update pay ui
This commit is contained in:
@@ -309,7 +309,11 @@ def generate_embedding(text: str) -> List[float]:
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def calculate_semantic_weight(query: str) -> float:
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"""根据查询长度动态计算语义权重"""
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query_length = len(query)
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# 空查询不需要语义搜索
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if not query or not query.strip():
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return 0.0
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query_length = len(query.strip())
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if query_length < 10:
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return 0.3
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@@ -321,6 +325,90 @@ def calculate_semantic_weight(query: str) -> float:
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return 0.7
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async def get_top_concepts_by_change(
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trade_date: Optional[date],
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limit: int = 100,
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offset: int = 0,
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filter_lv1: Optional[str] = None,
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filter_lv2: Optional[str] = None
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) -> tuple[List[Dict], int, date]:
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"""
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直接从 MySQL 获取涨跌幅排序的概念列表（用于空查询优化）
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返回: (概念列表, 总数, 实际查询日期)
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"""
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if not mysql_pool:
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return [], 0, None
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try:
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async with mysql_pool.acquire() as conn:
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async with conn.cursor(aiomysql.DictCursor) as cursor:
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# 获取交易日期
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query_date = trade_date
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if query_date is None:
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await cursor.execute("SELECT MAX(trade_date) as max_date FROM concept_daily_stats WHERE concept_type = 'leaf'")
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result = await cursor.fetchone()
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if not result or not result['max_date']:
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return [], 0, None
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query_date = result['max_date']
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# 构建基础条件
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where_conditions = ["trade_date = %s", "concept_type = 'leaf'"]
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params = [query_date]
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# 添加层级过滤（通过 concept_name 关联）
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# 注意：这里需要根据 concept_to_hierarchy 过滤
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if filter_lv1 or filter_lv2:
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# 获取符合层级条件的概念名称
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filtered_concepts = []
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for concept_name, hierarchy in concept_to_hierarchy.items():
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if filter_lv1 and hierarchy.get('lv1') != filter_lv1:
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continue
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if filter_lv2 and hierarchy.get('lv2') != filter_lv2:
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continue
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filtered_concepts.append(concept_name)
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if not filtered_concepts:
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return [], 0, query_date
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placeholders = ','.join(['%s'] * len(filtered_concepts))
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where_conditions.append(f"concept_name IN ({placeholders})")
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params.extend(filtered_concepts)
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where_clause = " AND ".join(where_conditions)
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# 查询总数
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count_query = f"SELECT COUNT(*) as cnt FROM concept_daily_stats WHERE {where_clause}"
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await cursor.execute(count_query, params)
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total = (await cursor.fetchone())['cnt']
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# 查询数据（按涨跌幅降序）
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data_query = f"""
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SELECT concept_id, concept_name, avg_change_pct, stock_count
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FROM concept_daily_stats
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WHERE {where_clause}
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ORDER BY avg_change_pct DESC
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LIMIT %s OFFSET %s
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"""
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await cursor.execute(data_query, params + [limit, offset])
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rows = await cursor.fetchall()
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concepts = []
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for row in rows:
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concepts.append({
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'concept_id': row['concept_id'],
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'concept_name': row['concept_name'],
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'avg_change_pct': float(row['avg_change_pct']) if row['avg_change_pct'] else None,
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'stock_count': row['stock_count'],
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'trade_date': query_date
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})
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return concepts, total, query_date
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except Exception as e:
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logger.error(f"获取涨跌幅排序概念失败: {e}")
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return [], 0, None
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async def get_concept_price_data(concept_ids: List[str], trade_date: Optional[date] = None) -> Dict[str, ConceptPriceInfo]:
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"""获取概念的涨跌幅数据"""
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if not mysql_pool or not concept_ids:
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@@ -451,10 +539,117 @@ async def root():
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async def search_concepts(request: SearchRequest):
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"""
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搜索概念 - 支持语义搜索和层级过滤
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优化：空查询 + 涨跌幅排序时，直接从 MySQL 查询，避免 ES 大量数据获取
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"""
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start_time = datetime.now()
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try:
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# ========== 优化路径：空查询 + 涨跌幅排序 ==========
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# 这是概念中心首页的默认场景，直接从 MySQL 获取排序结果
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is_empty_query = not request.query or not request.query.strip()
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is_change_sort = request.sort_by == "change_pct"
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no_stock_filter = not request.filter_stocks
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if is_empty_query and is_change_sort and no_stock_filter:
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logger.info(f"[Search优化] 使用 MySQL 快速路径: page={request.page}, size={request.size}")
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# 计算分页
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offset = (request.page - 1) * request.size
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# 从 MySQL 获取涨跌幅排序的概念
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top_concepts, total, actual_date = await get_top_concepts_by_change(
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trade_date=request.trade_date,
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limit=request.size,
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offset=offset,
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filter_lv1=request.filter_lv1,
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filter_lv2=request.filter_lv2
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)
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if not top_concepts:
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took_ms = int((datetime.now() - start_time).total_seconds() * 1000)
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return SearchResponse(
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total=0,
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took_ms=took_ms,
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results=[],
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search_info={"query": "", "semantic_weight": 0, "match_type": "mysql_optimized"},
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price_date=actual_date,
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page=request.page,
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total_pages=0
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)
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# 用 concept_id 从 ES 批量获取详细信息
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concept_ids = [c['concept_id'] for c in top_concepts]
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es_body = {
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"query": {"terms": {"concept_id": concept_ids}},
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"size": len(concept_ids),
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"_source": {"excludes": ["description_embedding", "insight"]}
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}
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es_response = es_client.search(index=INDEX_NAME, body=es_body, timeout="10s")
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# 构建 concept_id -> ES 详情的映射
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es_details = {}
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for hit in es_response['hits']['hits']:
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source = hit['_source']
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es_details[source.get('concept_id', '')] = source
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# 组装结果（保持 MySQL 的排序顺序）
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results = []
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for mysql_concept in top_concepts:
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cid = mysql_concept['concept_id']
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es_data = es_details.get(cid, {})
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concept_name = mysql_concept['concept_name']
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# 解析股票
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stocks_list, _ = parse_stocks_from_es(es_data)
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# 获取层级信息
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hierarchy_info = get_concept_hierarchy(concept_name)
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hierarchy = HierarchyInfo(**hierarchy_info) if hierarchy_info else None
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result = ConceptResult(
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concept_id=cid,
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concept=concept_name,
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description=es_data.get('description'),
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tags=es_data.get('tags', []),
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outbreak_dates=es_data.get('outbreak_dates', []),
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stocks=stocks_list,
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stock_count=mysql_concept['stock_count'] or len(es_data.get('stocks', [])),
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hierarchy=hierarchy,
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score=0.0,
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match_type="mysql_optimized",
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highlights=None,
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price_info=ConceptPriceInfo(
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trade_date=actual_date,
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avg_change_pct=mysql_concept['avg_change_pct']
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)
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)
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results.append(result)
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took_ms = int((datetime.now() - start_time).total_seconds() * 1000)
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total_pages = max(1, (total + request.size - 1) // request.size)
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logger.info(f"[Search优化] MySQL 快速路径完成: took={took_ms}ms, total={total}, returned={len(results)}")
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return SearchResponse(
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total=total,
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took_ms=took_ms,
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results=results,
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search_info={
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"query": "",
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"semantic_weight": 0,
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"match_type": "mysql_optimized",
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"filter_lv1": request.filter_lv1,
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"filter_lv2": request.filter_lv2,
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"sort_by": request.sort_by
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},
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price_date=actual_date,
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page=request.page,
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total_pages=total_pages
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)
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# ========== 常规路径：有搜索词或其他排序方式 ==========
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# 计算语义权重
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if request.semantic_weight is not None:
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semantic_weight = request.semantic_weight
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