98 lines
3.0 KiB
Python
98 lines
3.0 KiB
Python
"""动态编译唯一命令行入口。"""
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from __future__ import annotations
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import argparse
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import os
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import sys
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from pathlib import Path
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from scripts.provider_router import parse_model_reference
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from .pipeline import run_pipeline
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from .scoring.agentrm import (
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DEFAULT_BATCH_SIZE,
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DEFAULT_CONCURRENCY,
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DEFAULT_MAX_LENGTH,
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DEFAULT_RM_API_URL,
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DEFAULT_TIMEOUT,
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)
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def _provider_model(value: str) -> str:
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try:
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return parse_model_reference(value).value
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except ValueError as exc:
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raise argparse.ArgumentTypeError(str(exc)) from exc
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def build_parser() -> argparse.ArgumentParser:
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parser = argparse.ArgumentParser(
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prog="python -m scripts.dynamic_compile.fast",
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description="从一组 BenchFlow 历史轨迹生成一个动态编译候选 Skill。",
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)
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parser.add_argument("--traces", required=True, type=Path, help="BenchFlow 轨迹目录")
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parser.add_argument("--skill", required=True, type=Path, help="含根 SKILL.md 的 Skill 包")
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parser.add_argument("--score-output", type=Path, help="评分阶段产物目录")
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parser.add_argument("--output", type=Path, help="分析与候选 Skill 产物目录")
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parser.add_argument(
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"--model",
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required=True,
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type=_provider_model,
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help="所有外部模型调用使用的 provider/model",
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)
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parser.add_argument("--max-parallel", type=int, default=3)
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parser.add_argument(
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"--rm-api-url", default=os.environ.get("RM_API_URL", DEFAULT_RM_API_URL)
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)
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parser.add_argument(
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"--rm-max-length",
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type=int,
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default=os.environ.get("RM_MAX_LENGTH", str(DEFAULT_MAX_LENGTH)),
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)
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parser.add_argument(
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"--rm-timeout",
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type=float,
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default=os.environ.get("RM_TIMEOUT", str(DEFAULT_TIMEOUT)),
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)
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parser.add_argument(
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"--rm-concurrency",
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type=int,
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default=os.environ.get("RM_CONCURRENCY", str(DEFAULT_CONCURRENCY)),
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)
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parser.add_argument(
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"--rm-batch-size",
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type=int,
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default=os.environ.get("RM_BATCH_SIZE", str(DEFAULT_BATCH_SIZE)),
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)
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parser.add_argument(
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"--force",
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action="store_true",
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help="复用有效评分/Map 缓存，强制重建 Reduce、Patch 和候选 Skill",
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)
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return parser
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def main(argv: list[str] | None = None) -> int:
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args = build_parser().parse_args(argv)
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try:
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result = run_pipeline(
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args.traces,
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args.skill,
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score_output=args.score_output,
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output=args.output,
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model=args.model,
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max_parallel=args.max_parallel,
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rm_api_url=args.rm_api_url,
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rm_max_length=args.rm_max_length,
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rm_timeout=args.rm_timeout,
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rm_concurrency=args.rm_concurrency,
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rm_batch_size=args.rm_batch_size,
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force=args.force,
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)
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except (OSError, RuntimeError, ValueError) as exc:
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print(f"error: {exc}", file=sys.stderr)
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return 2
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print(result)
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return 0
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