diff --git a/scripts/log_viewer_optimized.py b/log_viewer/log_viewer_optimized.py similarity index 100% rename from scripts/log_viewer_optimized.py rename to log_viewer/log_viewer_optimized.py diff --git a/scripts/interest_value_analysis.py b/scripts/interest_value_analysis.py deleted file mode 100644 index bce37b4a..00000000 --- a/scripts/interest_value_analysis.py +++ /dev/null @@ -1,285 +0,0 @@ -import time -import sys -import os -from typing import Dict, List, Tuple, Optional -from datetime import datetime - -# Add project root to Python path -project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) -sys.path.insert(0, project_root) -from src.common.database.database_model import Messages, ChatStreams # noqa - - -def get_chat_name(chat_id: str) -> str: - """Get chat name from chat_id by querying ChatStreams table directly""" - try: - chat_stream = ChatStreams.get_or_none(ChatStreams.stream_id == chat_id) - if chat_stream is None: - return f"未知聊天 ({chat_id})" - - if chat_stream.group_name: - return f"{chat_stream.group_name} ({chat_id})" - elif chat_stream.user_nickname: - return f"{chat_stream.user_nickname}的私聊 ({chat_id})" - else: - return f"未知聊天 ({chat_id})" - except Exception: - return f"查询失败 ({chat_id})" - - -def format_timestamp(timestamp: float) -> str: - """Format timestamp to readable date string""" - try: - return datetime.fromtimestamp(timestamp).strftime("%Y-%m-%d %H:%M:%S") - except (ValueError, OSError): - return "未知时间" - - -def calculate_interest_value_distribution(messages) -> Dict[str, int]: - """Calculate distribution of interest_value""" - distribution = { - "0.000-0.010": 0, - "0.010-0.050": 0, - "0.050-0.100": 0, - "0.100-0.500": 0, - "0.500-1.000": 0, - "1.000-2.000": 0, - "2.000-5.000": 0, - "5.000-10.000": 0, - "10.000+": 0, - } - - for msg in messages: - if msg.interest_value is None or msg.interest_value == 0.0: - continue - - value = float(msg.interest_value) - if value < 0.010: - distribution["0.000-0.010"] += 1 - elif value < 0.050: - distribution["0.010-0.050"] += 1 - elif value < 0.100: - distribution["0.050-0.100"] += 1 - elif value < 0.500: - distribution["0.100-0.500"] += 1 - elif value < 1.000: - distribution["0.500-1.000"] += 1 - elif value < 2.000: - distribution["1.000-2.000"] += 1 - elif value < 5.000: - distribution["2.000-5.000"] += 1 - elif value < 10.000: - distribution["5.000-10.000"] += 1 - else: - distribution["10.000+"] += 1 - - return distribution - - -def get_interest_value_stats(messages) -> Dict[str, float]: - """Calculate basic statistics for interest_value""" - values = [ - float(msg.interest_value) for msg in messages if msg.interest_value is not None and msg.interest_value != 0.0 - ] - - if not values: - return {"count": 0, "min": 0, "max": 0, "avg": 0, "median": 0} - - values.sort() - count = len(values) - - return { - "count": count, - "min": min(values), - "max": max(values), - "avg": sum(values) / count, - "median": values[count // 2] if count % 2 == 1 else (values[count // 2 - 1] + values[count // 2]) / 2, - } - - -def get_available_chats() -> List[Tuple[str, str, int]]: - """Get all available chats with message counts""" - try: - # 获取所有有消息的chat_id - chat_counts = {} - for msg in Messages.select(Messages.chat_id).distinct(): - chat_id = msg.chat_id - count = ( - Messages.select() - .where( - (Messages.chat_id == chat_id) - & (Messages.interest_value.is_null(False)) - & (Messages.interest_value != 0.0) - ) - .count() - ) - if count > 0: - chat_counts[chat_id] = count - - # 获取聊天名称 - result = [] - for chat_id, count in chat_counts.items(): - chat_name = get_chat_name(chat_id) - result.append((chat_id, chat_name, count)) - - # 按消息数量排序 - result.sort(key=lambda x: x[2], reverse=True) - return result - except Exception as e: - print(f"获取聊天列表失败: {e}") - return [] - - -def get_time_range_input() -> Tuple[Optional[float], Optional[float]]: - """Get time range input from user""" - print("\n时间范围选择:") - print("1. 最近1天") - print("2. 最近3天") - print("3. 最近7天") - print("4. 最近30天") - print("5. 自定义时间范围") - print("6. 不限制时间") - - choice = input("请选择时间范围 (1-6): ").strip() - - now = time.time() - - if choice == "1": - return now - 24 * 3600, now - elif choice == "2": - return now - 3 * 24 * 3600, now - elif choice == "3": - return now - 7 * 24 * 3600, now - elif choice == "4": - return now - 30 * 24 * 3600, now - elif choice == "5": - print("请输入开始时间 (格式: YYYY-MM-DD HH:MM:SS):") - start_str = input().strip() - print("请输入结束时间 (格式: YYYY-MM-DD HH:MM:SS):") - end_str = input().strip() - - try: - start_time = datetime.strptime(start_str, "%Y-%m-%d %H:%M:%S").timestamp() - end_time = datetime.strptime(end_str, "%Y-%m-%d %H:%M:%S").timestamp() - return start_time, end_time - except ValueError: - print("时间格式错误，将不限制时间范围") - return None, None - else: - return None, None - - -def analyze_interest_values( - chat_id: Optional[str] = None, start_time: Optional[float] = None, end_time: Optional[float] = None -) -> None: - """Analyze interest values with optional filters""" - - # 构建查询条件 - query = Messages.select().where((Messages.interest_value.is_null(False)) & (Messages.interest_value != 0.0)) - - if chat_id: - query = query.where(Messages.chat_id == chat_id) - - if start_time: - query = query.where(Messages.time >= start_time) - - if end_time: - query = query.where(Messages.time <= end_time) - - messages = list(query) - - if not messages: - print("没有找到符合条件的消息") - return - - # 计算统计信息 - distribution = calculate_interest_value_distribution(messages) - stats = get_interest_value_stats(messages) - - # 显示结果 - print("\n=== Interest Value 分析结果 ===") - if chat_id: - print(f"聊天: {get_chat_name(chat_id)}") - else: - print("聊天: 全部聊天") - - if start_time and end_time: - print(f"时间范围: {format_timestamp(start_time)} 到 {format_timestamp(end_time)}") - elif start_time: - print(f"时间范围: {format_timestamp(start_time)} 之后") - elif end_time: - print(f"时间范围: {format_timestamp(end_time)} 之前") - else: - print("时间范围: 不限制") - - print("\n基本统计:") - print(f"有效消息数量: {stats['count']} (排除null和0值)") - print(f"最小值: {stats['min']:.3f}") - print(f"最大值: {stats['max']:.3f}") - print(f"平均值: {stats['avg']:.3f}") - print(f"中位数: {stats['median']:.3f}") - - print("\nInterest Value 分布:") - total = stats["count"] - for range_name, count in distribution.items(): - if count > 0: - percentage = count / total * 100 - print(f"{range_name}: {count} ({percentage:.2f}%)") - - -def interactive_menu() -> None: - """Interactive menu for interest value analysis""" - - while True: - print("\n" + "=" * 50) - print("Interest Value 分析工具") - print("=" * 50) - print("1. 分析全部聊天") - print("2. 