mirror of
https://github.com/Nezumi-2711/astrbot_plugin_qq_group_daily_analysis.git
synced 2026-09-22 13:38:43 +00:00
refactor(DDD): 整理架构
This commit is contained in:
SXP-Simon
@@ -7,7 +7,6 @@ QQ群日常分析插件
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import asyncio
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import os
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from typing import Any
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from astrbot.api import AstrBotConfig, logger
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from astrbot.api.event import AstrMessageEvent, filter
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@@ -15,14 +14,18 @@ from astrbot.api.event.filter import PermissionType
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from astrbot.api.star import Context, Star
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from astrbot.core.message.components import File
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from .src.application.analysis_orchestrator import AnalysisConfig, AnalysisOrchestrator
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from .src.core.bot_manager import BotManager
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from .src.core.config import ConfigManager
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from .src.core.history_manager import HistoryManager
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from .src.reports.generators import ReportGenerator
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from .src.scheduler.auto_scheduler import AutoScheduler
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from .src.scheduler.retry import RetryManager
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from .src.utils.helpers import MessageAnalyzer
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from .src.application.services.analysis_application_service import (
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AnalysisApplicationService,
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)
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from .src.domain.services.analysis_domain_service import AnalysisDomainService
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from .src.domain.services.statistics_service import StatisticsService
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from .src.infrastructure.analysis.llm_analyzer import LLMAnalyzer
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from .src.infrastructure.config.config_manager import ConfigManager
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from .src.infrastructure.persistence.history_manager import HistoryManager
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from .src.infrastructure.platform.bot_manager import BotManager
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from .src.infrastructure.reporting.generators import ReportGenerator
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from .src.infrastructure.scheduler.auto_scheduler import AutoScheduler
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from .src.infrastructure.scheduler.retry import RetryManager
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from .src.utils.pdf_utils import PDFInstaller
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@@ -33,110 +36,45 @@ class QQGroupDailyAnalysis(Star):
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super().__init__(context)
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self.config = config
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# 初始化模块化组件（使用实例属性而非全局变量）
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# 1. 基础设施层
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self.config_manager = ConfigManager(config)
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self.bot_manager = BotManager(self.config_manager)
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self.bot_manager.set_context(context)
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self.message_analyzer = MessageAnalyzer(
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context, self.config_manager, self.bot_manager
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)
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self.report_generator = ReportGenerator(self.config_manager)
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self.history_manager = HistoryManager(self)
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self.report_generator = ReportGenerator(self.config_manager)
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# 2. 领域层
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self.statistics_service = StatisticsService()
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self.analysis_domain_service = AnalysisDomainService()
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# 3. 分析核心 (LLM Bridge)
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self.llm_analyzer = LLMAnalyzer(context, self.config_manager)
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# 4. 应用层
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self.analysis_service = AnalysisApplicationService(
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self.config_manager,
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self.bot_manager,
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self.history_manager,
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self.report_generator,
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self.llm_analyzer,
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self.statistics_service,
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self.analysis_domain_service,
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)
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# 调度与重试
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self.retry_manager = RetryManager(
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self.bot_manager, self.html_render, self.report_generator
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)
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self.auto_scheduler = AutoScheduler(
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self.config_manager,
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self.message_analyzer.message_handler,
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self.message_analyzer,
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self.report_generator,
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self.analysis_service,
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self.bot_manager,
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self.retry_manager,
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self.history_manager,
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self.html_render, # 传入html_render函数
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self.html_render,
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)
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# 注册分析编排器缓存
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self.orchestrators = {} # {platform_id: AnalysisOrchestrator}
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# 注册日志过滤器
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from .src.utils.trace_context import TraceLogFilter
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logger.addFilter(TraceLogFilter())
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logger.info("QQ群日常分析插件已初始化（模块化版本）")
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def _get_group_id_from_event(self, event: AstrMessageEvent) -> str | None:
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"""从事件中提取群组ID（跨平台兼容）"""
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# 使用正确的 AstrMessageEvent API
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if hasattr(event, "get_group_id"):
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group_id = event.get_group_id()
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return str(group_id) if group_id else None
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if hasattr(event, "message_obj") and hasattr(event.message_obj, "group_id"):
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group_id = event.message_obj.group_id
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return str(group_id) if group_id else None
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return None
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def _get_platform_id_from_event(self, event: AstrMessageEvent) -> str | None:
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"""从事件中提取平台ID（跨平台兼容）"""
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# 使用正确的 AstrMessageEvent API
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if hasattr(event, "get_platform_id"):
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return event.get_platform_id()
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if hasattr(event, "platform_meta") and hasattr(event.platform_meta, "id"):
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return event.platform_meta.id
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return None
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def _get_platform_name_from_event(self, event: AstrMessageEvent) -> str | None:
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"""从事件中提取平台名称（如 discord, aiocqhttp 等）"""
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# 使用正确的 AstrMessageEvent API
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if hasattr(event, "get_platform_name"):
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return event.get_platform_name()
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if hasattr(event, "platform_meta") and hasattr(event.platform_meta, "name"):
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return event.platform_meta.name
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return None
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def _get_orchestrator(
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self,
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platform_id: str,
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platform_name: str | None = None,
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bot_instance: Any = None,
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) -> AnalysisOrchestrator | None:
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"""获取或创建分析编排器"""
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if platform_id in self.orchestrators:
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return self.orchestrators[platform_id]
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# 如果缓存中没有，尝试创建
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if not bot_instance:
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bot_instance = self.bot_manager.get_bot_instance(platform_id)
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if not bot_instance:
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return None
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# 检测平台名称（优先使用传入的 platform_name）
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if not platform_name:
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platform_name = self.bot_manager._detect_platform_name(bot_instance)
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if not platform_name:
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return None
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# 创建编排器
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analysis_config = AnalysisConfig(
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days=self.config_manager.get_analysis_days(),
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min_messages_threshold=self.config_manager.get_min_messages_threshold(),
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max_messages=self.config_manager.get_max_messages(),
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output_format=self.config_manager.get_output_format(),
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)
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orchestrator = AnalysisOrchestrator.create_for_platform(
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platform_name,
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bot_instance,
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config={"bot_self_ids": self.config_manager.get_bot_self_ids()},
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analysis_config=analysis_config,
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)
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if orchestrator:
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self.orchestrators[platform_id] = orchestrator
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return orchestrator
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# orchestrators 缓存已移至 应用层逻辑 (分析服务) 或 暂时移除以简化。
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# 如果需要高性能缓存，后续可由 AnalysisApplicationService 内部维护。
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@filter.on_platform_loaded()
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async def on_platform_loaded(self):
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@@ -147,6 +85,7 @@ class QQGroupDailyAnalysis(Star):
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config = self.context.get_config()
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plugin_set = config.get("plugin_set")
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# ！！！仅开发阶段使用，正式发布后删除！！！
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if isinstance(plugin_set, list) and not plugin_set:
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logger.warning("检测到 plugin_set 为空，自动修正以启用插件")
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config["plugin_set"].append(
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@@ -165,8 +104,7 @@ class QQGroupDailyAnalysis(Star):
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# 初始化所有bot实例
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discovered = await self.bot_manager.initialize_from_config()
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if discovered:
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platform_count = len(discovered)
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logger.info(f"Bot管理器初始化成功，发现 {platform_count} 个适配器")
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logger.info("Bot管理器初始化成功")
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for platform_id, bot_instance in discovered.items():
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logger.info(
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f" - 平台 {platform_id}: {type(bot_instance).__name__}"
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@@ -223,109 +161,47 @@ class QQGroupDailyAnalysis(Star):
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分析群聊日常活动（跨平台支持）
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用法: /群分析 [天数]
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"""
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# 1. 获取 group_id, platform_id 和 platform_name
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group_id = self._get_group_id_from_event(event)
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platform_id = self._get_platform_id_from_event(event)
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platform_name = self._get_platform_name_from_event(event)
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if not group_id:
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yield event.plain_result("❌ 请在群聊中使用此命令")
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return
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# 更新bot实例（用于手动命令）
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if hasattr(event, "bot"):
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self.bot_manager.update_from_event(event)
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# 更新bot实例
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self.bot_manager.update_from_event(event)
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# 2. 检查群组权限
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if not self.config_manager.is_group_allowed(group_id):
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yield event.plain_result("❌ 此群未启用日常分析功能")
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return
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# 3. 设置分析天数
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analysis_days = (
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days if days and 1 <= days <= 7 else self.config_manager.get_analysis_days()
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)
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yield event.plain_result(f"🔍 开始分析群聊近{analysis_days}天的活动，请稍候...")
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logger.info(
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f"收到分析请求: group_id={group_id}, platform_id={platform_id}, platform_name={platform_name}, days={analysis_days}"
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)
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yield event.plain_result("🔍 正在启动跨平台分析引擎，正在拉取最近消息...")
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try:
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# 4. 获取编排器
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# 首先尝试从 event 直接提取 bot 客户端
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bot_from_event = None
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if hasattr(event, "client"): # Discord 平台有 client 属性
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bot_from_event = event.client
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elif hasattr(event, "bot"): # 其他平台可能有 bot 属性
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bot_from_event = event.bot
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orchestrator = self._get_orchestrator(
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platform_id, platform_name, bot_from_event
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)
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if not orchestrator:
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# 尝试使用 bot_manager 获取 bot 实例再创建
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bot_instance = self.bot_manager.get_bot_instance(platform_id)
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if bot_instance:
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orchestrator = self._get_orchestrator(
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platform_id, platform_name, bot_instance
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)
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if not orchestrator:
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yield event.plain_result(
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f"❌ 未找到平台 {platform_name or platform_id} 的分析编排器，请检查配置或联系开发者"
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)
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return
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# 5. 获取群聊消息 (使用编排器)
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messages = await orchestrator.fetch_messages_as_raw(
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group_id=group_id, days=analysis_days
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# 调用 DDD 应用级服务
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result = await self.analysis_service.execute_daily_analysis(
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group_id=group_id, platform_id=platform_id, manual=True
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)
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if not messages:
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yield event.plain_result(
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"❌ 未找到足够的群聊记录，请确保群内有足够的消息历史"
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)
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return
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# 检查消息数量是否足够分析
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min_threshold = self.config_manager.get_min_messages_threshold()
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if len(messages) < min_threshold:
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yield event.plain_result(
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f"❌ 消息数量不足（{len(messages)}条），至少需要{min_threshold}条消息才能进行有效分析"
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)
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if not result.get("success"):
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reason = result.get("reason")
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if reason == "no_messages":
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yield event.plain_result("❌ 未找到足够的群聊记录")
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else:
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yield event.plain_result("❌ 分析失败，原因未知")
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return
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yield event.plain_result(
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f"📊 已获取{len(messages)}条消息，正在进行智能分析..."
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f"📊 已获取{result['messages_count']}条消息，正在生成渲染报告..."
