forked from admin/PlantAI-rag-new
feat(aqua): figure chain dual-key generalization (PMCID/DOI)
- answer_composer: prefer [[FIG:PMCID]], fallback [[FIG:DOI:fullDOI]] - sse_relay: marker regex accepts DOI form; DOI key passed through to figures - figures: local index dual-key (pmcid + doi via registry paper_id/doi); resolve_figures recognizes DOI form -> local first, EPMC search (DOI->PMCID) fallback; silent degrade semantics unchanged - normalize/humanizer: block protection covers [[FIG:DOI:...]] form - plant KB unaffected: PMCID path byte-for-byte behavior kept; retrieval chain untouched; 52 sdk tests pass Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
Claude Fable 5
@@ -209,7 +209,7 @@ If the provided data are insufficient, say so directly.
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--- Figure Marker ---
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When citing a paper for the first time, you may insert a marker [[FIG:PMCID]] on its own line immediately after the paragraph containing the citation, to indicate where a figure from that paper should be displayed. Use at most one marker per paper, at most 6 markers total. Do not write image URLs yourself; the system will resolve markers into figures.
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When citing a paper for the first time, you may insert a marker on its own line immediately after the paragraph containing the citation, to indicate where a figure from that paper should be displayed. Use at most one marker per paper, at most 6 markers total. Prefer [[FIG:PMCID]]; when the paper has no PMCID, use [[FIG:DOI:完整DOI]] (the full DOI string, e.g. [[FIG:DOI:10.1111/j.1365-2109.2010.02587.x]]). Do not write image URLs yourself; the system will resolve markers into figures.
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{correction_block}{dialogue_block}{web_block}Now answer the following question:
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+91
-20
@@ -46,8 +46,8 @@ PMC_IMAGE_BASE = "https://pmc.ncbi.nlm.nih.gov/articles/instance/{num}/bin/{file
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# BFF 代理端点路径（前端经此访问图片，内网可达 + 磁盘缓存）
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PROXY_PATH = "/api/figures/proxy?pmcid={pmcid}&url={url}"
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_cache: dict[str, dict[str, Any]] = {} # pmcid -> {ts, figures, license}
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_local_index: dict[str, list[dict]] | None = None # pmcid数字 -> 本地图片清单
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_cache: dict[str, dict[str, Any]] = {} # 键(pmcid 或 doi 原串) -> {ts, figures, license}
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_local_index: dict[str, list[dict]] | None = None # 双键: pmcid数字 与 doi 原串 -> 本地图片清单
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EXTERNAL_TIMEOUT = 15.0 # 176 实测 EBI 2-8s 波动，5s 必超时（2026-09-12 S2 部署质检）
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CACHE_TTL = 3600.0
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@@ -58,20 +58,39 @@ def _pmcid_num(pmcid: str) -> str:
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return m.group(1) if m else pmcid.strip()
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def _norm_doi_key(doi: str) -> str:
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"""DOI 形态键归一：去 'doi:' 前缀与首尾空白，保留原样大小写（DOI 大小写不敏感，存两键）。"""
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value = (doi or "").strip()
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if value.lower().startswith("doi:"):
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value = value[len("doi:"):]
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return value.strip()
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def _doi_key(pmcid_param: str) -> str | None:
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"""识别 DOI 形态入参（'DOI:...' 或裸 '10.xxxx/...'），返回归一化 doi；否则 None。"""
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value = _norm_doi_key(pmcid_param)
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if not value:
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return None
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if re.match(r"^10\.\d{4,9}/", value):
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return value
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return None
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# ---------------------------------------------------------------------------
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# 本地索引（懒构建）
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# ---------------------------------------------------------------------------
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def _build_local_index() -> dict[str, list[dict]]:
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"""扫描 methodology_upload_jobs 的 completed 任务，pmcid数字 -> 图片清单。
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无 registry 时跳过映射（返回空索引），不影响 PMC 兜底。"""
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"""扫描 methodology_upload_jobs 的 completed 任务，双键（pmcid数字 + doi 原串）
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-> 图片清单。无 registry 时跳过映射（返回空索引），不影响 PMC 兜底。"""
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global _local_index
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if _local_index is not None:
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return _local_index
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idx: dict[str, list[dict]] = {}
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try:
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# registry: pmcid -> paper_id(DOI风格)；job 目录名含 paper_id 前缀
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# registry: 双向映射 —— paper_id(DOI风格) <-> pmcid / doi
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pmcid_to_paper = {}
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doi_to_paper = {}
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if REGISTRY_PATH.exists():
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with REGISTRY_PATH.open(encoding="utf-8") as f:
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for line in f:
