feat: add compare, trends routes, embedder service, and phase5 tests
This commit is contained in:
@@ -139,6 +139,13 @@ async def delete_papers_by_date_range(
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{"paper_id": paper_id},
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)
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# 1.5 Phase 5: 从 ChromaDB 删除语义索引
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try:
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from app.services.embedder import delete_paper
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delete_paper(arxiv_id)
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except Exception:
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logger.warning("Failed to delete %s from ChromaDB", arxiv_id, exc_info=True)
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# 2. 删除本地文件 data/papers/{arxiv_id}/
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paper_dir = _PAPERS_DIR / arxiv_id
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if paper_dir.exists():
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@@ -0,0 +1,314 @@
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"""ChromaDB 语义搜索服务 — embedding 生成、索引管理、相似查询。"""
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from __future__ import annotations
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import logging
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from pathlib import Path
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import httpx
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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.models import Paper
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logger = logging.getLogger(__name__)
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# ── 单例客户端和 collection ─────────────────────────────────────────────
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_client = None
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_collection = None
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def _chroma_dir() -> Path:
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return Path(settings.CHROMA_DIR)
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def init_chroma() -> None:
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"""CHROMA_ENABLED=true 时初始化 ChromaDB 持久客户端和 collection。"""
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global _client, _collection
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if not settings.CHROMA_ENABLED:
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logger.debug("ChromaDB disabled, skip init")
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return
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if _client is not None:
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return
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try:
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import chromadb
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chroma_path = _chroma_dir()
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chroma_path.mkdir(parents=True, exist_ok=True)
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_client = chromadb.PersistentClient(path=str(chroma_path))
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_collection = _get_or_create_collection()
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logger.info("ChromaDB initialized at %s", chroma_path)
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except Exception:
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logger.exception("Failed to initialize ChromaDB")
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_client = None
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_collection = None
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def _get_or_create_collection():
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"""获取或创建 papers_embeddings collection，维度不匹配时记录日志并跳过。"""
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import chromadb
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try:
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col = _client.get_collection("papers_embeddings")
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logger.info("ChromaDB collection 'papers_embeddings' loaded, count=%d", col.count())
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return col
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except Exception:
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pass
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col = _client.create_collection(
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name="papers_embeddings",
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metadata={"hnsw:space": "cosine"},
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)
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logger.info("ChromaDB collection 'papers_embeddings' created")
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return col
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def get_collection():
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"""返回当前 collection，未初始化则返回 None。"""
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if not settings.CHROMA_ENABLED:
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return None
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if _collection is None:
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init_chroma()
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return _collection
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# ── Embedding API 调用 ──────────────────────────────────────────────────
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def _get_embedding(text: str) -> list[float] | None:
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"""调用 EMBED_API_BASE 的 embedding API 生成向量。
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POST /v1/embeddings, model=EMBED_MODEL
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校验返回向量长度 == EMBED_DIMENSIONS
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失败时返回 None 并记录日志。
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"""
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if not settings.EMBED_API_BASE or not settings.EMBED_MODEL:
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logger.warning("EMBED_API_BASE or EMBED_MODEL not configured, skip embedding")
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return None
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url = f"{settings.EMBED_API_BASE.rstrip('/')}/v1/embeddings"
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headers = {"Content-Type": "application/json"}
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if settings.EMBED_API_KEY:
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headers["Authorization"] = f"Bearer {settings.EMBED_API_KEY}"
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payload = {
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"model": settings.EMBED_MODEL,
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"input": text,
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}
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try:
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with httpx.Client(timeout=settings.HTTP_TIMEOUT_SECONDS) as client:
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resp = client.post(url, json=payload, headers=headers)
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resp.raise_for_status()
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data = resp.json()
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vec = data["data"][0]["embedding"]
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if settings.EMBED_DIMENSIONS > 0 and len(vec) != settings.EMBED_DIMENSIONS:
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logger.warning(
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"Embedding dimension mismatch: expected=%d got=%d, skip",
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settings.EMBED_DIMENSIONS,
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len(vec),
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)
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return None
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return vec
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except Exception:
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logger.exception("Embedding API call failed")
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return None
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# ── 索引文本拼接 ────────────────────────────────────────────────────────
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def _build_index_text(paper: Paper, summary_dict: dict | None) -> str:
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"""拼接高信号字段为一段文本用于 embedding。"""
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parts: list[str] = []
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if paper.title_zh:
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parts.append(paper.title_zh)
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if paper.title_en:
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parts.append(paper.title_en)
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if paper.tags:
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tag_str = " ".join(t.tag for t in paper.tags)
