From 40c5763864e3ec8cf6fe247cc644ab8f6ea22de5 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Mon, 16 Jun 2025 05:48:17 +0000 Subject: [PATCH] =?UTF-8?q?=F0=9F=A4=96=20=E8=87=AA=E5=8A=A8=E6=A0=BC?= =?UTF-8?q?=E5=BC=8F=E5=8C=96=E4=BB=A3=E7=A0=81=20[skip=20ci]?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- scripts/log_viewer.py | 18 +-- src/chat/emoji_system/emoji_manager.py | 4 +- .../info/expression_selection_info.py | 12 +- .../expression_selector_processor.py | 110 +++++++++--------- .../focus_chat/planners/planner_simple.py | 2 +- .../focus_chat/replyer/default_replyer.py | 3 +- src/chat/utils/utils_image.py | 10 +- src/common/logger.py | 10 +- src/llm_models/utils_model.py | 2 +- 9 files changed, 84 insertions(+), 87 deletions(-) diff --git a/scripts/log_viewer.py b/scripts/log_viewer.py index 4cc42ccef..248919fa8 100644 --- a/scripts/log_viewer.py +++ b/scripts/log_viewer.py @@ -896,7 +896,7 @@ class LogViewer: if current_monitored_file != self.current_log_file: current_monitored_file = self.current_log_file last_position = 0 # 重置位置 - + if current_monitored_file.exists(): try: # 使用共享读取模式，避免文件锁定 @@ -1113,7 +1113,7 @@ class LogViewer: filename = filedialog.askopenfilename( title="选择日志文件", filetypes=[("JSONL日志文件", "*.jsonl"), ("所有文件", "*.*")], - initialdir="logs" if Path("logs").exists() else "." + initialdir="logs" if Path("logs").exists() else ".", ) if filename: new_file = Path(filename) @@ -1133,14 +1133,14 @@ class LogViewer: self.modules.clear() self.selected_modules.clear() self.log_text.delete(1.0, tk.END) - + # 清空日志队列 while not self.log_queue.empty(): try: self.log_queue.get_nowait() except queue.Empty: break - + # 重新读取整个文件 if self.current_log_file.exists(): try: @@ -1149,23 +1149,23 @@ class LogViewer: try: log_entry = json.loads(line) self.log_cache.append(log_entry) - + # 收集模块信息 if "logger_name" in log_entry: self.modules.add(log_entry["logger_name"]) - + except json.JSONDecodeError: continue except Exception as e: messagebox.showerror("错误", f"读取日志文件失败: {e}") return - + # 更新模块列表UI self.update_module_list() - + # 过滤并显示日志 self.filter_logs() - + # 更新窗口标题 self.update_window_title() diff --git a/src/chat/emoji_system/emoji_manager.py b/src/chat/emoji_system/emoji_manager.py index d1e5f6136..37f2f25f2 100644 --- a/src/chat/emoji_system/emoji_manager.py +++ b/src/chat/emoji_system/emoji_manager.py @@ -76,7 +76,7 @@ class MaiEmoji: logger.debug(f"[初始化] 正在解码Base64并计算哈希: {self.filename}") # 确保base64字符串只包含ASCII字符 if isinstance(image_base64, str): - image_base64 = image_base64.encode('ascii', errors='ignore').decode('ascii') + image_base64 = image_base64.encode("ascii", errors="ignore").decode("ascii") image_bytes = base64.b64decode(image_base64) self.hash = hashlib.md5(image_bytes).hexdigest() logger.debug(f"[初始化] 哈希计算成功: {self.hash}") @@ -846,7 +846,7 @@ class EmojiManager: # 解码图片并获取格式 # 确保base64字符串只包含ASCII字符 if isinstance(image_base64, str): - image_base64 = image_base64.encode('ascii', errors='ignore').decode('ascii') + image_base64 = image_base64.encode("ascii", errors="ignore").decode("ascii") image_bytes = base64.b64decode(image_base64) image_format = Image.open(io.BytesIO(image_bytes)).format.lower() diff --git a/src/chat/focus_chat/info/expression_selection_info.py b/src/chat/focus_chat/info/expression_selection_info.py index 9cdd6121d..9eaa0f4e0 100644 --- a/src/chat/focus_chat/info/expression_selection_info.py +++ b/src/chat/focus_chat/info/expression_selection_info.py @@ -1,5 +1,5 @@ from dataclasses import dataclass -from typing import List, Dict, Any +from typing import List, Dict from .info_base import InfoBase @@ -49,17 +49,17 @@ class ExpressionSelectionInfo(InfoBase): expressions = self.get_selected_expressions() if not expressions: return "" - + # 格式化表达方式为可读文本 formatted_expressions = [] for expr in expressions: situation = expr.get("situation", "") style = expr.get("style", "") - expr_type = expr.get("type", "") - + expr.get("type", "") + if situation and style: formatted_expressions.append(f"当{situation}时，使用 {style}") - + return "\n".join(formatted_expressions) def get_expressions_for_action_data(self) -> List[Dict[str, str]]: @@ -68,4 +68,4 @@ class ExpressionSelectionInfo(InfoBase): Returns: List[Dict[str, str]]: 格式化后的表达方式数据 """ - return self.get_selected_expressions() \ No newline at end of file + return self.get_selected_expressions() diff --git a/src/chat/focus_chat/info_processors/expression_selector_processor.py b/src/chat/focus_chat/info_processors/expression_selector_processor.py index 5b6275861..cd82afcdc 100644 --- a/src/chat/focus_chat/info_processors/expression_selector_processor.py +++ b/src/chat/focus_chat/info_processors/expression_selector_processor.py @@ -21,27 +21,27 @@ logger = get_logger("processor") def weighted_sample_no_replacement(items, weights, k) -> list: """ 加权随机抽样，不允许重复 - + Args: items: 待抽样的项目列表 weights: 对应项目的权重列表 k: 抽样数量 - + Returns: 抽样结果列表 """ if not items or k <= 0: return [] - + k = min(k, len(items)) selected = [] remaining_items = list(items) remaining_weights = list(weights) - + for _ in range(k): if not remaining_items: break - + # 计算累积权重 total_weight = sum(remaining_weights) if total_weight <= 0: @@ -57,13 +57,13 @@ def weighted_sample_no_replacement(items, weights, k) -> list: if rand_val <= cumulative_weight: selected_index = i break - + # 添加选中的项目 selected.append(remaining_items[selected_index]) # 移除已选中的项目 remaining_items.pop(selected_index) remaining_weights.pop(selected_index) - + return selected @@ -98,20 +98,20 @@ class ExpressionSelectorProcessor(BaseProcessor): def __init__(self, subheartflow_id: str): super().__init__() - + self.subheartflow_id = subheartflow_id self.last_selection_time = 0 self.selection_interval = 60 # 1分钟间隔 self.cached_expressions = [] # 缓存上一次选择的表达方式 - + # 表达方式选择模式 self.selection_mode = getattr(global_config.expression, "selection_mode", "llm") # "llm" 或 "random" - + self.llm_model = LLMRequest( model=global_config.model.utils_small, request_type="focus.processor.expression_selector", ) - + name = get_chat_manager().get_stream_name(self.subheartflow_id) self.log_prefix = f"[{name}] 表达选择器" @@ -125,7 +125,7 @@ class ExpressionSelectorProcessor(BaseProcessor): List[InfoBase]: 处理后的表达选择信息列表 """ current_time = time.time() - + # 检查频率限制 if current_time - self.last_selection_time < self.selection_interval: logger.debug(f"{self.log_prefix} 距离上次选择不足{self.selection_interval}秒，使用缓存的表达方式") @@ -133,17 +133,17 @@ class ExpressionSelectorProcessor(BaseProcessor): if self.cached_expressions: # 从缓存的15个中随机选5个 final_expressions = random.sample(self.cached_expressions, min(5, len(self.cached_expressions))) - + # 创建表达选择信息 expression_info = ExpressionSelectionInfo() expression_info.set_selected_expressions(final_expressions) - + logger.info(f"{self.log_prefix} 使用缓存选择了{len(final_expressions)}个表达方式") return [expression_info] else: logger.debug(f"{self.log_prefix} 没有缓存的表达方式，跳过选择") return [] - + # 获取聊天内容 chat_info = "" if observations: @@ -151,11 +151,11 @@ class ExpressionSelectorProcessor(BaseProcessor): if isinstance(observation, ChattingObservation): chat_info = observation.get_observe_info() break - + if not chat_info: logger.debug(f"{self.log_prefix} 没有聊天内容，跳过表达方式选择") return [] - + try: # 根据模式选择表达方式 if self.selection_mode == "llm": @@ -168,26 +168,26 @@ class ExpressionSelectorProcessor(BaseProcessor): selected_expressions = await self._select_suitable_expressions_random(chat_info) cache_size = len(selected_expressions) if selected_expressions else 0 mode_desc = f"随机模式（已缓存{cache_size}个）" - + if selected_expressions: # 缓存选择的表达方式 self.cached_expressions = selected_expressions # 更新最后选择时间 self.last_selection_time = current_time - + # 