feat: IMAP mail sync with thread-to-contact matching (PRD §6.1)
Real IMAP connection via imapflow library: - Connects to IMAP server (IMAPFlow, TLS on port 993) - Fetches recent messages (configurable limit, default 20) - Extracts: from, fromEmail, subject, date, snippet (200 chars) - Thread-to-contact matching (PRD §6.1): 1. Match sender email against persons table 2. If no person match, extract domain and match against company.website 3. Returns matchedCompany + matchedPerson for each email - Audit-logged (action: crm.mailsync:imap) - Zod validated (host, port, user, password, folder, limit) - 502 on IMAP connection failure with detail - 400 on validation failure Tested: invalid creds → 502 'IMAP connection failed', missing host → 400
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#!/usr/bin/env python3
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from __future__ import annotations
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import argparse
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import json
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import sys
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from pathlib import Path
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from typing import Any
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import yaml
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if __package__ in {None, ""}:
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sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
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from scripts.common import write_json
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from scripts.constants import DEFAULT_TOP_K
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from scripts.rec5_api import (
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build_api_request,
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call_rec5_api,
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normalize_rec5_paper,
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resolve_rec5_url,
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resolve_token,
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)
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def _clean_text(value: Any) -> str:
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return " ".join(str(value or "").split()).strip()
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def _load_yaml(path: Path | None) -> dict[str, Any]:
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if path is None or not path.exists():
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return {}
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return yaml.safe_load(path.read_text(encoding="utf-8")) or {}
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def _stage_error(stage: str, detail: Any) -> RuntimeError:
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compact = _clean_text(str(detail)) or "unknown_error"
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return RuntimeError(f"{stage}_failed:{compact}")
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def _format_papers_as_markdown(papers: list[dict[str, Any]], profile_topics: list[str]) -> str:
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"""Render recommended papers as Markdown for the host to display."""
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lines: list[str] = []
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topic_hint = " / ".join(profile_topics[:5]) if profile_topics else ""
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header = f"为你推荐 {len(papers)} 篇相关论文"
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if topic_hint:
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header += f"（研究方向：{topic_hint}）"
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lines.append(header)
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for idx, paper in enumerate(papers, start=1):
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lines.append("")
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lines.append("---")
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lines.append("")
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title = _clean_text(paper.get("title") or "")
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url = _clean_text(paper.get("aminer_paper_url") or paper.get("abs_url") or "")
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title_line = f"**{idx}. [{title}]({url})**" if url else f"**{idx}. {title}**"
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lines.append(title_line)
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year = paper.get("year")
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keywords = paper.get("keywords") or []
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authors = paper.get("authors") or []
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summary = _clean_text(paper.get("summary") or "")
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meta_parts: list[str] = []
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if year:
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meta_parts.append(f"年份：{year}")
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if keywords:
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meta_parts.append(f"关键词：{' / '.join(str(k) for k in keywords[:5])}")
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if meta_parts:
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lines.append(" | ".join(meta_parts))
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if authors:
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author_str = "、".join(str(a) for a in authors[:6])
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if len(authors) > 6:
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author_str += " et al."
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lines.append(f"作者：{author_str}")
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if summary:
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truncated = summary if len(summary) <= 300 else summary[:300].rstrip() + "…"
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lines.append("")
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lines.append(truncated)
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return "\n".join(lines)
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def _topics_from_paper_titles(paper_titles: list[str]) -> list[str]:
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"""Extract simple topic hints from paper titles when no explicit topics provided."""
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topics: list[str] = []
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seen: set[str] = set()
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for title in paper_titles:
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cleaned = _clean_text(title)
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if not cleaned:
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continue
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candidate = cleaned.split(":")[0].strip() if ":" in cleaned else cleaned
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if candidate and candidate.casefold() not in seen and len(candidate) <= 80:
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seen.add(candidate.casefold())
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topics.append(candidate)
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return topics[:5]
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def run_pipeline(
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*,
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output_dir: Path,
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config: dict[str, Any],
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aminer_author_id: str,
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topics: list[str],
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scholar_name: str,
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scholar_org: str,
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paper_titles: list[str],
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papers_file: str,
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free_text: str,
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language_sort: str = "",
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size: int = 0,
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) -> dict[str, Any]:
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output_dir.mkdir(parents=True, exist_ok=True)
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token = resolve_token(config)
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if not token:
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raise _stage_error("auth", "AMINER_API_KEY is not set")
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all_topics = list(topics)
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if paper_titles and not all_topics and not scholar_name and not aminer_author_id:
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all_topics = _topics_from_paper_titles(paper_titles)
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search_config = config.get("search") if isinstance(config.get("search"), dict) else {}
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if size <= 0:
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size = max(1, min(int(search_config.get("top_k") or DEFAULT_TOP_K), 20))
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# language_sort only when user explicitly passed language_sort: zh|en in the trigger (see SKILL).
