diff --git a/app.py b/app.py
index 3c1cb77..cf95d19 100644
--- a/app.py
+++ b/app.py
@@ -30,6 +30,7 @@ from logging.handlers import RotatingFileHandler
from flask import Flask, Response, redirect, render_template, request, session, url_for
from flask_sqlalchemy import SQLAlchemy
+from sqlalchemy import or_, and_
from werkzeug.exceptions import HTTPException
from werkzeug.security import check_password_hash, generate_password_hash
@@ -339,6 +340,11 @@ SEARCH_FUZZY_PROFILES = {
},
}
+# 搜索结果最低展示分数，低于该分数的匹配将被隐藏（可按需调整）
+SEARCH_MIN_DISPLAY_SCORE = 3.0
+# 每次搜索最多评分的候选元件数量，避免对整个库逐条打分导致页面刷新变慢
+SEARCH_MAX_CANDIDATES = 800
+
def _apply_box_type_overrides() -> None:
"""加载盒型覆盖配置。
@@ -2332,6 +2338,10 @@ def _build_rule_based_search_plan(query: str) -> dict:
if values:
summary_bits.append(f"{field_labels[field]}: {' / '.join(values)}")
+ # 保证 field_map 四个字段都为 list，防止模板渲染出错
+ for k in ("part_no", "name", "specification", "note"):
+ if k not in field_map or not isinstance(field_map[k], list):
+ field_map[k] = []
return {
"query": query,
"mode": "rule",
@@ -5179,6 +5189,12 @@ def lcsc_import_to_edit_slot(box_id: int, slot: int):
def search_page():
keyword = request.args.get("q", "").strip()
fuzziness = _parse_search_fuzziness(request.args.get("fuzziness", "balanced"))
+ # 从请求参数读取最小展示分数（allow override），否则使用全局常量
+ min_score_raw = (request.args.get("min_score", "") or "").strip()
+ try:
+ min_display_score = float(min_score_raw) if min_score_raw else SEARCH_MIN_DISPLAY_SCORE
+ except (TypeError, ValueError):
+ min_display_score = SEARCH_MIN_DISPLAY_SCORE
notice = request.args.get("notice", "").strip()
error = request.args.get("error", "").strip()
results = []
@@ -5186,21 +5202,101 @@ def search_page():
search_parse_notice = ""
search_trace = None
+ # 解析是否启用 AI：支持通过 GET 参数 `use_ai=0/1` 控制，
+ # 如果未提供则根据是否配置 AI API 自动决定（已配置则默认开启）。
+ use_ai_raw = (request.args.get("use_ai", "") or "").strip().lower()
+ if use_ai_raw in ("0", "false", "no", "off"):
+ use_ai = False
+ elif use_ai_raw in ("1", "true", "yes", "on"):
+ use_ai = True
+ else:
+ tmp_settings = _get_ai_settings()
+ use_ai = bool((tmp_settings.get("api_key") or "") and (tmp_settings.get("api_url") or "") and (tmp_settings.get("model") or ""))
+
if keyword:
+ # 读取优先级控制：name（名称优先）或 part_no（料号优先）
+ priority = (request.args.get("priority", "") or "").strip().lower() or "name"
settings = _get_ai_settings()
- search_plan, search_parse_notice, search_trace = _build_search_plan(keyword, settings)
+ if use_ai:
+ search_plan, search_parse_notice, search_trace = _build_search_plan(keyword, settings)
+ else:
+ # 用户显式关闭 AI，直接使用规则兜底计划
+ fallback = _build_rule_based_search_plan(keyword)
+ search_plan = fallback
+ search_parse_notice = ""
+ search_trace = {
+ "query": keyword,
+ "used_ai": False,
+ "used_fallback": True,
+ "final_mode": "rule",
+ "fallback_plan": fallback,
+ "ai_raw": "",
+ "ai_error": "",
+ }
+
if search_trace is None:
search_trace = {}
search_trace["fuzziness"] = fuzziness
- search_trace["fuzziness_label"] = SEARCH_FUZZY_PROFILES.get(fuzziness, SEARCH_FUZZY_PROFILES["balanced"])["label"]
- enabled_components = Component.query.filter_by(is_enabled=True).order_by(Component.part_no.asc(), Component.name.asc()).all()
+ search_trace["fuzziness_label"] = SEARCH_FUZZY_PROFILES.get(fuzziness, SEARCH_FUZZY_PROFILES["balanced"])['label']
+ # 只拉取一定数量候选项以加快页面响应；如需全库扫描可调大 SEARCH_MAX_CANDIDATES
+ # 非 AI 模式下使用 SQL 预筛选：对每个词生成 OR 子句（匹配 part_no/name/specification/note），
+ # 并用 AND 将各词串联，要求每个词至少在某个字段中出现以增强精确度。
+ if not use_ai:
+ # 优先按字段顺序拉取候选：料号 > 名称 > 规格 > 备注
+ terms = [t for t in _split_natural_language_terms(keyword) if t]
+ candidates = []
+ matched_ids = set()
+ remaining = SEARCH_MAX_CANDIDATES
+
+ # 根据 priority 参数设置字段搜索顺序
+ if priority == "part_no":
+ fields_order = ("part_no", "name", "specification", "note")
+ else:
+ fields_order = ("name", "part_no", "specification", "note")
+ for field in fields_order:
+ if remaining <= 0:
+ break
+ if not terms:
+ break
+ like_clauses = [getattr(Component, field).ilike(f"%{term}%") for term in terms]
+ if not like_clauses:
+ continue
+ q = Component.query.filter(or_(*like_clauses), Component.is_enabled == True)
+ if matched_ids:
+ q = q.filter(~Component.id.in_(matched_ids))
+ rows = q.order_by(Component.part_no.asc(), Component.name.asc()).limit(remaining).all()
+ for r in rows:
+ candidates.append(r)
+ matched_ids.add(r.id)
+ remaining = SEARCH_MAX_CANDIDATES - len(candidates)
+
+ # 如果仍不足，补充其他已启用的组件（排除已选）
+ if remaining > 0:
+ q = Component.query.filter(Component.is_enabled == True)
+ if matched_ids:
+ q = q.filter(~Component.id.in_(matched_ids))
+ rows = q.order_by(Component.part_no.asc(), Component.name.asc()).limit(remaining).all()
+ for r in rows:
+ candidates.append(r)
+
+ enabled_components = candidates
+ else:
+ enabled_components = (
+ Component.query.filter_by(is_enabled=True)
+ .order_by(Component.part_no.asc(), Component.name.asc())
+ .limit(SEARCH_MAX_CANDIDATES)
+ .all()
+ )
box_by_id = {box.id: box for box in Box.query.all()}
matched_rows = []
for c in enabled_components:
match_info = _search_component_match_info(c, search_plan, fuzziness=fuzziness)
+ # 过滤极低置信度的匹配，避免界面显示大量无关条目
if not match_info["is_match"]:
continue
+ if match_info.get("score", 0) < min_display_score:
+ continue
box = box_by_id.get(c.box_id)
matched_rows.append(
{
@@ -5237,6 +5333,8 @@ def search_page():
search_parse_notice=search_parse_notice,
notice=notice,
error=error,
+ min_display_score=min_display_score,
+ priority=priority if 'priority' in locals() else 'name',
)
diff --git a/templates/search.html b/templates/search.html
index 0417470..b3d66ee 100644
--- a/templates/search.html
+++ b/templates/search.html
@@ -35,6 +35,22 @@
{% endfor %}
+
+
+
+
+
+
@@ -195,6 +211,47 @@
});
}
+ // AI 开关行为：从 localStorage 读取用户偏好并在提交时保存
+ var useAiToggle = document.getElementById('use-ai-toggle');
+ var useAiHidden = document.getElementById('use-ai-hidden');
+ var minScoreInput = document.getElementById('min-score-input');
+ var prioritySelect = document.getElementById('priority-select');
+ try {
+ var saved = localStorage.getItem('use_ai_enabled');
+ if (saved !== null) {
+ var enabled = saved === '1' || saved === 'true';
+ if (useAiToggle) useAiToggle.checked = enabled;
+ if (useAiHidden) useAiHidden.value = enabled ? '1' : '0';
+ }
+ var savedScore = localStorage.getItem('search_min_score');
+ if (savedScore !== null && minScoreInput) {
+ minScoreInput.value = savedScore;
+ }
+ var savedPriority = localStorage.getItem('search_priority');
+ if (savedPriority !== null && prioritySelect) {
+ try { prioritySelect.value = savedPriority; } catch (e) {}
+ }
+ } catch (e) {
+ // ignore localStorage errors
+ }
+ if (searchForm) {
+ searchForm.addEventListener('submit', function () {
+ var enabled = !!(useAiToggle && useAiToggle.checked);
+ if (useAiHidden) useAiHidden.value = enabled ? '1' : '0';
+ try {
+ if (minScoreInput) {
+ localStorage.setItem('search_min_score', String(minScoreInput.value));
+ }
+ if (prioritySelect) {
+ localStorage.setItem('search_priority', String(prioritySelect.value));
+ }
+ } catch (e) {}
+ try {
+ localStorage.setItem('use_ai_enabled', enabled ? '1' : '0');
+ } catch (e) {}
+ });
+ }
+
document.querySelectorAll('[data-example]').forEach(function (button) {
button.addEventListener('click', function () {
if (!searchInput || !searchForm) {