jsonl"))
	ap.add_argument("--eval", default=str(root / "data" / "splits" / "actuator_il_eval.jsonl"))
	ap.add_argument("--ratio", type=float, default=0.8)
	args = ap.parse_args()

	n_tr, n_ev = write_split(Path(args.src), Path(args.train), Path(args.eval), max(0.0, min(1.0, float(args.ratio))))
	print(json.dumps({"train": n_tr, "eval": n_ev}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


def write_split(src: Path, out_train: Path, out_eval: Path, ratio: float) -> Tuple[int, int]:
	out_train.parent.mkdir(parents=True, exist_ok=True)
	out_eval.parent.mkdir(parents=True, exist_ok=True)
	n_tr = 0
	n_ev = 0
	with out_train.open("w", encoding="utf-8") as ftr, out_eval.open("w", encoding="utf-8") as fev:
		for obj in iter_jsonl(src):
			h = int(hashlib.sha256(key_for_il(obj).encode("utf-8")).hexdigest(), 16)
			p = (h % 1000) / 1000.0
			line = json.dumps(obj, ensure_ascii=False) + "\n"
			if p < ratio:
				ftr.write(line)
				n_tr += 1
			else:
				fev.write(line)
				n_ev += 1
	return n_tr, n_ev

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--src", default=str(root / "data" / "skills" / "actuator_il_combined.jsonl"))
	ap.add_argument("--train", default=str(root / "data" / "splits" / "actuator_il_train.jsonl"))
	ap.add_argument("--eval", default=str(root / "data" / "splits" / "actuator_il_eval.jsonl"))
	ap.add_argument("--ratio", type=float, default=0.8)
	args = ap.parse_args()

	n_tr, n_ev = write_split(Path(args.src), Path(args.train), Path(args.eval), max(0.0, min(1.0, float(args.ratio))))
	print(json.dumps({"train": n_tr, "eval": n_ev}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


import logging
import argparse
import json
from pathlib import Path
from typing import Dict, Any, Tuple

def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def signature(rec: Dict[str, Any]) -> Tuple[str, str, str]:
	obs = rec.get("obs", {}) if isinstance(rec.get("obs"), dict) else {}
	meta = obs.get("meta", {}) if isinstance(obs, dict) else {}
	domain = str(obs.get("kind", ""))
	url = str(meta.get("url", "")) if isinstance(meta, dict) else ""
	sel = str(meta.get("selector", "")) if isinstance(meta, dict) else ""
	return domain, url, sel

def main() -> int:
	ap = argparse.ArgumentParser(description="Build a balanced, capped trace set from one or more JSONL inputs")
	ap.add_argument("--inputs", nargs="*", required=True)
	ap.add_argument("--out", required=True)
	ap.add_argument("--per_signature_cap", type=int, default=3)
	ap.add_argument("--success_fraction", type=float, default=0.5, help="Target fraction of successes [0..1]")
	args = ap.parse_args()

	# Counters per signature and per success bucket
	cap = max(1, int(args.per_signature_cap))
	max_success = None
	max_failure = None
	try:
		ratio = float(args.success_fraction)
		ratio = min(1.0, max(0.0, ratio))
		max_success = ratio * cap
		max_failure = (1.0 - ratio) * cap
	except Exception:
		max_success = None
		max_failure = None

	counts: Dict[Tuple[str, str, str], Dict[str, int]] = {}
	out_path = Path(args.out)
	out_path.parent.mkdir(parents=True, exist_ok=True)
	kept = 0
	seen = 0
	with out_path.open("w", encoding="utf-8") as fout:
		for raw in args.inputs:
			p = Path(raw)
			for rec in iter_jsonl(p):
				seen += 1
				dom, url, sel = signature(rec)
				key = (dom, url, sel)
				bucket = "success" if str((rec.get("result", {}) or {}).get("status", "")).lower() == "ok" else "failure"
				cmap = counts.setdefault(key, {"success": 0, "failure": 0})
				allow = True
				# Enforce per-signature cap and bucket ratio if configured
				if cmap["success"] + cmap["failure"] >= cap:
					allow = False
				elif bucket == "success" and max_success is not None and cmap["success"] >= int(max_success + 1e-9):
					allow = False
				elif bucket == "failure" and max_failure is not None and cmap["failure"] >= int(max_failure + 1e-9):
					allow = False
				if not allow:
					continue
				fout.write(json.dumps(rec, ensure_ascii=False) + "\n")
				cmap[bucket] += 1
				kept += 1
	print(json.dumps({"ok": True, "inputs": len(args.inputs), "seen": seen, "kept": kept, "per_signature_cap": cap, "target_success_fraction": args.success_fraction}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


import logging
import argparse
import json
from pathlib import Path
from typing import Dict, Any, Tuple

def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def signature(rec: Dict[str, Any]) -> Tuple[str, str, str]:
	obs = rec.get("obs", {}) if isinstance(rec.get("obs"), dict) else {}
	meta = obs.get("meta", {}) if isinstance(obs, dict) else {}
	domain = str(obs.get("kind", ""))
	url = str(meta.get("url", "")) if isinstance(meta, dict) else ""
	sel = str(meta.get("selector", "")) if isinstance(meta, dict) else ""
	return domain, url, sel

def main() -> int:
	ap = argparse.ArgumentParser(description="Build a balanced, capped trace set from one or more JSONL inputs")
	ap.add_argument("--inputs", nargs="*", required=True)
	ap.add_argument("--out", required=True)
	ap.add_argument("--per_signature_cap", type=int, default=3)
	ap.add_argument("--success_fraction", type=float, default=0.5, help="Target fraction of successes [0..1]")
	args = ap.parse_args()

	# Counters per signature and per success bucket


signature

import argparse
import json
from pathlib import Path
from typing import Dict, Any, Tuple

def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def signature(rec: Dict[str, Any]) -> Tuple[str, str, str]:
	obs = rec.get("obs", {}) if isinstance(rec.get("obs"), dict) else {}
	meta = obs.get("meta", {}) if isinstance(obs, dict) else {}
	domain = str(obs.get("kind", ""))
	url = str(meta.get("url", "")) if isinstance(meta, dict) else ""
	sel = str(meta.get("selector", "")) if isinstance(meta, dict) else ""
	return domain, url, sel

def main() -> int:
	ap = argparse.ArgumentParser(description="Build a balanced, capped trace set from one or more JSONL inputs")
	ap.add_argument("--inputs", nargs="*", required=True)
	ap.add_argument("--out", required=True)
	ap.add_argument("--per_signature_cap", type=int, default=3)
	ap.add_argument("--success_fraction", type=float, default=0.5, help="Target fraction of successes [0..1]")
	args = ap.parse_args()

	# Counters per signature and per success bucket
	cap = max(1, int(args.per_signature_cap))
	max_success = None
	max_failure = None
	try:
		ratio = float(args.success_fraction)
		ratio = min(1.0, max(0.0, ratio))
		max_success = ratio * cap
		max_failure = (1.0 - ratio) * cap
	except Exception:


main

	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def signature(rec: Dict[str, Any]) -> Tuple[str, str, str]:
	obs = rec.get("obs", {}) if isinstance(rec.get("obs"), dict) else {}
	meta = obs.get("meta", {}) if isinstance(obs, dict) else {}
	domain = str(obs.get("kind", ""))
	url = str(meta.get("url", "")) if isinstance(meta, dict) else ""
	sel = str(meta.get("selector", "")) if isinstance(meta, dict) else ""
	return domain, url, sel

def main() -> int:
	ap = argparse.ArgumentParser(description="Build a balanced, capped trace set from one or more JSONL inputs")
	ap.add_argument("--inputs", nargs="*", required=True)
	ap.add_argument("--out", required=True)
	ap.add_argument("--per_signature_cap", type=int, default=3)
	ap.add_argument("--success_fraction", type=float, default=0.5, help="Target fraction of successes [0..1]")
	args = ap.parse_args()