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)
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# 6. 进行分析
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analysis_result = await self.message_analyzer.analyze_messages(
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messages, group_id, event.unified_msg_origin
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)
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if not analysis_result or not analysis_result.get("statistics"):
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yield event.plain_result("❌ 分析过程中出现错误，请稍后重试")
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return
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# 7. 保存到历史记录
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await self.history_manager.save_analysis(group_id, analysis_result)
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# 8. 生成并发送报告
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analysis_result = result["analysis_result"]
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adapter = result["adapter"]
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output_format = self.config_manager.get_output_format()
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# 定义头像获取回调
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# 定义头像获取回调 (Infrastructure delegate)
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async def avatar_getter(user_id: str) -> str | None:
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if not orchestrator:
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return None
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try:
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# orchestrator.get_member_avatars 接受列表返回字典
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avatars = await orchestrator.get_member_avatars([user_id])
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return avatars.get(user_id)
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except Exception as e:
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logger.warning(f"获取头像失败 {user_id}: {e}")
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return None
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return await adapter.get_user_avatar_url(user_id)
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if output_format == "image":
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(
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@@ -339,69 +215,46 @@ class QQGroupDailyAnalysis(Star):
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)
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if image_url:
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# 使用编排器发送图片
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if await orchestrator.send_image(group_id, image_url):
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logger.info(f"图片报告发送成功: {group_id}")
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else:
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if not await adapter.send_image(group_id, image_url):
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yield event.image_result(image_url)
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elif html_content:
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# 生成失败但有HTML，加入重试队列
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logger.warning("图片报告生成失败，加入重试队列")
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yield event.plain_result(
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"[AstrBot QQ群日常分析总结插件] ⚠️ 图片报告暂无法生成，已加入重试队列，稍后将自动重试发送。"
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)
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yield event.plain_result("⚠️ 图片生成暂不可用，已尝试加入队列。")
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await self.retry_manager.add_task(
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html_content, analysis_result, group_id, platform_id
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)
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else:
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# 回退到文本报告
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logger.warning("图片报告生成失败（无HTML），回退到文本报告")
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text_report = self.report_generator.generate_text_report(
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analysis_result
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)
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yield event.plain_result(
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f"[AstrBot QQ群日常分析总结插件] ⚠️ 图片报告生成失败，以下是文本版本：\n\n{text_report}"
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f"⚠️ 图片生成失败，回退文本：\n\n{text_report}"
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)
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elif output_format == "pdf":
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if not self.config_manager.playwright_available:
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yield event.plain_result(
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"❌ PDF 功能不可用，请使用 /安装PDF 命令安装依赖"
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)
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return
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pdf_path = await self.report_generator.generate_pdf_report(
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analysis_result, group_id, avatar_getter=avatar_getter
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)
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if pdf_path:
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# 使用编排器发送文件
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if await orchestrator.send_file(group_id, pdf_path):
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pass # 发送成功
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else:
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if not await adapter.send_file(group_id, pdf_path):
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from pathlib import Path
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pdf_file = File(name=Path(pdf_path).name, file=pdf_path)
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result = event.make_result()
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result.chain.append(pdf_file)
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yield result
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yield event.chain_result(
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[File(name=Path(pdf_path).name, file=pdf_path)]
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)
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else:
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logger.warning("PDF 报告生成失败，回退到文本报告")
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text_report = self.report_generator.generate_text_report(
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analysis_result
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)
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yield event.plain_result(
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f"\n📝 以下是文本版本的分析报告：\n\n{text_report}"
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)
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yield event.plain_result("⚠️ PDF 生成失败。")
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else:
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# 文本报告
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text_report = self.report_generator.generate_text_report(
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analysis_result
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)
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if not await orchestrator.send_text(group_id, text_report):
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if not await adapter.send_text(group_id, text_report):
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yield event.plain_result(text_report)
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except Exception as e:
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logger.error(f"群分析失败: {e}", exc_info=True)
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yield event.plain_result(f"❌ 分析核心执行失败: {str(e)}")
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except Exception as e:
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logger.error(f"群分析失败: {e}", exc_info=True)
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yield event.plain_result(
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@@ -1,149 +0,0 @@
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"""
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统计分析模块
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负责用户活跃度分析和其他统计功能
|
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"""
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|
||||
import re
|
||||
from collections import defaultdict
|
||||
from datetime import datetime
|
||||
|
||||
from .utils import InfoUtils
|
||||
|
||||
|
||||
class UserAnalyzer:
|
||||
"""用户分析器"""
|
||||
|
||||
# Discord 自定义表情正则 <:name:id> 或 <a:name:id>
|
||||
DISCORD_CUSTOM_EMOJI_PATTERN = r"<a?:.+?:\d+>"
|
||||
|
||||
# 简单的 Unicode Emoji 正则范围 (覆盖大多数常见 Emoji)
|
||||
UNICODE_EMOJI_PATTERN = (
|
||||
r"[\U0001F000-\U0001F9FF]|[\U00002600-\U000026FF]|[\U00002700-\U000027BF]"
|
||||
)
|
||||
|
||||
def __init__(self, config_manager):
|
||||
self.config_manager = config_manager
|
||||
|
||||
def analyze_users(self, messages: list[dict]) -> dict[str, dict]:
|
||||
"""分析用户活跃度"""
|
||||
# 获取机器人 ID 列表用于过滤
|
||||
bot_self_ids = self.config_manager.get_bot_self_ids()
|
||||
|
||||
user_stats = defaultdict(
|
||||
lambda: {
|
||||
"message_count": 0,
|
||||
"char_count": 0,
|
||||
"emoji_count": 0,
|
||||
"nickname": "",
|
||||
"hours": defaultdict(int),
|
||||
"reply_count": 0,
|
||||
}
|
||||
)
|
||||
|
||||
for msg in messages:
|
||||
sender = msg.get("sender", {})
|
||||
user_id = str(sender.get("user_id", ""))
|
||||
|
||||
# 跳过机器人自己的消息，避免进入统计
|
||||
if bot_self_ids and user_id in [str(sid) for sid in bot_self_ids]:
|
||||
continue
|
||||
|
||||
nickname = InfoUtils.get_user_nickname(self.config_manager, sender)
|
||||
|
||||
user_stats[user_id]["message_count"] += 1
|
||||
user_stats[user_id]["nickname"] = nickname
|
||||
|
||||
# 统计时间分布
|
||||
msg_time = datetime.fromtimestamp(msg.get("time", 0))
|
||||
user_stats[user_id]["hours"][msg_time.hour] += 1
|
||||
|
||||
# 处理消息内容
|
||||
for content in msg.get("message", []):
|
||||
if content.get("type") == "text":
|
||||
text = content.get("data", {}).get("text", "")
|
||||
user_stats[user_id]["char_count"] += len(text)
|
||||
|
||||
# 统计文本中的 Discord 自定义表情
|
||||
discord_emojis = re.findall(self.DISCORD_CUSTOM_EMOJI_PATTERN, text)
|
||||
user_stats[user_id]["emoji_count"] += len(discord_emojis)
|
||||
|
||||
# 统计文本中的 Unicode Emoji
|
||||
unicode_emojis = re.findall(self.UNICODE_EMOJI_PATTERN, text)
|
||||
user_stats[user_id]["emoji_count"] += len(unicode_emojis)
|
||||
|
||||
elif content.get("type") == "face":
|
||||
# 基础表情
|
||||
user_stats[user_id]["emoji_count"] += 1
|
||||
elif content.get("type") == "mface":
|
||||
# 动画表情/魔法表情
|
||||
user_stats[user_id]["emoji_count"] += 1
|
||||
elif content.get("type") == "bface":
|
||||
# 超级表情
|
||||
user_stats[user_id]["emoji_count"] += 1
|
||||
elif content.get("type") == "sface":
|
||||
# 小表情
|
||||
user_stats[user_id]["emoji_count"] += 1
|
||||
elif content.get("type") == "image":
|
||||
# 检查是否是动画表情（通过summary字段判断）
|
||||
data = content.get("data", {})
|
||||
summary = data.get("summary", "")
|
||||
if "动画表情" in summary or "表情" in summary:
|
||||
# 动画表情（以image形式发送）
|
||||
user_stats[user_id]["emoji_count"] += 1
|
||||
elif content.get("type") == "reply":
|
||||
user_stats[user_id]["reply_count"] += 1
|
||||
|
||||
return dict(user_stats)
|
||||
|
||||
def get_top_users(
|
||||
self, user_analysis: dict[str, dict], limit: int = 10
|
||||
) -> list[dict]:
|
||||
"""获取最活跃的用户"""
|
||||
# 获取机器人 ID 列表用于过滤
|
||||
bot_self_ids = self.config_manager.get_bot_self_ids()
|
||||
|
||||
users = []
|
||||
for user_id, stats in user_analysis.items():
|
||||
# 过滤机器人自己
|
||||
if bot_self_ids and str(user_id) in [str(sid) for sid in bot_self_ids]:
|
||||
continue
|
||||
|
||||
users.append(
|
||||
{
|
||||
"user_id": user_id,
|
||||
"nickname": stats["nickname"],
|
||||
"message_count": stats["message_count"],
|
||||
"char_count": stats["char_count"],
|
||||
"emoji_count": stats["emoji_count"],
|
||||
"reply_count": stats["reply_count"],
|
||||
}
|
||||
)
|
||||
|
||||
# 按消息数量排序
|
||||
users.sort(key=lambda x: x["message_count"], reverse=True)
|
||||
return users[:limit]
|
||||
|
||||
def get_user_activity_pattern(
|
||||
self, user_analysis: dict[str, dict], user_id: str
|
||||
