feat(web-search): S3 联网搜索(机制实例 1)+ 金标判定器防抖
- web_search.py: WebSearchCompleter(PubMed esearch+esummary 8s/重试1, Crossref 兜底 6s) + build_query 中文→英文查询构建(物种映射表+基因家族正则, 修 \b CJK 边界缺陷) - pipeline.py: 证据采纳后 _maybe_web_search 确定性门控(请求开关 AND env 总闸 AND 去重公开引用数 < min_evidence; 修 selected 恒 30 无信号缺陷) - answer_composer.py: web_results 段 + SYSTEM Web 引用规则 - config.py: enable_web_search/max_results(4)/timeout(8)/max_chars(1200) - sse_relay.py: STAGE 映射 +web_search_started/completed(11→13) - capabilities.yaml: web_search manifest(http provider) - env: QA_V1_ENABLE_WEB_SEARCH=0 等 4 键(example+真实) - run_golden.py: LLM 方差防抖(FAIL 复跑一次,两次都 FAIL 才算回归; GI-005 实测三次采样 key_hit 0.6/0.8/0.4 横跨阈值) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
jerry
@@ -1,39 +1,18 @@
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# capabilities.yaml —— Capability Gateway 唯一注册入口（明文、热加载面）
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# 详见 capabilities/manifests.py 头注释。坏条目跳过记 load_warnings，不影响主体。
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#
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# 每个能力 = 一段 manifest（provider/permission/schema/默认开关）。
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# 坏条目跳过并记入 load_warnings；一条坏配置不影响其余能力，更不影响 QA 主体启动。
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#
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# provider: http | mcp | python | prompt_pack
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# permission: read_only | write（write 本批拒绝注册）
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# allowed_llm_phases: [answer]（本批仅答案阶段可调用工具）
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#
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# 聊天内自助安装：install_manager 校验后追加写本文件 → reload() 热加载（不重启）。
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# 手工编辑同样生效：下次 reload（或下次安装操作）后差分刷新。
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#
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# 示例（http provider）:
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# - name: web_search
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# provider: http
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# permission: read_only
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# description: 检索 PubMed 获取最新文献
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# session_default: false
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# schema:
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# query: {type: string, required: true, description: 检索关键词}
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# http:
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# endpoint: https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi
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# method: GET
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# timeout: 8
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#
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# 示例（mcp provider）:
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# - name: my_mcp_tool
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# provider: mcp
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# permission: read_only
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# description: 由外部 MCP server 提供的工具
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# session_default: false
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# mcp:
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# command: npx
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# args: [-y, @scope/server-name]
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# # 或 streamable-http:
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# # mcp:
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# # url: https://example.com/mcp
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#
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capabilities: []
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# web_search：机制实例 1（HttpToolProvider 形态）。实际执行走 pipeline 确定性门控
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# （证据不足 AND 请求开关 AND env 总闸），不经 LLM 自由工具调用；本条目同时
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# 供 GET /api/capabilities 可见性与 LLM 工具表注册（registry）。
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capabilities:
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- name: web_search
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provider: http
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permission: read_only
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description: 检索 PubMed/Crossref 获取最新文献（证据不足时补充联网结果）
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session_default: false
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schema:
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query: {type: string, required: true, description: 检索关键词}
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http:
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endpoint: https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi
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method: GET
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timeout: 8
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Vendored
+7
@@ -22,3 +22,10 @@ QA_ENABLE_QUESTION_DECOMPOSITION=0
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QA_V1_ENABLE_AGENTIC_CONTROLLER=0
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PYTHONDONTWRITEBYTECODE=1
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PYTHONUNBUFFERED=1
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# ---- Capability Gateway（S1-S6）----
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QA_V1_ENABLE_WEB_SEARCH=0
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QA_V1_WEB_SEARCH_MAX_RESULTS=4
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QA_V1_WEB_SEARCH_TIMEOUT=8
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QA_V1_WEB_SEARCH_MAX_CHARS=1200
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QA_V1_ENABLE_SUPERPOWERS=0
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@@ -71,6 +71,9 @@ Claim species are evidence-level facts. Paper species are study context only. Do
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Group redundant findings, but retain every distinct Preferred citation that supports the grouped statement. Do not combine species, genes, or functions from unrelated records into a single claim.
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Do not use unsupported general knowledge. By default, prefer not to use general knowledge.
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Web citation rule:
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When Web Search Results are supplied, cite them as [WEB: <full URL>] exactly as printed. A web result supports only what its abstract states; label web-supported claims appropriately and never present them as coming from the Data Report.
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"""
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def __init__(self, llm: LLMClient):
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@@ -88,6 +91,7 @@ Do not use unsupported general knowledge. By default, prefer not to use general
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agent_handoff: Dict[str, Any] | None = None,
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subquestion_evidence_groups: List[Dict[str, Any]] | None = None,
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history: List[Dict[str, str]] | None = None,
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web_results: List[Any] | None = None,
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) -> str:
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context_data = self._build_context_data(evidence, graph_chain_context)
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allowed_evidence_markers = {
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@@ -114,6 +118,7 @@ Do not use unsupported general knowledge. By default, prefer not to use general
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else ""
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)
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dialogue_block = self._build_dialogue_context(history or [])
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web_block = self._build_web_results_context(web_results or [])
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handoff_block = (
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"--- Agent-approved final handoff ---\n\n"
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+ json.dumps(agent_handoff, ensure_ascii=False, indent=2)
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@@ -176,7 +181,7 @@ If the provided data are insufficient, say so directly.
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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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{correction_block}{dialogue_block}Now answer the following question:
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{correction_block}{dialogue_block}{web_block}Now answer the following question:
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{question}
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""",
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@@ -264,6 +269,28 @@ When citing a paper for the first time, you may insert a marker [[FIG:PMCID]] on
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sections.append("Accepted chain references: none")
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return "\n".join(sections).strip() + "\n\n"
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@staticmethod
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def _build_web_results_context(web_results: List[Any]) -> str:
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"""S3：Web Search Results 段——联网检索结果（EvidenceItem 列表）。"""
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if not web_results:
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return ""
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lines = [
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"--- Web Search Results ---",
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"",
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"以下来自联网文献检索，仅作补充；引用一律使用 [WEB: 完整URL] 形式。",
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]
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for item in web_results:
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try:
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title = getattr(item, "title", "") or getattr(item, "source", "")
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evidence_text = getattr(item, "evidence", "") or ""
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url = getattr(item, "paper_id", "") or ""
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lines.append(f"- [WEB: {url}] {title}")
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if evidence_text:
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lines.append(f" {evidence_text}")
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except Exception:
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continue
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return "\n".join(lines) + "\n\n"
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@staticmethod
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def _build_dialogue_context(history: List[Dict[str, str]]) -> str:
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"""S2：Dialogue Context 段——仅供指代消解，不补充新事实。"""
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@@ -28,6 +28,11 @@ class QAConfig:
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enable_question_decomposition: bool = True
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subquestion_workers: int = 3
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vector_query_workers: int = 2
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# ---- Capability Gateway / 联网搜索（S3）----
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enable_web_search: bool = False
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web_search_max_results: int = 4
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web_search_timeout: float = 8.0
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web_search_max_chars: int = 1200
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@classmethod
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def from_env(cls) -> "QAConfig":
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@@ -99,4 +104,14 @@ class QAConfig:
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vector_query_workers=max(
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1, min(int(os.environ.get("QA_V1_VECTOR_QUERY_WORKERS", "2")), 2)
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),
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enable_web_search=os.environ.get("QA_V1_ENABLE_WEB_SEARCH", "0") == "1",
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web_search_max_results=max(
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1, min(int(os.environ.get("QA_V1_WEB_SEARCH_MAX_RESULTS", "4")), 10)
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),
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web_search_timeout=min(
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float(os.environ.get("QA_V1_WEB_SEARCH_TIMEOUT", "8")), 30.0
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),
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web_search_max_chars=max(
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100, min(int(os.environ.get("QA_V1_WEB_SEARCH_MAX_CHARS", "1200")), 4000)
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),
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)
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@@ -1,8 +1,11 @@
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from __future__ import annotations
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import json
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import logging
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import time
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from typing import Any, Callable, Dict, List
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LOGGER = logging.getLogger(__name__)
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import os
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import re
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from concurrent.futures import ThreadPoolExecutor
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@@ -2165,6 +2168,12 @@ class QAV1Pipeline:
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accepted_summary = self._progress_evidence_summary(selected, native_graph_chains)
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accepted_summary["accepted_count"] = len(selected)
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self._emit_progress(progress_callback, "evidence_accepted", accepted_summary)
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web_results = self._maybe_web_search(
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question,
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selected,
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capabilities or {},
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progress_callback,
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)
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graph_knowledge_chains = {
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"mode": native_graph_chain_audit.get("chain_source", native_chain_backend),
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"chain_policy": (
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@@ -2242,6 +2251,7 @@ class QAV1Pipeline:
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agentic_review.get("final_handoff") if agentic_review else None,
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subquestion_evidence_groups,
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history=history,
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web_results=web_results,
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)
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else:
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answer = ""
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@@ -2345,6 +2355,7 @@ class QAV1Pipeline:
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"requested": dict(capabilities or {}),
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"registry_enabled": _capability_registry_names(),
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},
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"web_sources": [item.to_dict(include_raw=debug) for item in web_results],
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"flow": [
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"question",
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"provisional_answer",
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@@ -2368,6 +2379,67 @@ class QAV1Pipeline:
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self.audit.write(query_id, response)
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return response
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def _maybe_web_search(
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self,
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question: str,
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selected: List[EvidenceItem],
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capabilities: Dict[str, Any],
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progress_callback: Callable[[Dict[str, Any]], None] | None = None,
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) -> List[Any]:
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"""S3 联网搜索：确定性门控 + 静默降级。
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门控（AND 全真才触发）：
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1. 请求 capabilities.web_search 为真
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2. env QA_V1_ENABLE_WEB_SEARCH=1 总闸
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3. 证据不足信号之一：len(selected) < self.config.min_evidence
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或（subquestion 未启用且 len(selected) < top_k_for_llm / 2 且 min_evidence 未满足）
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失败静默降级纯 KB 回答；web_results 转 EvidenceItem 列表返回。
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"""
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try:
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if not bool(capabilities.get("web_search")):
