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https://github.com/bytedance/deer-flow.git
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63ce88f874
* add caller identity in replay e2e * make format * fix(replay-e2e): stabilize title caller replay * fix(replay-e2e): use captured caller without run manager --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
46 lines
1.7 KiB
Python
46 lines
1.7 KiB
Python
"""Turn a record-through-browser JSONL capture into a replay fixture.
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The recording gateway (``record_gateway.py``) appends ``{input_hash, output}``
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lines as the frontend drives a real run; the record spec writes a ``.meta.json``
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sidecar with ``{scenario, mode, prompt}``. This stitches them into the fixture
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the replay provider + tests consume.
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"""
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from __future__ import annotations
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import argparse
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import json
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from pathlib import Path
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def main() -> int:
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parser = argparse.ArgumentParser()
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parser.add_argument("--jsonl", required=True)
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parser.add_argument("--meta", required=True)
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parser.add_argument("--out", required=True)
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parser.add_argument("--model", default="gpt-5.5")
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args = parser.parse_args()
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turns = [json.loads(line) for line in Path(args.jsonl).read_text(encoding="utf-8").splitlines() if line.strip()]
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meta = json.loads(Path(args.meta).read_text(encoding="utf-8"))
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fixture = {
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"scenario": meta["scenario"],
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"mode": meta["mode"],
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"model": args.model,
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"prompt": meta["prompt"],
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"context": meta.get("context", {}),
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"turns": turns,
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}
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Path(args.out).write_text(json.dumps(fixture, ensure_ascii=False, indent=2), encoding="utf-8")
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print(f"wrote {len(turns)} turn(s) -> {args.out}")
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for index, turn in enumerate(turns):
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data = turn["output"].get("data", {})
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tool_calls = [tc.get("name") for tc in (data.get("tool_calls") or [])]
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caller = turn.get("caller", "legacy")
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print(f" turn {index}: caller={caller} hash={turn['input_hash'][:12]} tool_calls={tool_calls} content={str(data.get('content'))[:50]!r}")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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