选择特定聊天分析") - print("q. 退出") - - choice = input("\n请选择分析模式 (1-2, q): ").strip() - - if choice.lower() == "q": - print("再见！") - break - - chat_id = None - - if choice == "2": - # 显示可用的聊天列表 - chats = get_available_chats() - if not chats: - print("没有找到有interest_value数据的聊天") - continue - - print(f"\n可用的聊天 (共{len(chats)}个):") - for i, (_cid, name, count) in enumerate(chats, 1): - print(f"{i}. {name} ({count}条有效消息)") - - try: - chat_choice = int(input(f"\n请选择聊天 (1-{len(chats)}): ").strip()) - if 1 <= chat_choice <= len(chats): - chat_id = chats[chat_choice - 1][0] - else: - print("无效选择") - continue - except ValueError: - print("请输入有效数字") - continue - - elif choice != "1": - print("无效选择") - continue - - # 获取时间范围 - start_time, end_time = get_time_range_input() - - # 执行分析 - analyze_interest_values(chat_id, start_time, end_time) - - input("\n按回车键继续...") - - -if __name__ == "__main__": - interactive_menu() diff --git a/scripts/text_length_analysis.py b/scripts/text_length_analysis.py deleted file mode 100644 index 5a329b93..00000000 --- a/scripts/text_length_analysis.py +++ /dev/null @@ -1,397 +0,0 @@ -import time -import sys -import os -import re -from typing import Dict, List, Tuple, Optional -from datetime import datetime - -# Add project root to Python path -project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) -sys.path.insert(0, project_root) -from src.common.database.database_model import Messages, ChatStreams # noqa - - -def contains_emoji_or_image_tags(text: str) -> bool: - """Check if text contains [表情包xxxxx] or [图片xxxxx] tags""" - if not text: - return False - - # 检查是否包含 [表情包] 或 [图片] 标记 - emoji_pattern = r"\[表情包[^\]]*\]" - image_pattern = r"\[图片[^\]]*\]" - - return bool(re.search(emoji_pattern, text) or re.search(image_pattern, text)) - - -def clean_reply_text(text: str) -> str: - """Remove reply references like [回复 xxxx...] from text""" - if not text: - return text - - # 匹配 [回复 xxxx...] 格式的内容 - # 使用非贪婪匹配，匹配到第一个 ] 就停止 - cleaned_text = re.sub(r"\[回复[^\]]*\]", "", text) - - # 去除多余的空白字符 - cleaned_text = cleaned_text.strip() - - return cleaned_text - - -def get_chat_name(chat_id: str) -> str: - """Get chat name from chat_id by querying ChatStreams table directly""" - try: - chat_stream = ChatStreams.get_or_none(ChatStreams.stream_id == chat_id) - if chat_stream is None: - return f"未知聊天 ({chat_id})" - - if chat_stream.group_name: - return f"{chat_stream.group_name} ({chat_id})" - elif chat_stream.user_nickname: - return f"{chat_stream.user_nickname}的私聊 ({chat_id})" - else: - return f"未知聊天 ({chat_id})" - except Exception: - return f"查询失败 ({chat_id})" - - -def format_timestamp(timestamp: float) -> str: - """Format timestamp to readable date string""" - try: - return datetime.fromtimestamp(timestamp).strftime("%Y-%m-%d %H:%M:%S") - except (ValueError, OSError): - return "未知时间" - - -def calculate_text_length_distribution(messages) -> Dict[str, int]: - """Calculate distribution of processed_plain_text length""" - distribution = { - "0": 0, # 空文本 - "1-5": 0, # 极短文本 - "6-10": 0, # 很短文本 - "11-20": 0, # 短文本 - "21-30": 0, # 较短文本 - "31-50": 0, # 中短文本 - "51-70": 0, # 中等文本 - "71-100": 0, # 较长文本 - "101-150": 0, # 长文本 - "151-200": 0, # 很长文本 - "201-300": 0, # 超长文本 - "301-500": 0, # 极长文本 - "501-1000": 0, # 巨长文本 - "1000+": 0, # 超巨长文本 - } - - for