daily-paper/app/services/summary_persister.py

"""AI 总结持久化 — DB 写入、文件保存、FTS 索引、图片提取、ChromaDB 索引。"""

from __future__ import annotations

import logging
from sqlalchemy.orm import Session

from app.models import (
    Paper,
    PaperSummary,
    PaperTag,
    SummaryState,
)
from app.services.derived import reindex_paper_fts
from app.services.pdf_downloader import paper_dir
from app.services.schemas import (
    SummarySchema,
    assess_quality,
    flatten_for_db,
)
from app.services.summary_generator import _classify_error
from app.utils import TMP_DIR, truncate_error, utc_now

logger = logging.getLogger(__name__)


# ── FTS5 文本构建 ───────────────────────────────────────────────────────


def _build_fts_summary_text(schema: SummarySchema) -> str:
    """拼接用于 FTS5 索引的总结文本。"""
    parts = [
        schema.one_line or "",
        schema.motivation.problem or "",
        schema.motivation.goal or "",
        schema.method.overview or "",
        schema.method.key_idea or "",
        schema.results.main_findings or "",
    ]
    return " ".join(p for p in parts if p)


# ── DB 更新 ─────────────────────────────────────────────────────────────


def _update_summary_in_db(
    db: Session,
    paper: Paper,
    schema: SummarySchema,
    quality: str,
    raw_output: str,
) -> None:
    """将校验后的总结写入 DB：paper_summaries + papers + paper_tags + FTS5。"""
    # 1. paper_summaries：upsert
    existing = db.get(PaperSummary, paper.id)
    flat = flatten_for_db(schema)
    if existing:
        for k, v in flat.items():
            setattr(existing, k, v)
    else:
        db.add(PaperSummary(paper_id=paper.id, **flat))

    # 2. papers 表
    paper.title_zh = schema.title_zh
    paper.summary_quality = quality
    p_dir = paper_dir(paper.arxiv_id)
    paper.summary_path = str(p_dir / "summary.json")
    paper.raw_output_path = str(p_dir / "raw_output.txt")

    # 3. AI 标签
    existing_tag_names = {t.tag for t in paper.tags}
    for tag_name in schema.tags:
        if tag_name not in existing_tag_names:
            db.add(PaperTag(paper_id=paper.id, tag=tag_name, source="ai"))
            existing_tag_names.add(tag_name)

    # 4. FTS5 派生索引
    db.flush()
    reindex_paper_fts(db, paper)

    db.commit()
    logger.info("DB updated: paper=%s quality=%s", paper.arxiv_id, quality)


# ── 文件操作 ────────────────────────────────────────────────────────────


def _save_files(arxiv_id: str, schema: SummarySchema | None, raw_output: str) -> None:
    d = paper_dir(arxiv_id)
    d.mkdir(parents=True, exist_ok=True)
    if schema:
        (d / "summary.json").write_text(
            schema.model_dump_json(ensure_ascii=False, indent=2),
            encoding="utf-8",
        )
    (d / "raw_output.txt").write_text(raw_output, encoding="utf-8")


# ── 失败处理 ────────────────────────────────────────────────────────────


def _handle_summary_failure(
    db: Session,
    paper: Paper,
    exc: Exception,
    raw_output: str,
) -> dict:
    """记录失败：保存 raw_output、重试计数、错误分类。"""
    from app.config import settings

    error_type = _classify_error(exc)
    logger.error(
        "Summarize failed: %s error_type=%s %s",
        paper.arxiv_id,
        error_type,
        truncate_error(exc),
    )

    status = paper.summary_status
    if raw_output:
        _save_files(paper.arxiv_id, None, raw_output)
        status.raw_output_saved = True

    status.retry_count = (status.retry_count or 0) + 1
    status.error_type = error_type
    status.error = truncate_error(exc, limit=2000)

    if status.retry_count >= settings.SUMMARY_MAX_RETRIES + 1:
        status.status = SummaryState.PERMANENT_FAILURE
    else:
        status.status = SummaryState.PENDING

    status.completed_at = utc_now()
    db.commit()

    return {
        "arxiv_id": paper.arxiv_id,
        "status": "failed",
        "error_type": error_type,
        "error": truncate_error(exc),
        "retry_count": status.retry_count,
    }