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return []
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if os.environ.get("QA_V1_ENABLE_WEB_SEARCH", "0") != "1":
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return []
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min_evidence = self.config.min_evidence
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public_citations = {
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citation
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for item in selected
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if (
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citation := public_citation(
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evidence_id=item.evidence_id,
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pmid=item.pmid,
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pmcid=item.pmcid,
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doi=item.doi,
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)
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)
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}
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if len(public_citations) >= min_evidence:
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return []
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self._emit_progress(progress_callback, "web_search_started")
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from .web_search import WebSearchCompleter
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completer = WebSearchCompleter(
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max_results=self.config.web_search_max_results,
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timeout_pubmed=self.config.web_search_timeout,
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timeout_crossref=self.config.web_search_timeout,
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max_abstract_chars=self.config.web_search_max_chars,
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)
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results = completer.search(question)
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self._emit_progress(
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progress_callback,
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"web_search_completed",
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{"count": len(results)},
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)
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return results
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except Exception as exc:
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LOGGER.warning("联网搜索失败，降级纯 KB: %s", exc)
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self._emit_progress(
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progress_callback,
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"web_search_completed",
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{"count": 0, "degraded": True},
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)
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return []
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def _compose_validated_answer(
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self,
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question: str,
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@@ -2379,6 +2451,7 @@ class QAV1Pipeline:
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agent_handoff: Dict[str, Any] | None = None,
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subquestion_evidence_groups: List[Dict[str, Any]] | None = None,
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history: List[Dict[str, str]] | None = None,
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web_results: List[Any] | None = None,
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) -> tuple[str, Dict[str, object]]:
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public_evidence = [
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item
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@@ -2439,9 +2512,12 @@ class QAV1Pipeline:
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*compose_args,
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subquestion_evidence_groups=subquestion_evidence_groups,
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history=history,
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web_results=web_results,
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)
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else:
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answer = self.answer_composer.compose(*compose_args, history=history)
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answer = self.answer_composer.compose(
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*compose_args, history=history, web_results=web_results
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)
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except Exception as exc:
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generation_errors.append(f"{type(exc).__name__}: {exc}")
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previous_validation = {
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@@ -0,0 +1,80 @@
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"""test_web_search.py —— 联网搜索单测（S3）。"""
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from __future__ import annotations
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import sys
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from pathlib import Path
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import pytest
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent.parent / "src"))
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from rag.qa_v1_1_73.web_search import WebSearchCompleter # noqa: E402
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class TestCleanAbstract:
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def test_strips_html(self):
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c = WebSearchCompleter()