	# Counters per signature and per success bucket
	cap = max(1, int(args.per_signature_cap))
	max_success = None
	max_failure = None
	try:
		ratio = float(args.success_fraction)
		ratio = min(1.0, max(0.0, ratio))
		max_success = ratio * cap
		max_failure = (1.0 - ratio) * cap
	except Exception:
		max_success = None
		max_failure = None

	counts: Dict[Tuple[str, str, str], Dict[str, int]] = {}
	out_path = Path(args.out)
	out_path.parent.mkdir(parents=True, exist_ok=True)
	kept = 0
	seen = 0
	with out_path.open("w", encoding="utf-8") as fout:
		for raw in args.inputs:
			p = Path(raw)
			for rec in iter_jsonl(p):
				seen += 1
				dom, url, sel = signature(rec)
				key = (dom, url, sel)
				bucket = "success" if str((rec.get("result", {}) or {}).get("status", "")).lower() == "ok" else "failure"
				cmap = counts.setdefault(key, {"success": 0, "failure": 0})
				allow = True
				# Enforce per-signature cap and bucket ratio if configured
				if cmap["success"] + cmap["failure"] >= cap:
					allow = False
				elif bucket == "success" and max_success is not None and cmap["success"] >= int(max_success + 1e-9):
					allow = False
				elif bucket == "failure" and max_failure is not None and cmap["failure"] >= int(max_failure + 1e-9):
					allow = False
				if not allow:
					continue
				fout.write(json.dumps(rec, ensure_ascii=False) + "\n")
				cmap[bucket] += 1
				kept += 1
	print(json.dumps({"ok": True, "inputs": len(args.inputs), "seen": seen, "kept": kept, "per_signature_cap": cap, "target_success_fraction": args.success_fraction}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


import logging
import argparse
import json
from pathlib import Path
from typing import Any, Dict, List

def _extract_effects(trace: Dict[str, Any]) -> str:
	# Prefer domain-specific effects fields
	res = trace.get("result", {}) or {}
	if isinstance(res, dict):
		# DOM text
		dom_text = res.get("dom")
		if isinstance(dom_text, str) and dom_text:
			return dom_text[:1000]
		# CLI stdout
		stdout = res.get("stdout")
		if isinstance(stdout, str) and stdout:
			return stdout[:1000]
	# Fallback: empty
	return ""

def featurize(trace: Dict[str, Any]) -> Dict[str, Any]:
	obs = trace.get("obs", {})
	plan = trace.get("plan", {})
	action = trace.get("action", {})
	result = trace.get("result", {})
	return {
		"obs": json.dumps(obs, ensure_ascii=False),
		"plan": json.dumps(plan, ensure_ascii=False),
		"action": json.dumps(action, ensure_ascii=False),
		"effects": _extract_effects(trace),
		"status": str(result.get("status", "error")),
	}

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	# Backwards-compatible: default CLI verified; allow multiple --src to merge, and default-include DOM if present
	ap.add_argument("dst", nargs="?", default=str(root / "data" / "skills" / "wm_ds.jsonl"))
	ap.add_argument("--src", action="append", help="Add one or more verified trace JSONL sources", default=None)
	ap.add_argument("--validate", action="store_true", help="Validate rows against WM schema before writing")
	args = ap.parse_args()

	# Build source list
	default_cli = root / "data" / "traces" / "seed_os_cli.verified.llm.jsonl"
	default_dom = root / "data" / "traces" / "web_dom.verified.jsonl"
	src_paths: List[Path] = []
	if args.src:
		src_paths.extend([Path(p) for p in args.src])
	else:
		if default_cli.exists():
			src_paths.append(default_cli)
		if default_dom.exists():
			src_paths.append(default_dom)
	if not src_paths:
		print("No source verified traces found.")
		return 0

	dst = Path(args.dst)
	dst.parent.mkdir(parents=True, exist_ok=True)

	# Optional validator
	validator = None
	if args.validate:
		try:
			from agi_dw.core.world_model.schema import validate_row  # type: ignore
			validator = validate_row
		except Exception:
			validator = None

	n = 0
	with dst.open("w", encoding="utf-8") as fout:
		for src in src_paths:
			if not src.exists():
				continue
			with src.open("r", encoding="utf-8") as fin:
				for line in fin:
					line = line.strip()
					if not line:
						continue
					try:
						tr: Dict[str, Any] = json.loads(line)
					except Exception:
						continue
					feat = featurize(tr)
					status = feat.pop("status", "error")
					success = 1 if status == "ok" else 0
					# Prefer risk from verifier critique if present
					try:
						risk_val = float((tr.get("critique") or {}).get("risk", 0.5))
					except Exception:
						risk_val = 0.2 if success else 0.6
					ex = {"input": feat, "success": success, "risk": risk_val}
					if validator is not None and not validator(ex):
						continue
					fout.write(json.dumps(ex, ensure_ascii=False) + "\n")
					n += 1
	print(f"Wrote {n} WM examples -> {dst}")
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


import logging
import argparse
import json
from pathlib import Path
from typing import Any, Dict, List

def _extract_effects(trace: Dict[str, Any]) -> str:
	# Prefer domain-specific effects fields
	res = trace.get("result", {}) or {}
	if isinstance(res, dict):
		# DOM text
		dom_text = res.get("dom")
		if isinstance(dom_text, str) and dom_text:
			return dom_text[:1000]
		# CLI stdout
		stdout = res.get("stdout")
		if isinstance(stdout, str) and stdout:
			return stdout[:1000]
	# Fallback: empty
	return ""

def featurize(trace: Dict[str, Any]) -> Dict[str, Any]:
	obs = trace.get("obs", {})
	plan = trace.get("plan", {})
	action = trace.get("action", {})
	result = trace.get("result", {})
	return {
		"obs": json.dumps(obs, ensure_ascii=False),
		"plan": json.dumps(plan, ensure_ascii=False),
		"action": json.dumps(action, ensure_ascii=False),
		"effects": _extract_effects(trace),
		"status": str(result.get("status", "error")),
	}

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	# Backwards-compatible: default CLI verified; allow multiple --src to merge, and default-include DOM if present


featurize

from pathlib import Path
from typing import Any, Dict, List

def _extract_effects(trace: Dict[str, Any]) -> str:
	# Prefer domain-specific effects fields
	res = trace.get("result", {}) or {}
	if isinstance(res, dict):
		# DOM text
		dom_text = res.get("dom")
		if isinstance(dom_text, str) and dom_text:
			return dom_text[:1000]
		# CLI stdout
		stdout = res.get("stdout")
		if isinstance(stdout, str) and stdout:
			return stdout[:1000]
	# Fallback: empty
	return ""

def featurize(trace: Dict[str, Any]) -> Dict[str, Any]:
	obs = trace.get("obs", {})
	plan = trace.get("plan", {})
	action = trace.get("action", {})
	result = trace.get("result", {})
	return {
		"obs": json.dumps(obs, ensure_ascii=False),
		"plan": json.dumps(plan, ensure_ascii=False),
		"action": json.dumps(action, ensure_ascii=False),
		"effects": _extract_effects(trace),
		"status": str(result.get("status", "error")),
	}

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	# Backwards-compatible: default CLI verified; allow multiple --src to merge, and default-include DOM if present
	ap.add_argument("dst", nargs="?", default=str(root / "data" / "skills" / "wm_ds.jsonl"))
	ap.add_argument("--src", action="append", help="Add one or more verified trace JSONL sources", default=None)
	ap.add_argument("--validate", action="store_true", help="Validate rows against WM schema before writing")
	args = ap.parse_args()