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if tag_str:
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parts.append(tag_str)
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if summary_dict:
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for key in ("one_line", "motivation_problem", "method_key_idea"):
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val = summary_dict.get(key)
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if val:
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parts.append(val)
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return " ".join(parts)
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# ── 单篇索引 ────────────────────────────────────────────────────────────
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def index_paper(paper_id: str, texts_dict: dict | None = None) -> bool:
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"""将单篇论文写入 ChromaDB 语义索引。
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Args:
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paper_id: arxiv_id
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texts_dict: 可选的预拼接字段 dict，包含 title_zh, title_en, tags, one_line 等
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如果为 None，则从 DB 加载。
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Returns:
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True 表示成功，False 表示失败或跳过。
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"""
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col = get_collection()
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if col is None:
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return False
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try:
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# 如果没传 texts_dict，从 DB 加载
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if texts_dict is None:
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from app.database import SessionLocal
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db = SessionLocal()
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try:
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paper = (
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db.query(Paper)
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.filter(Paper.arxiv_id == paper_id)
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.options(joinedload(Paper.tags), joinedload(Paper.summary))
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.first()
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)
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if not paper:
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logger.warning("Paper %s not found for indexing", paper_id)
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return False
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summary_dict = None
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if paper.summary:
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summary_dict = {
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"one_line": paper.summary.one_line or "",
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"motivation_problem": paper.summary.motivation_problem or "",
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"method_key_idea": paper.summary.method_key_idea or "",
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}
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index_text = _build_index_text(paper, summary_dict)
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arxiv_id = paper.arxiv_id
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title_zh = paper.title_zh or ""
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paper_date = paper.paper_date.isoformat() if paper.paper_date else ""
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finally:
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db.close()
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else:
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index_text = " ".join(
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v for v in texts_dict.values() if isinstance(v, str) and v
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)
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arxiv_id = texts_dict.get("arxiv_id", paper_id)
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title_zh = texts_dict.get("title_zh", "")
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paper_date = texts_dict.get("paper_date", "")
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if not index_text.strip():
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logger.warning("Empty index text for %s, skip", paper_id)
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return False
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vec = _get_embedding(index_text)
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if vec is None:
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return False
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col.upsert(
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ids=[arxiv_id],
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embeddings=[vec],
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metadatas=[{"arxiv_id": arxiv_id, "title_zh": title_zh, "paper_date": paper_date}],
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)
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logger.info("Indexed paper %s in ChromaDB", arxiv_id)
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return True
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except Exception:
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logger.exception("Failed to index paper %s in ChromaDB", paper_id)
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return False
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# ── 批量索引 ────────────────────────────────────────────────────────────
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def index_batch(paper_ids: list[str]) -> dict:
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"""批量索引论文，单篇失败不影响其他。
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Returns:
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{"total": int, "success": int, "failed": int}
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"""
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if not paper_ids:
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return {"total": 0, "success": 0, "failed": 0}
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col = get_collection()
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if col is None:
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return {"total": len(paper_ids), "success": 0, "failed": len(paper_ids)}
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success = 0
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failed = 0
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for pid in paper_ids:
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if index_paper(pid):
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success += 1
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else:
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failed += 1
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logger.info("Batch index: total=%d success=%d failed=%d", len(paper_ids), success, failed)
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return {"total": len(paper_ids), "success": success, "failed": failed}
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# ── 删除 ────────────────────────────────────────────────────────────────
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def delete_paper(paper_id: str) -> bool:
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"""从 ChromaDB 删除论文索引。
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Args:
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paper_id: arxiv_id
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"""
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col = get_collection()
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if col is None:
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return False
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try:
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col.delete(ids=[paper_id])
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logger.info("Deleted paper %s from ChromaDB", paper_id)
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return True
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except Exception:
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logger.exception("Failed to delete paper %s from ChromaDB", paper_id)
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return False
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# ── 相似查询 ────────────────────────────────────────────────────────────
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def search_similar(query_text: str, top_k: int = 20) -> list[dict]:
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"""语义相似搜索。
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Args:
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query_text: 查询文本
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top_k: 返回前 K 个结果
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Returns:
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[{"arxiv_id": str, "distance": float}, ...]
