feat: traces -> hf dataset converter

skills/configs/SKILL.md

@@ -60,6 +60,8 @@ env.agent.runtime.type = "subprocess"
 ```
 
 CLI: `--orchestrator.train.source.0.env.taskset.id reverse-text` or `--orchestrator.eval.source.0.env.taskset.id reverse-text`.
+Use a JSON literal for a one-item list. For example, use `--data.subsets '["default"]'` and
+`--data.splits '["train"]'`. A bare scalar does not pass list validation.
 
 The `sft` entrypoint takes the same eval shape at the top level for online evals: `[eval]` + `[[eval.source]]` (with `[inference]` for the server), e.g. `--eval.source.0.env.taskset.id reverse-text`.
 

tools/convert_traces_to_hf_dataset.py

@@ -0,0 +1,188 @@
+"""Convert episode traces into a branch-level Hugging Face dataset.
+
+Train and eval runs save one episode per line in `traces.jsonl`. This tool writes one
+dataset row for every branch of every agent trace. It does not select or filter rows.
+
+Each row includes `messages` and JSON-encoded `tools` for SFT. It also includes trace,
+agent, task, run, outcome, error, timing, and usage metadata. Scalar outcome fields such
+as `reward`, `stop_condition`, `has_error`, and `is_truncated` stay as top-level columns
+so later scripts can filter them directly. Metadata with variable schemas stays as JSON.
+
+Usage (from the prime-rl repo):
+    uv run python tools/convert_traces_to_hf_dataset.py <traces.jsonl> --name <dir-or-repo-id>
+        [--subset default] [--split train] [--private] [--local]
+
+By default, the tool pushes to the Hugging Face Hub repo `<name>`. Use `--private` when
+creating a private repo. With `--local`, it writes `<name>/<subset>/<split>.parquet` and
+registers it in `<name>/README.md` instead.
+"""
+
+import argparse
+import json
+from pathlib import Path
+from typing import Any
+
+import yaml
+from datasets import Dataset
+from pydantic import BaseModel
+from verifiers.v1 import Trace, WireEpisode
+from verifiers.v1.dialects.chat import message_to_wire
+
+
+def jsonable(value: Any) -> Any:
+    if isinstance(value, BaseModel):
+        return value.model_dump(mode="json", exclude_none=True)
+    if isinstance(value, list):
+        return [jsonable(item) for item in value]
+    if isinstance(value, dict):
+        return {key: jsonable(item) for key, item in value.items()}
+    return value
+
+
+def as_json(value: Any) -> str:
+    return json.dumps(jsonable(value), separators=(",", ":"))
+
+
+def trace_rows(episode: WireEpisode, trace: Trace) -> list[dict]:
+    """Convert each branch of one trace without selecting or filtering it."""
+    last_error = trace.last_error
+    run = episode.run
+    work = getattr(run, "work", None)
+    policy = getattr(work, "policy", None)
+    common = {
+        "episode_id": episode.id,
+        "episode_ok": episode.ok,
+        "episode_has_error": bool(episode.errors),
+        "episode_errors": as_json(episode.errors),
+        "env_id": episode.env.id,
+        "env_name": episode.env.name,
+        "group_id": episode.group.id if episode.group else None,
+        "run_type": run.type if run else None,
+        "run_id": run.id if run else None,
+        "run_name": run.name if run else None,
+        "work_type": work.type if work else None,
+        "step": getattr(work, "step", None),
+        "policy_start": policy.start if policy else None,
+        "policy_end": policy.end if policy else None,
+        "trace_id": trace.id,
+        "trace_version": trace.version,
+        "verifiers_version": trace.verifiers.version,
+        "verifiers_commit": trace.verifiers.commit,
+        "task_type": trace.task.type,
+        "task_data": as_json(trace.task.data),
+        "task_key": trace.task.key,
+        "task_hash": trace.task.hash,
+        "agent": trace.agent.name,
+        "trainable": trace.agent.trainable,
+        "agent_config": as_json(trace.agent.config),
+        "agent_runtime": as_json(trace.agent.runtime),
+        "tools": as_json(trace.tools),
+        "reward": trace.reward,
+        "rewards": as_json(trace.rewards),
+        "metrics": as_json(trace.metrics),
+        "info": as_json(trace.info),
+        "is_completed": trace.is_completed,
+        "ok": trace.ok,
+        "stop_condition": trace.stop_condition,
+        "has_error": trace.has_error,
+        "error_type": last_error.type if last_error else None,
+        "error_message": last_error.message if last_error else None,