msg in messages: - if msg.processed_plain_text is None: - continue - - # 排除包含表情包或图片标记的消息 - if contains_emoji_or_image_tags(msg.processed_plain_text): - continue - - # 清理文本中的回复引用 - cleaned_text = clean_reply_text(msg.processed_plain_text) - length = len(cleaned_text) - - if length == 0: - distribution["0"] += 1 - elif length <= 5: - distribution["1-5"] += 1 - elif length <= 10: - distribution["6-10"] += 1 - elif length <= 20: - distribution["11-20"] += 1 - elif length <= 30: - distribution["21-30"] += 1 - elif length <= 50: - distribution["31-50"] += 1 - elif length <= 70: - distribution["51-70"] += 1 - elif length <= 100: - distribution["71-100"] += 1 - elif length <= 150: - distribution["101-150"] += 1 - elif length <= 200: - distribution["151-200"] += 1 - elif length <= 300: - distribution["201-300"] += 1 - elif length <= 500: - distribution["301-500"] += 1 - elif length <= 1000: - distribution["501-1000"] += 1 - else: - distribution["1000+"] += 1 - - return distribution - - -def get_text_length_stats(messages) -> Dict[str, float]: - """Calculate basic statistics for processed_plain_text length""" - lengths = [] - null_count = 0 - excluded_count = 0 # 被排除的消息数量 - - for msg in messages: - if msg.processed_plain_text is None: - null_count += 1 - elif contains_emoji_or_image_tags(msg.processed_plain_text): - # 排除包含表情包或图片标记的消息 - excluded_count += 1 - else: - # 清理文本中的回复引用 - cleaned_text = clean_reply_text(msg.processed_plain_text) - lengths.append(len(cleaned_text)) - - if not lengths: - return { - "count": 0, - "null_count": null_count, - "excluded_count": excluded_count, - "min": 0, - "max": 0, - "avg": 0, - "median": 0, - } - - lengths.sort() - count = len(lengths) - - return { - "count": count, - "null_count": null_count, - "excluded_count": excluded_count, - "min": min(lengths), - "max": max(lengths), - "avg": sum(lengths) / count, - "median": lengths[count // 2] if count % 2 == 1 else (lengths[count // 2 - 1] + lengths[count // 2]) / 2, - } - - -def get_available_chats() -> List[Tuple[str, str, int]]: - """Get all available chats with message counts""" - try: - # 获取所有有消息的chat_id，排除特殊类型消息 - chat_counts = {} - for msg in Messages.select(Messages.chat_id).distinct(): - chat_id = msg.chat_id - count = ( - Messages.select() - .where( - (Messages.chat_id == chat_id) - & (Messages.is_emoji != 1) - & (Messages.is_picid != 1) - & (Messages.is_command != 1) - ) - .count() - ) - if count > 0: - chat_counts[chat_id] = count - - # 获取聊天名称 - result = [] - for chat_id, count in chat_counts.items(): - chat_name = get_chat_name(chat_id) - result.append((chat_id, chat_name, count)) - - # 按消息数量排序 - result.sort(key=lambda x: x[2], reverse=True) - return result - except Exception as e: - print(f"获取聊天列表失败: {e}") - return [] - - -def get_time_range_input() -> Tuple[Optional[float], Optional[float]]: - """Get time range input from user""" - print("\n时间范围选择:") - print("1. 最近1天") - print("2. 最近3天") - print("3. 最近7天") - print("4. 最近30天") - print("5. 自定义时间范围") - print("6. 