	# Build source list
	default_cli = root / "data" / "traces" / "seed_os_cli.verified.llm.jsonl"
	default_dom = root / "data" / "traces" / "web_dom.verified.jsonl"
	src_paths: List[Path] = []
	if args.src:
		src_paths.extend([Path(p) for p in args.src])
	else:
		if default_cli.exists():
			src_paths.append(default_cli)


main

		if isinstance(stdout, str) and stdout:
			return stdout[:1000]
	# Fallback: empty
	return ""

def featurize(trace: Dict[str, Any]) -> Dict[str, Any]:
	obs = trace.get("obs", {})
	plan = trace.get("plan", {})
	action = trace.get("action", {})
	result = trace.get("result", {})
	return {
		"obs": json.dumps(obs, ensure_ascii=False),
		"plan": json.dumps(plan, ensure_ascii=False),
		"action": json.dumps(action, ensure_ascii=False),
		"effects": _extract_effects(trace),
		"status": str(result.get("status", "error")),
	}

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	# Backwards-compatible: default CLI verified; allow multiple --src to merge, and default-include DOM if present
	ap.add_argument("dst", nargs="?", default=str(root / "data" / "skills" / "wm_ds.jsonl"))
	ap.add_argument("--src", action="append", help="Add one or more verified trace JSONL sources", default=None)
	ap.add_argument("--validate", action="store_true", help="Validate rows against WM schema before writing")
	args = ap.parse_args()

	# Build source list
	default_cli = root / "data" / "traces" / "seed_os_cli.verified.llm.jsonl"
	default_dom = root / "data" / "traces" / "web_dom.verified.jsonl"
	src_paths: List[Path] = []
	if args.src:
		src_paths.extend([Path(p) for p in args.src])
	else:
		if default_cli.exists():
			src_paths.append(default_cli)
		if default_dom.exists():
			src_paths.append(default_dom)
	if not src_paths:
		print("No source verified traces found.")
		return 0

	dst = Path(args.dst)
	dst.parent.mkdir(parents=True, exist_ok=True)

	# Optional validator
	validator = None
	if args.validate:
		try:
			from agi_dw.core.world_model.schema import validate_row  # type: ignore
			validator = validate_row
		except Exception:
			validator = None

	n = 0
	with dst.open("w", encoding="utf-8") as fout:
		for src in src_paths:
			if not src.exists():
				continue
			with src.open("r", encoding="utf-8") as fin:
				for line in fin:
					line = line.strip()
					if not line:
						continue
					try:
						tr: Dict[str, Any] = json.loads(line)
					except Exception:
						continue
					feat = featurize(tr)
					status = feat.pop("status", "error")
					success = 1 if status == "ok" else 0
					# Prefer risk from verifier critique if present
					try:
						risk_val = float((tr.get("critique") or {}).get("risk", 0.5))
					except Exception:
						risk_val = 0.2 if success else 0.6
					ex = {"input": feat, "success": success, "risk": risk_val}
					if validator is not None and not validator(ex):
						continue
					fout.write(json.dumps(ex, ensure_ascii=False) + "\n")
					n += 1
	print(f"Wrote {n} WM examples -> {dst}")
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


from __future__ import annotations
import logging

import argparse
from pathlib import Path
import sys

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--inputs", nargs="*", default=[
		str(root / "data" / "traces" / "dev_loop.jsonl"),
		str(root / "data" / "traces" / "dev_loop.ci.jsonl"),
	])
	ap.add_argument("--out", default=str(root / "data" / "traces" / "nearmiss.jsonl"))
	args = ap.parse_args()

	# Delegate to existing near-miss replay builder
	cmd = [
		sys.executable,
		str(root / "scripts" / "build" / "build_near_miss_replay.py"),
		"--out", str(args.out),
	]
	for inp in (args.inputs or []):
		cmd.extend(["--inputs", str(inp)])
	import subprocess
	p = subprocess.run(cmd, capture_output=True, text=True)
	print(p.stdout)
	if p.returncode != 0:
		print(p.stderr, file=sys.stderr)
	return p.returncode

if __name__ == "__main__":
	raise SystemExit(main())

import argparse
import json
from pathlib import Path
from typing import Any, Dict

def _iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			s = line.strip()
			if not s:
				continue
			try:
				yield json.loads(s)
			except Exception:
				continue

def _is_near_miss(rec: Dict[str, Any]) -> bool:
	try:
		plan = rec.get("plan", {}) if isinstance(rec.get("plan"), dict) else {}
		touches = bool(plan.get("touches_primary"))
		plausible = bool(plan.get("plausible_return_fix"))
		res = rec.get("result", {}) if isinstance(rec.get("result"), dict) else {}
		status = str(res.get("status", "")).lower()
		return (touches and plausible and status != "ok")
	except Exception:
		return False

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--traces", default=str(root / "data" / "traces" / "dev_loop.ci.jsonl"))
	ap.add_argument("--out", default=str(root / "data" / "traces" / "nearmiss.jsonl"))
	ap.add_argument("--limit", type=int, default=0)
	args = ap.parse_args()

	tp = Path(args.traces)
	outp = Path(args.out)
	outp.parent.mkdir(parents=True, exist_ok=True)

	n_written = 0
	with outp.open("w", encoding="utf-8") as w:
		for rec in _iter_jsonl(tp):
			if not isinstance(rec, dict):
				continue
			if not _is_near_miss(rec):
				continue
			try:
				w.write(json.dumps(rec, ensure_ascii=False) + "\n")
				n_written += 1
				if int(args.limit or 0) > 0 and n_written >= int(args.limit):
					break
			except Exception:
				continue

	print(json.dumps({"ok": True, "items": int(n_written), "out": str(outp)}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


			if not s:
				continue
			try:
				yield json.loads(s)
			except Exception:
				continue

def _is_near_miss(rec: Dict[str, Any]) -> bool:
	try:
		plan = rec.get("plan", {}) if isinstance(rec.get("plan"), dict) else {}
		touches = bool(plan.get("touches_primary"))
		plausible = bool(plan.get("plausible_return_fix"))
		res = rec.get("result", {}) if isinstance(rec.get("result"), dict) else {}
		status = str(res.get("status", "")).lower()
		return (touches and plausible and status != "ok")
	except Exception:
		return False

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--traces", default=str(root / "data" / "traces" / "dev_loop.ci.jsonl"))
	ap.add_argument("--out", default=str(root / "data" / "traces" / "nearmiss.jsonl"))
	ap.add_argument("--limit", type=int, default=0)
	args = ap.parse_args()

	tp = Path(args.traces)
	outp = Path(args.out)
	outp.parent.mkdir(parents=True, exist_ok=True)

	n_written = 0
	with outp.open("w", encoding="utf-8") as w:
		for rec in _iter_jsonl(tp):
			if not isinstance(rec, dict):
				continue
			if not _is_near_miss(rec):
				continue
			try:
				w.write(json.dumps(rec, ensure_ascii=False) + "\n")
				n_written += 1
				if int(args.limit or 0) > 0 and n_written >= int(args.limit):
					break
			except Exception:
				continue

	print(json.dumps({"ok": True, "items": int(n_written), "out": str(outp)}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


	]
	for inp in (args.inputs or []):
		cmd.extend(["--inputs", str(inp)])
	import subprocess
	p = subprocess.run(cmd, capture_output=True, text=True)
	print(p.stdout)
	if p.returncode != 0:
		print(p.stderr, file=sys.stderr)
	return p.returncode

if __name__ == "__main__":
	raise SystemExit(main())

import argparse
import json
from pathlib import Path
from typing import Any, Dict

def _iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			s = line.strip()
			if not s:
				continue
			try:
				yield json.loads(s)
			except Exception:
				continue

def _is_near_miss(rec: Dict[str, Any]) -> bool:
	try:
		plan = rec.get("plan", {}) if isinstance(rec.get("plan"), dict) else {}
		touches = bool(plan.get("touches_primary"))
		plausible = bool(plan.get("plausible_return_fix"))
		res = rec.get("result", {}) if isinstance(rec.get("result"), dict) else {}
		status = str(res.get("status", "")).lower()
		return (touches and plausible and status != "ok")
	except Exception:
		return False