# ── 持久化 ──────────────────────────────────────────────────────────────


def _persist_summary(
    db: Session, paper: Paper, json_data: dict, raw_output: str
) -> str:
    """Pydantic 校验 → 质量评估 → 保存文件 → 更新 DB → 返回 quality。"""
    import time as _time

    arxiv_id = paper.arxiv_id

    _t0 = _time.monotonic()
    schema = SummarySchema.model_validate(json_data)
    quality = assess_quality(schema)
    _t1 = _time.monotonic()

    _save_files(arxiv_id, schema, raw_output)
    _t2 = _time.monotonic()

    _update_summary_in_db(db, paper, schema, quality, raw_output)
    _t3 = _time.monotonic()

    # 状态 → done
    paper.summary_status.status = SummaryState.DONE
    paper.summary_status.quality = quality
    paper.summary_status.completed_at = utc_now()
    paper.summary_status.raw_output_saved = True
    db.commit()
    _t4 = _time.monotonic()

    logger.info(
        "  [%s] persist: pydantic=%.2fs  文件=%.2fs  DB写入=%.2fs  状态commit=%.2fs",
        arxiv_id,
        _t1 - _t0,
        _t2 - _t1,
        _t3 - _t2,
        _t4 - _t3,
    )

    # 触发性增强（失败不影响总结）
    _t5 = _time.monotonic()
    _maybe_extract_images(arxiv_id, schema)
    _t6 = _time.monotonic()
    _maybe_index_chroma(arxiv_id, paper, schema)
    _t7 = _time.monotonic()

    logger.info(
        "  [%s] 后处理: 图片提取=%.2fs  ChromaDB=%.2fs",
        arxiv_id,
        _t6 - _t5,
        _t7 - _t6,
    )

    return quality


# ── 清理 ────────────────────────────────────────────────────────────────


def _cleanup_old_images(db: Session, paper: Paper) -> None:
    """清理旧的图片文件和 figures_json，避免重新总结时残留。"""
    arxiv_id = paper.arxiv_id
    images_dir = paper_dir(arxiv_id) / "images"
    if images_dir.exists():
        for old_file in images_dir.iterdir():
            if (
                old_file.suffix.lower() in (".png", ".jpg", ".jpeg", ".gif", ".svg")
                or old_file.name == "manifest.json"
            ):
                old_file.unlink(missing_ok=True)
    # 清除数据库中的 figures_json
    if paper.summary and paper.summary.figures_json:
        paper.summary.figures_json = None
        db.commit()


# ── 触发性增强 ──────────────────────────────────────────────────────────


def _maybe_extract_images(arxiv_id: str, schema: SummarySchema) -> None:
    """从 PDF 提取图片和表格（失败不影响总结）。

    两阶段流水线：
    1. PicoDet 检测 + 渲染截图（通用标签）
    2. 用 summary 的 figures ID 在 PDF 中搜索定位 → 重命名
    """
    try:
        from app.services.pdf_image_extractor import (
            extract_images_from_pdf,
            label_images_by_summary,
        )

        pdf_path = TMP_DIR / arxiv_id / "paper.pdf"
        extract_images_from_pdf(arxiv_id, pdf_path)
        if schema.figures:
            label_images_by_summary(arxiv_id, schema.figures, pdf_path)
    except Exception:
        logger.warning("Failed to extract images for %s", arxiv_id, exc_info=True)


def _maybe_index_chroma(arxiv_id: str, paper: Paper, schema: SummarySchema) -> None:
    """写入 ChromaDB 语义索引（失败不影响总结）。"""
    try:
        from app.services.embedder import index_paper

        texts_dict = {
            "arxiv_id": arxiv_id,
            "title_zh": schema.title_zh or "",
            "title_en": paper.title_en or "",
            "tags": " ".join(t.tag for t in paper.tags) if paper.tags else "",
            "one_line": schema.one_line or "",
            "motivation_problem": schema.motivation.problem or "",
            "method_key_idea": schema.method.key_idea or "",
            "paper_date": paper.paper_date.isoformat() if paper.paper_date else "",
        }
        index_paper(arxiv_id, texts_dict)
    except Exception:
        logger.warning("Failed to index paper %s in ChromaDB", arxiv_id, exc_info=True)