不限制时间") - - choice = input("请选择时间范围 (1-6): ").strip() - - now = time.time() - - if choice == "1": - return now - 24 * 3600, now - elif choice == "2": - return now - 3 * 24 * 3600, now - elif choice == "3": - return now - 7 * 24 * 3600, now - elif choice == "4": - return now - 30 * 24 * 3600, now - elif choice == "5": - print("请输入开始时间 (格式: YYYY-MM-DD HH:MM:SS):") - start_str = input().strip() - print("请输入结束时间 (格式: YYYY-MM-DD HH:MM:SS):") - end_str = input().strip() - - try: - start_time = datetime.strptime(start_str, "%Y-%m-%d %H:%M:%S").timestamp() - end_time = datetime.strptime(end_str, "%Y-%m-%d %H:%M:%S").timestamp() - return start_time, end_time - except ValueError: - print("时间格式错误，将不限制时间范围") - return None, None - else: - return None, None - - -def get_top_longest_messages(messages, top_n: int = 10) -> List[Tuple[str, int, str, str]]: - """Get top N longest messages""" - message_lengths = [] - - for msg in messages: - if msg.processed_plain_text is not None: - # 排除包含表情包或图片标记的消息 - if contains_emoji_or_image_tags(msg.processed_plain_text): - continue - - # 清理文本中的回复引用 - cleaned_text = clean_reply_text(msg.processed_plain_text) - length = len(cleaned_text) - chat_name = get_chat_name(msg.chat_id) - time_str = format_timestamp(msg.time) - # 截取前100个字符作为预览 - preview = cleaned_text[:100] + "..." if len(cleaned_text) > 100 else cleaned_text - message_lengths.append((chat_name, length, time_str, preview)) - - # 按长度排序，取前N个 - message_lengths.sort(key=lambda x: x[1], reverse=True) - return message_lengths[:top_n] - - -def analyze_text_lengths( - chat_id: Optional[str] = None, start_time: Optional[float] = None, end_time: Optional[float] = None -) -> None: - """Analyze processed_plain_text lengths with optional filters""" - - # 构建查询条件，排除特殊类型的消息 - query = Messages.select().where((Messages.is_emoji != 1) & (Messages.is_picid != 1) & (Messages.is_command != 1)) - - if chat_id: - query = query.where(Messages.chat_id == chat_id) - - if start_time: - query = query.where(Messages.time >= start_time) - - if end_time: - query = query.where(Messages.time <= end_time) - - messages = list(query) - - if not messages: - print("没有找到符合条件的消息") - return - - # 计算统计信息 - distribution = calculate_text_length_distribution(messages) - stats = get_text_length_stats(messages) - top_longest = get_top_longest_messages(messages, 10) - - # 显示结果 - print("\n=== Processed Plain Text 长度分析结果 ===") - print("(已排除表情、图片ID、命令类型消息，已排除[表情包]和[图片]标记消息，已清理回复引用)") - if chat_id: - print(f"聊天: {get_chat_name(chat_id)}") - else: - print("聊天: 全部聊天") - - if start_time and end_time: - print(f"时间范围: {format_timestamp(start_time)} 到 {format_timestamp(end_time)}") - elif start_time: - print(f"时间范围: {format_timestamp(start_time)} 之后") - elif end_time: - print(f"时间范围: {format_timestamp(end_time)} 之前") - else: - print("时间范围: 不限制") - - print("\n基本统计:") - print(f"总消息数量: {len(messages)}") - print(f"有文本消息数量: {stats['count']}") - print(f"空文本消息数量: {stats['null_count']}") - print(f"被排除的消息数量: {stats['excluded_count']}") - if stats["count"] > 0: - print(f"最短长度: {stats['min']} 字符") - print(f"最长长度: {stats['max']} 字符") - print(f"平均长度: {stats['avg']:.2f} 字符") - print(f"中位数长度: {stats['median']:.2f} 字符") - - print("\n文本长度分布:") - total = stats["count"] - if total > 0: - for range_name, count in distribution.items(): - if count > 0: - percentage = count / total * 100 - print(f"{range_name} 字符: {count} ({percentage:.2f}%)") - - # 显示最长的消息 - if top_longest: - print(f"\n最长的 {len(top_longest)} 条消息:") - for i, (chat_name, length, time_str, preview) in enumerate(top_longest, 1): - print(f"{i}. [{chat_name}] {time_str}") - print(f" 长度: {length} 字符") - print(f" 预览: {preview}") - print() - - -def interactive_menu() -> None: - """Interactive menu for text length analysis""" - - while True: - print("\n" + "=" * 50) - print("Processed Plain Text 长度分析工具") - print("=" * 50) - print("1. 