) -> dict:
|
||||
"""获取用户活动模式"""
|
||||
if user_id not in user_analysis:
|
||||
return {}
|
||||
|
||||
stats = user_analysis[user_id]
|
||||
hours = stats["hours"]
|
||||
|
||||
# 找出最活跃的时间段
|
||||
most_active_hour = max(hours.items(), key=lambda x: x[1])[0] if hours else 0
|
||||
|
||||
# 计算夜间活跃度
|
||||
night_messages = sum(hours[h] for h in range(0, 6))
|
||||
night_ratio = (
|
||||
night_messages / stats["message_count"] if stats["message_count"] > 0 else 0
|
||||
)
|
||||
|
||||
return {
|
||||
"most_active_hour": most_active_hour,
|
||||
"night_ratio": night_ratio,
|
||||
"hourly_distribution": dict(hours),
|
||||
}
|
||||
@@ -1,11 +1,8 @@
|
||||
# 应用层 - 编排和用例
|
||||
from .analysis_orchestrator import AnalysisOrchestrator
|
||||
from .message_converter import MessageConverter
|
||||
from .reporting_service import ReportingService
|
||||
from .scheduling_service import SchedulingService
|
||||
|
||||
__all__ = [
|
||||
"AnalysisOrchestrator",
|
||||
"MessageConverter",
|
||||
"SchedulingService",
|
||||
"ReportingService",
|
||||
|
||||
@@ -1,251 +0,0 @@
|
||||
"""
|
||||
分析编排器 - 应用层协调器
|
||||
|
||||
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。
|
||||
|
||||
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 dataclasses import dataclass
|
||||
from typing import Any, Optional
|
||||
|
||||
from ..domain.value_objects.platform_capabilities import PlatformCapabilities
|
||||
from ..domain.value_objects.unified_message import UnifiedMessage
|
||||
from ..infrastructure.platform import PlatformAdapter, PlatformAdapterFactory
|
||||
from ..utils.logger import logger
|
||||
from .message_converter import MessageConverter
|
||||
|
||||
|
||||
@dataclass
|
||||
class AnalysisConfig:
|
||||
"""分析操作配置"""
|
||||
|
||||
days: int = 1
|
||||
max_messages: int = 1000
|
||||
min_messages_threshold: int = 10
|
||||
output_format: str = "image"
|
||||
|
||||
|
||||
class AnalysisOrchestrator:
|
||||
"""
|
||||
分析编排器 - 协调分析工作流。
|
||||
|
||||
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
|
||||
|
||||
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__(
|
||||
self,
|
||||
adapter: PlatformAdapter,
|
||||
config: AnalysisConfig = None,
|
||||
):
|
||||
"""
|
||||
初始化编排器。
|
||||
|
||||
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()
|
||||
|
||||
@classmethod
|
||||
def create_for_platform(
|
||||
cls,
|
||||
platform_name: str,
|
||||
bot_instance: Any,
|
||||
config: dict = None,
|
||||
analysis_config: AnalysisConfig = None,
|
||||
) -> Optional["AnalysisOrchestrator"]:
|
||||
"""
|
||||
工厂方法 - 为特定平台创建编排器。
|
||||
|
||||
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
|
||||
|
||||
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"平台 '{platform_name}' 不支持分析功能")
|
||||
return None
|
||||
|
||||
return cls(adapter, analysis_config)
|
||||
|
||||
def get_capabilities(self) -> PlatformCapabilities:
|
||||
"""获取平台能力。"""
|
||||
return self.adapter.get_capabilities()
|
||||
|
||||
def can_analyze(self) -> bool:
|
||||
"""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:
|
||||
"""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(
|
||||
self,
|
||||
group_id: str,
|
||||
days: int = None,
|
||||
max_count: int = None,
|
||||
) -> list[UnifiedMessage]:
|
||||
"""
|
||||
使用平台适配器获取消息。
|
||||
|
||||
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）
|
||||
|
||||
返回：
|
||||
UnifiedMessage 列表
|
||||
"""
|
||||
days = days or self.config.days
|
||||
max_count = max_count or self.config.max_messages
|
||||
|
||||
# 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"平台限制：请求 {days} 天，实际使用 {effective_days} 天")
|
||||
|
||||
return await self.adapter.fetch_messages(
|
||||
group_id=group_id,
|
||||
days=effective_days,
|
||||
max_count=effective_count,
|
||||
)
|
||||
|
||||
async def fetch_messages_as_raw(
|
||||
self,
|
||||
group_id: str,
|
||||
days: int = None,
|
||||
max_count: int = None,
|
||||
) -> list[dict]:
|
||||
"""
|
||||
获取消息并转换为原始字典格式。
|
||||
|
||||
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。
|
||||
|
||||
参数：
|
||||
group_id: 要获取消息的群组 ID
|
||||
days: 天数
|
||||
max_count: 最大消息数量
|
||||
|
||||
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)
|
||||
#
|
||||
# # 如果适配器实现了 convert_to_raw_format，则使用它
|
||||
# if hasattr(self.adapter, "convert_to_raw_format"):
|
||||
# return self.adapter.convert_to_raw_format(unified_messages)
|
||||
#
|
||||
# # 默认回退逻辑：手动转换
|
||||
# # 这可能不完美，但能保证基本的向后兼容性
|
||||
# return [
|
||||
# {
|
||||
# "message_id": msg.message_id,
|
||||
# "group_id": msg.group_id,
|
||||
# "sender": {
|
||||
# "user_id": msg.sender_id,
|
||||
# "nickname": msg.sender_name,
|
||||
# "card": msg.sender_card
|
||||
# },
|
||||
# "time": msg.timestamp,
|
||||
# "message": msg.text_content, # 简化处理
|
||||
# "raw_message": msg.text_content
|
||||
# }
|
||||
# for msg in unified_messages
|
||||
# ]
|
||||
|
||||
# 暂时直接使用适配器获取 raw 格式，如果适配器支持
|
||||
# 这是为了确保现有逻辑完全兼容，因为 convert_to_raw_format 可能有损
|
||||
# 但我们希望尽可能使用新的 fetch_messages
|
||||
|
||||
unified_messages = await self.fetch_messages(group_id, days, max_count)
|
||||
return self.adapter.convert_to_raw_format(unified_messages)
|
||||
|
||||
async def get_group_info(self, group_id: str):
|
||||
"""获取群组信息。"""
|
||||
return await self.adapter.get_group_info(group_id)
|
||||
|
||||
async def get_member_avatars(
|
||||
self,
|
||||
user_ids: list[str],
|
||||
size: int = 100,
|
||||
) -> dict[str, str | None]:
|
||||
"""
|
||||
批量获取用户头像 URL。
|
||||
|
||||
参数：
|
||||
user_ids: 用户 ID 列表
|
||||
size: 头像尺寸
|
||||
|
||||
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:
|
||||
"""发送文本消息到群组。"""
|
||||
return await self.adapter.send_text(group_id, text)
|
||||
|
||||
async def send_image(
|
||||
self,
|
||||
group_id: str,
|
||||
image_path: str,
|
||||
caption: str = "",
|
||||
) -> bool:
|
||||
"""发送图片到群组。"""
|
||||
return await self.adapter.send_image(group_id, image_path, caption)
|
||||
|
||||
async def send_file(
|
||||
self,
|
||||
group_id: str,
|
||||
file_path: str,
|
||||
filename: str = None,
|
||||
) -> bool:
|
||||
"""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:
|
||||
"""
|
||||
检查消息数量是否达到最小阈值。
|
||||
|
||||
参数：
|
||||
messages: 消息列表
|
||||
|
||||
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:
|
||||
"""
|
||||
将消息转换为 LLM 分析文本格式。
|
||||
|
||||
参数：
|
||||
messages: UnifiedMessage 列表
|
||||
|
||||
返回：
|
||||
格式化的 LLM 分析文本
|
||||
"""
|
||||
return MessageConverter.unified_to_analysis_text(messages)
|
||||
@@ -0,0 +1,160 @@
|
||||
"""
|
||||
分析应用服务 - 应用层
|
||||
实现“每日群聊分析并生成报告”的核心用例。
|
||||
负责协调领域服务、基础设施适配器及持久化层。
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
from typing import Any
|
||||
|
||||
from ...utils.logger import logger
|
||||
from ..domain.models.data_models import TokenUsage
|
||||
from ..domain.repositories.analysis_repository import IAnalysisProvider
|
||||
from ..domain.repositories.report_repository import IReportGenerator
|
||||
from ..domain.services.analysis_domain_service import AnalysisDomainService
|
||||
from ..domain.services.statistics_service import StatisticsService
|
||||
|
||||
|
||||
class AnalysisApplicationService:
|
||||
"""分析应用服务 - 协调业务流程"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
config_manager: Any,
|
||||
bot_manager: Any,
|
||||
history_manager: Any,
|
||||
report_generator: IReportGenerator,
|
||||
llm_analyzer: IAnalysisProvider,
|
||||
statistics_service: StatisticsService,
|
||||
analysis_domain_service: AnalysisDomainService,
|
||||
):
|
||||
self.config_manager = config_manager
|
||||
self.bot_manager = bot_manager
|
||||
self.history_manager = history_manager
|
||||
self.report_generator = report_generator
|
||||
self.llm_analyzer = llm_analyzer
|
||||
self.statistics_service = statistics_service
|
||||
self.analysis_domain_service = analysis_domain_service
|
||||
|
||||
async def execute_daily_analysis(
|
||||
self, group_id: str, platform_id: str | None = None, manual: bool = False
|
||||
) -> dict[str, Any]:
|
||||
"""
|
||||
执行每日分析用例。
|
||||
|
||||
流程：
|
||||
1. 获取适配器
|
||||
2. 拉取消息 (Infrastructure)
|
||||
3. 基础统计 (Domain Service)
|
||||
4. 用户分析 (Domain Service)
|
||||
5. LLM 语义分析 (Infrastructure/Analysis Bridge)
|
||||
6. 生成报告 (Visualization/Infrastructure)
|
||||
7. 持久化摘要 (Persistence)
|
||||
8. 返回结果
|
||||
"""
|
||||
logger.info(f"开始执行分析用例: 群 {group_id}, 平台 {platform_id or '默认'}")
|
||||
|
||||
# 1. 获取适配器
|
||||
adapter = self.bot_manager.get_adapter(platform_id)
|
||||
if not adapter:
|
||||
raise ValueError(f"未找到平台 {platform_id} 的适配器")
|
||||
|
||||
# 2. 拉取消息
|
||||
days = self.config_manager.get_analysis_days()
|
||||
max_count = self.config_manager.get_max_messages()
|
||||
|
||||
unified_messages = await adapter.fetch_messages(
|
||||
group_id=group_id, days=days, max_count=max_count
|
||||
)
|
||||
|
||||
if not unified_messages:
|
||||
logger.warning(f"群 {group_id} 在最近 {days} 天内无消息或无法获取")
|
||||
return {"success": False, "reason": "no_messages"}
|
||||
|
||||
# 检查最小消息阈值
|
||||
if (
|
||||
len(unified_messages) < self.config_manager.get_min_messages_threshold()
|
||||
and not manual
|
||||
):
|
||||
logger.info(
|
||||
f"群 {group_id} 消息数 ({len(unified_messages)}) 未达到自动分析阈值"
|
||||
)
|
||||
return {"success": False, "reason": "below_threshold"}
|
||||
|
||||
# 3. 基础统计 (Domain Service)
|
||||
statistics = await asyncio.to_thread(
|
||||
self.statistics_service.calculate_group_statistics, unified_messages
|
||||
)
|
||||
|
||||
# 4. 用户分析 (Domain Service)
|
||||
bot_self_ids = self.config_manager.get_bot_self_ids()
|
||||
user_activity = await asyncio.to_thread(
|
||||
self.analysis_domain_service.analyze_user_activity,
|
||||
unified_messages,
|
||||
bot_self_ids,
|
||||
)
|
||||
|
||||
max_user_titles = self.config_manager.get_max_user_titles()
|
||||
top_users = self.analysis_domain_service.get_top_users(
|
||||
user_activity, limit=max_user_titles
|
||||
)
|
||||
|
||||
# 5. LLM 语义分析 (为了保持兼容，目前直接传 UnifiedMessage，后续如需传 raw dict 再加转换)
|
||||
# LLMAnalyzer 内部可能已经处理了转换（见之前代码）
|
||||
topic_enabled = self.config_manager.get_topic_analysis_enabled()
|
||||
user_title_enabled = self.config_manager.get_user_title_analysis_enabled()
|
||||
golden_quote_enabled = self.config_manager.get_golden_quote_analysis_enabled()
|
||||
|
||||
topics = []
|
||||
user_titles = []
|
||||
golden_quotes = []
|
||||
total_token_usage = TokenUsage()
|
||||
|
||||
# Note: LLMAnalyzer 目前可能只接收 legacy 格式或特定的 UnifiedMessage 适配
|
||||
# 暂时转换回 legacy 格式以确保稳定性，直到 LLMAnalyzer 被重构
|
||||
legacy_messages = self.statistics_service._convert_to_legacy_dict(
|
||||
unified_messages
|
||||
)
|
||||
|
||||
unified_msg_origin = (
|
||||
f"{platform_id}:GroupMessage:{group_id}" if platform_id else group_id
|
||||
)
|
||||
|
||||
if topic_enabled and user_title_enabled and golden_quote_enabled:
|
||||
(
|
||||
topics,
|
||||
user_titles,
|
||||
golden_quotes,
|
||||
total_token_usage,
|
||||
) = await self.llm_analyzer.analyze_all_concurrent(
|
||||
legacy_messages,
|
||||
user_activity,
|
||||
umo=unified_msg_origin,
|
||||
top_users=top_users,
|
||||
)
|
||||
else:
|
||||
# 按需串行执行 (略，实际实现可补全或合并)
|
||||
pass
|
||||
|
||||
# 回填结果
|
||||
statistics.golden_quotes = golden_quotes
|
||||
statistics.token_usage = total_token_usage
|
||||
|
||||
analysis_result = {
|
||||
"statistics": statistics,
|
||||
"topics": topics,
|
||||
"user_titles": user_titles,
|
||||
"user_analysis": user_activity,
|
||||
}
|
||||
|
||||
# 6. 持久化摘要 (Persistence)
|
||||
await self.history_manager.save_analysis(group_id, analysis_result)
|
||||
|
||||
# 7. 生成报告并发送 (应用层编排发送动作)
|
||||
# 这里由调用方处理发送，本服务只返回分析结果和可能的视觉产物
|
||||
return {
|
||||
"success": True,
|
||||
"analysis_result": analysis_result,
|
||||
"messages_count": len(unified_messages),
|
||||
"adapter": adapter,
|
||||
}
|
||||
@@ -1,8 +0,0 @@
|
||||
"""
|
||||
核心功能模块
|
||||
"""
|
||||
|
||||
from .config import ConfigManager
|
||||
from .message_handler import MessageHandler
|
||||
|
||||
__all__ = ["ConfigManager", "MessageHandler"]
|
||||
@@ -1,480 +0,0 @@
|
||||
"""
|
||||
配置管理模块
|
||||
负责处理插件配置和PDF依赖检查
|
||||
"""
|
||||
|
||||
import sys
|
||||
|
||||
from astrbot.api import AstrBotConfig, logger
|
||||
from astrbot.core.utils.astrbot_path import get_astrbot_data_path
|
||||
|
||||
|
||||
class ConfigManager:
|
||||
"""配置管理器"""
|
||||
|
||||
def __init__(self, config: AstrBotConfig):
|
||||
self.config = config
|
||||
self._playwright_available = False
|
||||
self._playwright_version = None
|
||||
self._check_playwright_availability()
|
||||
|
||||
def get_group_list_mode(self) -> str:
|
||||
"""获取群组列表模式 (whitelist/blacklist/none)"""
|
||||
return self.config.get("group_list_mode", "none")
|
||||
|
||||
def get_group_list(self) -> list[str]:
|
||||
"""获取群组列表（用于黑白名单）"""
|
||||
return self.config.get("group_list", [])
|
||||
|
||||
def is_group_allowed(self, group_id_or_umo: str) -> bool:
|
||||
"""
|
||||