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sort_for_api = _clean_text(language_sort) if _clean_text(language_sort) in {"zh", "en"} else ""
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api_request = build_api_request(
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aminer_author_id=aminer_author_id,
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author_name=scholar_name,
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author_org=scholar_org,
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topics=all_topics,
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size=size,
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language_sort=sort_for_api,
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)
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try:
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result = call_rec5_api(api_request, token=token, url=resolve_rec5_url(config))
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raw_papers = result["papers"]
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api_analyzed_topics = result.get("analyzed_topics") or []
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except Exception as exc:
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raise _stage_error("recall", exc) from exc
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if not raw_papers:
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raise _stage_error("recall", "no_papers_returned")
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papers = [normalize_rec5_paper(p) for p in raw_papers]
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papers = [p for p in papers if _clean_text(p.get("title"))]
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profile_topics = api_analyzed_topics or all_topics or ([scholar_name] if scholar_name else [])
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summarized_payload = {
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"status": "success",
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"profile_topics": profile_topics,
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"profile_name": scholar_name or "",
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"profile_source": "scholar_path" if (aminer_author_id or scholar_name) else "topic_path",
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"papers": papers,
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}
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mode = "scholar_path" if (aminer_author_id or scholar_name) else "topic_path"
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write_json(
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output_dir / "request_context.json",
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{
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"aminer_author_id": aminer_author_id,
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"input_topics": topics,
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"topics": all_topics,
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"scholar_name": scholar_name,
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"scholar_org": scholar_org,
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"paper_titles": paper_titles,
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"papers_file": papers_file,
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"free_text": free_text,
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"language_sort": language_sort,
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"api_request": api_request,
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},
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)
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summarized_path = output_dir / "papers_summarized.json"
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write_json(summarized_path, summarized_payload)
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markdown_text = _format_papers_as_markdown(papers, profile_topics)
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return {
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"status": "success",
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"summarized_path": str(summarized_path),
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"final_response": "TEXT",
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"reply_text": markdown_text,
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"mode": mode,
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"paper_count": len(papers),
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}
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def main() -> int:
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parser = argparse.ArgumentParser(description="Run aminer-daily-paper pipeline via rec5 API.")
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parser.add_argument("--base-dir", type=Path, default=Path(__file__).resolve().parents[1])
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parser.add_argument("--config", type=Path, default=None)
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parser.add_argument("--output-dir", type=Path, default=Path(__file__).resolve().parents[1] / "outputs")
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parser.add_argument("--aminer-author-id", default="")
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parser.add_argument("--topics", nargs="*", default=[])
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parser.add_argument("--scholar-name", default="")
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parser.add_argument("--scholar-org", default="")
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parser.add_argument("--paper-title", action="append", dest="paper_titles", default=[])
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parser.add_argument("--papers-file", default="")
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parser.add_argument("--free-text", default="")
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parser.add_argument("--language-sort", default="")
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parser.add_argument("--size", type=int, default=0)
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args = parser.parse_args()
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resolved_config = args.config.resolve() if args.config else None
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config = _load_yaml(resolved_config)
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result = run_pipeline(
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output_dir=args.output_dir.resolve(),
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config=config,
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aminer_author_id=args.aminer_author_id,
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topics=list(args.topics or []),
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scholar_name=args.scholar_name,
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scholar_org=args.scholar_org,
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paper_titles=list(args.paper_titles or []),
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papers_file=args.papers_file,
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free_text=args.free_text,
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language_sort=args.language_sort,
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size=args.size,
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)
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print(json.dumps(result, ensure_ascii=False, indent=2))
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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