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"""
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col = get_collection()
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if col is None:
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return []
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try:
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vec = _get_embedding(query_text)
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if vec is None:
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return []
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results = col.query(
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query_embeddings=[vec],
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n_results=min(top_k, col.count()) if col.count() > 0 else top_k,
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include=["metadatas", "distances"],
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)
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if not results["ids"] or not results["ids"][0]:
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return []
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items = []
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for i, arxiv_id in enumerate(results["ids"][0]):
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dist = results["distances"][0][i] if results["distances"] else 0.0
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items.append({"arxiv_id": arxiv_id, "distance": dist})
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return items
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except Exception:
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logger.exception("ChromaDB search_similar failed")
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return []
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@@ -1,15 +1,19 @@
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"""FTS5 全文搜索服务 — 关键词 + 标签筛选，命中片段高亮，分页。"""
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"""搜索服务 — FTS5 关键词搜索 + ChromaDB 语义搜索，命中片段高亮，分页。"""
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from __future__ import annotations
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import logging
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import math
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import re
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from sqlalchemy import text
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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.models import Paper
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logger = logging.getLogger(__name__)
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# ── 输入清洗 ──────────────────────────────────────────────────────────
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# FTS5 查询语法中的特殊字符，用户输入时需要移除
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@@ -41,8 +45,9 @@ def search_papers(
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sort: str = "relevance",
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page: int = 1,
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page_size: int = 20,
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mode: str = "keyword",
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) -> dict:
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"""FTS5 搜索论文。
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"""搜索论文，支持 keyword (FTS5) 和 semantic (ChromaDB) 两种模式。
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返回::
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{
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@@ -51,8 +56,14 @@ def search_papers(
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"total": int,
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"page": int,
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"total_pages": int,
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"distances": dict[str, float], # arxiv_id → distance (仅 semantic)
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}
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"""
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# ── semantic 模式 ──
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if mode == "semantic" and settings.CHROMA_ENABLED and query:
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return _search_semantic(db, query, tag, sort, page, page_size)
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# ── keyword 模式（默认）──
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match_expr = _sanitize_query(query) if query else None
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# ── 无关键词 + 无标签 → 空结果 ──
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@@ -63,6 +74,7 @@ def search_papers(
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"total": 0,
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"page": page,
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"total_pages": 0,
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"distances": {},
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}
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# ── 构建条件性 JOIN 和 WHERE 片段 ──
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@@ -146,6 +158,75 @@ def _search_with_fts(