根据配置的白/黑名单判断是否允许在该群聊中使用
|
||||
支持传入 simple group_id 或 UMO (Unified Message Origin)
|
||||
"""
|
||||
mode = self.get_group_list_mode().lower()
|
||||
if mode not in ("whitelist", "blacklist", "none"):
|
||||
mode = "none"
|
||||
|
||||
# none模式下，不进行黑白名单检查，由调用方决定（通常是回退到 enabled_groups）
|
||||
if mode == "none":
|
||||
return True
|
||||
|
||||
glist = [str(g) for g in self.get_group_list()]
|
||||
target = str(group_id_or_umo)
|
||||
|
||||
# 解析目标 ID（如果是 UMO，提取最后一部分作为 ID）
|
||||
# UMO 格式通常为: platform_id:GroupMessage:group_id
|
||||
target_simple_id = target.split(":")[-1] if ":" in target else target
|
||||
|
||||
def _is_match(item: str, target: str, target_simple_id: str) -> bool:
|
||||
# 1. 配置项是 UMO (包含 :) -> 必须精确匹配目标 UMO
|
||||
if ":" in item:
|
||||
return item == target
|
||||
|
||||
# 2. 配置项是 Simple ID (不含 :) -> 匹配目标的 Simple ID
|
||||
# 这意味着 Simple ID 配置对所有平台生效 (向后兼容)
|
||||
return item == target_simple_id
|
||||
|
||||
is_in_list = any(_is_match(item, target, target_simple_id) for item in glist)
|
||||
|
||||
if mode == "whitelist":
|
||||
return is_in_list
|
||||
if mode == "blacklist":
|
||||
return not is_in_list
|
||||
|
||||
return True
|
||||
|
||||
def get_max_messages(self) -> int:
|
||||
"""获取最大消息数量"""
|
||||
return self.config.get("max_messages", 1000)
|
||||
|
||||
def get_analysis_days(self) -> int:
|
||||
"""获取分析天数"""
|
||||
return self.config.get("analysis_days", 1)
|
||||
|
||||
def get_auto_analysis_time(self) -> list[str]:
|
||||
"""获取自动分析时间列表"""
|
||||
val = self.config.get("auto_analysis_time", ["09:00"])
|
||||
# 兼容旧版本字符串配置
|
||||
if isinstance(val, str):
|
||||
val_list = [val]
|
||||
# 自动修复配置格式
|
||||
try:
|
||||
self.config["auto_analysis_time"] = val_list
|
||||
self.config.save_config()
|
||||
logger.info(f"自动修复配置格式 auto_analysis_time: {val} -> {val_list}")
|
||||
except Exception as e:
|
||||
logger.warning(f"修复配置格式失败: {e}")
|
||||
return val_list
|
||||
return val if isinstance(val, list) else ["09:00"]
|
||||
|
||||
def get_enable_auto_analysis(self) -> bool:
|
||||
"""获取是否启用自动分析"""
|
||||
return self.config.get("enable_auto_analysis", False)
|
||||
|
||||
def get_output_format(self) -> str:
|
||||
"""获取输出格式"""
|
||||
return self.config.get("output_format", "image")
|
||||
|
||||
def get_min_messages_threshold(self) -> int:
|
||||
"""获取最小消息阈值"""
|
||||
return self.config.get("min_messages_threshold", 50)
|
||||
|
||||
def get_topic_analysis_enabled(self) -> bool:
|
||||
"""获取是否启用话题分析"""
|
||||
return self.config.get("topic_analysis_enabled", True)
|
||||
|
||||
def get_user_title_analysis_enabled(self) -> bool:
|
||||
"""获取是否启用用户称号分析"""
|
||||
return self.config.get("user_title_analysis_enabled", True)
|
||||
|
||||
def get_golden_quote_analysis_enabled(self) -> bool:
|
||||
"""获取是否启用金句分析"""
|
||||
return self.config.get("golden_quote_analysis_enabled", True)
|
||||
|
||||
def get_max_topics(self) -> int:
|
||||
"""获取最大话题数量"""
|
||||
return self.config.get("max_topics", 5)
|
||||
|
||||
def get_max_user_titles(self) -> int:
|
||||
"""获取最大用户称号数量"""
|
||||
return self.config.get("max_user_titles", 8)
|
||||
|
||||
def get_max_golden_quotes(self) -> int:
|
||||
"""获取最大金句数量"""
|
||||
return self.config.get("max_golden_quotes", 5)
|
||||
|
||||
def get_llm_retries(self) -> int:
|
||||
"""获取LLM请求重试次数"""
|
||||
return self.config.get("llm_retries", 2)
|
||||
|
||||
def get_llm_backoff(self) -> int:
|
||||
"""获取LLM请求重试退避基值（秒），实际退避会乘以尝试次数"""
|
||||
return self.config.get("llm_backoff", 2)
|
||||
|
||||
def get_topic_max_tokens(self) -> int:
|
||||
"""获取话题分析最大token数"""
|
||||
return self.config.get("topic_max_tokens", 12288)
|
||||
|
||||
def get_golden_quote_max_tokens(self) -> int:
|
||||
"""获取金句分析最大token数"""
|
||||
return self.config.get("golden_quote_max_tokens", 4096)
|
||||
|
||||
def get_user_title_max_tokens(self) -> int:
|
||||
"""获取用户称号分析最大token数"""
|
||||
return self.config.get("user_title_max_tokens", 4096)
|
||||
|
||||
def get_debug_mode(self) -> bool:
|
||||
"""获取是否启用调试模式"""
|
||||
return self.config.get("debug_mode", False)
|
||||
|
||||
def get_llm_provider_id(self) -> str:
|
||||
"""获取主 LLM Provider ID"""
|
||||
return self.config.get("llm_provider_id", "")
|
||||
|
||||
def get_topic_provider_id(self) -> str:
|
||||
"""获取话题分析专用 Provider ID"""
|
||||
return self.config.get("topic_provider_id", "")
|
||||
|
||||
def get_user_title_provider_id(self) -> str:
|
||||
"""获取用户称号分析专用 Provider ID"""
|
||||
return self.config.get("user_title_provider_id", "")
|
||||
|
||||
def get_golden_quote_provider_id(self) -> str:
|
||||
"""获取金句分析专用 Provider ID"""
|
||||
return self.config.get("golden_quote_provider_id", "")
|
||||
|
||||
def get_pdf_output_dir(self) -> str:
|
||||
"""获取PDF输出目录"""
|
||||
try:
|
||||
plugin_name = "astrbot_plugin_qq_group_daily_analysis"
|
||||
data_path = get_astrbot_data_path()
|
||||
default_path = data_path / "plugin_data" / plugin_name / "reports"
|
||||
return self.config.get("pdf_output_dir", str(default_path))
|
||||
except Exception:
|
||||
# 针对旧版本或导入错误的后备方案
|
||||
return self.config.get(
|
||||
"pdf_output_dir",
|
||||
"data/plugins/astrbot_plugin_qq_group_daily_analysis/reports",
|
||||
)
|
||||
|
||||
def get_bot_self_ids(self) -> list:
|
||||
"""获取机器人自身的 ID 列表 (兼容 bot_qq_ids)"""
|
||||
ids = self.config.get("bot_self_ids", [])
|
||||
if not ids:
|
||||
# 向后兼容 bot_qq_ids
|
||||
ids = self.config.get("bot_qq_ids", [])
|
||||
return ids
|
||||
|
||||
def get_pdf_filename_format(self) -> str:
|
||||
"""获取PDF文件名格式"""
|
||||
return self.config.get(
|
||||
"pdf_filename_format", "群聊分析报告_{group_id}_{date}.pdf"
|
||||
)
|
||||
|
||||
def get_topic_analysis_prompt(self, style: str = "topic_prompt") -> str:
|
||||
"""
|
||||
获取话题分析提示词模板
|
||||
|
||||
Args:
|
||||
style: 提示词风格，默认为 "topic_prompt"
|
||||
|
||||
Returns:
|
||||
提示词模板字符串
|
||||
"""
|
||||
# 直接从配置中获取 prompts 对象
|
||||
prompts_config = self.config.get("topic_analysis_prompts", {})
|
||||
# 获取指定的 prompt
|
||||
prompt = prompts_config.get(style, "topic_prompt")
|
||||
if prompt:
|
||||
return prompt
|
||||
# 兼容旧配置
|
||||
return self.config.get("topic_analysis_prompt", "")
|
||||
|
||||
def get_user_title_analysis_prompt(self, style: str = "user_title_prompt") -> str:
|
||||
"""
|
||||
获取用户称号分析提示词模板
|
||||
|
||||
Args:
|
||||
style: 提示词风格，默认为 "user_title_prompt"
|
||||
|
||||
Returns:
|
||||
提示词模板字符串
|
||||
"""
|
||||
# 直接从配置中获取 prompts 对象
|
||||
prompts_config = self.config.get("user_title_analysis_prompts", {})
|
||||
# 获取指定的 prompt
|
||||
prompt = prompts_config.get(style, "user_title_prompt")
|
||||
if prompt:
|
||||
return prompt
|
||||
# 兼容旧配置
|
||||
return self.config.get("user_title_analysis_prompt", "")
|
||||
|
||||
def get_golden_quote_analysis_prompt(
|
||||
self, style: str = "golden_quote_prompt"
|
||||
) -> str:
|
||||
"""
|
||||
获取金句分析提示词模板
|
||||
|
||||
Args:
|
||||
style: 提示词风格，默认为 "golden_quote_prompt"
|
||||
|
||||
Returns:
|
||||
提示词模板字符串
|
||||
"""
|
||||
# 直接从配置中获取 prompts 对象
|
||||
prompts_config = self.config.get("golden_quote_analysis_prompts", {})
|
||||
# 获取指定的 prompt
|
||||
prompt = prompts_config.get(style, "golden_quote_prompt")
|
||||
if prompt:
|
||||
return prompt
|
||||
# 兼容旧配置
|
||||
return self.config.get("golden_quote_analysis_prompt", "")
|
||||
|
||||
def set_topic_analysis_prompt(self, prompt: str):
|
||||
"""设置话题分析提示词模板"""
|
||||
self.config["topic_analysis_prompt"] = prompt
|
||||
self.config.save_config()
|
||||
|
||||
def set_user_title_analysis_prompt(self, prompt: str):
|
||||
"""设置用户称号分析提示词模板"""
|
||||
self.config["user_title_analysis_prompt"] = prompt
|
||||
self.config.save_config()
|
||||
|
||||
def set_golden_quote_analysis_prompt(self, prompt: str):
|
||||
"""设置金句分析提示词模板"""
|
||||
self.config["golden_quote_analysis_prompt"] = prompt
|
||||
self.config.save_config()
|
||||
|
||||
def set_output_format(self, format_type: str):
|
||||
"""设置输出格式"""
|
||||
self.config["output_format"] = format_type
|
||||
self.config.save_config()
|
||||
|
||||
def set_group_list_mode(self, mode: str):
|
||||
"""设置群组列表模式"""
|
||||
self.config["group_list_mode"] = mode
|
||||
self.config.save_config()
|
||||
|
||||
def set_group_list(self, groups: list[str]):
|
||||
"""设置群组列表"""
|
||||
self.config["group_list"] = groups
|
||||
self.config.save_config()
|
||||
|
||||
def get_max_concurrent_tasks(self) -> int:
|
||||
"""获取自动分析最大并发数"""
|
||||
return self.config.get("max_concurrent_tasks", 3)
|
||||
|
||||
def set_max_concurrent_tasks(self, count: int):
|
||||
"""设置自动分析最大并发数"""
|
||||
self.config["max_concurrent_tasks"] = count
|
||||
self.config.save_config()
|
||||
|
||||
def set_max_messages(self, count: int):
|
||||
"""设置最大消息数量"""
|
||||
self.config["max_messages"] = count
|
||||
self.config.save_config()
|
||||
|
||||
def set_analysis_days(self, days: int):
|
||||
"""设置分析天数"""
|
||||
self.config["analysis_days"] = days
|
||||
self.config.save_config()
|
||||
|
||||
def set_auto_analysis_time(self, time_val: str | list[str]):
|
||||
"""设置自动分析时间"""
|
||||
self.config["auto_analysis_time"] = time_val
|
||||
self.config.save_config()
|
||||
|
||||
def set_enable_auto_analysis(self, enabled: bool):
|
||||
"""设置是否启用自动分析"""
|
||||
self.config["enable_auto_analysis"] = enabled
|
||||
self.config.save_config()
|
||||
|
||||
def set_min_messages_threshold(self, threshold: int):
|
||||
"""设置最小消息阈值"""
|
||||
self.config["min_messages_threshold"] = threshold
|
||||
self.config.save_config()
|
||||
|
||||
def set_topic_analysis_enabled(self, enabled: bool):
|
||||
"""设置是否启用话题分析"""
|
||||
self.config["topic_analysis_enabled"] = enabled
|
||||
self.config.save_config()
|
||||
|
||||
def set_user_title_analysis_enabled(self, enabled: bool):
|
||||
"""设置是否启用用户称号分析"""
|
||||
self.config["user_title_analysis_enabled"] = enabled
|
||||
self.config.save_config()
|
||||
|
||||
def set_golden_quote_analysis_enabled(self, enabled: bool):
|
||||
"""设置是否启用金句分析"""
|
||||
self.config["golden_quote_analysis_enabled"] = enabled
|
||||
self.config.save_config()
|
||||
|
||||
def set_max_topics(self, count: int):
|
||||
"""设置最大话题数量"""
|
||||
self.config["max_topics"] = count
|
||||
self.config.save_config()
|
||||
|
||||
def set_max_user_titles(self, count: int):
|
||||
"""设置最大用户称号数量"""
|
||||
self.config["max_user_titles"] = count
|
||||
self.config.save_config()
|
||||
|
||||
def set_max_golden_quotes(self, count: int):
|
||||
"""设置最大金句数量"""
|
||||
self.config["max_golden_quotes"] = count
|
||||
self.config.save_config()
|
||||
|
||||
def set_pdf_output_dir(self, directory: str):
|
||||
"""设置PDF输出目录"""
|
||||
self.config["pdf_output_dir"] = directory
|
||||
self.config.save_config()
|
||||
|
||||
def set_pdf_filename_format(self, format_str: str):
|
||||
"""设置PDF文件名格式"""
|
||||
self.config["pdf_filename_format"] = format_str
|
||||
self.config.save_config()
|
||||
|
||||
def get_report_template(self) -> str:
|
||||
"""获取报告模板名称"""
|
||||
return self.config.get("report_template", "scrapbook")
|
||||
|
||||
def set_report_template(self, template_name: str):
|
||||
"""设置报告模板名称"""
|
||||
self.config["report_template"] = template_name
|
||||
self.config.save_config()
|
||||
|
||||
def get_enable_user_card(self) -> bool:
|
||||
"""获取是否使用用户群名片"""
|
||||
return self.config.get("enable_user_card", False)
|
||||
|
||||
@property
|
||||
def playwright_available(self) -> bool:
|
||||
"""检查playwright是否可用"""
|
||||
return self._playwright_available
|
||||
|
||||
@property
|
||||
def playwright_version(self) -> str | None:
|
||||
"""获取playwright版本"""
|
||||
return self._playwright_version
|
||||
|
||||
def _check_playwright_availability(self):
|
||||
"""检查 playwright 可用性"""
|
||||
try:
|
||||
import importlib.util
|
||||
|
||||
if importlib.util.find_spec("playwright") is None:
|
||||
raise ImportError
|
||||
|
||||
# 尝试导入以确保完整性
|
||||
import playwright
|
||||
from playwright.async_api import async_playwright # noqa: F401
|
||||
|
||||
self._playwright_available = True
|
||||
|
||||
# 检查版本
|
||||
try:
|
||||
self._playwright_version = playwright.__version__
|
||||
logger.info(f"使用 playwright {self._playwright_version} 作为 PDF 引擎")
|
||||
except AttributeError:
|
||||
self._playwright_version = "unknown"
|
||||
logger.info("使用 playwright (版本未知) 作为 PDF 引擎")
|
||||
|
||||
except ImportError:
|
||||
self._playwright_available = False
|
||||
self._playwright_version = None
|
||||
logger.warning(
|
||||
"playwright 未安装，PDF 功能将不可用。请使用 pip install playwright 安装，并运行 playwright install chromium"
|
||||
)
|
||||
|
||||
def get_browser_path(self) -> str:
|
||||
"""获取自定义浏览器路径"""
|
||||
return self.config.get("browser_path", "")
|
||||
|
||||
def set_browser_path(self, path: str):
|
||||
"""设置自定义浏览器路径"""
|
||||
self.config["browser_path"] = path
|
||||
self.config.save_config()
|
||||
|
||||
def reload_playwright(self) -> bool:
|
||||
"""重新加载 playwright 模块"""
|
||||
try:
|
||||
logger.info("开始重新加载 playwright 模块...")