分析全部聊天") - print("2. 选择特定聊天分析") - print("q. 退出") - - choice = input("\n请选择分析模式 (1-2, q): ").strip() - - if choice.lower() == "q": - print("再见！") - break - - chat_id = None - - if choice == "2": - # 显示可用的聊天列表 - chats = get_available_chats() - if not chats: - print("没有找到聊天数据") - continue - - print(f"\n可用的聊天 (共{len(chats)}个):") - for i, (_cid, name, count) in enumerate(chats, 1): - print(f"{i}. {name} ({count}条消息)") - - try: - chat_choice = int(input(f"\n请选择聊天 (1-{len(chats)}): ").strip()) - if 1 <= chat_choice <= len(chats): - chat_id = chats[chat_choice - 1][0] - else: - print("无效选择") - continue - except ValueError: - print("请输入有效数字") - continue - - elif choice != "1": - print("无效选择") - continue - - # 获取时间范围 - start_time, end_time = get_time_range_input() - - # 执行分析 - analyze_text_lengths(chat_id, start_time, end_time) - - input("\n按回车键继续...") - - -if __name__ == "__main__": - interactive_menu() diff --git a/src/chat/brain_chat/brain_planner.py b/src/chat/brain_chat/brain_planner.py index 971a7356..30627a5b 100644 --- a/src/chat/brain_chat/brain_planner.py +++ b/src/chat/brain_chat/brain_planner.py @@ -492,7 +492,7 @@ class BrainPlanner: action.action_data = action.action_data or {} action.action_data["loop_start_time"] = loop_start_time - logger.info( + logger.debug( f"{self.log_prefix}规划器决定执行{len(actions)}个动作: {' '.join([a.action_type for a in actions])}" ) diff --git a/src/chat/heart_flow/heartFC_chat.py b/src/chat/heart_flow/heartFC_chat.py index 56d63fb4..b0cf9bbe 100644 --- a/src/chat/heart_flow/heartFC_chat.py +++ b/src/chat/heart_flow/heartFC_chat.py @@ -154,13 +154,16 @@ class HeartFChatting: # 记录循环信息和计时器结果 timer_strings = [] for name, elapsed in cycle_timers.items(): - formatted_time = f"{elapsed * 1000:.2f}毫秒" if elapsed < 1 else f"{elapsed:.2f}秒" + if elapsed < 0.1: + # 不显示小于0.1秒的计时器 + continue + formatted_time = f"{elapsed:.2f}秒" timer_strings.append(f"{name}: {formatted_time}") logger.info( f"{self.log_prefix} 第{self._current_cycle_detail.cycle_id}次思考," - f"耗时: {self._current_cycle_detail.end_time - self._current_cycle_detail.start_time:.1f}秒" # type: ignore - + (f"\n详情: {'; '.join(timer_strings)}" if timer_strings else "") + f"耗时: {self._current_cycle_detail.end_time - self._current_cycle_detail.start_time:.1f}秒;" # type: ignore + + (f"详情: {'; '.join(timer_strings)}" if timer_strings else "") ) async def _loopbody(self): # sourcery skip: hoist-if-from-if @@ -346,8 +349,8 @@ class HeartFChatting: ) logger.info( - f"{self.log_prefix}决定执行{len(action_to_use_info)}个动作: {' '.join([a.action_type for a in action_to_use_info])}" - ) + f"{self.log_prefix} 决定执行{len(action_to_use_info)}个动作: {' '.join([a.action_type for a in action_to_use_info])}" + ) # 3. 