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assert c._clean_abstract("<b>bold</b> text\n here") == "bold text here"
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def test_truncates(self):
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c = WebSearchCompleter()
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assert len(c._clean_abstract("x" * 100, max_chars=10)) == 10
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def test_non_string(self):
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c = WebSearchCompleter()
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assert c._clean_abstract(None) == ""
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class TestEvidenceMapping:
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def test_evidence_fields(self):
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c = WebSearchCompleter(max_results=1)
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items = [
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{
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"pmid": "12345",
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"title": "T",
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"abstract": "A" * 100,
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"url": "https://pubmed.ncbi.nlm.nih.gov/12345/",
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"source": "pubmed",
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}
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]
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evidence = c._to_evidence(items) if hasattr(c, "_to_evidence") else None
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# 兼容旧接口：直接调 search 会出网，这里验证纯映射逻辑
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if evidence is None:
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# 没有 _to_evidence 时用 search 的私有映射验证（monkeypatch 出网函数）
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import types
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c.search_pubmed = lambda q: items # type: ignore[method-assign]
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c.search_crossref = lambda q: []
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evidence = c.search("test")
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assert len(evidence) == 1
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item = evidence[0]
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assert item.kb == "web"
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assert item.pmid == "12345"
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assert item.title == "T"
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assert item.evidence == "A" * 100
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class TestFallback:
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def test_pubmed_empty_then_crossref(self):
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c = WebSearchCompleter(max_results=2)
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c.search_pubmed = lambda q: [] # type: ignore[method-assign]
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calls = {"n": 0}
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def fake_crossref(q):
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calls["n"] += 1
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return [
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{
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"pmid": "",
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"title": "Crossref T",
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"abstract": "Crossref A",
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"url": "https://doi.org/10.1/x",
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"source": "crossref",
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}
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]
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c.search_crossref = fake_crossref # type: ignore[method-assign]
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evidence = c.search("query")
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assert calls["n"] == 1
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assert len(evidence) == 1
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assert evidence[0].kb == "web"
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assert evidence[0].title == "Crossref T"
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@@ -0,0 +1,285 @@
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"""web_search.py —— 联网搜索（S3，机制实例 1）。
|
||||
|
||||
WebSearchCompleter：PubMed esearch+esummary（8s/重试 1）+ Crossref works 兜底（6s）；
|
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结果转 EvidenceItem(kb="web")，abstract ≤1200 字符，最多 max_results 条；
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全部失败返回空列表（静默降级纯 KB 回答）。
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|
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确定性门控（pipeline 证据采纳后调用，不是 agentic controller 自由决策）：
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- selected < min_evidence 或 agentic decision==ABSTAIN 或子问题证据组空且 selected < top_k/2
|
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- AND 请求 capabilities.web_search
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- AND env QA_V1_ENABLE_WEB_SEARCH=1 总闸
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"""
|
||||
from __future__ import annotations
|
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|
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import logging
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import re
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import time
|
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import xml.etree.ElementTree as ET
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
import requests
|
||||
|
||||
from .schemas import EvidenceItem
|
||||
|
||||
LOGGER = logging.getLogger(__name__)
|
||||
|
||||
PUBMED_ESEARCH = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi"
|
||||
PUBMED_ESUMMARY = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi"
|
||||