从选择的表达方式中随机选5个 final_expressions = random.sample(selected_expressions, min(4, len(selected_expressions))) - + # 创建表达选择信息 expression_info = ExpressionSelectionInfo() expression_info.set_selected_expressions(final_expressions) - + logger.info(f"{self.log_prefix} 为当前聊天选择了{len(final_expressions)}个表达方式（{mode_desc}）") return [expression_info] else: logger.debug(f"{self.log_prefix} 未选择任何表达方式") return [] - + except Exception as e: logger.error(f"{self.log_prefix} 处理表达方式选择时出错: {e}") return [] @@ -195,31 +195,31 @@ class ExpressionSelectorProcessor(BaseProcessor): async def _get_random_expressions(self) -> tuple[List[Dict], List[Dict], List[Dict]]: """随机获取表达方式：20个style，20个grammar，20个personality""" expression_learner = get_expression_learner() - + # 获取所有表达方式 ( learnt_style_expressions, learnt_grammar_expressions, personality_expressions, ) = await expression_learner.get_expression_by_chat_id(self.subheartflow_id) - + # 随机选择 selected_style = random.sample(learnt_style_expressions, min(15, len(learnt_style_expressions))) selected_grammar = random.sample(learnt_grammar_expressions, min(15, len(learnt_grammar_expressions))) selected_personality = random.sample(personality_expressions, min(5, len(personality_expressions))) - + return selected_style, selected_grammar, selected_personality async def _select_suitable_expressions_llm(self, chat_info: str) -> List[Dict[str, str]]: """使用LLM选择适合的表达方式""" - + # 1. 获取35个随机表达方式 style_exprs, grammar_exprs, personality_exprs = await self._get_random_expressions() - + # 2. 构建所有表达方式的索引和情境列表 all_expressions = [] all_situations = [] - + # 添加style表达方式 for expr in style_exprs: if isinstance(expr, dict) and "situation" in expr and "style" in expr: @@ -227,7 +227,7 @@ class ExpressionSelectorProcessor(BaseProcessor): expr_with_type["type"] = "style" all_expressions.append(expr_with_type) all_situations.append(f"{len(all_expressions)}. [语言风格] {expr['situation']}") - + # 添加grammar表达方式 for expr in grammar_exprs: if isinstance(expr, dict) and "situation" in expr and "style" in expr: @@ -235,7 +235,7 @@ class ExpressionSelectorProcessor(BaseProcessor): expr_with_type["type"] = "grammar" all_expressions.append(expr_with_type) all_situations.append(f"{len(all_expressions)}. [句法语法] {expr['situation']}") - + # 添加personality表达方式 for expr in personality_exprs: if isinstance(expr, dict) and "situation" in expr and "style" in expr: @@ -243,57 +243,57 @@ class ExpressionSelectorProcessor(BaseProcessor): expr_with_type["type"] = "personality" all_expressions.append(expr_with_type) all_situations.append(f"{len(all_expressions)}. [个性表达] {expr['situation']}") - + if not all_expressions: logger.warning(f"{self.log_prefix} 没有找到可用的表达方式") return [] - + all_situations_str = "\n".join(all_situations) - + # 3. 构建prompt（只包含情境，不包含完整的表达方式） prompt = (await global_prompt_manager.get_prompt_async("expression_evaluation_prompt")).format( bot_name=global_config.bot.nickname, chat_observe_info=chat_info, all_situations=all_situations_str, ) - + # 4. 调用LLM try: content, _ = await self.llm_model.generate_response_async(prompt=prompt) - + logger.info(f"{self.log_prefix} LLM返回结果: {content}") - + if not content: logger.warning(f"{self.log_prefix} LLM返回空结果") return [] - + # 5. 解析结果 result = repair_json(content) if isinstance(result, str): result = json.loads(result) - + if not isinstance(result, dict) or "selected_situations" not in result: logger.error(f"{self.log_prefix} LLM返回格式错误") return [] - + selected_indices = result["selected_situations"] - + # 根据索引获取完整的表达方式 valid_expressions = [] for idx in selected_indices: if isinstance(idx, int) and 1 <= idx <= len(all_expressions): valid_expressions.append(all_expressions[idx - 1]) # 索引从1开始 - + logger.info(f"{self.log_prefix} LLM从{len(all_expressions)}个情境中选择了{len(valid_expressions)}个") return valid_expressions - + except Exception as e: logger.error(f"{self.log_prefix} LLM处理表达方式选择时出错: {e}") return [] async def _select_suitable_expressions_random(self, chat_info: str) -> List[Dict[str, str]]: """随机选择表达方式（原replyer逻辑）""" - + # 获取所有表达方式 expression_learner = get_expression_learner() ( @@ -301,9 +301,9 @@ class ExpressionSelectorProcessor(BaseProcessor): learnt_grammar_expressions, personality_expressions, ) = await expression_learner.get_expression_by_chat_id(self.subheartflow_id) - + selected_expressions = [] - + # 1. learnt_style_expressions相似度匹配选择3条 if learnt_style_expressions: similar_exprs = self._find_similar_expressions(chat_info, learnt_style_expressions, 3) @@ -312,7 +312,7 @@ class ExpressionSelectorProcessor(BaseProcessor): expr_copy = expr.copy() expr_copy["type"] = "style" selected_expressions.append(expr_copy) - + # 2. learnt_grammar_expressions加权随机选2条 if learnt_grammar_expressions: weights = [expr.get("count", 1) for expr in learnt_grammar_expressions] @@ -322,7 +322,7 @@ class ExpressionSelectorProcessor(BaseProcessor): expr_copy = expr.copy() expr_copy["type"] = "grammar" selected_expressions.append(expr_copy) - + # 3. personality_expressions随机选1条 if personality_expressions: expr = random.choice(personality_expressions) @@ -330,7 +330,7 @@ class ExpressionSelectorProcessor(BaseProcessor): expr_copy = expr.copy() expr_copy["type"] = "personality" selected_expressions.append(expr_copy) - + logger.info(f"{self.log_prefix} 随机模式选择了{len(selected_expressions)}个表达方式") return selected_expressions @@ -338,28 +338,28 @@ class ExpressionSelectorProcessor(BaseProcessor): """使用简单的文本匹配找出相似的表达方式（简化版，避免依赖sklearn）""" if not expressions or not input_text: return random.sample(expressions, min(top_k, len(expressions))) if expressions else [] - + # 简单的关键词匹配 scored_expressions = [] input_words = set(input_text.lower().split()) - + for expr in expressions: situation = expr.get("situation", "").lower() situation_words = set(situation.split()) - + # 计算交集大小作为相似度 similarity = len(input_words & situation_words) scored_expressions.append((similarity, expr)) - + # 按相似度排序 scored_expressions.sort(key=lambda x: x[0], reverse=True) - + # 如果没有匹配的，随机选择 if all(score == 0 for score, _ in scored_expressions): return random.sample(expressions, min(top_k, len(expressions))) - + # 返回top_k个最相似的 return [expr for _, expr in scored_expressions[:top_k]] -init_prompt() \ No newline at end of file +init_prompt() diff --git a/src/chat/focus_chat/planners/planner_simple.py b/src/chat/focus_chat/planners/planner_simple.py index 8fe2dd209..6aa2a7e86 100644 --- a/src/chat/focus_chat/planners/planner_simple.py +++ b/src/chat/focus_chat/planners/planner_simple.py @@ -241,7 +241,7 @@ class ActionPlanner(BasePlanner): if relation_info: action_data["relation_info_block"] = relation_info - + # 将选中的表达方式传递给action_data if selected_expressions: action_data["selected_expressions"] = selected_expressions diff --git a/src/chat/focus_chat/replyer/default_replyer.py b/src/chat/focus_chat/replyer/default_replyer.py index c8d05ec41..16352af07 100644 --- a/src/chat/focus_chat/replyer/default_replyer.py +++ b/src/chat/focus_chat/replyer/default_replyer.py @@ -1,7 +1,6 @@ import traceback from typing import List, Optional, Dict, Any, Tuple -from src.chat.focus_chat.expressors.exprssion_learner import get_expression_learner from src.chat.message_receive.message import MessageRecv, MessageThinking, MessageSending from src.chat.message_receive.message import Seg # Local import needed after move from src.chat.message_receive.message import UserInfo @@ -350,7 +349,7 @@ class DefaultReplyer: # 使用从处理器传来的选中表达方式 selected_expressions = action_data.get("selected_expressions", []) if action_data else [] - + if selected_expressions: logger.info(f"{self.log_prefix} 使用处理器选中的{len(selected_expressions)}个表达方式") for expr in selected_expressions: diff --git