并行执行所有动作 action_tasks = [ diff --git a/src/chat/replyer/group_generator.py b/src/chat/replyer/group_generator.py index 69105eba..9ff77cd0 100644 --- a/src/chat/replyer/group_generator.py +++ b/src/chat/replyer/group_generator.py @@ -215,29 +215,30 @@ class DefaultReplyer: traceback.print_exc() return False, llm_response - async def build_relation_info(self, chat_content: str, sender: str, person_list: List[Person]): - if not global_config.relationship.enable_relationship: - return "" +#移动到 relation插件中构建 + # async def build_relation_info(self, chat_content: str, sender: str, person_list: List[Person]): + # if not global_config.relationship.enable_relationship: + # return "" - if not sender: - return "" + # if not sender: + # return "" - if sender == global_config.bot.nickname: - return "" + # if sender == global_config.bot.nickname: + # return "" - # 获取用户ID - person = Person(person_name=sender) - if not is_person_known(person_name=sender): - logger.warning(f"未找到用户 {sender} 的ID，跳过信息提取") - return f"你完全不认识{sender}，不理解ta的相关信息。" + # # 获取用户ID + # person = Person(person_name=sender) + # if not is_person_known(person_name=sender): + # logger.warning(f"未找到用户 {sender} 的ID，跳过信息提取") + # return f"你完全不认识{sender}，不理解ta的相关信息。" - sender_relation = await person.build_relationship(chat_content) - others_relation = "" - for person in person_list: - person_relation = await person.build_relationship() - others_relation += person_relation + # sender_relation = await person.build_relationship(chat_content) + # others_relation = "" + # for person in person_list: + # person_relation = await person.build_relationship() + # others_relation += person_relation - return f"{sender_relation}\n{others_relation}" + # return f"{sender_relation}\n{others_relation}" async def build_expression_habits(self, chat_history: str, target: str) -> Tuple[str, List[int]]: # sourcery skip: for-append-to-extend @@ -680,8 +681,8 @@ class DefaultReplyer: if person.is_known: person_list_short.append(person) - for person in person_list_short: - print(person.person_name) + # for person in person_list_short: + # print(person.person_name) chat_talking_prompt_short = build_readable_messages( message_list_before_short, @@ -956,7 +957,7 @@ class DefaultReplyer: prompt ) - logger.debug(f"replyer生成内容: {content}") + logger.info(f"使用{model_name}生成回复内容: {content}") return content, reasoning_content, model_name, tool_calls async def get_prompt_info(self, message: str, sender: str, target: str): diff --git a/src/chat/replyer/private_generator.py b/src/chat/replyer/private_generator.py index 65bd35dc..c134b64e 100644 --- a/src/chat/replyer/private_generator.py +++ b/src/chat/replyer/private_generator.py @@ -563,8 +563,8 @@ class PrivateReplyer: if person.is_known: person_list_short.append(person) - for person in person_list_short: - print(person.person_name) + # for person in person_list_short: + # print(person.person_name) chat_talking_prompt_short = build_readable_messages( message_list_before_short, @@ -829,7 +829,7 @@ class PrivateReplyer: prompt ) - logger.debug(f"replyer生成内容: {content}") + logger.info(f"使用 {model_name} 生成回复内容: {content}") return content, reasoning_content, model_name, tool_calls async def get_prompt_info(self, message: str, sender: str, target: str): diff --git a/src/common/logger.py b/src/common/logger.py index f980064f..c8bfa59e 100644 --- a/src/common/logger.py +++ b/src/common/logger.py @@ -363,8 +363,8 @@ MODULE_COLORS = { "planner": "\033[36m", "relation": "\033[38;5;139m", # 柔和的紫色，不刺眼 # 聊天相关模块 - "normal_chat": "\033[38;5;81m", # 亮蓝绿色 - "heartflow": "\033[38;5;175m", # 