CROSSREF_WORKS = "https://api.crossref.org/works"
|
||||
|
||||
TIMEOUT_PUBMED = 8.0
|
||||
TIMEOUT_CROSSREF = 6.0
|
||||
MAX_ABSTRACT_CHARS = 1200
|
||||
USER_AGENT = "PlantAI-rag-new/1.1.73 (plant research QA)"
|
||||
|
||||
|
||||
class WebSearchCompleter:
|
||||
"""PubMed 优先 + Crossref 兜底的文献联网搜索。"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
max_results: int = 4,
|
||||
timeout_pubmed: float = TIMEOUT_PUBMED,
|
||||
timeout_crossref: float = TIMEOUT_CROSSREF,
|
||||
max_abstract_chars: int = MAX_ABSTRACT_CHARS,
|
||||
) -> None:
|
||||
self.max_results = max(1, min(int(max_results), 10))
|
||||
self.timeout_pubmed = timeout_pubmed
|
||||
self.timeout_crossref = timeout_crossref
|
||||
self.max_abstract_chars = max_abstract_chars
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# PubMed
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
def search_pubmed(self, query: str) -> List[Dict[str, Any]]:
|
||||
"""esearch 拿 PMID 列表 → esummary 拿元数据。返回 [{"pmid","title","abstract","url","source"}]。"""
|
||||
try:
|
||||
ids = self._esearch(query)
|
||||
except Exception as exc:
|
||||
LOGGER.warning("PubMed esearch 失败: %s", exc)
|
||||
return []
|
||||
if not ids:
|
||||
return []
|
||||
try:
|
||||
summaries = self._esummary(ids[: self.max_results])
|
||||
except Exception as exc:
|
||||
LOGGER.warning("PubMed esummary 失败: %s", exc)
|
||||
# 降级：只给 PMID 与搜索 URL（无摘要）
|
||||
return [
|
||||
{
|
||||
"pmid": pmid,
|
||||
"title": f"PubMed 文献 {pmid}",
|
||||
"abstract": "",
|
||||
"url": f"https://pubmed.ncbi.nlm.nih.gov/{pmid}/",
|
||||
"source": "pubmed",
|
||||
}
|
||||
for pmid in ids[: self.max_results]
|
||||
]
|
||||
return summaries
|
||||
|
||||
def _esearch(self, query: str) -> List[str]:
|
||||
for attempt in (1, 2):
|
||||
try:
|
||||
response = requests.get(
|
||||
PUBMED_ESEARCH,
|
||||
params={
|
||||
"db": "pubmed",
|
||||
"term": query,
|
||||
"retmax": str(self.max_results),
|
||||
"retmode": "json",
|
||||
"sort": "relevance",
|
||||
},
|
||||
headers={"User-Agent": USER_AGENT},
|
||||
timeout=self.timeout_pubmed,
|
||||
)
|
||||
response.raise_for_status()
|
||||
payload = response.json()
|
||||
result = payload.get("esearchresult") or {}
|
||||
ids = result.get("idlist") or []
|
||||
return [str(i) for i in ids]
|
||||
except Exception as exc:
|
||||
if attempt == 2:
|
||||
raise
|
||||
LOGGER.warning("PubMed esearch 第 %s 次失败，重试: %s", attempt, exc)
|
||||
time.sleep(0.5)
|
||||
return []
|
||||
|
||||
def _esummary(self, ids: List[str]) -> List[Dict[str, Any]]:
|
||||
response = requests.get(
|
||||
PUBMED_ESUMMARY,
|
||||
params={"db": "pubmed", "id": ",".join(ids), "retmode": "json"},
|
||||
headers={"User-Agent": USER_AGENT},
|
||||
timeout=self.timeout_pubmed,
|
||||
)
|
||||
response.raise_for_status()
|
||||
payload = response.json()
|
||||
result = payload.get("result") or {}
|
||||
out: List[Dict[str, Any]] = []
|
||||
for pmid in ids:
|
||||
doc = result.get(pmid)
|
||||
if not isinstance(doc, dict):
|
||||
continue
|
||||
title = str(doc.get("title") or "").strip() or f"PubMed 文献 {pmid}"
|
||||
abstract = self._clean_abstract(doc.get("extra"), self.max_abstract_chars)
|
||||
out.append(
|
||||
{
|
||||
"pmid": pmid,
|
||||
"title": title,
|
||||
"abstract": abstract,
|
||||
"url": f"https://pubmed.ncbi.nlm.nih.gov/{pmid}/",
|
||||
"source": "pubmed",
|
||||
}
|
||||
)
|
||||
return out
|
||||
|
||||
@staticmethod
|
||||
def _clean_abstract(text: Any, max_chars: int = MAX_ABSTRACT_CHARS) -> str:
|
||||
if not isinstance(text, str):
|
||||
return ""
|
||||
cleaned = re.sub(r"<[^>]+>", " ", text)
|
||||
cleaned = re.sub(r"\s+", " ", cleaned).strip()
|
||||
return cleaned[:max_chars]
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Crossref 兜底
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
def search_crossref(self, query: str) -> List[Dict[str, Any]]:
|
||||
"""Crossref works 查询（PubMed 无结果时兜底）。"""
|
||||
try:
|
||||
response = requests.get(
|
||||
CROSSREF_WORKS,
|
||||
params={
|
||||
"query.bibliographic": query,
|
||||
"rows": str(self.max_results),
|
||||
"select": "DOI,title,abstract,URL",
|
||||
"mailto": "plantai@example.com",
|
||||
},
|
||||
headers={"User-Agent": USER_AGENT},
|
||||
timeout=self.timeout_crossref,
|
||||
)
|
||||
response.raise_for_status()
|
||||
payload = response.json()
|
||||
items = payload.get("message", {}).get("items") or []
|
||||
except Exception as exc:
|
||||
LOGGER.warning("Crossref 检索失败: %s", exc)
|
||||
return []
|
||||
out: List[Dict[str, Any]] = []
|
||||
for item in items:
|
||||
if not isinstance(item, dict):
|
||||
continue
|
||||
doi = str(item.get("DOI") or "").strip()
|
||||
if not doi:
|
||||
continue
|
||||
title = (
|
||||
" ".join(str(t) for t in item.get("title") or []) or f"Crossref 文献 {doi}"
|
||||
)
|
||||
abstract = re.sub(r"<[^>]+>", " ", str(item.get("abstract") or ""))
|
||||
abstract = re.sub(r"\s+", " ", abstract).strip()[: self.max_abstract_chars]
|
||||
url = str(item.get("URL") or f"https://doi.org/{doi}")
|
||||
out.append(
|
||||
{
|
||||
"pmid": "",
|
||||
"title": title,
|
||||
"abstract": abstract,
|
||||
"url": url,
|
||||
"source": "crossref",
|
||||
}
|
||||
)
|
||||
return out
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 查询构建（确定性启发式：PubMed 不认中文，必须转英文术语）
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
SPECIES_MAP = {
|
||||
"拟南芥": "Arabidopsis thaliana",
|
||||
"水稻": "Oryza sativa",
|
||||
"苦荞": "Fagopyrum tataricum",
|
||||
"荞麦": "Fagopyrum",
|
||||
"番茄": "Solanum lycopersicum",
|
||||
"大豆": "Glycine max",
|
||||
"玉米": "Zea mays",
|
||||
"小麦": "Triticum aestivum",
|
||||
"大麦": "Hordeum vulgare",
|
||||
"葡萄": "Vitis vinifera",
|
||||
"杨树": "Populus",
|
||||
"苹果": "Malus domestica",
|
||||
"苔藓": "Physcomitrella patens",
|
||||
"小立碗藓": "Physcomitrella patens",
|
||||
"棉花": "Gossypium",
|
||||
"黄瓜": "Cucumis sativus",
|
||||
"土豆": "Solanum tuberosum",
|
||||
"马铃薯": "Solanum tuberosum",
|
||||
"烟草": "Nicotiana",
|
||||
"拟芥蓝": "Arabidopsis",
|
||||
}
|
||||
|
||||
# 注意：不用 \b（CJK 字符同属 \w，词边界在中文语境不生效）；连字符家族名如 NF-Y
|
||||
GENE_FAMILY_PATTERN = re.compile(
|
||||
r"[A-Z]{2,6}(?:-[A-Z]{1,3})?[0-9]{0,3}|miR[0-9]{2,4}|CYP[0-9]{1,3}[A-Z]?"
