fix：修复引用回复逻辑

2025-05-02 02:03:24 +08:00
parent 1ca736cc32
commit 974839c1b5
14 changed files with 194 additions and 155 deletions
--- a/src/heart_flow/background_tasks.py
+++ b/src/heart_flow/background_tasks.py
@@ -18,7 +18,7 @@ INTEREST_EVAL_INTERVAL_SECONDS = 5
 # 新增聊天超时检查间隔
 NORMAL_CHAT_TIMEOUT_CHECK_INTERVAL_SECONDS = 60
 # 新增状态评估间隔
-HF_JUDGE_STATE_UPDATE_INTERVAL_SECONDS = 60
+HF_JUDGE_STATE_UPDATE_INTERVAL_SECONDS = 20
 # 新增私聊激活检查间隔
 PRIVATE_CHAT_ACTIVATION_CHECK_INTERVAL_SECONDS = 5  # 与兴趣评估类似，设为5秒

--- a/src/heart_flow/observation.py
+++ b/src/heart_flow/observation.py
@@ -14,6 +14,8 @@ from src.plugins.utils.chat_message_builder import (
 )
 from src.plugins.utils.prompt_builder import Prompt, global_prompt_manager
 from typing import Optional
+import difflib
+from src.plugins.chat.message import MessageRecv  # 添加 MessageRecv 导入

 # Import the new utility function
 from .utils_chat import get_chat_type_and_target_info
@@ -227,6 +229,70 @@ class ChattingObservation(Observation):
            f"Chat {self.chat_id} - 压缩早期记忆：{self.mid_memory_info}\n现在聊天内容：{self.talking_message_str}"
        )

+    async def find_best_matching_message(self, search_str: str, min_similarity: float = 0.6) -> Optional[MessageRecv]:
+        """
+        在 talking_message 中查找与 search_str 最匹配的消息。
+
+        Args:
+            search_str: 要搜索的字符串。
+            min_similarity: 要求的最低相似度（0到1之间）。
+
+        Returns:
+            匹配的 MessageRecv 实例，如果找不到则返回 None。
+        """
+        best_match_score = -1.0
+        best_match_dict = None
+
+        if not self.talking_message:
+            logger.debug(f"Chat {self.chat_id}: talking_message is empty, cannot find match for '{search_str}'")
+            return None
+
+        for message_dict in self.talking_message:
+            try:
+                # 临时创建 MessageRecv 以处理文本
+                temp_msg = MessageRecv(message_dict)
+                await temp_msg.process()  # 处理消息以获取 processed_plain_text
+                current_text = temp_msg.processed_plain_text
+
+                if not current_text:  # 跳过没有文本内容的消息
+                    continue
+
+                # 计算相似度
+                matcher = difflib.SequenceMatcher(None, search_str, current_text)
+                score = matcher.ratio()
+
+                # logger.debug(f"Comparing '{search_str}' with '{current_text}', score: {score}") # 可选：用于调试
+
+                if score > best_match_score:
+                    best_match_score = score
+                    best_match_dict = message_dict
+
+            except Exception as e:
+                logger.error(f"Error processing message for matching in chat {self.chat_id}: {e}", exc_info=True)
+                continue  # 继续处理下一条消息
+
+        if best_match_dict is not None and best_match_score >= min_similarity:
+            logger.debug(f"Found best match for '{search_str}' with score {best_match_score:.2f}")
+            try:
+                final_msg = MessageRecv(best_match_dict)
+                await final_msg.process()
+                # 确保 MessageRecv 实例有关联的 chat_stream
+                if hasattr(self, "chat_stream"):
+                    final_msg.update_chat_stream(self.chat_stream)
+                else:
+                    logger.warning(
+                        f"ChattingObservation instance for chat {self.chat_id} does not have a chat_stream attribute set."
+                    )
+                return final_msg
+            except Exception as e:
+                logger.error(f"Error creating final MessageRecv for chat {self.chat_id}: {e}", exc_info=True)
+                return None
+        else:
+            logger.debug(
+                f"No suitable match found for '{search_str}' in chat {self.chat_id} (best score: {best_match_score:.2f}, threshold: {min_similarity})"
+            )
+            return None
+
    async def has_new_messages_since(self, timestamp: float) -> bool:
        """检查指定时间戳之后是否有新消息"""
        count = num_new_messages_since(chat_id=self.chat_id, timestamp_start=timestamp)
--- a/src/heart_flow/sub_mind.py
+++ b/src/heart_flow/sub_mind.py
@@ -1,4 +1,4 @@
-from .observation import Observation, ChattingObservation
+from .observation import ChattingObservation
 from src.plugins.models.utils_model import LLMRequest
 from src.config.config import global_config
 import time
@@ -146,10 +146,9 @@ class SubMind:
        lines = ["【信息】"]
        for item in self.structured_info:
            # 简化展示，突出内容和类型，包含TTL供调试
-            type_str = item.get('type', '未知类型')
-            content_str = item.get('content', '')
-            ttl = item.get('ttl', '?')
-            
+            type_str = item.get("type", "未知类型")
+            content_str = item.get("content", "")
+
            if type_str == "info":
                lines.append(f"刚刚: {content_str}")
            elif type_str == "memory":
@@ -178,18 +177,24 @@ class SubMind:

        # ---------- 0. 更新和清理 structured_info ----------
        if self.structured_info:
-            logger.debug(f"{self.log_prefix} 更新前的 structured_info: {safe_json_dumps(self.structured_info, ensure_ascii=False)}")
+            logger.debug(
+                f"{self.log_prefix} 更新前的 structured_info: {safe_json_dumps(self.structured_info, ensure_ascii=False)}"
+            )
            updated_info = []
            for item in self.structured_info:
-                item['ttl'] -= 1
-                if item['ttl'] > 0:
+                item["ttl"] -= 1
+                if item["ttl"] > 0:
                    updated_info.append(item)
                else:
                    logger.debug(f"{self.log_prefix} 移除过期的 structured_info 项: {item['id']}")
            self.structured_info = updated_info
-            logger.debug(f"{self.log_prefix} 更新后的 structured_info: {safe_json_dumps(self.structured_info, ensure_ascii=False)}")
+            logger.debug(
+                f"{self.log_prefix} 更新后的 structured_info: {safe_json_dumps(self.structured_info, ensure_ascii=False)}"
+            )
            self._update_structured_info_str()
-        logger.debug(f"{self.log_prefix} 当前完整的 structured_info: {safe_json_dumps(self.structured_info, ensure_ascii=False)}")
+        logger.debug(
+            f"{self.log_prefix} 当前完整的 structured_info: {safe_json_dumps(self.structured_info, ensure_ascii=False)}"
+        )

        # ---------- 1. 准备基础数据 ----------
        # 获取现有想法和情绪状态
@@ -202,10 +207,10 @@ class SubMind:
            logger.error(f"{self.log_prefix} 无法获取有效的观察对象或缺少聊天类型信息")
            self.update_current_mind("(观察出错了...)")
            return self.current_mind, self.past_mind
-        
+
        is_group_chat = observation.is_group_chat
        # logger.debug(f"is_group_chat: {is_group_chat}")
-        
+
        chat_target_info = observation.chat_target_info
        chat_target_name = "对方"  # Default for private
        if not is_group_chat and chat_target_info:
@@ -496,7 +501,7 @@ class SubMind:
            tool_instance: 工具使用器实例
        """
        tool_results = []
-        new_structured_items = [] # 收集新产生的结构化信息
+        new_structured_items = []  # 收集新产生的结构化信息

        # 执行所有工具调用
        for tool_call in tool_calls:
@@ -506,26 +511,26 @@ class SubMind:
                    tool_results.append(result)
                    # 创建新的结构化信息项
                    new_item = {
-                        "type": result.get("type", "unknown_type"), # 使用 'type' 键
-                        "id": result.get("id", f"fallback_id_{time.time()}"), # 使用 'id' 键
-                        "content": result.get("content", ""), # 'content' 键保持不变
-                        "ttl": 3
+                        "type": result.get("type", "unknown_type"),  # 使用 'type' 键
+                        "id": result.get("id", f"fallback_id_{time.time()}"),  # 使用 'id' 键
+                        "content": result.get("content", ""),  # 'content' 键保持不变
+                        "ttl": 3,
                    }
                    new_structured_items.append(new_item)

            except Exception as tool_e:
                logger.error(f"[{self.subheartflow_id}] 工具执行失败: {tool_e}")
-                logger.error(traceback.format_exc()) # 添加 traceback 记录
+                logger.error(traceback.format_exc())  # 添加 traceback 记录

        # 如果有新的工具结果，记录并更新结构化信息
        if new_structured_items:
-            self.structured_info.extend(new_structured_items) # 添加到现有列表
+            self.structured_info.extend(new_structured_items)  # 添加到现有列表
            logger.debug(f"工具调用收集到新的结构化信息: {safe_json_dumps(new_structured_items, ensure_ascii=False)}")
            # logger.debug(f"当前完整的 structured_info: {safe_json_dumps(self.structured_info, ensure_ascii=False)}") # 可以取消注释以查看完整列表
-            self._update_structured_info_str() # 添加新信息后，更新字符串表示
+            self._update_structured_info_str()  # 添加新信息后，更新字符串表示

    def update_current_mind(self, response):
-        if self.current_mind: # 只有当 current_mind 非空时才添加到 past_mind
+        if self.current_mind:  # 只有当 current_mind 非空时才添加到 past_mind
            self.past_mind.append(self.current_mind)
            # 可以考虑限制 past_mind 的大小，例如:
            # max_past_mind_size = 10
--- a/src/heart_flow/subheartflow_manager.py
+++ b/src/heart_flow/subheartflow_manager.py
@@ -128,7 +128,7 @@ class SubHeartflowManager:
                # 添加聊天观察者
                observation = ChattingObservation(chat_id=subheartflow_id)
                await observation.initialize()
-                
+
                new_subflow.add_observation(observation)

                # 注册子心流