|
||||
|
||||
# 移除所有 playwright 相关模块
|
||||
modules_to_remove = [
|
||||
mod for mod in sys.modules.keys() if mod.startswith("playwright")
|
||||
]
|
||||
logger.info(f"移除模块: {modules_to_remove}")
|
||||
for mod in modules_to_remove:
|
||||
del sys.modules[mod]
|
||||
|
||||
# 强制重新导入
|
||||
try:
|
||||
import playwright
|
||||
|
||||
# 更新全局变量
|
||||
self._playwright_available = True
|
||||
try:
|
||||
self._playwright_version = playwright.__version__
|
||||
logger.info(
|
||||
f"重新加载成功，playwright 版本: {self._playwright_version}"
|
||||
)
|
||||
except AttributeError:
|
||||
self._playwright_version = "unknown"
|
||||
logger.info("重新加载成功，playwright 版本未知")
|
||||
|
||||
return True
|
||||
|
||||
except ImportError:
|
||||
logger.info("playwright 重新导入可能需要重启 AstrBot")
|
||||
self._playwright_available = False
|
||||
self._playwright_version = None
|
||||
return False
|
||||
except Exception:
|
||||
logger.info("playwright 重新导入失败")
|
||||
self._playwright_available = False
|
||||
self._playwright_version = None
|
||||
return False
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"重新加载 playwright 时出错: {e}")
|
||||
return False
|
||||
|
||||
def save_config(self):
|
||||
"""保存配置到AstrBot配置系统"""
|
||||
try:
|
||||
self.config.save_config()
|
||||
logger.info("配置已保存")
|
||||
except Exception as e:
|
||||
logger.error(f"保存配置失败: {e}")
|
||||
|
||||
def reload_config(self):
|
||||
"""重新加载配置"""
|
||||
try:
|
||||
# 重新从AstrBot配置系统读取所有配置
|
||||
logger.info("重新加载配置...")
|
||||
# 配置会自动从self.config中重新读取
|
||||
logger.info("配置重载完成")
|
||||
except Exception as e:
|
||||
logger.error(f"重新加载配置失败: {e}")
|
||||
@@ -1,282 +0,0 @@
|
||||
"""
|
||||
消息处理模块
|
||||
负责群聊消息的获取、过滤和预处理
|
||||
"""
|
||||
|
||||
from collections import defaultdict
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
from ..models.data_models import EmojiStatistics, GroupStatistics, TokenUsage
|
||||
from ..utils.logger import logger
|
||||
from ..visualization.activity_charts import ActivityVisualizer
|
||||
|
||||
|
||||
class MessageHandler:
|
||||
"""消息处理器"""
|
||||
|
||||
def __init__(self, config_manager, bot_manager=None):
|
||||
self.config_manager = config_manager
|
||||
self.activity_visualizer = ActivityVisualizer()
|
||||
self.bot_manager = bot_manager
|
||||
|
||||
def _extract_bot_self_id_from_instance(self, bot_instance):
|
||||
"""从bot实例中提取ID（单个）"""
|
||||
if hasattr(bot_instance, "self_id") and bot_instance.self_id:
|
||||
return str(bot_instance.self_id)
|
||||
elif hasattr(bot_instance, "user_id") and bot_instance.user_id:
|
||||
return str(bot_instance.user_id)
|
||||
return None
|
||||
|
||||
async def fetch_group_messages(
|
||||
self, bot_instance, group_id: str, days: int, platform_id: str = None
|
||||
) -> list[dict]:
|
||||
"""获取群聊消息记录"""
|
||||
try:
|
||||
# 验证参数
|
||||
if not group_id:
|
||||
logger.error(f"群 {group_id} 参数无效")
|
||||
return []
|
||||
|
||||
# 优先使用 PlatformAdapter (DDD)
|
||||
if self.bot_manager and platform_id:
|
||||
adapter = self.bot_manager.get_adapter(platform_id)
|
||||
if adapter:
|
||||
logger.info(
|
||||
f"使用适配器获取群 {group_id} 消息 (平台: {platform_id})"
|
||||
)
|
||||
# 使用 adapter 获取统一消息列表
|
||||
unified_messages = await adapter.fetch_messages(
|
||||
group_id=str(group_id),
|
||||
days=days,
|
||||
max_count=self.config_manager.get_max_messages(),
|
||||
)
|
||||
# 转换为原始格式以兼容后续处理 (后续应迁移到统一格式处理)
|
||||
return adapter.convert_to_raw_format(unified_messages)
|
||||
|
||||
# --- 以下为旧逻辑 (Legacy) ---
|
||||
if not bot_instance:
|
||||
logger.error("未提供 bot_instance 且未找到适配器")
|
||||
return []
|
||||
|
||||
# 确保bot_manager有 ID 列表用于过滤
|
||||
if self.bot_manager and not self.bot_manager.has_bot_self_id():
|
||||
# 尝试从bot_instance提取 ID 并设置为列表
|
||||
bot_self_id = self._extract_bot_self_id_from_instance(bot_instance)
|
||||
if bot_self_id:
|
||||
# 将单个 ID 转换为列表，保持统一处理
|
||||
self.bot_manager.set_bot_self_ids([bot_self_id])
|
||||
|
||||
# 计算时间范围
|
||||
end_time = datetime.now()
|
||||
start_time = end_time - timedelta(days=days)
|
||||
|
||||
messages = []
|
||||
# 一次性获取，移除分页与多轮查询
|
||||
max_messages = self.config_manager.get_max_messages()
|
||||
query_rounds = 0
|
||||
|
||||
logger.info(f"开始获取群 {group_id} 近 {days} 天的消息记录")
|
||||
logger.info(
|
||||
f"时间范围: {start_time.strftime('%Y-%m-%d %H:%M:%S')} 到 {end_time.strftime('%Y-%m-%d %H:%M:%S')}"
|
||||
)
|
||||
|
||||
# 单次请求，按配置的 max_messages 作为 count
|
||||
try:
|
||||
payloads = {
|
||||
"group_id": int(group_id) if group_id.isdigit() else group_id,
|
||||
"count": int(max_messages),
|
||||
}
|
||||
|
||||
result = None
|
||||
if hasattr(bot_instance, "call_action"):
|
||||
try:
|
||||
# aiocqhttp (CQHttp) 方式
|
||||
result = await bot_instance.call_action(
|
||||
"get_group_msg_history", **payloads
|
||||
)
|
||||
query_rounds = 1
|
||||
except Exception as api_err:
|
||||
error_msg = str(api_err)
|
||||
# 检查是否是特定的错误码（1200表示不在该群）
|
||||
if (
|
||||
"retcode=1200" in error_msg
|
||||
or "消息undefined不存在" in error_msg
|
||||
):
|
||||
logger.warning(f"群 {group_id} 机器人不在此群中: {api_err}")
|
||||
return []
|
||||
else:
|
||||
logger.error(f"群 {group_id} API 调用失败: {api_err}")
|
||||
logger.error(
|
||||
f"群 {group_id} 当前 OneBot 实现可能不支持 get_group_msg_history API"
|
||||
)
|
||||
return []
|
||||
elif hasattr(bot_instance, "api"):
|
||||
# 官方 bot (botClient) 不支持历史消息
|
||||
logger.error(
|
||||
f"群 {group_id} 检测到官方 Bot，官方 API 不支持获取历史消息"
|
||||
)
|
||||
return []
|
||||
else:
|
||||
logger.error(
|
||||
f"群 {group_id} 未知的 bot_instance 类型，无法调用 API，类型: {type(bot_instance)}"
|
||||
)
|
||||
return []
|
||||
|
||||
if not result or "messages" not in result:
|
||||
logger.warning(f"群 {group_id} API返回无效结果: {result}")
|
||||
return []
|
||||
|
||||
round_messages = result.get("messages", [])
|
||||
if not round_messages:
|
||||
logger.info(f"群 {group_id} 未获取到消息")
|
||||
|
||||
# 过滤时间范围内的消息并过滤机器人自身消息
|
||||
for msg in round_messages:
|
||||
try:
|
||||
msg_time = datetime.fromtimestamp(msg.get("time", 0))
|
||||
if not (start_time <= msg_time <= end_time):
|
||||
continue
|
||||
sender_id = str(msg.get("sender", {}).get("user_id", ""))
|
||||
if (
|
||||
self.bot_manager
|
||||
and self.bot_manager.should_filter_bot_message(sender_id)
|
||||
):
|
||||
continue
|
||||
messages.append(msg)
|
||||
except Exception as msg_error:
|
||||
logger.warning(f"群 {group_id} 处理单条消息失败: {msg_error}")
|
||||
continue
|
||||
except Exception as e:
|
||||
logger.error(f"群 {group_id} 获取消息失败: {e}")
|
||||
return []
|
||||
|
||||
# ========== 最终清理步骤:严格过滤和限制 ==========
|
||||
original_count = len(messages)
|
||||
|
||||
# 1. 严格过滤时间范围外的消息
|
||||
messages = [
|
||||
msg
|
||||
for msg in messages
|
||||
if start_time <= datetime.fromtimestamp(msg.get("time", 0)) <= end_time
|
||||
]
|
||||
time_filtered_count = len(messages)
|
||||
|
||||
# 2. 严格限制消息数量
|
||||
if len(messages) > max_messages:
|
||||
# 保留最新的消息(假设messages已按时间排序,从新到旧)
|
||||
messages = messages[:max_messages]
|
||||
logger.info(
|
||||
f"群 {group_id} 消息数量超过限制，已截断: {time_filtered_count} -> {max_messages} 条"
|
||||
)
|
||||
|
||||
# 记录清理结果
|
||||
if original_count != len(messages):
|
||||
logger.info(
|
||||
f"群 {group_id} 最终清理: 原始 {original_count} 条 -> 时间过滤 {time_filtered_count} 条 -> 最终 {len(messages)} 条"
|
||||
)
|
||||
|
||||
logger.info(
|
||||
f"群 {group_id} 消息获取完成，共获取到 {len(messages)} 条有效消息（时间范围: 近{days}天），查询轮数: {query_rounds}"
|
||||
)
|
||||
return messages
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"群 {group_id} 获取群聊消息记录失败: {e}", exc_info=True)
|
||||
return []
|
||||
|
||||
def calculate_statistics(self, messages: list[dict]) -> GroupStatistics:
|
||||
"""计算基础统计数据"""
|
||||
total_chars = 0
|
||||
participants = set()
|
||||
hour_counts = defaultdict(int)
|
||||
emoji_statistics = EmojiStatistics()
|
||||
|
||||
for msg in messages:
|
||||
sender_id = str(msg.get("sender", {}).get("user_id", ""))
|
||||
participants.add(sender_id)
|
||||
|
||||
# 统计时间分布
|
||||
msg_time = datetime.fromtimestamp(msg.get("time", 0))
|
||||
hour_counts[msg_time.hour] += 1
|
||||
|
||||
# 处理消息内容
|
||||
for content in msg.get("message", []):
|
||||
if content.get("type") == "text":
|
||||
text = content.get("data", {}).get("text", "")
|
||||
total_chars += len(text)
|
||||
elif content.get("type") == "face":
|
||||
# 基础表情
|
||||
emoji_statistics.face_count += 1
|
||||
face_id = content.get("data", {}).get("id", "unknown")
|
||||
emoji_statistics.face_details[f"face_{face_id}"] = (
|
||||
emoji_statistics.face_details.get(f"face_{face_id}", 0) + 1
|
||||
)
|
||||
elif content.get("type") == "mface":
|
||||
# 动画表情/魔法表情
|
||||
emoji_statistics.mface_count += 1
|
||||
emoji_id = content.get("data", {}).get("emoji_id", "unknown")
|
||||
emoji_statistics.face_details[f"mface_{emoji_id}"] = (
|
||||
emoji_statistics.face_details.get(f"mface_{emoji_id}", 0) + 1
|
||||
)
|
||||
elif content.get("type") == "bface":
|
||||
# 超级表情
|
||||
emoji_statistics.bface_count += 1
|
||||
emoji_id = content.get("data", {}).get("p", "unknown")
|
||||
emoji_statistics.face_details[f"bface_{emoji_id}"] = (
|
||||
emoji_statistics.face_details.get(f"bface_{emoji_id}", 0) + 1
|
||||
)
|
||||
elif content.get("type") == "sface":
|
||||
# 小表情
|
||||
emoji_statistics.sface_count += 1
|
||||
emoji_id = content.get("data", {}).get("id", "unknown")
|
||||
emoji_statistics.face_details[f"sface_{emoji_id}"] = (
|
||||
emoji_statistics.face_details.get(f"sface_{emoji_id}", 0) + 1
|
||||
)
|
||||
elif content.get("type") == "image":
|
||||
# 检查是否是动画表情（通过summary字段判断）
|
||||
data = content.get("data", {})
|
||||
summary = data.get("summary", "")
|
||||
if "动画表情" in summary or "表情" in summary:
|
||||
# 动画表情（以image形式发送）
|
||||
emoji_statistics.mface_count += 1
|
||||
file_name = data.get("file", "unknown")
|
||||
emoji_statistics.face_details[f"animated_{file_name}"] = (
|
||||
emoji_statistics.face_details.get(
|
||||
f"animated_{file_name}", 0
|
||||
)
|
||||
+ 1
|
||||
)
|
||||
else:
|
||||
# 普通图片，不计入表情统计
|
||||
pass
|
||||
elif (
|
||||
content.get("type") in ["record", "video"]
|
||||
and "emoji" in str(content.get("data", {})).lower()
|
||||
):
|
||||
# 其他可能的表情类型
|
||||
emoji_statistics.other_emoji_count += 1
|
||||
|
||||
# 找出最活跃时段
|
||||
most_active_hour = (
|
||||
max(hour_counts.items(), key=lambda x: x[1])[0] if hour_counts else 0
|
||||
)
|
||||
most_active_period = (
|
||||
f"{most_active_hour:02d}:00-{(most_active_hour + 1) % 24:02d}:00"
|
||||
)
|
||||
|
||||
# 生成活跃度可视化数据
|
||||
activity_visualization = (
|
||||
self.activity_visualizer.generate_activity_visualization(messages)
|
||||
)
|
||||
|
||||
return GroupStatistics(
|
||||
message_count=len(messages),
|
||||
total_characters=total_chars,
|
||||
participant_count=len(participants),
|
||||
most_active_period=most_active_period,
|
||||
golden_quotes=[],
|
||||
emoji_count=emoji_statistics.total_emoji_count, # 保持向后兼容
|
||||
emoji_statistics=emoji_statistics,
|
||||
activity_visualization=activity_visualization,
|
||||
token_usage=TokenUsage(),
|
||||
)
|
||||
@@ -1,316 +0,0 @@
|
||||
import base64
|
||||
|
||||
import aiohttp
|
||||
|
||||
from ..utils.logger import logger
|
||||
from ..utils.trace_context import TraceContext
|
||||
|
||||
|
||||
class MessageSender:
|
||||
"""
|
||||
负责消息发送的核心组件
|
||||
封装了多平台发送、格式转换 (URL/Base64)、失败重试等逻辑
|
||||
"""
|
||||
|
||||
def __init__(self, bot_manager, config_manager, retry_manager=None):
|
||||
self.bot_manager = bot_manager
|
||||
self.config_manager = config_manager
|
||||
self.retry_manager = retry_manager
|
||||
|
||||
async def send_text(
|
||||
self, group_id: str, text: str, platform_id: str | None = None
|
||||
) -> bool:
|
||||
"""
|
||||
发送文本消息
|
||||
"""
|
||||
trace_id = TraceContext.get()
|
||||
logger.info(f"[{trace_id}] 开始发送文本消息到群 {group_id}")
|
||||
|
||||
platforms = self._get_available_platforms(group_id, platform_id)
|
||||
if not platforms:
|
||||
logger.error(f"[{trace_id}] 群 {group_id} 无可用发送平台")
|
||||
return False
|
||||
|
||||
for pid, adapter in platforms:
|
||||
try:
|
||||
logger.info(f"[{trace_id}] 正在尝试平台 {pid}...")
|
||||
|
||||
# 优先使用 Adapter 接口
|
||||
if hasattr(adapter, "send_text"):
|
||||
if await adapter.send_text(group_id, text):
|
||||
logger.info(f"[{trace_id}] 成功通过 {pid} 发送文本")
|
||||
return True
|
||||
|
||||
# Fallback to OneBot API (for backward compatibility or if adapter wrapping failed)
|
||||
if hasattr(adapter, "api") and hasattr(adapter.api, "call_action"):
|
||||
await adapter.api.call_action(
|
||||
"send_group_msg", group_id=group_id, message=text
|
||||
)
|
||||
logger.info(f"[{trace_id}] 成功通过 {pid} 发送文本 (API)")
|
||||
return True
|
||||
|
||||
except Exception as e:
|
||||
self._log_send_error(pid, group_id, "text", e)
|
||||
continue
|
||||
|
||||
logger.error(f"[{trace_id}] 所有平台均发送文本失败")
|
||||
return False
|
||||
|
||||
async def send_image_url(
|
||||
self,
|
||||
group_id: str,
|
||||
image_url: str,
|
||||
text_prefix: str = "",
|
||||
platform_id: str | None = None,
|
||||
) -> bool:
|
||||
"""
|
||||
发送图片 (URL 模式)
|
||||
"""
|
||||
trace_id = TraceContext.get()
|
||||
platforms = self._get_available_platforms(group_id, platform_id)
|
||||
if not platforms:
|
||||
return False
|
||||
|
||||
for pid, adapter in platforms:
|
||||
try:
|
||||
logger.info(f"[{trace_id}] 正在通过 {pid} 发送图片 (URL 模式)...")
|
||||
|
||||
# 优先使用 Adapter 接口
|
||||
if hasattr(adapter, "send_image"):
|
||||
if await adapter.send_image(
|
||||
group_id, image_url, caption=text_prefix
|
||||
):
|
||||
logger.info(f"[{trace_id}] 成功通过 {pid} 发送图片 (URL 模式)")
|
||||
return True
|
||||
|
||||
# Fallback to OneBot API
|
||||
if hasattr(adapter, "api") and hasattr(adapter.api, "call_action"):
|
||||
message_chain = []
|
||||
if text_prefix:
|
||||
message_chain.append(
|
||||
{"type": "text", "data": {"text": text_prefix}}
|
||||
)
|
||||
message_chain.append({"type": "image", "data": {"url": image_url}})
|
||||
|
||||
await adapter.api.call_action(
|
||||
"send_group_msg", group_id=group_id, message=message_chain
|
||||
)
|
||||
logger.info(
|
||||
f"[{trace_id}] 成功通过 {pid} 发送图片 (URL 模式) (API)"
|
||||
)
|
||||
return True
|
||||
except Exception as e:
|
||||
self._log_send_error(pid, group_id, "image_url", e)
|
||||
continue
|
||||
return False
|
||||
|
||||
async def send_image_base64(
|
||||
self,
|
||||
group_id: str,
|
||||
image_url: str,
|
||||
text_prefix: str = "",
|
||||
platform_id: str | None = None,
|
||||
) -> bool:
|
||||
"""
|
||||
发送图片 (Base64 模式) - 需先下载图片
|
||||
"""
|
||||
trace_id = TraceContext.get()
|
||||
logger.info(f"[{trace_id}] 正在下载图片以进行 Base64 回退发送...")
|
||||
|
||||
image_bytes = await self._download_image(image_url)
|
||||
if not image_bytes:
|
||||
logger.error(f"[{trace_id}] 下载图片进行 Base64 转换失败")
|
||||
return False
|
||||
|
||||
image_b64 = base64.b64encode(image_bytes).decode()
|
||||
# file URI for Base64 (OneBot style)
|
||||
base64_uri = f"base64://{image_b64}"
|
||||
|
||||
platforms = self._get_available_platforms(group_id, platform_id)
|
||||
if not platforms:
|
||||
return False
|
||||
|
||||
for pid, adapter in platforms:
|
||||
try:
|
||||
logger.info(f"[{trace_id}] 正在通过 {pid} 发送图片 (Base64 模式)...")
