File size: 6,649 Bytes
2a2e170
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
#!/usr/bin/env python3
"""Export session trajectories as raw multi-turn tool-calling SFT data.

Reads the source sessions dataset (JSONL, one file per session at
``sessions/YYYY-MM-DD/<session_id>.jsonl``) and writes a re-shaped row to a
target dataset at ``sft/YYYY-MM-DD/<session_id>.jsonl``.

**No filtering, no cleaning, no dedup.** Raw passthrough of messages + tools,
with session-level metadata and derived tags (see ``agent/sft/tagger.py``)
attached for downstream slicing.

Output row schema::

    {
      "session_id": "...",
      "model": "claude-opus-4-6",
      "timestamp": "2026-04-24T...",
      "tags": ["tool:hf_jobs", "gpu:a100", "hf_job:succeeded", ...],
      "messages": [...],   # OpenAI / TRL SFTTrainer format
      "tools":   [...]     # OpenAI tool schemas the session had access to
    }

Usage::

    python scripts/build_sft.py \\
        --source smolagents/ml-intern-sessions \\
        --target smolagents/ml-intern-sft \\
        --days 7

Env:
    HF_TOKEN (or HF_SFT_WRITE_TOKEN) — write access to target dataset.
"""

from __future__ import annotations

import argparse
import json
import logging
import os
import sys
import tempfile
from datetime import date, datetime, timedelta, timezone
from typing import Iterable

# Make ``agent`` importable when this script is run outside the project venv.
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from agent.sft.tagger import tag_session  # noqa: E402

logger = logging.getLogger("build_sft")


def _iter_session_files(api, repo_id: str, day: date, token: str) -> Iterable[str]:
    prefix = f"sessions/{day.isoformat()}/"
    try:
        files = api.list_repo_files(repo_id=repo_id, repo_type="dataset", token=token)
    except Exception as e:
        logger.warning("list_repo_files(%s) failed: %s", repo_id, e)
        return []
    return [f for f in files if f.startswith(prefix) and f.endswith(".jsonl")]


def _download_and_parse(repo_id: str, path: str, token: str) -> dict | None:
    from huggingface_hub import hf_hub_download
    try:
        local = hf_hub_download(
            repo_id=repo_id, filename=path, repo_type="dataset", token=token,
        )
    except Exception as e:
        logger.warning("hf_hub_download(%s) failed: %s", path, e)
        return None
    try:
        with open(local, "r") as f:
            line = f.readline().strip()
        if not line:
            return None
        row = json.loads(line)
        # Session uploader stores messages/events/tools as JSON strings.
        for key in ("messages", "events", "tools"):
            v = row.get(key)
            if isinstance(v, str):
                try:
                    row[key] = json.loads(v)
                except Exception:
                    row[key] = []
        return row
    except Exception as e:
        logger.warning("parse(%s) failed: %s", path, e)
        return None


def _reshape_to_sft(row: dict) -> dict:
    """Raw passthrough: reshape one session row into SFT format + tags.

    Trajectories predating the ``tools`` addition to ``get_trajectory`` will
    have an empty tools list — still valid, just less useful downstream.
    """
    trajectory = {
        "events": row.get("events") or [],
        "messages": row.get("messages") or [],
        "model_name": row.get("model_name"),
    }
    return {
        "session_id": row.get("session_id"),
        "model": row.get("model_name"),
        "timestamp": row.get("session_start_time"),
        "tags": tag_session(trajectory),
        "messages": row.get("messages") or [],
        "tools": row.get("tools") or [],
    }


def _upload_row(api, row: dict, day: date, target_repo: str, token: str) -> None:
    session_id = row["session_id"]
    path_in_repo = f"sft/{day.isoformat()}/{session_id}.jsonl"
    with tempfile.NamedTemporaryFile(mode="w", suffix=".jsonl", delete=False) as tmp:
        json.dump(row, tmp, ensure_ascii=False)
        tmp_path = tmp.name
    try:
        api.create_repo(
            repo_id=target_repo, repo_type="dataset", exist_ok=True, token=token,
        )
        api.upload_file(
            path_or_fileobj=tmp_path,
            path_in_repo=path_in_repo,
            repo_id=target_repo,
            repo_type="dataset",
            token=token,
            commit_message=f"Add SFT row {session_id}",
        )
    finally:
        try:
            os.unlink(tmp_path)
        except Exception:
            pass


def run_for_day(
    api, source_repo: str, target_repo: str, day: date, token: str,
) -> int:
    paths = _iter_session_files(api, source_repo, day, token)
    n = 0
    for path in paths:
        sess = _download_and_parse(source_repo, path, token)
        if not sess:
            continue
        sft_row = _reshape_to_sft(sess)
        if not sft_row.get("session_id"):
            continue
        try:
            _upload_row(api, sft_row, day, target_repo, token)
            n += 1
        except Exception as e:
            logger.warning("upload failed for %s: %s", sft_row["session_id"], e)
    logger.info("Exported %d sessions for %s", n, day)
    return n


def main(argv: list[str] | None = None) -> int:
    logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s")
    ap = argparse.ArgumentParser()
    ap.add_argument("--source", default="smolagents/ml-intern-sessions")
    ap.add_argument("--target", default="smolagents/ml-intern-sft")
    ap.add_argument(
        "--days", type=int, default=1,
        help="Number of trailing days to export (default: 1 = yesterday).",
    )
    ap.add_argument(
        "--date", type=str, default=None,
        help="Single YYYY-MM-DD to export; overrides --days.",
    )
    args = ap.parse_args(argv)

    token = (
        os.environ.get("HF_SFT_WRITE_TOKEN")
        or os.environ.get("HF_SESSION_UPLOAD_TOKEN")
        or os.environ.get("HF_TOKEN")
        or os.environ.get("HF_ADMIN_TOKEN")
    )
    if not token:
        logger.error(
            "No HF token found. Set one of: HF_SFT_WRITE_TOKEN, "
            "HF_SESSION_UPLOAD_TOKEN, HF_TOKEN, HF_ADMIN_TOKEN."
        )
        return 1

    from huggingface_hub import HfApi
    api = HfApi()

    if args.date:
        target_days = [date.fromisoformat(args.date)]
    else:
        today = datetime.now(timezone.utc).date()
        target_days = [today - timedelta(days=i) for i in range(1, args.days + 1)]

    total = 0
    for day in target_days:
        total += run_for_day(api, args.source, args.target, day, token)
    logger.info("Total exported: %d sessions", total)
    return 0


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