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def build_query(cls, question: str) -> str:
|
||||
"""从中文问题构建 PubMed 英文查询。
|
||||
|
||||
规则：抽基因家族词（大写 token）→ 加 "gene family" →
|
||||
中文物种名映射英文；两者皆无时退化为清理后的原文（Crossref 仍可查中文）。
|
||||
"""
|
||||
families = cls.GENE_FAMILY_PATTERN.findall(question or "")
|
||||
species = []
|
||||
for zh, en in cls.SPECIES_MAP.items():
|
||||
if zh in (question or ""):
|
||||
species.append(en)
|
||||
parts = []
|
||||
if families:
|
||||
# 过滤误抽（基因名长度启发：2-6 大写字母 + 数字）；只取前 4 个
|
||||
unique = list(dict.fromkeys(families))
|
||||
parts.append(" ".join(unique[:4]))
|
||||
parts.append("gene family")
|
||||
if species:
|
||||
parts.extend(species[:2])
|
||||
if parts:
|
||||
return " ".join(parts)
|
||||
# 无任何可抽取术语：清理后原文（至少保留英文 token）
|
||||
cleaned = " ".join(
|
||||
w for w in re.findall(r"[A-Za-z0-9\-]+", question or "") if len(w) > 1
|
||||
)
|
||||
return cleaned or (question or "").strip()[:120]
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 入口
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
def search(self, query: str) -> List[EvidenceItem]:
|
||||
"""检索入口：构建英文查询 → PubMed → Crossref 兜底 → EvidenceItem 列表。"""
|
||||
started = time.perf_counter()
|
||||
pubmed_query = self.build_query(query)
|
||||
results = self.search_pubmed(pubmed_query)
|
||||
if not results:
|
||||
results = self.search_crossref(query)
|
||||
evidence: List[EvidenceItem] = []
|
||||
for item in results:
|
||||
evidence.append(
|
||||
EvidenceItem(
|
||||
evidence_id=f"WEB-{item.get('pmid') or item.get('url', '').split('/')[-1] or item.get('source', 'web')}",
|
||||
kb="web",
|
||||
source=item.get("title", ""),
|
||||
relation="web_search_result",
|
||||
target=item.get("title", ""),
|
||||
evidence=item.get("abstract", "") or item.get("title", ""),
|
||||
paper_id=item.get("url", ""),
|
||||
title=item.get("title", ""),
|
||||
pmid=item.get("pmid") or "",
|
||||
raw={"web": item},
|
||||
)
|
||||
)
|
||||
LOGGER.info(
|
||||
"web_search '%s' -> %d results in %.2fs",
|
||||
query[:80],
|
||||
len(evidence),
|
||||
time.perf_counter() - started,
|
||||
)
|
||||
return evidence
|
||||
@@ -67,6 +67,8 @@ STAGE_PHASE: dict[str, str] = {
|
||||
"subquestion_retry_started": "retrieval",
|
||||
"evidence_accepted": "evidence",
|
||||
"evidence_review_completed": "evidence",
|
||||
"web_search_started": "retrieval",
|
||||
"web_search_completed": "evidence",
|
||||
"answer_generation_started": "generation",
|
||||
"completed": "done",
|
||||
}
|
||||
@@ -81,6 +83,8 @@ STAGE_LABEL: dict[str, str] = {
|
||||
"subquestion_retry_started": "子问题重试中",
|
||||
"evidence_accepted": "证据已采纳",
|
||||
"evidence_review_completed": "证据审核完成",
|
||||
"web_search_started": "开始联网检索",
|
||||
"web_search_completed": "联网检索完成",
|
||||
"answer_generation_started": "开始生成答案",
|
||||
"completed": "检索完成",
|
||||
}
|
||||
|
||||
@@ -48,7 +48,7 @@ def _sse_bytes(events: list[tuple[bytes, bytes]]) -> list[bytes]:
|
||||
# ===========================================================================
|
||||
|
||||
|
||||
def test_stage_phase_maps_all_11_known_stages():
|
||||
def test_stage_phase_maps_all_13_known_stages():
|
||||
expected = {
|
||||
"understanding_started": ("planning", "开始理解问题"),
|
||||
"entities_identified": ("planning", "已识别实体"),
|
||||
@@ -62,8 +62,8 @@ def test_stage_phase_maps_all_11_known_stages():
|
||||
"answer_generation_started": ("generation", "开始生成答案"),
|
||||
"completed": ("done", "检索完成"),
|
||||
}
|
||||
assert len(STAGE_PHASE) == 11
|
||||
assert len(STAGE_LABEL) == 11
|
||||
assert len(STAGE_PHASE) == 13
|
||||
assert len(STAGE_LABEL) == 13
|
||||
for stage, (phase, label) in expected.items():
|
||||
assert STAGE_PHASE[stage] == phase
|
||||
assert STAGE_LABEL[stage] == label
|
||||
|
||||
Reference in New Issue
Block a user