From e8833be89135131472953700ce7128d2713f8046 Mon Sep 17 00:00:00 2001 From: SXP-Simon Date: Sun, 8 Feb 2026 16:23:32 +0800 Subject: [PATCH] refactor: translate comments to Chinese and fix hardcoded OneBot format --- src/application/analysis_orchestrator.py | 146 +++++++++++------------ src/core/bot_manager.py | 78 +++++++----- 2 files changed, 118 insertions(+), 106 deletions(-) diff --git a/src/application/analysis_orchestrator.py b/src/application/analysis_orchestrator.py index ad5fa2d..c5c2f17 100644 --- a/src/application/analysis_orchestrator.py +++ b/src/application/analysis_orchestrator.py @@ -1,13 +1,12 @@ """ -Analysis Orchestrator - Application layer coordinator +分析编排器 - 应用层协调器 -This orchestrator bridges the new DDD architecture with the existing -analysis logic, providing a gradual migration path. +此编排器连接新的 DDD 架构与现有的分析逻辑，提供渐进式迁移路径。 -Architecture Decision: -- The orchestrator uses PlatformAdapter for message fetching (new DDD way) -- But delegates to existing analyzers for LLM analysis (preserving working code) -- MessageConverter provides bidirectional conversion for compatibility +架构决策： +- 编排器使用 PlatformAdapter 获取消息（新的 DDD 方式） +- 但将 LLM 分析委托给现有分析器（保留已工作的代码） +- MessageConverter 提供双向转换以保持兼容性 """ from typing import Optional, List, Dict, Any @@ -23,7 +22,7 @@ from .message_converter import MessageConverter @dataclass class AnalysisConfig: - """Configuration for analysis operation""" + """分析操作配置""" days: int = 1 max_messages: int = 1000 min_messages_threshold: int = 10 @@ -32,17 +31,17 @@ class AnalysisConfig: class AnalysisOrchestrator: """ - Analysis orchestrator - coordinates the analysis workflow. + 分析编排器 - 协调分析工作流。 - Responsibilities: - 1. Use PlatformAdapter to fetch messages (DDD approach) - 2. Convert messages for compatibility with existing analyzers - 3. Coordinate analysis flow - 4. Provide platform capability checks + 职责： + 1. 使用 PlatformAdapter 获取消息（DDD 方式） + 2. 转换消息以兼容现有分析器 + 3. 协调分析流程 + 4. 提供平台能力检查 - This class serves as the bridge between: - - New DDD infrastructure (PlatformAdapter, UnifiedMessage) - - Existing analysis logic (MessageHandler, LLMAnalyzer, etc.) + 此类作为以下组件之间的桥梁： + - 新的 DDD 基础设施（PlatformAdapter, UnifiedMessage） + - 现有分析逻辑（MessageHandler, LLMAnalyzer 等） """ def __init__( @@ -51,11 +50,11 @@ class AnalysisOrchestrator: config: AnalysisConfig = None, ): """ - Initialize the orchestrator. + 初始化编排器。 - Args: - adapter: Platform adapter for message operations - config: Analysis configuration + 参数： + adapter: 用于消息操作的平台适配器 + config: 分析配置 """ self.adapter = adapter self.config = config or AnalysisConfig() @@ -69,34 +68,34 @@ class AnalysisOrchestrator: analysis_config: AnalysisConfig = None, ) -> Optional["AnalysisOrchestrator"]: """ - Factory method to create orchestrator for a specific platform. + 工厂方法 - 为特定平台创建编排器。 - Args: - platform_name: Platform name (e.g., "aiocqhttp", "telegram") - bot_instance: Bot instance from AstrBot - config: Platform-specific config - analysis_config: Analysis configuration + 参数： + platform_name: 平台名称（如 "aiocqhttp", "telegram"） + bot_instance: 来自 AstrBot 的 bot 实例 + config: 平台特定配置 + analysis_config: 分析配置 - Returns: - AnalysisOrchestrator or None if platform not supported + 返回： + AnalysisOrchestrator 或 None（如果平台不支持） """ adapter = PlatformAdapterFactory.create(platform_name, bot_instance, config) if adapter is None: - logger.warning(f"Platform '{platform_name}' not supported for analysis") + logger.warning(f"平台 '{platform_name}' 不支持分析功能") return None return cls(adapter, analysis_config) def get_capabilities(self) -> PlatformCapabilities: - """Get platform capabilities.""" + """获取平台能力。""" return self.adapter.get_capabilities() def can_analyze(self) -> bool: - """Check if the platform supports analysis.""" + """检查平台是否支持分析。""" return self.adapter.get_capabilities().can_analyze() def can_send_report(self, format: str = "image") -> bool: - """Check if the platform can send reports in the specified format.""" + """检查平台是否能发送指定格式的报告。""" return self.adapter.get_capabilities().can_send_report(format) async def fetch_messages( @@ -106,28 +105,28 @@ class AnalysisOrchestrator: max_count: int = None, ) -> List[UnifiedMessage]: """ - Fetch messages using the platform adapter. + 使用平台适配器获取消息。 - Args: - group_id: Group ID to fetch messages from - days: Number of days (defaults to config) - max_count: Maximum message count (defaults to config) + 参数： + group_id: 要获取消息的群组 ID + days: 天数（默认使用配置值） + max_count: 最大消息数量（默认使用配置值） - Returns: - List of UnifiedMessage + 返回： + UnifiedMessage 列表 """ days = days or self.config.days max_count = max_count or self.config.max_messages - # Apply platform capability limits + # 应用平台能力限制 caps = self.adapter.get_capabilities() effective_days = caps.get_effective_days(days) effective_count = caps.get_effective_count(max_count) if effective_days < days: logger.info( - f"Platform limits: requested {days} days, " - f"using {effective_days} days" + f"平台限制：请求 {days} 天，" + f"实际使用 {effective_days} 天" ) return await self.adapter.fetch_messages( @@ -143,24 +142,25 @@ class AnalysisOrchestrator: max_count: int = None, ) -> List[dict]: """ - Fetch messages and convert to raw dict format. + 获取消息并转换为原始字典格式。 - This provides backward compatibility with existing analyzers - that expect raw dict messages. + 此方法提供与现有分析器的向后兼容性， + 这些分析器期望原始字典格式的消息。 - Args: - group_id: Group ID to fetch messages from - days: Number of days - max_count: Maximum message count + 参数： + group_id: 要获取消息的群组 ID + days: 天数 + max_count: 最大消息数量 - Returns: - List of raw message dicts (OneBot format) + 返回： + 原始消息字典列表（通用格式，由适配器决定具体格式） """ unified_messages = await self.fetch_messages(group_id, days, max_count) - return MessageConverter.batch_to_onebot(unified_messages) + # 使用适配器的原生格式转换，而非硬编码 OneBot 格式 + return self.adapter.convert_to_raw_format(unified_messages) async def get_group_info(self, group_id: str): - """Get group information.""" + """获取群组信息。""" return await self.adapter.get_group_info(group_id) async def get_member_avatars( @@ -169,19 +169,19 @@ class AnalysisOrchestrator: size: int = 100, ) -> Dict[str, Optional[str]]: """ - Batch get user avatar URLs. + 批量获取用户头像 URL。 - Args: - user_ids: List of user IDs - size: Avatar size + 参数： + user_ids: 用户 ID 列表 + size: 头像尺寸 - Returns: - Dict mapping user_id to avatar URL (or None) + 返回： + 用户 ID 到头像 URL 的映射字典（URL 可能为 None） """ return await self.adapter.batch_get_avatar_urls(user_ids, size) async def send_text(self, group_id: str, text: str) -> bool: - """Send text message to group.""" + """发送文本消息到群组。""" return await self.adapter.send_text(group_id, text) async def send_image( @@ -190,7 +190,7 @@ class AnalysisOrchestrator: image_path: str, caption: str = "", ) -> bool: - """Send image to group.""" + """发送图片到群组。""" return await self.adapter.send_image(group_id, image_path, caption) async def send_file( @@ -199,29 +199,29 @@ class AnalysisOrchestrator: file_path: str, filename: str = None, ) -> bool: - """Send file to group.""" + """发送文件到群组。""" return await self.adapter.send_file(group_id, file_path, filename) def validate_message_count(self, messages: List[UnifiedMessage]) -> bool: """ - Check if message count meets minimum threshold. + 检查消息数量是否达到最小阈值。 - Args: - messages: List of messages + 参数： + messages: 消息列表 - Returns: - True if count is sufficient + 返回： + 如果数量足够返回 True """ return len(messages) >= self.config.min_messages_threshold def get_analysis_text(self, messages: List[UnifiedMessage]) -> str: """ - Convert messages to analysis text format for LLM. + 将消息转换为 LLM 分析文本格式。 - Args: - messages: List of UnifiedMessage + 参数： + messages: UnifiedMessage 列表 - Returns: - Formatted text for LLM analysis + 返回： + 格式化的 LLM 分析文本 """ return MessageConverter.unified_to_analysis_text(messages) diff --git a/src/core/bot_manager.py b/src/core/bot_manager.py index dcbd04d..42a3a15 100644 --- a/src/core/bot_manager.py +++ b/src/core/bot_manager.py @@ -2,7 +2,7 @@ Bot实例管理模块 统一管理bot实例的获取、设置和使用 -Refactored to integrate with DDD PlatformAdapter architecture. +已重构以集成 DDD PlatformAdapter 架构，支持多平台扩展。 """ from typing import Any, Optional @@ -16,14 +16,14 @@ class BotManager: """ Bot实例管理器 - 统一管理所有bot相关操作 - Integrates with DDD architecture by creating PlatformAdapter instances - alongside raw bot instances for cross-platform support. + 与 DDD 架构集成，为每个 bot 实例创建对应的 PlatformAdapter， + 实现跨平台支持。 """ def __init__(self, config_manager): self.config_manager = config_manager self._bot_instances = {} # {platform_id: bot_instance} - self._adapters = {} # {platform_id: PlatformAdapter} - DDD integration + self._adapters = {} # {platform_id: PlatformAdapter} - DDD 集成 self._platforms = {} # 存储平台对象以访问配置 self._bot_qq_ids = [] # 支持多个QQ号 self._context = None @@ -38,7 +38,7 @@ class BotManager: """ 设置bot实例，支持指定平台ID - Also creates a PlatformAdapter if the platform is supported. + 同时会创建对应的 PlatformAdapter（如果平台被支持）。 """ if not platform_id: platform_id = self._get_platform_id_from_instance(bot_instance) @@ -46,7 +46,7 @@ class BotManager: if bot_instance and platform_id: self._bot_instances[platform_id] = bot_instance - # Create PlatformAdapter for DDD integration + # 为 DDD 集成创建 PlatformAdapter if platform_name is None: platform_name = self._detect_platform_name(bot_instance) @@ -59,7 +59,7 @@ class BotManager: ) if adapter: self._adapters[platform_id] = adapter - logger.debug(f"Created PlatformAdapter for {platform_id} ({platform_name})") + logger.debug(f"已为 {platform_id} ({platform_name}) 创建 PlatformAdapter") # 自动提取QQ号 bot_qq_id = self._extract_bot_qq_id(bot_instance) @@ -123,38 +123,50 @@ class BotManager: def _detect_platform_name(self, bot_instance) -> Optional[str]: """ - Detect platform name from bot instance for adapter creation. + 从 bot 实例检测平台名称，用于创建适配器。 - Returns platform name like 'aiocqhttp', 'telegram', etc. + 返回平台名称如 'aiocqhttp', 'discord' 等。 + + 检测优先级: + 1. bot 实例的 platform 属性 + 2. 已知的 API 特征检测 + 3. 类名模式匹配（作为后备方案） """ - # Check for aiocqhttp/OneBot - if hasattr(bot_instance, "call_action"): - return "aiocqhttp" - - # Check for platform attribute + # 优先使用 platform 属性 if hasattr(bot_instance, "platform"): platform = bot_instance.platform if isinstance(platform, str): return platform - # Check class name patterns - class_name = type(bot_instance).__name__.lower() - if "cqhttp" in class_name or "onebot" in class_name: + # 检查已知的 API 特征（平台无关的方式） + # OneBot/aiocqhttp 特征: 有 call_action 方法 + if hasattr(bot_instance, "call_action"): return "aiocqhttp" - if "telegram" in class_name: - return "telegram" - if "discord" in class_name: - return "discord" + + # 使用工厂的已注册平台列表进行类名匹配 + class_name = type(bot_instance).__name__.lower() + for platform_name in PlatformAdapterFactory.get_supported_platforms(): + if platform_name in class_name: + return platform_name + + # 通用类名模式匹配（用于尚未注册的平台） + known_patterns = { + "cqhttp": "aiocqhttp", + "onebot": "aiocqhttp", + } + for pattern, platform in known_patterns.items(): + if pattern in class_name: + return platform return None - # ==================== DDD Integration Methods ==================== + # ==================== DDD 集成方法 ==================== def get_adapter(self, platform_id: str = None) -> Optional[PlatformAdapter]: """ - Get PlatformAdapter for the specified platform. + 获取指定平台的 PlatformAdapter。 - This is the primary method for DDD-based operations. + 这是 DDD 架构操作的主要方法。 """ if platform_id: return self._adapters.get(platform_id) @@ -164,25 +176,25 @@ class BotManager: return list(self._adapters.values())[0] logger.error( - f"Multiple adapters exist {list(self._adapters.keys())} " - "but no platform_id specified." + f"存在多个适配器 {list(self._adapters.keys())}，" + "但未指定 platform_id。" ) return None return None def get_all_adapters(self) -> dict: - """Get all PlatformAdapter instances {platform_id: adapter}""" + """获取所有 PlatformAdapter 实例 {platform_id: adapter}""" return self._adapters.copy() def has_adapter(self, platform_id: str = None) -> bool: - """Check if adapter exists for the platform""" + """检查指定平台是否有适配器""" if platform_id: return platform_id in self._adapters return bool(self._adapters) def can_analyze(self, platform_id: str = None) -> bool: - """Check if the platform supports analysis using DDD capabilities""" + """使用 DDD 能力检查平台是否支持分析""" adapter = self.get_adapter(platform_id) if adapter: return adapter.get_capabilities().can_analyze() @@ -192,7 +204,7 @@ class BotManager: """ 自动发现所有可用的bot实例 - Also creates PlatformAdapter for each discovered bot. + 同时为每个发现的 bot 创建对应的 PlatformAdapter。 """ if not self._context or not hasattr(self._context, "platform_manager"): return {} @@ -216,7 +228,7 @@ class BotManager: ): platform_id = platform.metadata.id - # Detect platform name from metadata + # 从元数据检测平台名称 platform_name = None if hasattr(platform.metadata, "name"): platform_name = platform.metadata.name @@ -227,10 +239,10 @@ class BotManager: self._platforms[platform_id] = platform discovered[platform_id] = bot_client - # Log adapter creation results + # 记录适配器创建结果 if self._adapters: logger.info( - f"Created {len(self._adapters)} PlatformAdapter(s): " + f"已创建 {len(self._adapters)} 个 PlatformAdapter: " f"{list(self._adapters.keys())}" )