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@@ -82,8 +101,11 @@ def _build_local_index() -> dict[str, list[dict]]:
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rec = _json.loads(line)
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pmcid = rec.get("pmcid") or ""
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paper = rec.get("paper_id") or ""
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doi = _norm_doi_key(rec.get("doi") or "")
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if pmcid and paper:
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pmcid_to_paper[pmcid] = paper
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if doi and paper:
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doi_to_paper[doi] = paper
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if not MINERU_ROOT.is_dir():
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_local_index = idx
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return idx
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@@ -127,7 +149,13 @@ def _build_local_index() -> dict[str, list[dict]]:
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})
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if figures:
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figures.sort(key=lambda x: x["page_idx"])
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# 双键索引：pmcid 数字键 + doi 键（同一清单对象）
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idx[_pmcid_num(pmcid)] = figures
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paper_ref = pmcid_to_paper.get(pmcid)
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if paper_ref:
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for doi, paper in doi_to_paper.items():
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if paper == paper_ref or paper_ref.startswith(paper.split("_")[0]):
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idx[doi] = figures
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except Exception as exc: # 索引构建失败不阻断服务
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logger.warning("本地图片索引构建失败（降级为纯 PMC）: %s", exc)
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_local_index = idx
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@@ -243,19 +271,25 @@ async def _epmc_figures(client: httpx.AsyncClient, pmcid: str) -> tuple[list[dic
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# ---------------------------------------------------------------------------
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async def resolve_figures(pmcid: str, limit: int = 4) -> dict[str, Any]:
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"""按 PMCID 返回 {pmcid, license, figures:[{url,caption,source}]}。
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本地优先，PMC 兜底；缓存 TTL 1 小时。"""
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"""按 PMCID 或 DOI 形态入参返回 {pmcid, license, figures:[{url,caption,source}]}。
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- PMCID 形态（PMC123）：原路径不变 —— 本地双键索引 + PMC fullTextXML 兜底。
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- DOI 形态（DOI:10.xxx/... 或裸 10.xxx/...）：pmcid 参数填 DOI 原串传入，
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先查本地双键索引；未命中再经 EPMC search（DOI→PMCID）走原 PMC 兜底路径。
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本地优先，PMC 兜底；缓存 TTL 1 小时。失败静默降级为空清单。"""
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doi = _doi_key(pmcid)
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cache_key = doi if doi else pmcid
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now = time.monotonic()
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cached = _cache.get(pmcid)
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cached = _cache.get(cache_key)
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if cached and now - cached["ts"] < CACHE_TTL:
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return cached["data"]
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figures: list[dict] = []
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license_ = ""
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# 1. 本地优先
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# 1. 本地优先（双键索引：DOI 形态查 doi 键，PMCID 形态查 pmcid 数字键）
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idx = _build_local_index()
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local = idx.get(_pmcid_num(pmcid)) or []
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local = idx.get(doi or _pmcid_num(pmcid)) or []
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for f in local[:limit]:
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figures.append({
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"url": PROXY_PATH.format(pmcid=pmcid, url=quote(f["url"], safe="")),
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@@ -263,22 +297,59 @@ async def resolve_figures(pmcid: str, limit: int = 4) -> dict[str, Any]:
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"source": "local",
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})
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# 2. PMC 兜底（本地不足 limit 时补）
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# 2. PMC 兜底（本地不足 limit 时补；DOI 形态先经 EPMC search 换 PMCID）
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if len(figures) < limit:
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async with httpx.AsyncClient() as client:
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pmc_figs, license_ = await _epmc_figures(client, pmcid)
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for f in pmc_figs[: limit - len(figures)]:
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figures.append({
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"url": PROXY_PATH.format(pmcid=pmcid, url=quote(f["url"], safe="")),
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"caption": f["caption"],
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"source": "pmc",
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})
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fallback_id = pmcid
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if doi:
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fallback_id = await _doi_to_pmcid(doi) or ""
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if fallback_id:
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async with httpx.AsyncClient() as client:
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pmc_figs, license_ = await _epmc_figures(client, fallback_id)
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for f in pmc_figs[: limit - len(figures)]:
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figures.append({
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"url": PROXY_PATH.format(pmcid=pmcid, url=quote(f["url"], safe="")),
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"caption": f["caption"],
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"source": "pmc",
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})
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data = {"pmcid": pmcid, "license": license_, "figures": figures}
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_cache[pmcid] = {"ts": now, "data": data}
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_cache[cache_key] = {"ts": now, "data": data}
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return data
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async def _doi_to_pmcid(doi: str) -> str:
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"""EPMC search 用 DOI 查 PMCID（DOI 形态兜底）。失败返回空串（静默降级）。
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与 _epmc_figures 一致的冷连接重试：EBI 冷 TLS 握手偶发超时，重试一次。"""
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for attempt in (1, 2):
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try:
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async with httpx.AsyncClient() as client:
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r = await client.get(
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EPMC_SEARCH,
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params={
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"query": f"DOI:\"{doi}\"",
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"format": "json",
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"pageSize": 1,
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"resultType": "LITE",
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},
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timeout=EXTERNAL_TIMEOUT,
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)
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if r.status_code != 200:
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return ""
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res = r.json().get("resultList", {}).get("result", [])
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if not res:
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return ""
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pmcid = res[0].get("pmcid") or ""
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if pmcid:
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return pmcid.upper()
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return ""
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except Exception as exc:
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if attempt == 2:
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logger.info("EPMC DOI→PMCID 查询失败（%s）: %s", doi, exc)
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return ""
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return ""
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async def proxy_figure(pmcid: str, raw_url: str) -> tuple[bytes, str] | None:
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"""图片代理：本地文件直接读；外网图拉取并磁盘缓存。
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返回 (content_bytes, content_type)；失败返回 None。"""
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@@ -52,6 +52,7 @@ RULES: List[Tuple[str, str]] = [
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# 块级保护：整块跳过（不应用任何规则）
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_CODE_FENCE = re.compile(r"```[\s\S]*?```")
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_TABLE_ROW = re.compile(r"^\s*\|.*\|\s*$", re.MULTILINE)
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# 双键形态：[[FIG:PMC123]] 与 [[FIG:DOI:10.xxx/...]] 均为整块保护对象（2026-09-12）
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_FIG_MARKER = re.compile(r"\[\[FIG:[^\]]+\]\]")
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_IMG_MARKDOWN = re.compile(r"!\[[^\]]*\]\([^)]*\)")
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_HEADING = re.compile(r"^#{1,6}\s+.*$", re.MULTILINE)
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@@ -300,7 +300,8 @@ def normalize_qa_response(raw: dict[str, Any] | None) -> dict[str, Any]:
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# 图片注入（2026-08-28 图文并茂方案）
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# ---------------------------------------------------------------------------
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_FIG_MARKER = re.compile(r"\[\[FIG:([A-Za-z0-9]+)\]\]")
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# 双键形态：[[FIG:PMC123]]（原形态）与 [[FIG:DOI:10.xxx/...]]（2026-09-12 通用化）
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_FIG_MARKER = re.compile(r"\[\[FIG:([A-Za-z0-9]+|DOI:[^\]]+)\]\]")
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_MAX_FIGURES = 8
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@@ -309,13 +310,13 @@ def inject_figure_markdown(
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figures_map: dict[str, dict[str, Any]],
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base_url: str = "",
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) -> str:
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"""把 LLM 的 [[FIG:PMCID]] 标记替换为 markdown 图注块（纯同步函数）。
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"""把 LLM 的 [[FIG:PMCID]] / [[FIG:DOI:...]] 标记替换为 markdown 图注块（纯同步函数）。
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参数 figures_map: pmcid -> {"license": str, "figures": [{url, caption, source}]}
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参数 figures_map: 键为 PMCID（大写）或 DOI 原串 -> {"license": str, "figures": [...]}
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由调用方（sse_relay）预先异步解析后传入，本函数不做 IO，便于单测。
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规则：
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- 标记 → 该 PMCID 前 2 张图；无图删标记
