feat：修复部分破损json的解析问题

src/chat/emoji_system/emoji_manager.py

@@ -13,7 +13,7 @@ from typing import Optional, Tuple, List, Any
 from PIL import Image
 from rich.traceback import install
 
-from src.common.database.database_model import Emoji
+from src.common.database.database_model import Emoji, EmojiDescriptionCache
 from src.common.database.database import db as peewee_db
 from src.common.logger import get_logger
 from src.config.config import global_config, model_config
@@ -398,6 +398,7 @@ class EmojiManager:
             raise RuntimeError("数据库连接失败")
         _ensure_emoji_dir()
         Emoji.create_table(safe=True)  # Ensures table exists
+        EmojiDescriptionCache.create_table(safe=True)
         self._initialized = True
 
     def _ensure_db(self) -> None:
@@ -918,17 +919,15 @@ class EmojiManager:
             image_hash = hashlib.md5(image_bytes).hexdigest()
             image_format = Image.open(io.BytesIO(image_bytes)).format.lower()  # type: ignore
 
-            # 尝试从Images表获取已有的详细描述（可能在收到表情包时已生成）
+            # 尝试从 EmojiDescriptionCache 表获取已有的详细描述
             existing_description = None
             try:
-                from src.common.database.database_model import Images
+                cache_record = EmojiDescriptionCache.get_or_none(EmojiDescriptionCache.emoji_hash == image_hash)
-
+                if cache_record and cache_record.description:
-                existing_image = Images.get_or_none((Images.emoji_hash == image_hash) & (Images.type == "emoji"))
+                    existing_description = cache_record.description
-                if existing_image and existing_image.description:
+                    logger.info(f"[复用描述] 表情描述缓存命中: {existing_description[:50]}...")
-                    existing_description = existing_image.description
-                    logger.info(f"[复用描述] 找到已有详细描述: {existing_description[:50]}...")
             except Exception as e:
-                logger.debug(f"查询已有描述时出错: {e}")
+                logger.debug(f"查询表情描述缓存时出错: {e}")
 
             # 第一步：VLM视觉分析（如果没有已有描述才调用）
             if existing_description:
@@ -950,6 +949,21 @@ class EmojiManager:
                         prompt, image_base64, image_format, temperature=0.5
                     )
 
+            # 若是新生成的描述，写入缓存表（此时还没有情感标签，稍后会更新）
+            if not existing_description:
+                try:
+                    cache_record, created = EmojiDescriptionCache.get_or_create(
+                        emoji_hash=image_hash,
+                        defaults={"description": description, "timestamp": time.time()},
+                    )
+                    if not created:
+                        # 更新描述，但保留已有的情感标签（如果有）
+                        cache_record.description = description
+                        cache_record.timestamp = time.time()
+                        cache_record.save()
+                except Exception as cache_error:
+                    logger.debug(f"写入表情描述缓存失败: {cache_error}")
+
             # 审核表情包
             if global_config.emoji.content_filtration:
                 prompt = f'''
@@ -989,6 +1003,30 @@ class EmojiManager:
 
             logger.info(f"[注册分析] 详细描述: {description[:50]}... -> 情感标签: {emotions}")
 
+            # 将情感标签列表转换为逗号分隔的字符串
+            emotion_tags_str = ",".join(emotions)
+
+            # 更新EmojiDescriptionCache，保存情感标签
+            try:
+                cache_record = EmojiDescriptionCache.get_or_none(EmojiDescriptionCache.emoji_hash == image_hash)
+                if cache_record:
+                    # 更新已有记录的情感标签
+                    cache_record.emotion_tags = emotion_tags_str
+                    cache_record.timestamp = time.time()
+                    cache_record.save()
+                    logger.info(f"[缓存更新] 表情包情感标签已更新到EmojiDescriptionCache: {image_hash[:8]}...")
+                else:
+                    # 如果缓存不存在，创建新记录（包含描述和情感标签）
+                    EmojiDescriptionCache.create(
+                        emoji_hash=image_hash,
+                        description=description,
+                        emotion_tags=emotion_tags_str,
+                        timestamp=time.time(),
+                    )
+                    logger.info(f"[缓存创建] 表情包描述和情感标签已保存到EmojiDescriptionCache: {image_hash[:8]}...")
+            except Exception as cache_error:
+                logger.debug(f"更新表情包情感标签缓存失败: {cache_error}")
+
             return f"[表情包：{description}]", emotions
 
         except Exception as e:

src/chat/replyer/group_generator.py

@@ -852,7 +852,7 @@ class DefaultReplyer:
         memory_retrieval: str = results_dict["memory_retrieval"]
         keywords_reaction_prompt = await self.build_keywords_reaction_prompt(target)
         mood_state_prompt: str = results_dict["mood_state_prompt"]
-        jargon_explanation: Optional[str] = results_dict.get("jargon_explanation")
+        jargon_explanation: str = results_dict.get("jargon_explanation") or ""
 
