前端适配
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Miyamizu-MitsuhaSang
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commit
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@ -140,19 +140,18 @@ async def suggest_autocomplete(
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text_field: str = "text",
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hira_field: str = "hiragana",
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freq_field: str = "freq",
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english_field: str = "eng_explanation",
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limit: int = 10,
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) -> List[Dict[str, str]]:
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"""
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通用自动补全建议接口（增强版）：
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- 法语: 按 search_text / text 搜索，同时反查 DefinitionFr 的英文释义
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- 日语: 先按原文 text 匹配，再按假名 search_text 匹配
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通用自动补全建议接口：
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- 法语: 按 search_text / text 搜索 + 反查 DefinitionFr 英/中释义
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- 日语: 先按原文 text 匹配，再按假名匹配 + 反查 DefinitionJp 中文释义
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统一返回结构：
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[
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{
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"word": "étudier",
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"hiragana": None,
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"meanings": [],
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"meanings": ["学习", "研究"],
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"english": ["to study", "to learn"]
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}
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]
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@ -161,19 +160,25 @@ async def suggest_autocomplete(
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if not keyword:
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return []
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# ========== 法语 ==========
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# ========== 法语分支 ==========
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if dict_lang == "fr":
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start_condition = Q(**{f"{search_field}__istartswith": keyword}) | Q(**{f"{text_field}__istartswith": keyword})
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contain_condition = Q(**{f"{search_field}__icontains": keyword}) | Q(**{f"{text_field}__icontains": keyword})
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start_condition = (
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Q(**{f"{search_field}__istartswith": keyword})
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| Q(**{f"{text_field}__istartswith": keyword})
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)
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contain_condition = (
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Q(**{f"{search_field}__icontains": keyword})
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| Q(**{f"{text_field}__icontains": keyword})
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)
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value_fields = ["id", text_field, freq_field, search_field]
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# ========== 日语 ==========
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# ========== 日语分支 ==========
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elif dict_lang == "jp":
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kana_word = all_in_kana(keyword)
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start_condition = Q(**{f"{text_field}__istartswith": keyword})
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start_condition = Q(**{f"{text_field}__startswith": keyword})
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contain_condition = Q(**{f"{text_field}__icontains": keyword})
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kana_start = Q(**{f"{hira_field}__istartswith": kana_word})
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kana_start = Q(**{f"{hira_field}__startswith": kana_word})
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kana_contain = Q(**{f"{hira_field}__icontains": kana_word})
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start_condition |= kana_start
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@ -183,7 +188,7 @@ async def suggest_autocomplete(
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else:
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return []
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# ✅ 1. 开头匹配
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# ✅ 获取匹配单词
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start_matches = await (
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model.filter(start_condition)
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.order_by(f"-{freq_field}", "id")
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@ -191,7 +196,6 @@ async def suggest_autocomplete(
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.values(*value_fields)
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)
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# ✅ 2. 包含匹配
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contain_matches = await (
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model.filter(contain_condition & ~start_condition)
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.order_by(f"-{freq_field}", "id")
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@ -199,33 +203,55 @@ async def suggest_autocomplete(
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.values(*value_fields)
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)
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# ✅ 3. 合并去重
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results = []
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seen_ids = set()
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for row in start_matches + contain_matches:
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if row["id"] in seen_ids:
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continue
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if row["id"] not in seen_ids:
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seen_ids.add(row["id"])
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result = {
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results.append({
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"id": row["id"],
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"word": row[text_field],
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"hiragana": row.get(hira_field) if dict_lang == "jp" else None,
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"meanings": [],
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"english": [],
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}
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})
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# ✅ 若为法语，则反查 DefinitionFr 的英文释义
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# ✅ 批量反查 Definition 表，防止 N+1 查询
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if dict_lang == "fr":
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# 获取关联的 definitions
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word_obj = await model.get(id=row["id"]).prefetch_related("definitions")
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english_list = [
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d.eng_explanation.strip()
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for d in word_obj.definitions
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if d.eng_explanation and d.eng_explanation.strip()
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]
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result["english"] = list(set(english_list))
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from app.models import DefinitionFr # 避免循环导入
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word_ids = [r["id"] for r in results]
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defs = await DefinitionFr.filter(word_id__in=word_ids).values("word_id", "meaning", "eng_explanation")
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results.append(result)
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meaning_map: Dict[int, Dict[str, List[str]]] = {}
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for d in defs:
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meaning_map.setdefault(d["word_id"], {"meanings": [], "english": []})
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if d["meaning"]:
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meaning_map[d["word_id"]]["meanings"].append(d["meaning"].strip())
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if d["eng_explanation"]:
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meaning_map[d["word_id"]]["english"].append(d["eng_explanation"].strip())
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for r in results:
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if r["id"] in meaning_map:
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r["meanings"] = list(set(meaning_map[r["id"]]["meanings"]))
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r["english"] = list(set(meaning_map[r["id"]]["english"]))
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elif dict_lang == "jp":
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from app.models import DefinitionJp
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word_ids = [r["id"] for r in results]
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defs = await DefinitionJp.filter(word_id__in=word_ids).values("word_id", "meaning")
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meaning_map: Dict[int, List[str]] = {}
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for d in defs:
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if d["meaning"]:
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meaning_map.setdefault(d["word_id"], []).append(d["meaning"].strip())
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for r in results:
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if r["id"] in meaning_map:
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r["meanings"] = list(set(meaning_map[r["id"]]))
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# ✅ 删除 id，只保留用户需要字段
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for r in results:
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r.pop("id", None)
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return results[:limit]
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