Function start_reading_reports_task

deployments/desktop/shared/agents.py:2753–2818

(
    *,
    user_id: str,
    push_id: str,
    paper_numbers: Iterable[Any],
    write_feishu: Optional[bool] = None,
    response_language: str = "zh",
)

    with _READING_TASK_LOCK:
        task = _READING_TASKS.get(task_id)
        if task:
            task["status"] = "failed" if errors and not completed_docs else "completed"
            task["progress_phase"] = task["status"]
            task["completed_docs"] = completed_docs
            task["errors"] = errors
            task["completed_at"] = _task_timestamp()
            task["updated_at"] = task["completed_at"]


def start_reading_reports_task(
    *,
    user_id: str,
    push_id: str,
    paper_numbers: Iterable[Any],
    write_feishu: Optional[bool] = None,
    response_language: str = "zh",
) -> Dict[str, Any]:
    push = db_ops.get_push_papers(push_id)
    if not push or not push.get("papers"):
        raise ValueError(f"Push not found: {push_id}")
    papers = list(push["papers"])
    selected = _unique_ints(paper_numbers, maximum=len(papers))
    selected_papers = reading_agent.resolve_selected_papers(selected, papers)
    docs: List[Dict[str, Any]] = []
    language = _normalize_response_language(response_language)
    for paper in selected_papers:
        normalized_paper = reading_agent._normalize_paper(paper)  # noqa: SLF001
        report_path = _reading_placeholder_path(user_id, normalized_paper)
        _write_reading_placeholder(
            user_id=user_id,
            paper=normalized_paper,
            report_path=report_path,
            status="queued",
            steps=["已加入后台精读队列。", _reading_language_notice(language), "刷新本页面可查看最新进度。"],
            response_language=language,
        )
        docs.append(
            {
                "title": f"[精读] {normalized_paper.get('title', 'Unknown')[:80]}",
                "url": None,
                "doc_token": None,
                "report_path": str(report_path),
                "pdf_path": normalized_paper.get("pdf_path"),
                "paper": normalized_paper,
                "paper_raw": normalized_paper,
                "report_payload": {"generation_provider": "paperflow", "generation_model": "background-reading-task"},
            }
        )

    task_id = f"reading_{datetime.now().strftime('%Y%m%d_%H%M%S')}_{uuid4().hex[:8]}"
    now = _task_timestamp()
    task: Dict[str, Any] = {
        "task_id": task_id,
        "kind": "reading_reports",
        "status": "queued",
        "progress_phase": "queued",
        "user_id": user_id,