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"total": total,
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"page": page,
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"total_pages": math.ceil(total / page_size) if total else 0,
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"distances": {},
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}
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def _search_semantic(
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db: Session,
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query: str,
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tag: str | None,
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sort: str,
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page: int,
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page_size: int,
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) -> dict:
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"""ChromaDB 语义搜索，失败时回退到 FTS5。"""
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try:
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from app.services.embedder import search_similar
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top_k = page_size * 3 # 多取一些用于 tag 过滤
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candidates = search_similar(query, top_k=top_k)
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except Exception:
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logger.exception("Semantic search failed, falling back to keyword")
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candidates = []
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if not candidates:
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# 回退到 FTS5
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return _search_with_fts(
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db,
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_sanitize_query(query) or query,
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"JOIN paper_tags pt ON pt.paper_id = p.id" if tag else "",
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"AND pt.tag = :tag" if tag else "",
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{"tag": tag} if tag else {},
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sort, page, page_size, (page - 1) * page_size,
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)
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# 按 arxiv_id 从 DB 加载完整数据
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arxiv_ids = [c["arxiv_id"] for c in candidates]
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distance_map = {c["arxiv_id"]: c["distance"] for c in candidates}
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papers_query = (
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db.query(Paper)
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.filter(Paper.arxiv_id.in_(arxiv_ids))
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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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joinedload(Paper.bookmark),
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joinedload(Paper.reading_status),
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)
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)
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if tag:
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papers_query = papers_query.filter(Paper.tags.any(tag=tag))
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papers = papers_query.all()
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# 按语义距离排序
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id_order = {aid: idx for idx, aid in enumerate(arxiv_ids)}
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papers.sort(key=lambda p: id_order.get(p.arxiv_id, 999))
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# 分页
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total = len(papers)
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start = (page - 1) * page_size
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page_papers = papers[start:start + page_size]
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return {
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"results": page_papers,
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"snippets": {},
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"total": total,
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"page": page,
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"total_pages": math.ceil(total / page_size) if total else 0,
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"distances": distance_map,
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}
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@@ -187,6 +268,7 @@ def _search_tag_only(
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"total": total,
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"page": page,
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"total_pages": math.ceil(total / page_size) if total else 0,
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"distances": {},
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}
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@@ -359,6 +359,127 @@ def _cleanup_tmp(arxiv_id: str) -> None:
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logger.warning("Failed to clean tmp for %s", arxiv_id, exc_info=True)
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# ── LaTeX 图片提取（Phase 5）───────────────────────────────────────────
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_INCLUDEGRAPHICS_RE = re.compile(
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r"\\includegraphics\s*(?:\[[^\]]*\])?\s*\{([^}]+)\}", re.MULTILINE
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||||
)
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_IMAGE_EXTS = {".png", ".jpg", ".jpeg", ".gif", ".svg", ".pdf", ".eps"}
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async def _extract_images_from_source(arxiv_id: str, tmp_source: Path | None = None) -> int:
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||||
"""从 LaTeX 源码中提取图片文件。
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||||
|
||||
流程：
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||||
1. 下载源码 zip 到 data/tmp/{arxiv_id}/source/
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||||
2. 扫描 .tex 文件中的 \\includegraphics
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||||
3. 复制图片到 data/papers/{arxiv_id}/images/
|
||||
4. 清理源码临时文件
|
||||
|
||||
Returns:
|
||||
提取的图片数量
|
||||
"""
|
||||
tmp_source = _tmp_dir(arxiv_id) / "source"
|
||||
images_dest = _paper_dir(arxiv_id) / "images"
|
||||
|
||||
try:
|
||||
# 下载源码 zip（如果还没下载）
|
||||
if not tmp_source.exists():
|
||||
source_url = f"https://arxiv.org/e-print/{arxiv_id}"
|
||||
await _download_source_zip(arxiv_id, source_url, tmp_source)
|
||||
|
||||
if not tmp_source.exists():
|
||||
return 0
|
||||
|
||||
# 扫描 .tex 文件，收集图片路径
|
||||
image_paths: set[str] = set()
|
||||
for tex_file in tmp_source.rglob("*.tex"):
|
||||
try:
|
||||
content = tex_file.read_text(encoding="utf-8", errors="replace")
|
||||
for match in _INCLUDEGRAPHICS_RE.finditer(content):
|
||||
img_path = match.group(1).strip()
|
||||
image_paths.add(img_path)
|
||||
except Exception:
|
||||
continue
|
||||
|
||||
if not image_paths:
|
||||
return 0
|
||||
|
||||
# 查找并复制图片
|
||||
images_dest.mkdir(parents=True, exist_ok=True)
|
||||
copied = 0
|
||||
for img_rel in image_paths:
|
||||
# 尝试在源码目录中找到文件
|
||||
for ext in ("", ".png", ".jpg", ".jpeg", ".gif", ".pdf", ".eps"):
|
||||
candidate = tmp_source / (img_rel + ext)
|
||||
if candidate.is_file():
|
||||
dest_name = candidate.name
|
||||
# 避免文件名冲突
|
||||
dest = images_dest / dest_name
|
||||
if dest.exists():
|
||||
stem = dest.stem
|
||||
suffix = dest.suffix
|
||||
dest = images_dest / f"{stem}_{copied}{suffix}"
|
||||
shutil.copy2(candidate, dest)
|
||||
copied += 1
|
||||
break
|
||||
|
||||
if copied > 0:
|
||||
logger.info("Extracted %d images from source for %s", copied, arxiv_id)
|
||||
return copied
|
||||
|
||||
except Exception:
|
||||
logger.warning("Failed to extract images for %s", arxiv_id, exc_info=True)
|
||||
return 0
|
||||
|
||||
|
||||
async def _download_source_zip(
|
||||
arxiv_id: str, source_url: str, dest_dir: Path
|
||||
) -> None:
|
||||
"""下载 arXiv 源码并解压。"""
|
||||
import zipfile
|
||||
|
||||
dest_dir.mkdir(parents=True, exist_ok=True)
|
||||
zip_path = _tmp_dir(arxiv_id) / "source.zip"
|
||||
|
||||
transport = None
|
||||
if settings.http_proxy:
|
||||
transport = httpx.AsyncHTTPTransport(proxy=settings.http_proxy)
|
||||
|
||||
try:
|
||||
async with httpx.AsyncClient(
|
||||
timeout=settings.HTTP_TIMEOUT_SECONDS,
|
||||
headers={"User-Agent": settings.HTTP_USER_AGENT},
|
||||
transport=transport,
|
||||
follow_redirects=True,
|
||||
) as client:
|
||||
resp = await client.get(source_url)
|
||||
resp.raise_for_status()
|
||||
zip_path.write_bytes(resp.content)
|
||||
except Exception as exc:
|
||||
logger.debug("Failed to download source for %s: %s", arxiv_id, exc)
|
||||
return
|
||||
|
||||
try:
|
||||
with zipfile.ZipFile(zip_path, "r") as zf:
|
||||
zf.extractall(dest_dir)
|
||||
logger.debug("Extracted source for %s", arxiv_id)
|
||||
except zipfile.BadZipFile:
|
||||
# 可能是 tar.gz
|
||||
import tarfile
|
||||
try:
|
||||
with tarfile.open(zip_path, "r:*") as tf:
|
||||
tf.extractall(dest_dir)
|
||||
logger.debug("Extracted source (tar) for %s", arxiv_id)
|
||||
except Exception:
|
||||
logger.warning("Cannot extract source for %s", arxiv_id)
|
||||
except Exception:
|
||||
logger.warning("Cannot extract source for %s", arxiv_id, exc_info=True)
|
||||
finally:
|
||||
if zip_path.exists():
|
||||
zip_path.unlink()
|
||||
|
||||
|
||||
# ── 单篇总结 ────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
@@ -441,6 +562,30 @@ async def _do_summarize_one(db: Session, paper: Paper) -> dict:
|
||||
status.raw_output_saved = True
|
||||
db.commit()
|
||||
|
||||
# Phase 5: LaTeX 图片提取（可选增强，失败不影响总结）
|
||||
try:
|
||||
await _extract_images_from_source(arxiv_id)
|
||||
except Exception:
|
||||
logger.warning("Failed to extract images for %s", arxiv_id, exc_info=True)
|
||||
|
||||
# Phase 5: 同步写入语义索引（失败仅 log）
|
||||
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)
|
||||
|
||||
logger.info("Summarize done: %s quality=%s", arxiv_id, quality)
|
||||
return {"arxiv_id": arxiv_id, "status": "done", "quality": quality}
|
||||
|
||||
|
||||
Reference in New Issue
Block a user