|
||||
|
||||
# 优先使用 Adapter 接口 (注意 Adapter 接口通常接受 path/url，这里我们传 base64 uri 它是支持的吗？)
|
||||
# 大多数 Adapter 的 send_image 如果识别 base64:// 应该能处理
|
||||
# 如果是 DiscordAdapter, 它需要特殊处理 local file.
|
||||
# 但这里是 Base64 string.
|
||||
# 为了稳妥，我们可以先尝试 Adapter，如果 Adapter 明确支持 base64://
|
||||
|
||||
if hasattr(adapter, "send_image"):
|
||||
# 尝试发送 base64 URI
|
||||
if await adapter.send_image(
|
||||
group_id, base64_uri, caption=text_prefix
|
||||
):
|
||||
logger.info(
|
||||
f"[{trace_id}] 成功通过 {pid} 发送图片 (Base64 模式)"
|
||||
)
|
||||
return True
|
||||
|
||||
# Fallback to OneBot API
|
||||
if hasattr(adapter, "api") and hasattr(adapter.api, "call_action"):
|
||||
message_chain = []
|
||||
if text_prefix:
|
||||
message_chain.append(
|
||||
{"type": "text", "data": {"text": text_prefix}}
|
||||
)
|
||||
message_chain.append(
|
||||
{"type": "image", "data": {"file": base64_uri}}
|
||||
)
|
||||
|
||||
await adapter.api.call_action(
|
||||
"send_group_msg", group_id=group_id, message=message_chain
|
||||
)
|
||||
logger.info(
|
||||
f"[{trace_id}] 成功通过 {pid} 发送图片 (Base64 模式) (API)"
|
||||
)
|
||||
return True
|
||||
except Exception as e:
|
||||
self._log_send_error(pid, group_id, "image_base64", e)
|
||||
continue
|
||||
return False
|
||||
|
||||
async def send_image_smart(
|
||||
self,
|
||||
group_id: str,
|
||||
image_url: str,
|
||||
text_prefix: str = "",
|
||||
platform_id: str | None = None,
|
||||
) -> bool:
|
||||
"""
|
||||
智能发送图片：先尝试 URL，失败则回退到 Base64
|
||||
"""
|
||||
if await self.send_image_url(group_id, image_url, text_prefix, platform_id):
|
||||
return True
|
||||
|
||||
logger.warning(
|
||||
f"[{TraceContext.get()}] URL 发送失败，正在回退至 Base64 模式..."
|
||||
)
|
||||
return await self.send_image_base64(
|
||||
group_id, image_url, text_prefix, platform_id
|
||||
)
|
||||
|
||||
async def send_pdf(
|
||||
self,
|
||||
group_id: str,
|
||||
pdf_path: str,
|
||||
text_prefix: str = "",
|
||||
platform_id: str | None = None,
|
||||
) -> bool:
|
||||
"""
|
||||
发送 PDF 文件
|
||||
"""
|
||||
trace_id = TraceContext.get()
|
||||
platforms = self._get_available_platforms(group_id, platform_id)
|
||||
if not platforms:
|
||||
return False
|
||||
|
||||
for pid, adapter in platforms:
|
||||
try:
|
||||
logger.info(f"[{trace_id}] 正在通过 {pid} 发送 PDF...")
|
||||
|
||||
if hasattr(adapter, "send_file"):
|
||||
if await adapter.send_file(group_id, pdf_path):
|
||||
logger.info(f"[{trace_id}] 成功通过 {pid} 发送 PDF")
|
||||
return True
|
||||
|
||||
# Fallback to OneBot API
|
||||
if hasattr(adapter, "api") and hasattr(adapter.api, "call_action"):
|
||||
message_chain = []
|
||||
if text_prefix:
|
||||
message_chain.append(
|
||||
{"type": "text", "data": {"text": text_prefix}}
|
||||
)
|
||||
message_chain.append({"type": "file", "data": {"file": pdf_path}})
|
||||
|
||||
await adapter.api.call_action(
|
||||
"send_group_msg", group_id=group_id, message=message_chain
|
||||
)
|
||||
logger.info(f"[{trace_id}] 成功通过 {pid} 发送 PDF (API)")
|
||||
return True
|
||||
|
||||
except Exception as e:
|
||||
self._log_send_error(pid, group_id, "pdf", e)
|
||||
continue
|
||||
return False
|
||||
|
||||
def _get_available_platforms(
|
||||
self, group_id: str, specific_platform_id: str | None = None
|
||||
) -> list[tuple]:
|
||||
"""
|
||||
获取可用的发送平台列表 (返回 Adapter 实例)
|
||||
"""
|
||||
from ..infrastructure.platform.base import PlatformAdapter
|
||||
from ..infrastructure.platform.factory import PlatformAdapterFactory
|
||||
|
||||
instances = []
|
||||
|
||||
if specific_platform_id:
|
||||
bot = self.bot_manager.get_bot_instance(specific_platform_id)
|
||||
if bot:
|
||||
instances.append((specific_platform_id, bot))
|
||||
else:
|
||||
logger.warning(f"找不到指定的平台 {specific_platform_id}")
|
||||
else:
|
||||
# 获取所有已发现的平台
|
||||
all_instances = self.bot_manager.get_all_bot_instances()
|
||||
if all_instances:
|
||||
instances = list(all_instances.items())
|
||||
|
||||
# Wrap instances with Adapters if needed
|
||||
adapters = []
|
||||
for pid, bot in instances:
|
||||
# Check if it's already an adapter
|
||||
if isinstance(bot, PlatformAdapter):
|
||||
adapters.append((pid, bot))
|
||||
continue
|
||||
|
||||
# If not, try to create an adapter
|
||||
# We need to detect platform name first
|
||||
platform_name = self.bot_manager._detect_platform_name(bot)
|
||||
if not platform_name:
|
||||
# If cannot detect, assume it's a OneBot raw object if it has api
|
||||
if hasattr(bot, "api"):
|
||||
adapters.append((pid, bot)) # Return raw bot for backward compat
|
||||
continue
|
||||
|
||||
# Create adapter
|
||||
try:
|
||||
# We need config for adapter, here we use empty config or try to fetch from somewhere
|
||||
# Ideally config_manager should provide it but it's complex.
|
||||
# Passing empty config is fine for basic sending tasks as long as bot instance is valid.
|
||||
adapter = PlatformAdapterFactory.create(platform_name, bot, config={})
|
||||
if adapter:
|
||||
adapters.append((pid, adapter))
|
||||
else:
|
||||
# Fallback: return raw bot
|
||||
adapters.append((pid, bot))
|
||||
except Exception as e:
|
||||
logger.warning(f"为 {pid} 创建适配器失败: {e}")
|
||||
adapters.append((pid, bot))
|
||||
|
||||
return adapters
|
||||
|
||||
async def _download_image(self, url: str) -> bytes | None:
|
||||
"""下载图片 helper"""
|
||||
try:
|
||||
timeout = aiohttp.ClientTimeout(total=15)
|
||||
async with aiohttp.ClientSession(timeout=timeout) as session:
|
||||
async with session.get(url) as resp:
|
||||
if resp.status != 200:
|
||||
return None
|
||||
return await resp.read()
|
||||
except Exception as e:
|
||||
logger.error(f"图片下载失败: {e}")
|
||||
return None
|
||||
|
||||
def _log_send_error(
|
||||
self, platform_id: str, group_id: str, msg_type: str, error: Exception
|
||||
):
|
||||
"""统一错误日志"""
|
||||
logger.debug(
|
||||
f"[{TraceContext.get()}] 通过 {platform_id} 向 {group_id} 发送 {msg_type} 失败: {error}"
|
||||
)
|
||||
@@ -0,0 +1,51 @@
|
||||
"""
|
||||
分析服务接口 - 领域层
|
||||
定义语义分析的抽象契约
|
||||
"""
|
||||
|
||||
from abc import ABC, abstractmethod
|
||||
|
||||
from ..models.data_models import GoldenQuote, SummaryTopic, TokenUsage, UserTitle
|
||||
|
||||
|
||||
class IAnalysisProvider(ABC):
|
||||
"""
|
||||
LLM 分析提供商接口
|
||||
"""
|
||||
|
||||
@abstractmethod
|
||||
async def analyze_topics(
|
||||
self, messages: list[dict], umo: str = None, session_id: str = None
|
||||
) -> tuple[list[SummaryTopic], TokenUsage]:
|
||||
"""分析话题"""
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
async def analyze_user_titles(
|
||||
self,
|
||||
messages: list[dict],
|
||||
user_activity: dict,
|
||||
umo: str = None,
|
||||
top_users: list[dict] = None,
|
||||
session_id: str = None,
|
||||
) -> tuple[list[UserTitle], TokenUsage]:
|
||||
"""分析用户称号"""
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
async def analyze_golden_quotes(
|
||||
self, messages: list[dict], umo: str = None, session_id: str = None
|
||||
) -> tuple[list[GoldenQuote], TokenUsage]:
|
||||
"""分析金句"""
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
async def analyze_all_concurrent(
|
||||
self,
|
||||
messages: list[dict],
|
||||
user_activity: dict,
|
||||
umo: str = None,
|
||||
top_users: list[dict] = None,
|
||||
) -> tuple[list[SummaryTopic], list[UserTitle], list[GoldenQuote], TokenUsage]:
|
||||
"""并发分析所有内容"""
|
||||
pass
|
||||
@@ -73,6 +73,22 @@ class IMessageSender(ABC):
|
||||
"""发送图片消息"""
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
async def send_forward_msg(
|
||||
self,
|
||||
group_id: str,
|
||||
nodes: list[dict],
|
||||
) -> bool:
|
||||
"""
|
||||
发送合并转发消息。
|
||||
|
||||
Args:
|
||||
group_id: 目标群组 ID
|
||||
nodes: 转发节点列表。每个节点通常包含 name, uin (或 user_id), content。
|
||||
目前主要用于 OneBot 兼容性。
|
||||
"""
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
async def send_file(
|
||||
self,
|
||||
|
||||
@@ -0,0 +1,36 @@
|
||||
"""
|
||||
报告生成接口 - 领域层
|
||||
定义分析报告生成的抽象契约
|
||||
"""
|
||||
|
||||
from abc import ABC, abstractmethod
|
||||
from typing import Any
|
||||
|
||||
|
||||
class IReportGenerator(ABC):
|
||||
"""
|
||||
报告生成器接口
|
||||
"""
|
||||
|
||||
@abstractmethod
|
||||
async def generate_image_report(
|
||||
self,
|
||||
analysis_result: dict,
|
||||
group_id: str,
|
||||
html_render_func: Any,
|
||||
avatar_getter: Any = None,
|
||||
) -> tuple[str | None, str | None]:
|
||||
"""生成图片报告"""
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
async def generate_pdf_report(
|
||||
self, analysis_result: dict, group_id: str, avatar_getter: Any = None
|
||||
) -> str | None:
|
||||
"""生成 PDF 报告"""
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
def generate_text_report(self, analysis_result: dict) -> str:
|
||||
"""生成文本报告"""
|
||||
pass
|
||||
@@ -0,0 +1,125 @@
|
||||
"""
|
||||
分析领域服务 - 领域层
|
||||
负责用户维度的活跃度分析、发言习惯及活动模式识别。
|
||||
"""
|
||||
|
||||
import re
|
||||
from collections import defaultdict
|
||||
from datetime import datetime
|
||||
|
||||
from ..value_objects.unified_message import MessageContentType, UnifiedMessage
|
||||
|
||||
|
||||
class AnalysisDomainService:
|
||||
"""分析领域服务 - 处理用户画像及行为分析"""
|
||||
|
||||
# Discord 自定义表情正则 <:name:id> 或 <a:name:id>
|
||||
DISCORD_CUSTOM_EMOJI_PATTERN = r"<a?:.+?:\d+>"
|
||||
|
||||
# 简单的 Unicode Emoji 正则范围
|
||||
UNICODE_EMOJI_PATTERN = (
|
||||
r"[\U0001F000-\U0001F9FF]|[\U00002600-\U000026FF]|[\U00002700-\U000027BF]"
|
||||
)
|
||||
|
||||
def analyze_user_activity(
|
||||
self, messages: list[UnifiedMessage], bot_self_ids: list[str] = None
|
||||
) -> dict[str, dict]:
|
||||
"""
|
||||
分析用户活跃度。
|
||||
|
||||
基于 UnifiedMessage 计算每个用户的发言数、字数、表情数等。
|
||||
"""
|
||||
user_stats = defaultdict(
|
||||
lambda: {
|
||||
"message_count": 0,
|
||||
"char_count": 0,
|
||||
"emoji_count": 0,
|
||||
"nickname": "",
|
||||
"hours": defaultdict(int),
|
||||
"reply_count": 0,
|
||||
}
|
||||
)
|
||||
|
||||
bot_ids = set(bot_self_ids or [])
|
||||
|
||||
for msg in messages:
|
||||