+        "error_status_code": last_error.status_code if last_error else None,
+        "errors": as_json(trace.errors),
+        "is_truncated": trace.is_truncated,
+        "request_rewrites": as_json(trace.request_rewrites),
+        "response_rewrites": as_json(trace.response_rewrites),
+        "extra_usage": as_json(trace.extra_usage),
+        "timing": as_json(trace.timing),
+        "num_branches": trace.num_branches,
+        "num_turns": trace.num_turns,
+        "num_input_tokens": trace.num_input_tokens,
+        "num_output_tokens": trace.num_output_tokens,
+        "num_total_tokens": trace.num_total_tokens,
+    }
+    return [
+        {
+            **common,
+            "branch_index": branch.index,
+            "messages": [message_to_wire(m) for m in branch.messages],
+            "calls": as_json(branch.calls),
+            "branch_num_input_tokens": branch.num_input_tokens,
+            "branch_num_output_tokens": branch.num_output_tokens,
+            "branch_num_total_tokens": branch.num_total_tokens,
+        }
+        for branch in trace.branches
+    ]
+
+
+def register_in_dataset_card(root: Path, subset: str, split: str, rel_path: str) -> None:
+    """Point the dataset card's `configs` metadata at the parquet, so
+    `load_dataset(root, subset, split=split)` resolves it."""
+    readme = root / "README.md"
+    meta: dict = {}
+    body = ""
+    if readme.exists():
+        text = readme.read_text()
+        if text.startswith("---"):
+            _, header, body = text.split("---", 2)
+            meta = yaml.safe_load(header) or {}
+    configs = meta.setdefault("configs", [])
+    config = next((c for c in configs if c["config_name"] == subset), None)
+    if config is None:
+        config = {"config_name": subset, "data_files": []}
+        configs.append(config)
+    entry = next((e for e in config["data_files"] if e["split"] == split), None)
+    if entry is None:
+        config["data_files"].append({"split": split, "path": rel_path})
+    else:
+        entry["path"] = rel_path
+    text = f"---\n{yaml.safe_dump(meta, sort_keys=False)}---{body}"
+    readme.write_text(text if text.endswith("\n") else text + "\n")
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description=__doc__.splitlines()[0])
+    parser.add_argument("traces", type=Path, help="a run's traces.jsonl (one episode per line)")
+    parser.add_argument("--name", required=True, help="HF repo id, or output dataset dir with --local")
+    parser.add_argument("--subset", default="default", help="dataset config name")
+    parser.add_argument("--split", default="train", help="dataset split name")
+    parser.add_argument("--private", action="store_true", help="make a new Hub dataset private")
+    parser.add_argument("--local", action="store_true", help="write parquet locally instead of pushing")
+    args = parser.parse_args()
+    if args.local and args.private:
+        parser.error("--private cannot be used with --local")
+
+    num_episodes, num_traces, rows = 0, 0, []
+    with args.traces.open(encoding="utf-8") as f:
+        for line in f:
+            if not line.strip():
+                continue
+            num_episodes += 1
+            episode = WireEpisode.model_validate(json.loads(line))
+            for trace in episode.traces:
+                num_traces += 1
+                rows.extend(trace_rows(episode, trace))
+    print(f"traces-to-hf: {num_episodes} episode(s) -> {num_traces} trace(s) -> {len(rows)} branch(es)")
+    if not rows:
+        raise SystemExit("traces-to-hf: no branches found")
+
+    dataset = Dataset.from_list(rows)
+    if not args.local:
+        dataset.push_to_hub(
+            args.name,
+            config_name=args.subset,
+            split=args.split,
+            private=True if args.private else None,
+        )
+        print(f"traces-to-hf: pushed to {args.name} (subset={args.subset}, split={args.split}, private={args.private})")
+        return
+    root = Path(args.name)
+    rel_path = f"{args.subset}/{args.split}.parquet"
+    path = root / rel_path
+    path.parent.mkdir(parents=True, exist_ok=True)
+    dataset.to_parquet(str(path))
+    register_in_dataset_card(root, args.subset, args.split, rel_path)
+    print(f"traces-to-hf: wrote {path} (subset={args.subset}, split={args.split})")
+
+
+if __name__ == "__main__":
+    main()