From 3ed2ddeb916e7e74a73396ccb458cd1aa81719d9 Mon Sep 17 00:00:00 2001
From: SengokuCola <1026294844@qq.com>
Date: Tue, 18 Nov 2025 20:55:33 +0800
Subject: [PATCH] =?UTF-8?q?feat=EF=BC=9A=E4=BC=98=E5=8C=96=E8=A1=A8?=
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---
 src/express/express_utils.py       | 56 +++++++++++++++++++++++++-----
 src/express/expression_selector.py |  1 +
 2 files changed, 49 insertions(+), 8 deletions(-)

diff --git a/src/express/express_utils.py b/src/express/express_utils.py
index c27306d1..20095561 100644
--- a/src/express/express_utils.py
+++ b/src/express/express_utils.py
@@ -61,6 +61,37 @@ def format_create_date(timestamp: float) -> str:
         return "未知时间"
 
 
+def _compute_weights(population: List[Dict]) -> List[float]:
+    """
+    根据表达的count计算权重，范围限定在1~3之间。
+    count越高，权重越高，但最多为基础权重的3倍。
+    """
+    if not population:
+        return []
+
+    counts = []
+    for item in population:
+        count = item.get("count", 1)
+        try:
+            count_value = float(count)
+        except (TypeError, ValueError):
+            count_value = 1.0
+        counts.append(max(count_value, 0.0))
+
+    min_count = min(counts)
+    max_count = max(counts)
+
+    if max_count == min_count:
+        return [1.0 for _ in counts]
+
+    weights = []
+    for count_value in counts:
+        # 线性映射到[1,3]区间
+        normalized = (count_value - min_count) / (max_count - min_count)
+        weights.append(1.0 + normalized * 2.0)  # 1~3
+    return weights
+
+
 def weighted_sample(population: List[Dict], k: int) -> List[Dict]:
     """
     随机抽样函数
@@ -78,15 +109,24 @@ def weighted_sample(population: List[Dict], k: int) -> List[Dict]:
     if len(population) <= k:
         return population.copy()
 
-    # 使用随机抽样
-    selected = []
+    selected: List[Dict] = []
     population_copy = population.copy()
 
-    for _ in range(k):
-        if not population_copy:
-            break
-        # 随机选择一个元素
-        idx = random.randint(0, len(population_copy) - 1)
-        selected.append(population_copy.pop(idx))
+    for _ in range(min(k, len(population_copy))):
+        weights = _compute_weights(population_copy)
+        total_weight = sum(weights)
+        if total_weight <= 0:
+            # 回退到均匀随机
+            idx = random.randint(0, len(population_copy) - 1)
+            selected.append(population_copy.pop(idx))
+            continue
+
+        threshold = random.uniform(0, total_weight)
+        cumulative = 0.0
+        for idx, weight in enumerate(weights):
+            cumulative += weight
+            if threshold <= cumulative:
+                selected.append(population_copy.pop(idx))
+                break
 
     return selected
diff --git a/src/express/expression_selector.py b/src/express/expression_selector.py
index 031cc714..66c49def 100644
--- a/src/express/expression_selector.py
+++ b/src/express/expression_selector.py
@@ -139,6 +139,7 @@ class ExpressionSelector:
                     "last_active_time": expr.last_active_time,
                     "source_id": expr.chat_id,
                     "create_date": expr.create_date if expr.create_date is not None else expr.last_active_time,
+                    "count": expr.count if getattr(expr, "count", None) is not None else 1,
                 }
                 for expr in style_query
             ]