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明天好像没什么
2025-11-07 21:01:45 +08:00
parent 80b040da2f
commit c8d7c09625
49 changed files with 854 additions and 872 deletions
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23
src/chat/express/expression_learner.py
View File

@@ -1,5 +1,4 @@
import os
import random
import time
from datetime import datetime
from typing import Any
@@ -135,20 +134,20 @@ class ExpressionLearner:
async def cleanup_expired_expressions(self, expiration_days: int | None = None) -> int:
"""
清理过期的表达方式
Args:
expiration_days: 过期天数，超过此天数未激活的表达方式将被删除（不指定则从配置读取）
Returns:
int: 删除的表达方式数量
"""
# 从配置读取过期天数
if expiration_days is None:
expiration_days = global_config.expression.expiration_days
current_time = time.time()
expiration_threshold = current_time - (expiration_days * 24 * 3600)
try:
deleted_count = 0
async with get_db_session() as session:
@@ -160,15 +159,15 @@ class ExpressionLearner:
)
)
expired_expressions = list(query.scalars())
if expired_expressions:
for expr in expired_expressions:
await session.delete(expr)
deleted_count += 1
await session.commit()
logger.info(f"清理了 {deleted_count} 个过期表达方式（超过 {expiration_days} 天未使用）")
# 清除缓存
from src.common.database.optimization.cache_manager import get_cache
from src.common.database.utils.decorators import generate_cache_key
@@ -176,7 +175,7 @@ class ExpressionLearner:
await cache.delete(generate_cache_key("chat_expressions", self.chat_id))
else:
logger.debug(f"没有发现过期的表达方式（阈值：{expiration_days} 天）")
return deleted_count
except Exception as e:
logger.error(f"清理过期表达方式失败: {e}")
@@ -460,7 +459,7 @@ class ExpressionLearner:
)
)
same_situation_expr = query_same_situation.scalar()
# 情况2：相同 chat_id + type + style（相同表达，不同情景）
query_same_style = await session.execute(
select(Expression).where(
@@ -470,7 +469,7 @@ class ExpressionLearner:
)
)
same_style_expr = query_same_style.scalar()
# 情况3：完全相同（相同情景+相同表达）
query_exact_match = await session.execute(
select(Expression).where(
@@ -481,7 +480,7 @@ class ExpressionLearner:
)
)
exact_match_expr = query_exact_match.scalar()
# 优先处理完全匹配的情况
if exact_match_expr:
# 完全相同：增加count，更新时间

10
src/chat/express/expressor_model/model.py
View File

@@ -72,21 +72,21 @@ class ExpressorModel:
是否删除成功
"""
removed = False
if cid in self._candidates:
del self._candidates[cid]
removed = True
if cid in self._situations:
del self._situations[cid]
# 从nb模型中删除
if cid in self.nb.cls_counts:
del self.nb.cls_counts[cid]
if cid in self.nb.token_counts:
del self.nb.token_counts[cid]
return removed
def predict(self, text: str, k: int | None = None) -> tuple[str | None, dict[str, float]]:

52
src/chat/express/style_learner.py
View File

@@ -72,7 +72,7 @@ class StyleLearner:
# 检查是否需要清理
current_count = len(self.style_to_id)
cleanup_trigger = int(self.max_styles * self.cleanup_threshold)
if current_count >= cleanup_trigger:
if current_count >= self.max_styles:
# 已经达到最大限制，必须清理
@@ -109,7 +109,7 @@ class StyleLearner:
def _cleanup_styles(self):
"""
清理低价值的风格，为新风格腾出空间
清理策略：
1. 综合考虑使用次数和最后使用时间
2. 删除得分最低的风格
@@ -118,34 +118,34 @@ class StyleLearner:
try:
current_time = time.time()
cleanup_count = max(1, int(len(self.style_to_id) * self.cleanup_ratio))
# 计算每个风格的价值分数
style_scores = []
for style_id in self.style_to_id.values():
# 使用次数
usage_count = self.learning_stats["style_counts"].get(style_id, 0)
# 最后使用时间（越近越好）
last_used = self.learning_stats["style_last_used"].get(style_id, 0)
time_since_used = current_time - last_used if last_used > 0 else float('inf')
time_since_used = current_time - last_used if last_used > 0 else float("inf")
# 综合分数：使用次数越多越好，距离上次使用时间越短越好
# 使用对数来平滑使用次数的影响
import math
usage_score = math.log1p(usage_count) # log(1 + count)
# 时间分数：转换为天数，使用指数衰减
days_unused = time_since_used / 86400 # 转换为天
time_score = math.exp(-days_unused / 30) # 30天衰减因子
# 综合分数：80%使用频率 + 20%时间新鲜度
total_score = 0.8 * usage_score + 0.2 * time_score
style_scores.append((style_id, total_score, usage_count, days_unused))
# 按分数排序，分数低的先删除
style_scores.sort(key=lambda x: x[1])
# 删除分数最低的风格
deleted_styles = []
for style_id, score, usage, days in style_scores[:cleanup_count]:
@@ -156,27 +156,27 @@ class StyleLearner:
del self.id_to_style[style_id]
if style_id in self.id_to_situation:
del self.id_to_situation[style_id]
# 从统计中删除
if style_id in self.learning_stats["style_counts"]:
del self.learning_stats["style_counts"][style_id]
if style_id in self.learning_stats["style_last_used"]:
del self.learning_stats["style_last_used"][style_id]
# 从expressor模型中删除
self.expressor.remove_candidate(style_id)
deleted_styles.append((style_text[:30], usage, f"{days:.1f}天"))
logger.info(
f"风格清理完成: 删除了 {len(deleted_styles)}/{len(style_scores)} 个风格，"
f"剩余 {len(self.style_to_id)} 个风格"
)
# 记录前5个被删除的风格（用于调试）
if deleted_styles:
logger.debug(f"被删除的风格样例(前5): {deleted_styles[:5]}")
except Exception as e:
logger.error(f"清理风格失败: {e}", exc_info=True)
@@ -303,10 +303,10 @@ class StyleLearner:
def cleanup_old_styles(self, ratio: float | None = None) -> int:
"""
手动清理旧风格
Args:
ratio: 清理比例，如果为None则使用默认的cleanup_ratio
Returns:
清理的风格数量
"""
@@ -318,7 +318,7 @@ class StyleLearner:
self.cleanup_ratio = old_cleanup_ratio
else:
self._cleanup_styles()
new_count = len(self.style_to_id)
cleaned = old_count - new_count
logger.info(f"手动清理完成: chat_id={self.chat_id}, 清理了 {cleaned} 个风格")
@@ -357,11 +357,11 @@ class StyleLearner:
import pickle
meta_path = os.path.join(save_dir, "meta.pkl")
# 确保 learning_stats 包含所有必要字段
if "style_last_used" not in self.learning_stats:
self.learning_stats["style_last_used"] = {}
meta_data = {
"style_to_id": self.style_to_id,
"id_to_style": self.id_to_style,
@@ -416,7 +416,7 @@ class StyleLearner:
self.id_to_situation = meta_data["id_to_situation"]
self.next_style_id = meta_data["next_style_id"]
self.learning_stats = meta_data["learning_stats"]
# 确保旧数据兼容：如果没有 style_last_used 字段，添加它
if "style_last_used" not in self.learning_stats:
self.learning_stats["style_last_used"] = {}
@@ -526,10 +526,10 @@ class StyleLearnerManager:
def cleanup_all_old_styles(self, ratio: float | None = None) -> dict[str, int]:
"""
对所有学习器清理旧风格
Args:
ratio: 清理比例
Returns:
{chat_id: 清理数量}
"""
@@ -538,7 +538,7 @@ class StyleLearnerManager:
cleaned = learner.cleanup_old_styles(ratio)
if cleaned > 0:
cleanup_results[chat_id] = cleaned
total_cleaned = sum(cleanup_results.values())
logger.info(f"清理所有StyleLearner完成: 总共清理了 {total_cleaned} 个风格")
return cleanup_results