         # 从 chosen_actions 中提取 planner 的整体思考理由
         planner_reasoning = ""

src/chat/replyer/private_generator.py

@@ -773,7 +773,7 @@ class PrivateReplyer:
         mood_state_prompt: str = results_dict["mood_state_prompt"]
         memory_retrieval: str = results_dict["memory_retrieval"]
         keywords_reaction_prompt = await self.build_keywords_reaction_prompt(target)
-        jargon_explanation: Optional[str] = results_dict.get("jargon_explanation")
+        jargon_explanation: str = results_dict.get("jargon_explanation") or ""
 
         # 从 chosen_actions 中提取 planner 的整体思考理由
         planner_reasoning = ""

src/express/expression_learner.py

@@ -1,6 +1,7 @@
 import time
 import json
 import os
+import re
 from typing import List, Optional, Tuple
 import traceback
 from src.common.logger import get_logger
@@ -225,6 +226,19 @@ class ExpressionLearner:
         match_responses = []
         try:
             response = response.strip()
+            
+            # 尝试提取JSON代码块（如果存在）
+            json_pattern = r"```json\s*(.*?)\s*```"
+            matches = re.findall(json_pattern, response, re.DOTALL)
+            if matches:
+                response = matches[0].strip()
+            
+            # 移除可能的markdown代码块标记（如果没有找到```json，但可能有```）
+            if not matches:
+                response = re.sub(r"^```\s*", "", response, flags=re.MULTILINE)
+                response = re.sub(r"```\s*$", "", response, flags=re.MULTILINE)
+                response = response.strip()
+            
             # 检查是否已经是标准JSON数组格式
             if response.startswith("[") and response.endswith("]"):
                 match_responses = json.loads(response)
@@ -280,15 +294,60 @@ class ExpressionLearner:
                 logger.error(f"match_responses 不是列表或字典类型: {type(match_responses)}, 内容: {match_responses}")
                 return []
 
+        # 清理和规范化 match_responses 中的元素
+        normalized_responses = []
+        for item in match_responses:
+            if isinstance(item, dict):
+                # 已经是字典，直接添加
+                normalized_responses.append(item)
+            elif isinstance(item, str):
+                # 如果是字符串，尝试解析为 JSON
+                try:
+                    parsed = json.loads(item)
+                    if isinstance(parsed, dict):
+                        normalized_responses.append(parsed)
+                    elif isinstance(parsed, list):
+                        # 如果是列表，递归处理
+                        for sub_item in parsed:
+                            if isinstance(sub_item, dict):
+                                normalized_responses.append(sub_item)
+                            else:
+                                logger.debug(f"跳过非字典类型的子元素: {type(sub_item)}, 内容: {sub_item}")
+                    else:
+                        logger.debug(f"跳过无法转换为字典的字符串元素: {item}")
+                except (json.JSONDecodeError, TypeError):
+                    logger.debug(f"跳过无法解析为JSON的字符串元素: {item}")
+            elif isinstance(item, list):
+                # 如果是列表，展开并处理其中的字典
+                for sub_item in item:
+                    if isinstance(sub_item, dict):
+                        normalized_responses.append(sub_item)
+                    elif isinstance(sub_item, str):
+                        # 尝试解析字符串
+                        try:
+                            parsed = json.loads(sub_item)
+                            if isinstance(parsed, dict):
+                                normalized_responses.append(parsed)
+                            else:
+                                logger.debug(f"跳过非字典类型的解析结果: {type(parsed)}, 内容: {parsed}")
+                        except (json.JSONDecodeError, TypeError):
+                            logger.debug(f"跳过无法解析为JSON的字符串子元素: {sub_item}")
+                    else:
+                        logger.debug(f"跳过非字典类型的列表元素: {type(sub_item)}, 内容: {sub_item}")
+            else:
+                logger.debug(f"跳过无法处理的元素类型: {type(item)}, 内容: {item}")
+
+        match_responses = normalized_responses
+
         matched_expressions = []
         used_pair_indices = set()  # 用于跟踪已经使用的expression_pair索引
 
-        logger.debug(f"match_responses 类型: {type(match_responses)}, 长度: {len(match_responses)}")
+        logger.debug(f"规范化后的 match_responses 类型: {type(match_responses)}, 长度: {len(match_responses)}")
-        logger.debug(f"match_responses 内容: {match_responses}")
+        logger.debug(f"规范化后的 match_responses 内容: {match_responses}")
 
         for match_response in match_responses:
             try:
-                # 检查 match_response 的类型
+                # 检查 match_response 的类型（此时应该都是字典）
                 if not isinstance(match_response, dict):
                     logger.error(f"match_response 不是字典类型: {type(match_response)}, 内容: {match_response}")
                     continue