Add reviewed task-file flow for Codex sleep runs

skillopt_sleep/tasks_file.py

@@ -0,0 +1,81 @@
+"""Reviewed task-file helpers for privacy-safe SkillOpt-Sleep runs."""
+from __future__ import annotations
+
+import json
+import os
+from typing import Any, Dict, List, Tuple
+
+from skillopt_sleep.mine import assign_splits, normalize_legacy_split
+from skillopt_sleep.types import TaskRecord
+
+
+def make_tasks_payload(
+    tasks: List[TaskRecord],
+    *,
+    project: str,
+    transcript_source: str = "",
+    n_sessions: int = 0,
+    target_skill_path: str = "",
+) -> Dict[str, Any]:
+    return {
+        "format": "skillopt_sleep.tasks.v1",
+        "project": project,
+        "transcript_source": transcript_source,
+        "n_sessions": n_sessions,
+        "target_skill_path": target_skill_path,
+        "reviewed": False,
+        "tasks": [t.to_dict() for t in tasks],
+    }
+
+
+def write_tasks_file(path: str, payload: Dict[str, Any]) -> str:
+    out = os.path.abspath(os.path.expanduser(path))
+    parent = os.path.dirname(out)
+    if parent:
+        os.makedirs(parent, exist_ok=True)
+    with open(out, "w", encoding="utf-8") as f:
+        json.dump(payload, f, ensure_ascii=False, indent=2)
+        f.write("\n")
+    return out
+
+
+def _normalize_tasks(
+    tasks: List[TaskRecord],
+    *,
+    holdout_fraction: float,
+    seed: int,
+) -> List[TaskRecord]:
+    for task in tasks:
+        task.split = normalize_legacy_split(task.split or "train")
+    if len(tasks) >= 2 and not any(task.split in {"val", "test"} for task in tasks):
+        tasks = assign_splits(tasks, holdout_fraction=holdout_fraction, seed=seed)
+    return tasks
+
+
+def load_tasks_file(
+    path: str,
+    *,
+    holdout_fraction: float = 0.34,
+    seed: int = 42,
+) -> Tuple[List[TaskRecord], Dict[str, Any]]:
+    source = os.path.abspath(os.path.expanduser(path))
+    with open(source, encoding="utf-8") as f:
+        payload = json.load(f)
+    if isinstance(payload, list):
+        meta: Dict[str, Any] = {"format": "skillopt_sleep.tasks.v1", "tasks_file": source}
+        raw_tasks = payload
+    elif isinstance(payload, dict):
+        meta = {k: v for k, v in payload.items() if k != "tasks"}
+        meta["tasks_file"] = source
+        raw_tasks = payload.get("tasks", [])
+    else:
+        raise ValueError("tasks file must contain a JSON object with tasks or a JSON task array")
+    if not isinstance(raw_tasks, list):
+        raise ValueError("tasks file field 'tasks' must be an array")
+
+    tasks: List[TaskRecord] = []
+    for item in raw_tasks:
+        if not isinstance(item, dict):
+            raise ValueError("each task entry must be a JSON object")
+        tasks.append(TaskRecord.from_dict(item))
+    return _normalize_tasks(tasks, holdout_fraction=holdout_fraction, seed=seed), meta