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--traces", default=str(root / "data" / "traces" / "dev_loop.ci.jsonl"))
	ap.add_argument("--out", default=str(root / "data" / "traces" / "nearmiss.jsonl"))
	ap.add_argument("--limit", type=int, default=0)


import argparse
import json
from pathlib import Path
from typing import Any, Dict

def _iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			s = line.strip()
			if not s:
				continue
			try:
				yield json.loads(s)
			except Exception:
				continue

def _is_near_miss(rec: Dict[str, Any]) -> bool:
	try:
		plan = rec.get("plan", {}) if isinstance(rec.get("plan"), dict) else {}
		touches = bool(plan.get("touches_primary"))
		plausible = bool(plan.get("plausible_return_fix"))
		res = rec.get("result", {}) if isinstance(rec.get("result"), dict) else {}
		status = str(res.get("status", "")).lower()
		return (touches and plausible and status != "ok")
	except Exception:
		return False

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--traces", default=str(root / "data" / "traces" / "dev_loop.ci.jsonl"))
	ap.add_argument("--out", default=str(root / "data" / "traces" / "nearmiss.jsonl"))
	ap.add_argument("--limit", type=int, default=0)
	args = ap.parse_args()

	tp = Path(args.traces)
	outp = Path(args.out)
	outp.parent.mkdir(parents=True, exist_ok=True)

	n_written = 0
	with outp.open("w", encoding="utf-8") as w:
		for rec in _iter_jsonl(tp):
			if not isinstance(rec, dict):
				continue
			if not _is_near_miss(rec):


import logging
import json
from pathlib import Path
from typing import Any, Dict, Iterable, List
import sys

def build_example(obj: Dict[str, Any]) -> Dict[str, Any]:
	obs = obj.get("obs", {})
	plan = obj.get("plan", {})
	action = obj.get("action", {})
	input_text = json.dumps({"obs": obs, "plan": plan}, ensure_ascii=False)
	output_text = json.dumps(action, ensure_ascii=False)
	return {"input": input_text, "output": output_text}

def iter_jsonl(paths: Iterable[Path]) -> Iterable[Dict[str, Any]]:
	for p in paths:
		if not p.exists():
			continue
		for line in p.read_text(encoding="utf-8").splitlines():
			line = line.strip()
			if not line:
				continue
			yield json.loads(line)

def process(src_paths: List[str], out_jsonl: str) -> int:
	out = Path(out_jsonl)
	out.parent.mkdir(parents=True, exist_ok=True)
	count = 0
	with out.open("w", encoding="utf-8") as fout:
		for obj in iter_jsonl([Path(p) for p in src_paths]):
			ex = build_example(obj)
			fout.write(json.dumps(ex, ensure_ascii=False) + "\n")
			count += 1
	return count

def main() -> int:
	# Usage: build_actuator_il_combined.py <out.jsonl> <src1.jsonl> <src2.jsonl> ...
	if len(sys.argv) < 3:
		print("Usage: build_actuator_il_combined.py <out.jsonl> <src1> <src2> ...")
		return 2
	out = sys.argv[1]
	srcs = sys.argv[2:]
	n = process(srcs, out)
	print(f"Wrote {n} IL examples -> {out}")
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


import logging
import json
from pathlib import Path
from typing import Any, Dict, Iterable, List
import sys

def build_example(obj: Dict[str, Any]) -> Dict[str, Any]:
	obs = obj.get("obs", {})
	plan = obj.get("plan", {})
	action = obj.get("action", {})
	input_text = json.dumps({"obs": obs, "plan": plan}, ensure_ascii=False)
	output_text = json.dumps(action, ensure_ascii=False)
	return {"input": input_text, "output": output_text}

def iter_jsonl(paths: Iterable[Path]) -> Iterable[Dict[str, Any]]:
	for p in paths:
		if not p.exists():
			continue
		for line in p.read_text(encoding="utf-8").splitlines():
			line = line.strip()
			if not line:
				continue
			yield json.loads(line)

def process(src_paths: List[str], out_jsonl: str) -> int:
	out = Path(out_jsonl)
	out.parent.mkdir(parents=True, exist_ok=True)
	count = 0
	with out.open("w", encoding="utf-8") as fout:
		for obj in iter_jsonl([Path(p) for p in src_paths]):
			ex = build_example(obj)


import logging
import json
from pathlib import Path
from typing import Any, Dict, Iterable, List
import sys

def build_example(obj: Dict[str, Any]) -> Dict[str, Any]:
	obs = obj.get("obs", {})
	plan = obj.get("plan", {})
	action = obj.get("action", {})
	input_text = json.dumps({"obs": obs, "plan": plan}, ensure_ascii=False)
	output_text = json.dumps(action, ensure_ascii=False)
	return {"input": input_text, "output": output_text}

def iter_jsonl(paths: Iterable[Path]) -> Iterable[Dict[str, Any]]:
	for p in paths:
		if not p.exists():
			continue
		for line in p.read_text(encoding="utf-8").splitlines():
			line = line.strip()
			if not line:
				continue
			yield json.loads(line)

def process(src_paths: List[str], out_jsonl: str) -> int:
	out = Path(out_jsonl)
	out.parent.mkdir(parents=True, exist_ok=True)
	count = 0
	with out.open("w", encoding="utf-8") as fout:
		for obj in iter_jsonl([Path(p) for p in src_paths]):
			ex = build_example(obj)
			fout.write(json.dumps(ex, ensure_ascii=False) + "\n")
			count += 1
	return count

def main() -> int:
	# Usage: build_actuator_il_combined.py <out.jsonl> <src1.jsonl> <src2.jsonl> ...
	if len(sys.argv) < 3:
		print("Usage: build_actuator_il_combined.py <out.jsonl> <src1> <src2> ...")
		return 2
	out = sys.argv[1]


process

def build_example(obj: Dict[str, Any]) -> Dict[str, Any]:
	obs = obj.get("obs", {})
	plan = obj.get("plan", {})
	action = obj.get("action", {})
	input_text = json.dumps({"obs": obs, "plan": plan}, ensure_ascii=False)
	output_text = json.dumps(action, ensure_ascii=False)
	return {"input": input_text, "output": output_text}

def iter_jsonl(paths: Iterable[Path]) -> Iterable[Dict[str, Any]]:
	for p in paths:
		if not p.exists():
			continue
		for line in p.read_text(encoding="utf-8").splitlines():
			line = line.strip()
			if not line:
				continue
			yield json.loads(line)

def process(src_paths: List[str], out_jsonl: str) -> int:
	out = Path(out_jsonl)
	out.parent.mkdir(parents=True, exist_ok=True)
	count = 0
	with out.open("w", encoding="utf-8") as fout:
		for obj in iter_jsonl([Path(p) for p in src_paths]):
			ex = build_example(obj)
			fout.write(json.dumps(ex, ensure_ascii=False) + "\n")
			count += 1
	return count

def main() -> int:
	# Usage: build_actuator_il_combined.py <out.jsonl> <src1.jsonl> <src2.jsonl> ...
	if len(sys.argv) < 3:
		print("Usage: build_actuator_il_combined.py <out.jsonl> <src1> <src2> ...")
		return 2
	out = sys.argv[1]
	srcs = sys.argv[2:]
	n = process(srcs, out)
	print(f"Wrote {n} IL examples -> {out}")
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


main

			continue
		for line in p.read_text(encoding="utf-8").splitlines():
			line = line.strip()
			if not line:
				continue
			yield json.loads(line)

def process(src_paths: List[str], out_jsonl: str) -> int:
	out = Path(out_jsonl)
	out.parent.mkdir(parents=True, exist_ok=True)
	count = 0
	with out.open("w", encoding="utf-8") as fout:
		for obj in iter_jsonl([Path(p) for p in src_paths]):
			ex = build_example(obj)
			fout.write(json.dumps(ex, ensure_ascii=False) + "\n")
			count += 1
	return count

def main() -> int:
	# Usage: build_actuator_il_combined.py <out.jsonl> <src1.jsonl> <src2.jsonl> ...
	if len(sys.argv) < 3:
		print("Usage: build_actuator_il_combined.py <out.jsonl> <src1> <src2> ...")
		return 2
	out = sys.argv[1]
	srcs = sys.argv[2:]
	n = process(srcs, out)
	print(f"Wrote {n} IL examples -> {out}")
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


import logging
import argparse
import json
from pathlib import Path
from typing import List

def load_traces(paths: List[str]) -> List[dict]:
	out = []
	for p in paths:
		fp = Path(p)
		if not fp.exists():
			continue
		with fp.open("r", encoding="utf-8") as f:
			for line in f:
				line = line.strip()
				if not line:
					continue
				try:
					out.append(json.loads(line))
				except Exception:
					continue
	return out