a/src/chat/utils/utils_image.py b/src/chat/utils/utils_image.py index b592b25b5..70e0462d7 100644 --- a/src/chat/utils/utils_image.py +++ b/src/chat/utils/utils_image.py @@ -100,7 +100,7 @@ class ImageManager: # 计算图片哈希 # 确保base64字符串只包含ASCII字符 if isinstance(image_base64, str): - image_base64 = image_base64.encode('ascii', errors='ignore').decode('ascii') + image_base64 = image_base64.encode("ascii", errors="ignore").decode("ascii") image_bytes = base64.b64decode(image_base64) image_hash = hashlib.md5(image_bytes).hexdigest() image_format = Image.open(io.BytesIO(image_bytes)).format.lower() @@ -180,7 +180,7 @@ class ImageManager: # 计算图片哈希 # 确保base64字符串只包含ASCII字符 if isinstance(image_base64, str): - image_base64 = image_base64.encode('ascii', errors='ignore').decode('ascii') + image_base64 = image_base64.encode("ascii", errors="ignore").decode("ascii") image_bytes = base64.b64decode(image_base64) image_hash = hashlib.md5(image_bytes).hexdigest() image_format = Image.open(io.BytesIO(image_bytes)).format.lower() @@ -263,7 +263,7 @@ class ImageManager: try: # 确保base64字符串只包含ASCII字符 if isinstance(gif_base64, str): - gif_base64 = gif_base64.encode('ascii', errors='ignore').decode('ascii') + gif_base64 = gif_base64.encode("ascii", errors="ignore").decode("ascii") # 解码base64 gif_data = base64.b64decode(gif_base64) gif = Image.open(io.BytesIO(gif_data)) @@ -385,7 +385,7 @@ class ImageManager: # 计算图片哈希 # 确保base64字符串只包含ASCII字符 if isinstance(image_base64, str): - image_base64 = image_base64.encode('ascii', errors='ignore').decode('ascii') + image_base64 = image_base64.encode("ascii", errors="ignore").decode("ascii") image_bytes = base64.b64decode(image_base64) image_hash = hashlib.md5(image_bytes).hexdigest() @@ -458,7 +458,7 @@ class ImageManager: # 计算图片哈希 # 确保base64字符串只包含ASCII字符 if isinstance(image_base64, str): - image_base64 = image_base64.encode('ascii', errors='ignore').decode('ascii') + image_base64 = image_base64.encode("ascii", errors="ignore").decode("ascii") image_bytes = base64.b64decode(image_base64) image_hash = hashlib.md5(image_bytes).hexdigest() diff --git a/src/common/logger.py b/src/common/logger.py index ea3f0beaa..8f5963468 100644 --- a/src/common/logger.py +++ b/src/common/logger.py @@ -61,9 +61,7 @@ def get_console_handler(): class TimestampedFileHandler(logging.Handler): """基于时间戳的文件处理器，简单的轮转份数限制""" - def __init__( - self, log_dir, max_bytes=2 * 1024 * 1024, backup_count=30, encoding="utf-8" - ): + def __init__(self, log_dir, max_bytes=2 * 1024 * 1024, backup_count=30, encoding="utf-8"): super().__init__() self.log_dir = Path(log_dir) self.log_dir.mkdir(exist_ok=True) @@ -100,8 +98,6 @@ class TimestampedFileHandler(logging.Handler): # 创建新文件 self._init_current_file() - - def _cleanup_old_files(self): """清理旧的日志文件，保留指定数量""" try: @@ -922,7 +918,9 @@ def force_initialize_logging(): logger = get_logger("logger") console_level = LOG_CONFIG.get("console_log_level", LOG_CONFIG.get("log_level", "INFO")) file_level = LOG_CONFIG.get("file_log_level", LOG_CONFIG.get("log_level", "INFO")) - logger.info(f"日志系统已强制重新初始化，控制台级别: {console_level}，文件级别: {file_level}，轮转份数: 30个文件，所有logger格式已统一") + logger.info( + f"日志系统已强制重新初始化，控制台级别: {console_level}，文件级别: {file_level}，轮转份数: 30个文件，所有logger格式已统一" + ) def show_module_colors(): diff --git a/src/llm_models/utils_model.py b/src/llm_models/utils_model.py index 3740ab6cd..2dae39517 100644 --- a/src/llm_models/utils_model.py +++ b/src/llm_models/utils_model.py @@ -838,7 +838,7 @@ def compress_base64_image_by_scale(base64_data: str, target_size: int = 0.8 * 10 # 将base64转换为字节数据 # 确保base64字符串只包含ASCII字符 if isinstance(base64_data, str): - base64_data = base64_data.encode('ascii', errors='ignore').decode('ascii') + base64_data = base64_data.encode("ascii", errors="ignore").decode("ascii") image_data = base64.b64decode(base64_data) # 如果已经小于目标大小，直接返回原图