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- # -*- coding: utf-8 -*-
- """搜索 + 评估 · 任意 query → 多渠道搜索去重 → LLM 逐帖评估 → search_data 表
- ================================================================================
- 引擎函数全部只读复用 search_and_evaluate.py(搜索/去重/转写/评估/英平台翻译)。
- 用法(一般由 server.py 起子进程调):
- python pipeline/search_eval.py --query-id q0004 --query "AI 人像 图片 生成 怎么做"
- python pipeline/search_eval.py --query-id q0005 --query "GPT image2 评测" \
- --synonyms "GPT image2 测评,GPT image2 实测" --platforms xhs,gzh --max-count 10
- """
- import argparse
- import asyncio
- import json
- import sys
- from pathlib import Path
- PROJECT_ROOT = Path(__file__).resolve().parents[3] # …/Agent
- sys.path.insert(0, str(PROJECT_ROOT))
- from dotenv import load_dotenv
- load_dotenv()
- from examples.process_pipeline.script.search_eval.search_and_evaluate import (
- search_all, evaluate_posts, transcribe_video_posts, build_query_overrides,
- )
- from examples.process_pipeline.script.llm_evaluate_sources import (
- build_eval_llm_call, EVAL_MODELS, DEFAULT_EVAL_MODEL,
- )
- HERE = Path(__file__).resolve().parent
- MW = HERE.parent
- sys.path.insert(0, str(MW))
- import db
- async def run(args):
- phrasings = [args.query] + [s.strip() for s in (args.synonyms or "").split(",") if s.strip()]
- # 去重保序
- seen, uniq = set(), []
- for q in phrasings:
- if q not in seen:
- seen.add(q); uniq.append(q)
- phrasings = uniq
- platforms = [p.strip() for p in args.platforms.split(",") if p.strip()]
- eval_llm, eval_model_id = build_eval_llm_call(args.eval_model)
- print(f"▶ {args.query_id} query={args.query!r} 措辞={phrasings} 渠道={platforms}")
- overrides = await build_query_overrides(platforms, phrasings, eval_llm, eval_model_id)
- sources = await search_all(platforms, phrasings, args.max_count,
- args.max_concurrent, query_overrides=overrides)
- print(f"🔎 去重后 {len(sources)} 帖")
- if not sources:
- print("❌ 搜索无结果"); return 1
- try:
- from examples.process_pipeline.script.extract_sources import _convert_timestamps
- _convert_timestamps(sources)
- except Exception:
- pass
- if not args.no_transcribe:
- n = await transcribe_video_posts(sources, concurrency=args.max_concurrent)
- if n:
- print(f"🎙️ 视频转写 {n} 条")
- cost = 0.0
- if not args.no_eval:
- sources, cost = await evaluate_posts(
- sources, "", eval_llm, eval_model_id, args.max_concurrent,
- include_images=not args.no_images, max_images=args.max_images,
- image_mode=args.image_mode, query=args.query,
- )
- for s in sources:
- s.pop("_image_data_urls", None)
- n = db.upsert_search_posts(args.query_id, args.query, sources)
- print(f"🗄️ search_data 入库 {n} 行 · 评估成本 ${cost:.4f}")
- out_dir = MW / "runs" / "search"
- out_dir.mkdir(parents=True, exist_ok=True)
- (out_dir / f"{args.query_id}.json").write_text(json.dumps({
- "query_id": args.query_id, "query": args.query, "phrasings": phrasings,
- "platforms": platforms, "total": len(sources), "results": sources,
- }, ensure_ascii=False, indent=2), encoding="utf-8")
- return 0
- def main():
- p = argparse.ArgumentParser(description="搜索+评估 → search_data")
- p.add_argument("--query-id", required=True, help="如 q0004(server 自动分配)")
- p.add_argument("--query", required=True, help="基准 query(评估锚点)")
- p.add_argument("--synonyms", default="", help="逗号分隔的同义措辞(可选)")
- p.add_argument("--platforms", default="xhs,gzh")
- p.add_argument("--max-count", type=int, default=10)
- p.add_argument("--eval-model", default=DEFAULT_EVAL_MODEL, choices=list(EVAL_MODELS))
- p.add_argument("--max-concurrent", type=int, default=3)
- p.add_argument("--max-images", type=int, default=4)
- p.add_argument("--image-mode", choices=["url", "base64"], default="url")
- p.add_argument("--no-transcribe", action="store_true")
- p.add_argument("--no-eval", action="store_true")
- p.add_argument("--no-images", action="store_true")
- args = p.parse_args()
- raise SystemExit(asyncio.run(run(args)))
- if __name__ == "__main__":
- main()
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