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- 标记 → 该键对应前 2 张图；无图删标记
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- 兜底：无任何标记时，按引用 [PMID: xxx] 首次出现位置插入对应论文前 2 张图
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（pmcid 从 sources 的 paper_id/pmcid 推导）
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- 总图数上限 8，超出删除标记/跳过
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@@ -332,7 +333,7 @@ def inject_figure_markdown(
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for pmcid in markers:
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if inserted >= _MAX_FIGURES:
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break
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key = pmcid.upper()
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key = pmcid if pmcid.upper().startswith("DOI:") else pmcid.upper()
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data = figures_map.get(key) or figures_map.get(pmcid)
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figures = (data or {}).get("figures") or []
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take = min(2, len(figures), _MAX_FIGURES - inserted)
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@@ -544,13 +544,15 @@ async def relay_stream(
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async def _inject_figures_async(normalized: dict) -> dict:
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"""图文并茂（2026-08-28）：异步预取答案引用的论文图片，注入 markdown 图注块。
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流程：从 normalized 的 sources 提取 PMCID 清单 → 逐个 resolve_figures（本地优先
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PMC 兜底，缓存 1h）→ 组装 figures_map（含 pmid 供兜底路径）→ 调
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normalize.inject_figure_markdown 纯同步注入。无图/失败静默降级。
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流程：从 normalized 的 sources 提取 PMCID 清单 + 答案 [[FIG:PMCxxxx]] /
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[[FIG:DOI:10.xxx/...]] 标记（DOI 形态整体传给 resolve_figures，PMCID 原路径不变）
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→ 逐个 resolve_figures（本地优先 PMC 兜底，缓存 1h）→ 组装 figures_map
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（含 pmid 供兜底路径）→ 调 normalize.inject_figure_markdown 纯同步注入。
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无图/失败静默降级。
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预算控制（缺陷 #7，2026-09-10）：整体预取受 FIGURE_INJECT_BUDGET_MS（默认
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2500ms）硬截断，保证 complete 帧端到端延迟 ≤ 预算；PMCID 只取前 3 个；
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预算按 PMCID 均分，单篇 wait_for 截断。超时/失败仍静默降级——图片不影响
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2500ms）硬截断，保证 complete 帧端到端延迟 ≤ 预算；标记只取前 3 个；
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预算按标记均分，单篇 wait_for 截断。超时/失败仍静默降级——图片不影响
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答案主链，降级语义与修复前一致。
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"""
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from .figures import resolve_figures
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@@ -561,10 +563,12 @@ async def _inject_figures_async(normalized: dict) -> dict:
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if not answer or not sources:
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return normalized
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# 收集答案里引用的 PMCID（[[FIG:]] 标记 + sources 的 pmcid）
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# 收集答案里引用的图片标记：[[FIG:PMCxxxx]] 或 [[FIG:DOI:10.xxx/...]]
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# （[[FIG:DOI:...]] 形态把 DOI 原串直接传给 figures.resolve_figures，
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# 由其内部识别并走双键本地索引 + EPMC 兜底；/api/figures/{pmcid} 路由兼容不变。）
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import re
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marker_pmcids = re.findall(r"\[\[FIG:([A-Za-z0-9]+)\]\]", answer)
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marker_ids = re.findall(r"\[\[FIG:([A-Za-z0-9.:/_-]+)\]\]", answer)
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figures_map: dict = {}
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# 来源里 pmcid 优先（有 pmid 供兜底）
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for s in sources:
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@@ -573,11 +577,16 @@ async def _inject_figures_async(normalized: dict) -> dict:
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if not pmcid:
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continue
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figures_map.setdefault(pmcid, {"pmid": pmid, "figures": [], "license": ""})
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# 标记里的 PMCID 也加入（即使 sources 没有）
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for pmcid in marker_pmcids:
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figures_map.setdefault(pmcid.upper(), {"pmid": None, "figures": [], "license": ""})
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# 标记里的 PMCID / DOI 也加入（即使 sources 没有）
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for marker in marker_ids:
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upper = marker.upper()
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if upper.startswith("PMC"):
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figures_map.setdefault(upper, {"pmid": None, "figures": [], "license": ""})
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elif upper.startswith("DOI:"):
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doi_key = marker
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figures_map.setdefault(doi_key, {"pmid": None, "figures": [], "license": ""})
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# PMCID 裁 top 3（按出现顺序：sources 在前，标记补充在后）
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# 标记裁 top 3（按出现顺序：sources 在前，标记补充在后）
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pmcids = list(figures_map.keys())[:FIGURE_INJECT_MAX_PMCIDS]
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if not pmcids:
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base_url = "" # figures.resolve 已返回代理端点绝对路径，无需拼接
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