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--verified", nargs='*', default=[str(root / "data" / "traces" / "seed_os_cli.verified.llm.jsonl"), str(root / "data" / "traces" / "web_dom.verified.jsonl")])
	ap.add_argument("--out", default=str(root / "models" / "wm_mlp" / "wm_mlp.joblib"))
	ap.add_argument("--incremental", action="store_true", help="Use SGD partial_fit to incrementally update models if prior exists")
	args = ap.parse_args()

	# Build shallow TF-IDF + logistic/regression models over recent traces
	traces = load_traces(list(args.verified or []))
	texts = []
	y_cls = []
	y_risk = []
	for tr in traces[-5000:]:  # limit to last 5k
		try:
			txt = " \n ".join([str(tr.get("obs", {})), json.dumps(tr.get("plan", {}), ensure_ascii=False), json.dumps(tr.get("action", {}), ensure_ascii=False)])
			texts.append(txt)
			status = str(tr.get("result", {}).get("status", "")).lower()
			y_cls.append(1 if status == "ok" else 0)
			y_risk.append(float(tr.get("critique", {}).get("risk", 0.5)))
		except Exception:
			continue
	if not texts:
		print(json.dumps({"updated": False, "reason": "no data"}))
		return 0
	try:
		from sklearn.feature_extraction.text import TfidfVectorizer  # type: ignore
		from sklearn.linear_model import LogisticRegression, Ridge, SGDClassifier, SGDRegressor  # type: ignore
		import numpy as np  # type: ignore
		from joblib import dump as joblib_dump, load as joblib_load  # type: ignore
	except Exception:
		print(json.dumps({"updated": False, "reason": "sklearn not installed"}))
		return 0

	# Try to reuse existing vectorizer
	vec = None
	pack = None
	out_path = Path(args.out)
	if out_path.exists():
		try:
			pack = joblib_load(str(out_path))
			vec = pack.get("vec")
		except Exception:
			vec = None
	if vec is None:
		vec = TfidfVectorizer(max_features=20000)
	X = vec.fit_transform(texts) if not hasattr(vec, "transform") else vec.transform(texts)

	cls_arr = np.asarray(y_cls)
	risk_arr = np.asarray(y_risk)

	clf = None
	reg = None
	if args.incremental and isinstance(pack, dict) and pack.get("clf") is not None and pack.get("reg") is not None:
		# Incremental update using SGD, warm-start from scratch on current data
		clf = SGDClassifier(loss="log_loss", max_iter=5)
		clf.partial_fit(X, cls_arr, classes=np.array([0, 1]))
		reg = SGDRegressor(max_iter=20)
		reg.partial_fit(X, risk_arr)
	else:
		clf = LogisticRegression(max_iter=200)
		clf.fit(X, cls_arr)
		reg = Ridge(alpha=1.0)
		reg.fit(X, risk_arr)

	out_dir = Path(args.out).parent
	out_dir.mkdir(parents=True, exist_ok=True)
	# Preserve any existing calibration/risk_std if present
	risk_std = None
	cal = None
	if isinstance(pack, dict):
		risk_std = pack.get("risk_std")
		cal = pack.get("cal")
	joblib_dump({"vec": vec, "clf": clf, "reg": reg, "cal": cal, "risk_std": risk_std}, str(args.out))
	print(json.dumps({"updated": True, "path": str(args.out), "n": len(texts), "incremental": bool(args.incremental)}))
	return 0

if __name__ == "__main__":
	import sys
	sys.exit(main())


import logging
import argparse
import json
from pathlib import Path
from typing import List

def load_traces(paths: List[str]) -> List[dict]:
	out = []
	for p in paths:
		fp = Path(p)
		if not fp.exists():
			continue
		with fp.open("r", encoding="utf-8") as f:
			for line in f:
				line = line.strip()
				if not line:
					continue
				try:
					out.append(json.loads(line))
				except Exception:
					continue
	return out

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--verified", nargs='*', default=[str(root / "data" / "traces" / "seed_os_cli.verified.llm.jsonl"), str(root / "data" / "traces" / "web_dom.verified.jsonl")])
	ap.add_argument("--out", default=str(root / "models" / "wm_mlp" / "wm_mlp.joblib"))
	ap.add_argument("--incremental", action="store_true", help="Use SGD partial_fit to incrementally update models if prior exists")
	args = ap.parse_args()

	# Build shallow TF-IDF + logistic/regression models over recent traces
	traces = load_traces(list(args.verified or []))
	texts = []
	y_cls = []
	y_risk = []
	for tr in traces[-5000:]:  # limit to last 5k
		try:
			txt = " \n ".join([str(tr.get("obs", {})), json.dumps(tr.get("plan", {}), ensure_ascii=False), json.dumps(tr.get("action", {}), ensure_ascii=False)])
			texts.append(txt)
			status = str(tr.get("result", {}).get("status", "")).lower()


def load_traces(paths: List[str]) -> List[dict]:
	out = []
	for p in paths:
		fp = Path(p)
		if not fp.exists():
			continue
		with fp.open("r", encoding="utf-8") as f:
			for line in f:
				line = line.strip()
				if not line:
					continue
				try:
					out.append(json.loads(line))
				except Exception:
					continue
	return out

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--verified", nargs='*', default=[str(root / "data" / "traces" / "seed_os_cli.verified.llm.jsonl"), str(root / "data" / "traces" / "web_dom.verified.jsonl")])
	ap.add_argument("--out", default=str(root / "models" / "wm_mlp" / "wm_mlp.joblib"))
	ap.add_argument("--incremental", action="store_true", help="Use SGD partial_fit to incrementally update models if prior exists")
	args = ap.parse_args()

	# Build shallow TF-IDF + logistic/regression models over recent traces
	traces = load_traces(list(args.verified or []))
	texts = []
	y_cls = []
	y_risk = []
	for tr in traces[-5000:]:  # limit to last 5k
		try:
			txt = " \n ".join([str(tr.get("obs", {})), json.dumps(tr.get("plan", {}), ensure_ascii=False), json.dumps(tr.get("action", {}), ensure_ascii=False)])
			texts.append(txt)
			status = str(tr.get("result", {}).get("status", "")).lower()
			y_cls.append(1 if status == "ok" else 0)
			y_risk.append(float(tr.get("critique", {}).get("risk", 0.5)))
		except Exception:
			continue
	if not texts:
		print(json.dumps({"updated": False, "reason": "no data"}))
		return 0
	try:
		from sklearn.feature_extraction.text import TfidfVectorizer  # type: ignore
		from sklearn.linear_model import LogisticRegression, Ridge, SGDClassifier, SGDRegressor  # type: ignore
		import numpy as np  # type: ignore
		from joblib import dump as joblib_dump, load as joblib_load  # type: ignore
	except Exception:
		print(json.dumps({"updated": False, "reason": "sklearn not installed"}))
		return 0

	# Try to reuse existing vectorizer
	vec = None
	pack = None
	out_path = Path(args.out)
	if out_path.exists():
		try:
			pack = joblib_load(str(out_path))
			vec = pack.get("vec")
		except Exception:
			vec = None
	if vec is None:
		vec = TfidfVectorizer(max_features=20000)
	X = vec.fit_transform(texts) if not hasattr(vec, "transform") else vec.transform(texts)

	cls_arr = np.asarray(y_cls)
	risk_arr = np.asarray(y_risk)

	clf = None
	reg = None
	if args.incremental and isinstance(pack, dict) and pack.get("clf") is not None and pack.get("reg") is not None:
		# Incremental update using SGD, warm-start from scratch on current data
		clf = SGDClassifier(loss="log_loss", max_iter=5)
		clf.partial_fit(X, cls_arr, classes=np.array([0, 1]))
		reg = SGDRegressor(max_iter=20)
		reg.partial_fit(X, risk_arr)
	else:
		clf = LogisticRegression(max_iter=200)
		clf.fit(X, cls_arr)
		reg = Ridge(alpha=1.0)
		reg.fit(X, risk_arr)

	out_dir = Path(args.out).parent
	out_dir.mkdir(parents=True, exist_ok=True)
	# Preserve any existing calibration/risk_std if present
	risk_std = None
	cal = None
	if isinstance(pack, dict):
		risk_std = pack.get("risk_std")
		cal = pack.get("cal")
	joblib_dump({"vec": vec, "clf": clf, "reg": reg, "cal": cal, "risk_std": risk_std}, str(args.out))
	print(json.dumps({"updated": True, "path": str(args.out), "n": len(texts), "incremental": bool(args.incremental)}))
	return 0

if __name__ == "__main__":
	import sys
	sys.exit(main())


import logging
import json
from pathlib import Path
from typing import Any, Dict
import sys

def build_example(obj: Dict[str, Any]) -> Dict[str, Any]:
	obs = obj.get("obs", {})
	plan = obj.get("plan", {})
	action = obj.get("action", {})
	# Minimal text input for IL: obs + plan as JSON
	input_text = json.dumps({"obs": obs, "plan": plan}, ensure_ascii=False)
	output_text = json.dumps(action, ensure_ascii=False)
	return {"input": input_text, "output": output_text}

def process(src_jsonl: Path, out_jsonl: Path) -> int:
	out_jsonl.parent.mkdir(parents=True, exist_ok=True)
	count = 0
	with src_jsonl.open("r", encoding="utf-8") as fin, out_jsonl.open("w", encoding="utf-8") as fout:
		for line in fin:
			line = line.strip()
			if not line:
				continue
			obj: Dict[str, Any] = json.loads(line)
			ex = build_example(obj)
			fout.write(json.dumps(ex, ensure_ascii=False) + "\n")
			count += 1
	return count

def main() -> int:
	root = Path(__file__).resolve().parents[1]
	src = Path(sys.argv[1]) if len(sys.argv) > 1 else root / "data" / "traces" / "seed_os_cli.verified.llm.jsonl"
	dst = Path(sys.argv[2]) if len(sys.argv) > 2 else root / "data" / "skills" / "actuator_il.jsonl"
	n = process(src, dst)
	print(f"Wrote {n} IL examples -> {dst}")
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


import logging
import json
from pathlib import Path
from typing import Any, Dict
import sys

def build_example(obj: Dict[str, Any]) -> Dict[str, Any]:
	obs = obj.get("obs", {})
	plan = obj.get("plan", {})
	action = obj.get("action", {})
	# Minimal text input for IL: obs + plan as JSON
	input_text = json.dumps({"obs": obs, "plan": plan}, ensure_ascii=False)
	output_text = json.dumps(action, ensure_ascii=False)
	return {"input": input_text, "output": output_text}

def process(src_jsonl: Path, out_jsonl: Path) -> int:
	out_jsonl.parent.mkdir(parents=True, exist_ok=True)
	count = 0
	with src_jsonl.open("r", encoding="utf-8") as fin, out_jsonl.open("w", encoding="utf-8") as fout:
		for line in fin:
			line = line.strip()
			if not line:
				continue
			obj: Dict[str, Any] = json.loads(line)
			ex = build_example(obj)
			fout.write(json.dumps(ex, ensure_ascii=False) + "\n")
			count += 1
	return count

def main() -> int:
	root = Path(__file__).resolve().parents[1]
	src = Path(sys.argv[1]) if len(sys.argv) > 1 else root / "data" / "traces" / "seed_os_cli.verified.llm.jsonl"


	input_text = json.dumps({"obs": obs, "plan": plan}, ensure_ascii=False)
	output_text = json.dumps(action, ensure_ascii=False)
	return {"input": input_text, "output": output_text}

def process(src_jsonl: Path, out_jsonl: Path) -> int:
	out_jsonl.parent.mkdir(parents=True, exist_ok=True)
	count = 0
	with src_jsonl.open("r", encoding="utf-8") as fin, out_jsonl.open("w", encoding="utf-8") as fout:
		for line in fin:
			line = line.strip()
			if not line:
				continue
			obj: Dict[str, Any] = json.loads(line)
			ex = build_example(obj)
			fout.write(json.dumps(ex, ensure_ascii=False) + "\n")
			count += 1
	return count

def main() -> int:
	root = Path(__file__).resolve().parents[1]
	src = Path(sys.argv[1]) if len(sys.argv) > 1 else root / "data" / "traces" / "seed_os_cli.verified.llm.jsonl"
	dst = Path(sys.argv[2]) if len(sys.argv) > 2 else root / "data" / "skills" / "actuator_il.jsonl"
	n = process(src, dst)
	print(f"Wrote {n} IL examples -> {dst}")
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


from __future__ import annotations
import logging

import argparse
import json
from pathlib import Path
from typing import Any, Dict

def _safe(obj: Any) -> Any:
	try:
		json.dumps(obj, ensure_ascii=False)
		return obj
	except Exception:
		return str(obj)

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--in", dest="inp", required=True, help="Path to EBST JSONL input")
	ap.add_argument("--out", dest="out", default=str(root / "data" / "traces" / "coder_ds.ebst.jsonl"))
	ap.add_argument("--skills-out", dest="skills_out", default=str(root / "data" / "skills" / "coder_ds.ebst.jsonl"))
	args = ap.parse_args()

	inp = Path(args.inp)
	out = Path(args.out)
	skills_out = Path(args.skills_out)
	out.parent.mkdir(parents=True, exist_ok=True)
	skills_out.parent.mkdir(parents=True, exist_ok=True)

	if not inp.exists():
		print(json.dumps({"ok": False, "error": f"input not found: {str(inp)}"}, ensure_ascii=False))
		return 2

	written = 0
	with inp.open("r", encoding="utf-8") as f, out.open("w", encoding="utf-8") as g, skills_out.open("w", encoding="utf-8") as gs:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				rec: Dict[str, Any] = json.loads(line)
			except Exception:
				continue
			# Expected EBST fields (flexible); map into our schema
			obs = _safe(rec.get("obs") or rec.get("observation") or {})
			prompt = rec.get("prompt") or rec.get("plan_prompt") or ""
			status = str(rec.get("status") or rec.get("result", {}).get("status", "")).strip()
			patch_meta = rec.get("patch_meta") or rec.get("action") or {}
			row = {
				"obs": obs,
				"prompt": str(prompt),
				"result": {"status": status},
				"patch_meta": _safe(patch_meta),
			}
			line_out = json.dumps(row, ensure_ascii=False) + "\n"
			g.write(line_out)
			gs.write(line_out)
			written += 1

	print(json.dumps({"ok": True, "items": int(written), "out": str(out)}, ensure_ascii=False))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


from __future__ import annotations
import logging

import argparse
import json
from pathlib import Path
from typing import Any, Dict

def _safe(obj: Any) -> Any:
	try:
		json.dumps(obj, ensure_ascii=False)
		return obj
	except Exception:
		return str(obj)

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--in", dest="inp", required=True, help="Path to EBST JSONL input")
	ap.add_argument("--out", dest="out", default=str(root / "data" / "traces" / "coder_ds.ebst.jsonl"))
	ap.add_argument("--skills-out", dest="skills_out", default=str(root / "data" / "skills" / "coder_ds.ebst.jsonl"))
	args = ap.parse_args()

	inp = Path(args.inp)
	out = Path(args.out)
	skills_out = Path(args.skills_out)
	out.parent.mkdir(parents=True, exist_ok=True)
	skills_out.parent.mkdir(parents=True, exist_ok=True)

	if not inp.exists():
		print(json.dumps({"ok": False, "error": f"input not found: {str(inp)}"}, ensure_ascii=False))
		return 2


import logging
import argparse
import hashlib
import json
from pathlib import Path
from typing import Dict, Iterable, Tuple

def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def key_for_planner(obj: Dict) -> str:
	obs = obj.get("obs", {}) if isinstance(obj.get("obs"), dict) else {}
	pl = obj.get("plan", {}) if isinstance(obj.get("plan"), dict) else {}
	return json.dumps({"obs": obs.get("kind"), "content": obs.get("content"), "plan": pl}, ensure_ascii=False, sort_keys=True)

def write_planner_split(src: Path, out_train: Path, out_eval: Path, ratio: float) -> Tuple[int, int]:
	out_train.parent.mkdir(parents=True, exist_ok=True)
	out_eval.parent.mkdir(parents=True, exist_ok=True)
	n_tr = 0
	n_ev = 0
	with out_train.open("w", encoding="utf-8") as ftr, out_eval.open("w", encoding="utf-8") as fev:
		for obj in iter_jsonl(src):
			k = key_for_planner(obj)
			h = int(hashlib.sha256(k.encode("utf-8")).hexdigest(), 16)
			p = (h % 1000) / 1000.0
			line = json.dumps(obj, ensure_ascii=False) + "\n"
			if p < ratio:
				ftr.write(line)
				n_tr += 1
			else:
				fev.write(line)
				n_ev += 1
	return n_tr, n_ev

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--src", default=str(root / "data" / "traces" / "all.jsonl"))
	ap.add_argument("--train", default=str(root / "data" / "splits" / "planner_train.jsonl"))
	ap.add_argument("--eval", default=str(root / "data" / "splits" / "planner_eval.jsonl"))
	ap.add_argument("--ratio", type=float, default=0.8)
	args = ap.parse_args()

	n_tr, n_ev = write_planner_split(Path(args.src), Path(args.train), Path(args.eval), max(0.0, min(1.0, float(args.ratio))))
	print(json.dumps({"train": n_tr, "eval": n_ev}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


import logging
import argparse
import hashlib
import json
from pathlib import Path
from typing import Dict, Iterable, Tuple

def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def key_for_planner(obj: Dict) -> str:
	obs = obj.get("obs", {}) if isinstance(obj.get("obs"), dict) else {}
	pl = obj.get("plan", {}) if isinstance(obj.get("plan"), dict) else {}
	return json.dumps({"obs": obs.get("kind"), "content": obs.get("content"), "plan": pl}, ensure_ascii=False, sort_keys=True)

def write_planner_split(src: Path, out_train: Path, out_eval: Path, ratio: float) -> Tuple[int, int]:
	out_train.parent.mkdir(parents=True, exist_ok=True)
	out_eval.parent.mkdir(parents=True, exist_ok=True)
	n_tr = 0
	n_ev = 0
	with out_train.open("w", encoding="utf-8") as ftr, out_eval.open("w", encoding="utf-8") as fev:
		for obj in iter_jsonl(src):
			k = key_for_planner(obj)
			h = int(hashlib.sha256(k.encode("utf-8")).hexdigest(), 16)
			p = (h % 1000) / 1000.0
			line = json.dumps(obj, ensure_ascii=False) + "\n"
			if p < ratio:


import hashlib
import json
from pathlib import Path
from typing import Dict, Iterable, Tuple

def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def key_for_planner(obj: Dict) -> str:
	obs = obj.get("obs", {}) if isinstance(obj.get("obs"), dict) else {}
	pl = obj.get("plan", {}) if isinstance(obj.get("plan"), dict) else {}
	return json.dumps({"obs": obs.get("kind"), "content": obs.get("content"), "plan": pl}, ensure_ascii=False, sort_keys=True)

def write_planner_split(src: Path, out_train: Path, out_eval: Path, ratio: float) -> Tuple[int, int]:
	out_train.parent.mkdir(parents=True, exist_ok=True)
	out_eval.parent.mkdir(parents=True, exist_ok=True)
	n_tr = 0
	n_ev = 0
	with out_train.open("w", encoding="utf-8") as ftr, out_eval.open("w", encoding="utf-8") as fev:
		for obj in iter_jsonl(src):
			k = key_for_planner(obj)
			h = int(hashlib.sha256(k.encode("utf-8")).hexdigest(), 16)
			p = (h % 1000) / 1000.0
			line = json.dumps(obj, ensure_ascii=False) + "\n"
			if p < ratio:
				ftr.write(line)
				n_tr += 1
			else:
				fev.write(line)
				n_ev += 1
	return n_tr, n_ev


def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def key_for_planner(obj: Dict) -> str:
	obs = obj.get("obs", {}) if isinstance(obj.get("obs"), dict) else {}
	pl = obj.get("plan", {}) if isinstance(obj.get("plan"), dict) else {}
	return json.dumps({"obs": obs.get("kind"), "content": obs.get("content"), "plan": pl}, ensure_ascii=False, sort_keys=True)

def write_planner_split(src: Path, out_train: Path, out_eval: Path, ratio: float) -> Tuple[int, int]:
	out_train.parent.mkdir(parents=True, exist_ok=True)
	out_eval.parent.mkdir(parents=True, exist_ok=True)
	n_tr = 0
	n_ev = 0
	with out_train.open("w", encoding="utf-8") as ftr, out_eval.open("w", encoding="utf-8") as fev:
		for obj in iter_jsonl(src):
			k = key_for_planner(obj)
			h = int(hashlib.sha256(k.encode("utf-8")).hexdigest(), 16)
			p = (h % 1000) / 1000.0
			line = json.dumps(obj, ensure_ascii=False) + "\n"
			if p < ratio:
				ftr.write(line)
				n_tr += 1
			else:
				fev.write(line)
				n_ev += 1
	return n_tr, n_ev

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--src", default=str(root / "data" / "traces" / "all.jsonl"))
	ap.add_argument("--train", default=str(root / "data" / "splits" / "planner_train.jsonl"))
	ap.add_argument("--eval", default=str(root / "data" / "splits" / "planner_eval.jsonl"))
	ap.add_argument("--ratio", type=float, default=0.8)
	args = ap.parse_args()

	n_tr, n_ev = write_planner_split(Path(args.src), Path(args.train), Path(args.eval), max(0.0, min(1.0, float(args.ratio))))
	print(json.dumps({"train": n_tr, "eval": n_ev}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


def write_planner_split(src: Path, out_train: Path, out_eval: Path, ratio: float) -> Tuple[int, int]:
	out_train.parent.mkdir(parents=True, exist_ok=True)
	out_eval.parent.mkdir(parents=True, exist_ok=True)
	n_tr = 0
	n_ev = 0
	with out_train.open("w", encoding="utf-8") as ftr, out_eval.open("w", encoding="utf-8") as fev:
		for obj in iter_jsonl(src):
			k = key_for_planner(obj)
			h = int(hashlib.sha256(k.encode("utf-8")).hexdigest(), 16)
			p = (h % 1000) / 1000.0
			line = json.dumps(obj, ensure_ascii=False) + "\n"
			if p < ratio:
				ftr.write(line)
				n_tr += 1
			else:
				fev.write(line)
				n_ev += 1
	return n_tr, n_ev

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--src", default=str(root / "data" / "traces" / "all.jsonl"))
	ap.add_argument("--train", default=str(root / "data" / "splits" / "planner_train.jsonl"))
	ap.add_argument("--eval", default=str(root / "data" / "splits" / "planner_eval.jsonl"))
	ap.add_argument("--ratio", type=float, default=0.8)
	args = ap.parse_args()

	n_tr, n_ev = write_planner_split(Path(args.src), Path(args.train), Path(args.eval), max(0.0, min(1.0, float(args.ratio))))
	print(json.dumps({"train": n_tr, "eval": n_ev}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


import logging
import argparse
import hashlib
import json
from pathlib import Path
from typing import Dict, Tuple

def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def key_for_wm(obj: Dict) -> str:
	obs = obj.get("obs", {})
	action = obj.get("action", {})
	return json.dumps({"obs": obs, "action": action}, ensure_ascii=False, sort_keys=True)

def write_split(src: Path, out_train: Path, out_eval: Path, ratio: float) -> Tuple[int, int]:
	out_train.parent.mkdir(parents=True, exist_ok=True)
	out_eval.parent.mkdir(parents=True, exist_ok=True)
	n_tr = 0
	n_ev = 0
	with out_train.open("w", encoding="utf-8") as ftr, out_eval.open("w", encoding="utf-8") as fev:
		for obj in iter_jsonl(src):
			h = int(hashlib.sha256(key_for_wm(obj).encode("utf-8")).hexdigest(), 16)
			p = (h % 1000) / 1000.0
			line = json.dumps(obj, ensure_ascii=False) + "\n"
			if p < ratio:
				ftr.write(line)
				n_tr += 1
			else:
				fev.write(line)
				n_ev += 1
	return n_tr, n_ev

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--src", default=str(root / "data" / "skills" / "wm_ds.jsonl"))
	ap.add_argument("--train", default=str(root / "data" / "splits" / "wm_train.jsonl"))
	ap.add_argument("--eval", default=str(root / "data" / "splits" / "wm_eval.jsonl"))
	ap.add_argument("--ratio", type=float, default=0.8)
	args = ap.parse_args()

	n_tr, n_ev = write_split(Path(args.src), Path(args.train), Path(args.eval), max(0.0, min(1.0, float(args.ratio))))
	print(json.dumps({"train": n_tr, "eval": n_ev}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


import logging
import argparse
import hashlib
import json
from pathlib import Path
from typing import Dict, Tuple

def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def key_for_wm(obj: Dict) -> str:
	obs = obj.get("obs", {})
	action = obj.get("action", {})
	return json.dumps({"obs": obs, "action": action}, ensure_ascii=False, sort_keys=True)

def write_split(src: Path, out_train: Path, out_eval: Path, ratio: float) -> Tuple[int, int]:
	out_train.parent.mkdir(parents=True, exist_ok=True)
	out_eval.parent.mkdir(parents=True, exist_ok=True)
	n_tr = 0
	n_ev = 0
	with out_train.open("w", encoding="utf-8") as ftr, out_eval.open("w", encoding="utf-8") as fev:
		for obj in iter_jsonl(src):
			h = int(hashlib.sha256(key_for_wm(obj).encode("utf-8")).hexdigest(), 16)
			p = (h % 1000) / 1000.0
			line = json.dumps(obj, ensure_ascii=False) + "\n"
			if p < ratio:
				ftr.write(line)


import hashlib
import json
from pathlib import Path
from typing import Dict, Tuple

def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def key_for_wm(obj: Dict) -> str:
	obs = obj.get("obs", {})
	action = obj.get("action", {})
	return json.dumps({"obs": obs, "action": action}, ensure_ascii=False, sort_keys=True)

def write_split(src: Path, out_train: Path, out_eval: Path, ratio: float) -> Tuple[int, int]:
	out_train.parent.mkdir(parents=True, exist_ok=True)
	out_eval.parent.mkdir(parents=True, exist_ok=True)
	n_tr = 0
	n_ev = 0
	with out_train.open("w", encoding="utf-8") as ftr, out_eval.open("w", encoding="utf-8") as fev:
		for obj in iter_jsonl(src):
			h = int(hashlib.sha256(key_for_wm(obj).encode("utf-8")).hexdigest(), 16)
			p = (h % 1000) / 1000.0
			line = json.dumps(obj, ensure_ascii=False) + "\n"
			if p < ratio:
				ftr.write(line)
				n_tr += 1
			else:
				fev.write(line)
				n_ev += 1
	return n_tr, n_ev


def iter_jsonl(path: Path):
	if not path.exists():
		return
	with path.open("r", encoding="utf-8") as f:
		for line in f:
			line = line.strip()
			if not line:
				continue
			try:
				yield json.loads(line)
			except Exception:
				continue

def key_for_wm(obj: Dict) -> str:
	obs = obj.get("obs", {})
	action = obj.get("action", {})
	return json.dumps({"obs": obs, "action": action}, ensure_ascii=False, sort_keys=True)

def write_split(src: Path, out_train: Path, out_eval: Path, ratio: float) -> Tuple[int, int]:
	out_train.parent.mkdir(parents=True, exist_ok=True)
	out_eval.parent.mkdir(parents=True, exist_ok=True)
	n_tr = 0
	n_ev = 0
	with out_train.open("w", encoding="utf-8") as ftr, out_eval.open("w", encoding="utf-8") as fev:
		for obj in iter_jsonl(src):
			h = int(hashlib.sha256(key_for_wm(obj).encode("utf-8")).hexdigest(), 16)
			p = (h % 1000) / 1000.0
			line = json.dumps(obj, ensure_ascii=False) + "\n"
			if p < ratio:
				ftr.write(line)
				n_tr += 1
			else:
				fev.write(line)
				n_ev += 1
	return n_tr, n_ev

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--src", default=str(root / "data" / "skills" / "wm_ds.jsonl"))
	ap.add_argument("--train", default=str(root / "data" / "splits" / "wm_train.jsonl"))
	ap.add_argument("--eval", default=str(root / "data" / "splits" / "wm_eval.jsonl"))
	ap.add_argument("--ratio", type=float, default=0.8)
	args = ap.parse_args()

	n_tr, n_ev = write_split(Path(args.src), Path(args.train), Path(args.eval), max(0.0, min(1.0, float(args.ratio))))
	print(json.dumps({"train": n_tr, "eval": n_ev}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())


def write_split(src: Path, out_train: Path, out_eval: Path, ratio: float) -> Tuple[int, int]:
	out_train.parent.mkdir(parents=True, exist_ok=True)
	out_eval.parent.mkdir(parents=True, exist_ok=True)
	n_tr = 0
	n_ev = 0
	with out_train.open("w", encoding="utf-8") as ftr, out_eval.open("w", encoding="utf-8") as fev:
		for obj in iter_jsonl(src):
			h = int(hashlib.sha256(key_for_wm(obj).encode("utf-8")).hexdigest(), 16)
			p = (h % 1000) / 1000.0
			line = json.dumps(obj, ensure_ascii=False) + "\n"
			if p < ratio:
				ftr.write(line)
				n_tr += 1
			else:
				fev.write(line)
				n_ev += 1
	return n_tr, n_ev

def main() -> int:
	ap = argparse.ArgumentParser()
	root = Path(__file__).resolve().parents[1]
	ap.add_argument("--src", default=str(root / "data" / "skills" / "wm_ds.jsonl"))
	ap.add_argument("--train", default=str(root / "data" / "splits" / "wm_train.jsonl"))
	ap.add_argument("--eval", default=str(root / "data" / "splits" / "wm_eval.jsonl"))
	ap.add_argument("--ratio", type=float, default=0.8)
	args = ap.parse_args()

	n_tr, n_ev = write_split(Path(args.src), Path(args.train), Path(args.eval), max(0.0, min(1.0, float(args.ratio))))
	print(json.dumps({"train": n_tr, "eval": n_ev}))
	return 0

if __name__ == "__main__":
	raise SystemExit(main())