柔和的粉色，不显眼但保持粉色系 + "hfc": "\033[38;5;175m", # 柔和的粉色，不显眼但保持粉色系 + "bc": "\033[38;5;175m", # 柔和的粉色，不显眼但保持粉色系 "sub_heartflow": "\033[38;5;207m", # 粉紫色 "subheartflow_manager": "\033[38;5;201m", # 深粉色 "background_tasks": "\033[38;5;240m", # 灰色 @@ -372,8 +372,6 @@ MODULE_COLORS = { "chat_stream": "\033[38;5;51m", # 亮青色 "message_storage": "\033[38;5;33m", # 深蓝色 "expressor": "\033[38;5;166m", # 橙色 - # 专注聊天模块 - "memory_activator": "\033[38;5;117m", # 天蓝色 # 插件系统 "plugins": "\033[31m", # 红色 "plugin_api": "\033[33m", # 黄色 diff --git a/src/llm_models/utils_model.py b/src/llm_models/utils_model.py index b7a65842..78631d6b 100644 --- a/src/llm_models/utils_model.py +++ b/src/llm_models/utils_model.py @@ -148,6 +148,8 @@ class LLMRequest: ) logger.debug(f"LLM请求总耗时: {time.time() - start_time}") + logger.debug(f"LLM生成内容: {response}") + content = response.content reasoning_content = response.reasoning_content or "" tool_calls = response.tool_calls diff --git a/src/person_info/person_info.py b/src/person_info/person_info.py index 52ddfb9f..f4aeecc7 100644 --- a/src/person_info/person_info.py +++ b/src/person_info/person_info.py @@ -466,8 +466,8 @@ class Person: <分类1><分类2><分类3>...... 如果没有相关的分类，请输出""" response, _ = await relation_selection_model.generate_response_async(prompt) - print(prompt) - print(response) + # print(prompt) + # print(response) category_list = extract_categories_from_response(response) if "none" not in category_list: for category in category_list: diff --git a/src/plugin_system/apis/llm_api.py b/src/plugin_system/apis/llm_api.py index debb67d7..e454c486 100644 --- a/src/plugin_system/apis/llm_api.py +++ b/src/plugin_system/apis/llm_api.py @@ -66,8 +66,8 @@ async def generate_with_model( Tuple[bool, str, str, str]: (是否成功, 生成的内容, 推理过程, 模型名称) """ try: - model_name_list = model_config.model_list - logger.info(f"[LLMAPI] 使用模型集合 {model_name_list} 生成内容") + # model_name_list = model_config.model_list + # logger.info(f"[LLMAPI] 使用模型集合 {model_name_list} 生成内容") logger.debug(f"[LLMAPI] 完整提示词: {prompt}") llm_request = LLMRequest(model_set=model_config, request_type=request_type) diff --git a/src/plugin_system/apis/send_api.py b/src/plugin_system/apis/send_api.py index 6a43b586..e73504a4 100644 --- a/src/plugin_system/apis/send_api.py +++ b/src/plugin_system/apis/send_api.py @@ -100,7 +100,7 @@ async def _send_to_target( anchor_message: Union["MessageRecv", None] = None if reply_message: anchor_message = db_message_to_message_recv(reply_message) - logger.info(f"[SendAPI] 找到匹配的回复消息，发送者: {anchor_message.message_info.user_info.user_id}") # type: ignore + logger.debug(f"[SendAPI] 找到匹配的回复消息，发送者: {anchor_message.message_info.user_info.user_id}") # type: ignore if anchor_message: anchor_message.update_chat_stream(target_stream) assert anchor_message.message_info.user_info, "用户信息缺失" diff --git a/src/plugin_system/core/tool_use.py b/src/plugin_system/core/tool_use.py index 10a8b05d..56768a33 100644 --- a/src/plugin_system/core/tool_use.py +++ b/src/plugin_system/core/tool_use.py @@ -180,7 +180,6 @@ class ToolExecutor: tool_results.append(tool_info) used_tools.append(tool_name) - logger.info(f"{self.log_prefix}工具{tool_name}执行成功，类型: {tool_info['type']}") preview = content[:200] logger.debug(f"{self.log_prefix}工具{tool_name}结果内容: {preview}...") except Exception as e: