520 lines
16 KiB
Python
520 lines
16 KiB
Python
"""AI 总结编排服务 — 协调 PDF 下载、pi CLI 调用、JSON 校验、DB 写入、语义索引。"""
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from __future__ import annotations
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import json
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import logging
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import shutil
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from datetime import datetime, timezone
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from pathlib import Path
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from pydantic import ValidationError
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from sqlalchemy import select
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from sqlalchemy.orm import Session, joinedload
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from app.config import settings
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from app.database import SessionLocal
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from app.models import (
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CrawlLog,
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Paper,
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PaperSummary,
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PaperTag,
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SummaryStatus,
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TaskLock,
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)
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from app.services.image_extractor import extract_images_from_source
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from app.services.pdf_downloader import (
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PdfDownloadError,
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cleanup_tmp,
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download_pdf,
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paper_dir,
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)
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from app.services.pi_client import (
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JsonNotFoundError,
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PiProcessError,
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PiTimeoutError,
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call_pi,
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extract_json,
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write_meta_json,
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)
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from app.services.schemas import (
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SummarySchema,
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assess_quality,
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classify_validation_error,
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flatten_for_db,
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)
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from app.utils import PAPERS_DIR, release_lock
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logger = logging.getLogger(__name__)
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# ── 错误分类 ────────────────────────────────────────────────────────────
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def _classify_error(exc: Exception) -> str:
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"""将异常映射到 error_type 枚举值。"""
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if isinstance(exc, PdfDownloadError):
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return "pdf_download_failed"
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if isinstance(exc, PiTimeoutError):
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return "timeout"
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if isinstance(exc, PiProcessError):
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return "process_error"
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if isinstance(exc, JsonNotFoundError):
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return "json_not_found"
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if isinstance(exc, json.JSONDecodeError):
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return "json_invalid"
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if isinstance(exc, ValidationError):
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return classify_validation_error(exc)
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return "unknown"
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# ── FTS5 文本构建 ───────────────────────────────────────────────────────
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def _build_fts_summary_text(schema: SummarySchema) -> str:
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"""拼接用于 FTS5 索引的总结文本。"""
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parts = [
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schema.one_line or "",
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schema.motivation.problem or "",
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schema.motivation.goal or "",
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schema.method_overview if hasattr(schema, "method_overview") else "",
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schema.method.overview or "",
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schema.method.key_idea or "",
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" ".join(schema.results.main_findings or []),
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]
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return " ".join(p for p in parts if p)
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# ── DB 更新 ─────────────────────────────────────────────────────────────
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def _update_summary_in_db(
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db: Session,
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paper: Paper,
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schema: SummarySchema,
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quality: str,
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raw_output: str,
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) -> None:
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"""将校验后的总结写入 DB：paper_summaries + papers + paper_tags + FTS5。"""
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from sqlalchemy import text
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now = datetime.now(timezone.utc)
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# 1. paper_summaries：upsert
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existing = db.get(PaperSummary, paper.id)
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flat = flatten_for_db(schema)
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if existing:
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for k, v in flat.items():
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setattr(existing, k, v)
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else:
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db.add(PaperSummary(paper_id=paper.id, **flat))
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# 2. papers 表
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paper.title_zh = schema.title_zh
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paper.summary_quality = quality
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p_dir = paper_dir(paper.arxiv_id)
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paper.summary_path = str(p_dir / "summary.json")
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paper.raw_output_path = str(p_dir / "raw_output.txt")
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# 3. AI 标签
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existing_tag_names = {t.tag for t in paper.tags}
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for tag_name in schema.tags:
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if tag_name not in existing_tag_names:
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db.add(PaperTag(paper_id=paper.id, tag=tag_name, source="ai"))
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existing_tag_names.add(tag_name)
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# 4. FTS5 更新
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summary_text = _build_fts_summary_text(schema)
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db.execute(
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text(
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"UPDATE papers_fts SET title_zh=:title_zh, summary_text=:summary_text "
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"WHERE rowid=:paper_id"
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),
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{
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"title_zh": schema.title_zh,
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"summary_text": summary_text,
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"paper_id": paper.id,
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},
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)
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db.commit()
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logger.info("DB updated: paper=%s quality=%s", paper.arxiv_id, quality)
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# ── 文件操作 ────────────────────────────────────────────────────────────
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def _save_files(arxiv_id: str, schema: SummarySchema, raw_output: str) -> None:
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"""保存 summary.json 和 raw_output.txt。"""
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d = paper_dir(arxiv_id)
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d.mkdir(parents=True, exist_ok=True)
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(d / "summary.json").write_text(
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schema.model_dump_json(ensure_ascii=False, indent=2),
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encoding="utf-8",
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)
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(d / "raw_output.txt").write_text(raw_output, encoding="utf-8")
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def _save_raw_output_only(arxiv_id: str, raw_output: str) -> None:
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"""仅保存 raw_output.txt（失败时）。"""
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d = paper_dir(arxiv_id)
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d.mkdir(parents=True, exist_ok=True)
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(d / "raw_output.txt").write_text(raw_output, encoding="utf-8")
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# ── 单篇总结 ────────────────────────────────────────────────────────────
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async def summarize_one(
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db: Session,
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paper: Paper,
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semaphore: asyncio.Semaphore | None = None,
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*,
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force: bool = False,
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) -> dict:
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"""总结单篇论文的完整流程。"""
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import asyncio
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arxiv_id = paper.arxiv_id
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# 获取或创建 summary_status
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if not paper.summary_status:
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db.add(SummaryStatus(paper_id=paper.id, status="pending"))
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db.commit()
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db.refresh(paper)
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status = paper.summary_status
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# 跳过已完成的（除非 force）
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if status.status == "done" and not force:
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return {"arxiv_id": arxiv_id, "status": "skipped", "reason": "already_done"}
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# 跳过 permanent_failure（除非 force）
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if status.status == "permanent_failure" and not force:
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return {
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"arxiv_id": arxiv_id,
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"status": "skipped",
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"reason": "permanent_failure",
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}
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if semaphore:
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await semaphore.acquire()
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try:
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return await _do_summarize_one(db, paper)
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finally:
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if semaphore:
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semaphore.release()
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async def _do_summarize_one(db: Session, paper: Paper) -> dict:
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"""实际的单篇总结执行（在 semaphore 保护下）。"""
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import asyncio
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arxiv_id = paper.arxiv_id
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status = paper.summary_status
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now = datetime.now(timezone.utc)
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# 状态 → processing
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status.status = "processing"
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status.started_at = now
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db.commit()
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raw_output = ""
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try:
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# 写 meta.json
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meta_path = write_meta_json(paper)
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# 下载 PDF
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await download_pdf(arxiv_id, paper.pdf_url)
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# 调用 pi
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raw_output = await call_pi(meta_path, Path("data/tmp") / arxiv_id / "paper.pdf")
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# 提取 JSON
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json_data = extract_json(raw_output)
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# Pydantic 校验
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schema = SummarySchema.model_validate(json_data)
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# 质量评估
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quality = assess_quality(schema)
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# 保存文件
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_save_files(arxiv_id, schema, raw_output)
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# 更新 DB
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_update_summary_in_db(db, paper, schema, quality, raw_output)
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# 状态 → done
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status.status = "done"
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status.quality = quality
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status.completed_at = datetime.now(timezone.utc)
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status.raw_output_saved = True
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db.commit()
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# Phase 5: LaTeX 图片提取（可选增强，失败不影响总结）
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try:
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await extract_images_from_source(arxiv_id)
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except Exception:
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logger.warning("Failed to extract images for %s", arxiv_id, exc_info=True)
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# Phase 5: 同步写入语义索引（失败仅 log）
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try:
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from app.services.embedder import index_paper
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texts_dict = {
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"arxiv_id": arxiv_id,
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"title_zh": schema.title_zh or "",
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"title_en": paper.title_en or "",
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"tags": " ".join(t.tag for t in paper.tags) if paper.tags else "",
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"one_line": schema.one_line or "",
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"motivation_problem": schema.motivation_problem or "",
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"method_key_idea": schema.method_key_idea or "",
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"paper_date": paper.paper_date.isoformat() if paper.paper_date else "",
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}
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index_paper(arxiv_id, texts_dict)
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except Exception:
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logger.warning(
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"Failed to index paper %s in ChromaDB", arxiv_id, exc_info=True
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)
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logger.info("Summarize done: %s quality=%s", arxiv_id, quality)
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return {"arxiv_id": arxiv_id, "status": "done", "quality": quality}
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except Exception as exc:
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error_type = _classify_error(exc)
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logger.error(
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"Summarize failed: %s error_type=%s %s",
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arxiv_id,
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error_type,
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str(exc)[:200],
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)
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# 保存 raw_output（如果有）
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if raw_output:
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_save_raw_output_only(arxiv_id, raw_output)
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status.raw_output_saved = True
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# 重试逻辑
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status.retry_count = (status.retry_count or 0) + 1
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status.error_type = error_type
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status.error = str(exc)[:2000]
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if status.retry_count >= settings.SUMMARY_MAX_RETRIES + 1:
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status.status = "permanent_failure"
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else:
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status.status = "pending"
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status.completed_at = datetime.now(timezone.utc)
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db.commit()
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return {
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"arxiv_id": arxiv_id,
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"status": "failed",
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"error_type": error_type,
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"error": str(exc)[:200],
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"retry_count": status.retry_count,
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}
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finally:
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cleanup_tmp(arxiv_id)
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# ── 单篇入口 ────────────────────────────────────────────────────────────
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async def summarize_single(
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db: Session,
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arxiv_id: str,
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*,
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force: bool = True,
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_session_factory=None,
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) -> dict:
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"""单篇总结入口（供 admin 路由和 CLI 调用）。
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_session_factory: 可选的 session 工厂，测试时注入内存 DB 的 session。
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"""
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paper = (
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db.query(Paper)
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.filter(Paper.arxiv_id == arxiv_id)
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.options(
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joinedload(Paper.authors),
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joinedload(Paper.tags),
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joinedload(Paper.summary_status),
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)
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.first()
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)
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if not paper:
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return {"status": "not_found", "arxiv_id": arxiv_id}
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make_session = _session_factory or SessionLocal
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# 每篇用独立 session 避免并发问题
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paper_db = make_session()
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try:
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paper_in_new_session = (
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paper_db.query(Paper)
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.filter(Paper.arxiv_id == arxiv_id)
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.options(
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joinedload(Paper.authors),
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joinedload(Paper.tags),
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joinedload(Paper.summary_status),
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)
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.first()
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)
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result = await summarize_one(paper_db, paper_in_new_session, force=force)
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finally:
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paper_db.close()
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return result
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# ── 批量总结 ────────────────────────────────────────────────────────────
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async def summarize_batch(
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db: Session,
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arxiv_ids: list[str] | None = None,
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*,
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_session_factory=None,
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) -> dict:
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"""批量总结入口。arxiv_ids=None 时处理所有 pending 论文。
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_session_factory: 可选的 session 工厂，测试时注入内存 DB 的 session。
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"""
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import asyncio
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now = datetime.now(timezone.utc)
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# TaskLock 防重入
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lock = TaskLock(
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task="summarize",
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lock_key="batch",
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status="running",
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owner="summarize_batch",
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acquired_at=now,
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)
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try:
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db.add(lock)
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db.commit()
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except Exception:
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db.rollback()
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logger.warning("Summarize batch already running (lock conflict)")
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return {"status": "conflict", "error": "summarize batch already running"}
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# CrawlLog
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log_entry = CrawlLog(
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task="summarize",
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status="running",
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started_at=now,
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)
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db.add(log_entry)
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db.commit()
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try:
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# 查询待总结论文
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query = db.query(Paper).options(
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joinedload(Paper.authors),
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joinedload(Paper.tags),
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joinedload(Paper.summary_status),
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)
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if arxiv_ids:
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query = query.filter(Paper.arxiv_id.in_(arxiv_ids))
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else:
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# 只处理 pending 或 failed（可重试的）
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query = query.join(SummaryStatus).filter(
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SummaryStatus.status.in_(["pending", "failed"])
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)
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papers = query.all()
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total = len(papers)
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logger.info("Summarize batch: %d papers to process", total)
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if total == 0:
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log_entry.status = "success"
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log_entry.papers_found = 0
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log_entry.papers_new = 0
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log_entry.completed_at = datetime.now(timezone.utc)
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release_lock(db, lock)
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return {
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"status": "success",
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"done": 0,
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"failed": 0,
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"skipped": 0,
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"total": 0,
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}
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# 并发控制
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semaphore = asyncio.Semaphore(settings.SUMMARY_CONCURRENCY)
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make_session = _session_factory or SessionLocal
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async def _process_paper(paper: Paper) -> dict:
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paper_db = make_session()
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try:
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p = (
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paper_db.query(Paper)
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.filter(Paper.id == paper.id)
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.options(
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joinedload(Paper.authors),
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joinedload(Paper.tags),
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joinedload(Paper.summary_status),
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)
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.first()
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)
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return await summarize_one(paper_db, p, semaphore)
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finally:
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paper_db.close()
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results = await asyncio.gather(
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*[_process_paper(p) for p in papers],
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return_exceptions=True,
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)
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# 统计结果
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done = 0
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failed = 0
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skipped = 0
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for r in results:
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if isinstance(r, Exception):
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logger.error("Unexpected error in batch: %s", r)
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failed += 1
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elif isinstance(r, dict):
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if r.get("status") == "done":
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done += 1
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elif r.get("status") == "skipped":
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skipped += 1
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else:
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failed += 1
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log_entry.status = "success" if failed == 0 else "failed"
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log_entry.papers_found = total
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log_entry.papers_new = done
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log_entry.completed_at = datetime.now(timezone.utc)
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db.commit()
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logger.info(
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"Summarize batch done: total=%d done=%d failed=%d skipped=%d",
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total,
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done,
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failed,
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skipped,
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)
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return {
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"status": "success" if failed == 0 else "partial",
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"total": total,
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"done": done,
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"failed": failed,
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"skipped": skipped,
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}
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except Exception as exc:
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logger.exception("Summarize batch failed")
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log_entry.status = "failed"
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log_entry.error = str(exc)[:2000]
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log_entry.completed_at = datetime.now(timezone.utc)
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db.commit()
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return {"status": "failed", "error": str(exc)}
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finally:
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release_lock(db, lock)
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