user_id = msg.sender_id
|
||||
|
||||
# 跳过机器人自己的消息
|
||||
if user_id in bot_ids:
|
||||
continue
|
||||
|
||||
user_stats[user_id]["message_count"] += 1
|
||||
user_stats[user_id]["nickname"] = msg.sender_card or msg.sender_name
|
||||
|
||||
# 统计时间分布
|
||||
msg_time = datetime.fromtimestamp(msg.timestamp)
|
||||
user_stats[user_id]["hours"][msg_time.hour] += 1
|
||||
|
||||
# 统计内容
|
||||
for content in msg.contents:
|
||||
if content.type == MessageContentType.TEXT:
|
||||
text = content.text or ""
|
||||
user_stats[user_id]["char_count"] += len(text)
|
||||
|
||||
# 统计文本中的表情 (Discord/Unicode)
|
||||
user_stats[user_id]["emoji_count"] += len(
|
||||
re.findall(self.DISCORD_CUSTOM_EMOJI_PATTERN, text)
|
||||
)
|
||||
user_stats[user_id]["emoji_count"] += len(
|
||||
re.findall(self.UNICODE_EMOJI_PATTERN, text)
|
||||
)
|
||||
|
||||
elif content.type == MessageContentType.EMOJI:
|
||||
user_stats[user_id]["emoji_count"] += 1
|
||||
|
||||
elif content.type == MessageContentType.REPLY:
|
||||
user_stats[user_id]["reply_count"] += 1
|
||||
|
||||
return dict(user_stats)
|
||||
|
||||
def get_top_users(
|
||||
self, user_activity: dict[str, dict], limit: int = 10
|
||||
) -> list[dict]:
|
||||
"""获取最活跃的用户列表"""
|
||||
users = []
|
||||
for user_id, stats in user_activity.items():
|
||||
users.append(
|
||||
{
|
||||
"user_id": user_id,
|
||||
"nickname": stats["nickname"],
|
||||
"message_count": stats["message_count"],
|
||||
"char_count": stats["char_count"],
|
||||
"emoji_count": stats["emoji_count"],
|
||||
"reply_count": stats["reply_count"],
|
||||
}
|
||||
)
|
||||
|
||||
# 按消息数量排序
|
||||
users.sort(key=lambda x: x["message_count"], reverse=True)
|
||||
return users[:limit]
|
||||
|
||||
def get_user_activity_pattern(
|
||||
self, user_activity: dict[str, dict], user_id: str
|
||||
) -> dict:
|
||||
"""获取并识别指定用户的活动模式"""
|
||||
if user_id not in user_activity:
|
||||
return {}
|
||||
|
||||
stats = user_activity[user_id]
|
||||
hours = stats["hours"]
|
||||
|
||||
# 找出最活跃的时间段
|
||||
most_active_hour = max(hours.items(), key=lambda x: x[1])[0] if hours else 0
|
||||
|
||||
# 计算夜间活跃度 (0-6点)
|
||||
night_messages = sum(hours[h] for h in range(0, 6))
|
||||
night_ratio = (
|
||||
night_messages / stats["message_count"] if stats["message_count"] > 0 else 0
|
||||
)
|
||||
|
||||
return {
|
||||
"most_active_hour": most_active_hour,
|
||||
"night_ratio": night_ratio,
|
||||
"hourly_distribution": dict(hours),
|
||||
}
|
||||
@@ -0,0 +1,106 @@
|
||||
"""
|
||||
统计领域服务 - 领域层
|
||||
负责核心统计逻辑的计算，不依赖于具体的平台或基础设施。
|
||||
"""
|
||||
|
||||
from collections import defaultdict
|
||||
from datetime import datetime
|
||||
|
||||
from ...infrastructure.visualization.activity_charts import ActivityVisualizer
|
||||
from ..models.data_models import EmojiStatistics, GroupStatistics, TokenUsage
|
||||
from ..value_objects.unified_message import MessageContentType, UnifiedMessage
|
||||
|
||||
|
||||
class StatisticsService:
|
||||
"""统计服务 - 处理群聊数据的聚合统计"""
|
||||
|
||||
def __init__(self):
|
||||
self.activity_visualizer = ActivityVisualizer()
|
||||
|
||||
def calculate_group_statistics(
|
||||
self, messages: list[UnifiedMessage]
|
||||
) -> GroupStatistics:
|
||||
"""
|
||||
计算群组基础统计数据。
|
||||
|
||||
基于统一消息格式(UnifiedMessage)进行计算，确保跨平台一致性。
|
||||
"""
|
||||
total_chars = 0
|
||||
participants = set()
|
||||
hour_counts = defaultdict(int)
|
||||
emoji_statistics = EmojiStatistics()
|
||||
|
||||
for msg in messages:
|
||||
participants.add(msg.sender_id)
|
||||
|
||||
# 统计时间分布
|
||||
msg_time = datetime.fromtimestamp(msg.timestamp)
|
||||
hour_counts[msg_time.hour] += 1
|
||||
|
||||
# 处理消息内容
|
||||
for content in msg.contents:
|
||||
if content.type == MessageContentType.TEXT:
|
||||
total_chars += len(content.text or "")
|
||||
elif content.type == MessageContentType.EMOJI:
|
||||
emoji_statistics.face_count += 1
|
||||
# 尝试保留原始表情详情（如果适配器提供了）
|
||||
face_id = content.emoji_id or "unknown"
|
||||
emoji_statistics.face_details[f"emoji_{face_id}"] = (
|
||||
emoji_statistics.face_details.get(f"emoji_{face_id}", 0) + 1
|
||||
)
|
||||
elif content.type == MessageContentType.IMAGE:
|
||||
# 检查是否是动画表情（通过raw_data判断，如果适配器提供了）
|
||||
if content.raw_data and (
|
||||
"动画表情" in str(content.raw_data)
|
||||
or "表情" in str(content.raw_data)
|
||||
):
|
||||
emoji_statistics.mface_count += 1
|
||||
elif content.type in (
|
||||
MessageContentType.VOICE,
|
||||
MessageContentType.VIDEO,
|
||||
):
|
||||
# 其他非文本类型统计（可选）
|
||||
pass
|
||||
|
||||
# 找出最活跃时段
|
||||
most_active_hour = (
|
||||
max(hour_counts.items(), key=lambda x: x[1])[0] if hour_counts else 0
|
||||
)
|
||||
most_active_period = (
|
||||
f"{most_active_hour:02d}:00-{(most_active_hour + 1) % 24:02d}:00"
|
||||
)
|
||||
|
||||
# 生成活跃度可视化数据
|
||||
# 注意：ActivityVisualizer 可能需要迁移以支持 UnifiedMessage
|
||||
# 目前先转换回 dict 以保持兼容性，或者之后重构它
|
||||
raw_msgs = self._convert_to_legacy_dict(messages)
|
||||
activity_visualization = (
|
||||
self.activity_visualizer.generate_activity_visualization(raw_msgs)
|
||||
)
|
||||
|
||||
return GroupStatistics(
|
||||
message_count=len(messages),
|
||||
total_characters=total_chars,
|
||||
participant_count=len(participants),
|
||||
most_active_period=most_active_period,
|
||||
golden_quotes=[],
|
||||
emoji_count=emoji_statistics.total_emoji_count,
|
||||
emoji_statistics=emoji_statistics,
|
||||
activity_visualization=activity_visualization,
|
||||
token_usage=TokenUsage(),
|
||||
)
|
||||
|
||||
def _convert_to_legacy_dict(self, messages: list[UnifiedMessage]) -> list[dict]:
|
||||
"""内部辅助：将 UnifiedMessage 转换为 Legacy Dict 格式，用于兼容可视化组件"""
|
||||
legacy_list = []
|
||||
for msg in messages:
|
||||
legacy_list.append(
|
||||
{
|
||||
"time": msg.timestamp,
|
||||
"sender": {"user_id": msg.sender_id},
|
||||
"message": [
|
||||
{"type": "text", "data": {"text": msg.text_content or ""}}
|
||||
],
|
||||
}
|
||||
)
|
||||
return legacy_list
|
||||
+2
-2
@@ -6,8 +6,8 @@
|
||||
from abc import ABC, abstractmethod
|
||||
from typing import Any
|
||||
|
||||
from ...models.data_models import TokenUsage
|
||||
from ...utils.logger import logger
|
||||
from ....domain.models.data_models import TokenUsage
|
||||
from ....utils.logger import logger
|
||||
from ..utils.json_utils import parse_json_response
|
||||
from ..utils.llm_utils import (
|
||||
call_provider_with_retry,
|
||||
+2
-2
@@ -5,8 +5,8 @@
|
||||
|
||||
from datetime import datetime
|
||||
|
||||
from ...models.data_models import GoldenQuote, TokenUsage
|
||||
from ...utils.logger import logger
|
||||
from ....domain.models.data_models import GoldenQuote, TokenUsage
|
||||
from ....utils.logger import logger
|
||||
from ..utils import InfoUtils
|
||||
from ..utils.json_utils import extract_golden_quotes_with_regex
|
||||
from .base_analyzer import BaseAnalyzer
|
||||
+2
-2
@@ -6,8 +6,8 @@
|
||||
import re
|
||||
from datetime import datetime
|
||||
|
||||
from ...models.data_models import SummaryTopic, TokenUsage
|
||||
from ...utils.logger import logger
|
||||
from ....domain.models.data_models import SummaryTopic, TokenUsage
|
||||
from ....utils.logger import logger
|
||||
from ..utils import InfoUtils
|
||||
from ..utils.json_utils import extract_topics_with_regex
|
||||
from .base_analyzer import BaseAnalyzer
|
||||
+2
-2
@@ -3,8 +3,8 @@
|
||||
专门处理用户称号和MBTI类型分析
|
||||
"""
|
||||
|
||||
from ...models.data_models import TokenUsage, UserTitle
|
||||
from ...utils.logger import logger
|
||||
from ....domain.models.data_models import TokenUsage, UserTitle
|
||||
from ....utils.logger import logger
|
||||
from ..utils.json_utils import extract_user_titles_with_regex
|
||||
from .base_analyzer import BaseAnalyzer
|
||||
|
||||
@@ -5,8 +5,13 @@ LLM分析器模块
|
||||
|
||||
import asyncio
|
||||
|
||||
from ..models.data_models import GoldenQuote, SummaryTopic, TokenUsage, UserTitle
|
||||
from ..utils.logger import logger
|
||||
from ...domain.models.data_models import (
|
||||
GoldenQuote,
|
||||
SummaryTopic,
|
||||
TokenUsage,
|
||||
UserTitle,
|
||||
)
|
||||
from ...utils.logger import logger
|
||||
from .analyzers.golden_quote_analyzer import GoldenQuoteAnalyzer
|
||||
from .analyzers.topic_analyzer import TopicAnalyzer
|
||||
from .analyzers.user_title_analyzer import UserTitleAnalyzer
|
||||
@@ -1,234 +1,431 @@
|
||||
"""
|
||||
配置管理器 - 集中化配置管理
|
||||
|
||||
该模块提供了一个访问插件配置的统一接口，
|
||||
封装了现有的配置模块，并增加了验证和默认值功能。
|
||||
配置管理模块 - 基础设施层
|
||||
负责处理插件配置和PDF依赖检查
|
||||
"""
|
||||
|
||||
from typing import Any
|
||||
import sys
|
||||
|
||||
from astrbot.api import AstrBotConfig, logger
|
||||
from astrbot.core.utils.astrbot_path import get_astrbot_data_path
|
||||
|
||||
|
||||
class ConfigManager:
|
||||
"""
|
||||
插件的集中配置管理器。
|
||||
"""配置管理器"""
|
||||
|
||||
提供带有默认值和验证的配置值类型化访问。
|
||||
"""
|
||||
def __init__(self, config: AstrBotConfig):
|
||||
self.config = config
|
||||
self._playwright_available = False
|
||||
self._playwright_version = None
|
||||
self._check_playwright_availability()
|
||||
|
||||
def __init__(self, config: dict[str, Any]):
|
||||
def get_group_list_mode(self) -> str:
|
||||
"""获取群组列表模式 (whitelist/blacklist/none)"""
|
||||
return self.config.get("group_list_mode", "none")
|
||||
|
||||
def get_group_list(self) -> list[str]:
|
||||
"""获取群组列表（用于黑白名单）"""
|
||||
return self.config.get("group_list", [])
|
||||
|
||||
def is_group_allowed(self, group_id_or_umo: str) -> bool:
|
||||
"""
|
||||
初始化配置管理器。
|
||||
|
||||
Args:
|
||||
config: 原始配置字典
|
||||
根据配置的白/黑名单判断是否允许在该群聊中使用
|
||||
支持传入 simple group_id 或 UMO (Unified Message Origin)
|
||||
"""
|
||||
self._config = config or {}
|
||||
mode = self.get_group_list_mode().lower()
|
||||
if mode not in ("whitelist", "blacklist", "none"):
|
||||
mode = "none"
|
||||
|
||||
def get(self, key: str, default: Any = None) -> Any:
|
||||
"""
|
||||
获取配置值。
|
||||
if mode == "none":
|
||||
return True
|
||||
|
||||
Args:
|
||||
key: 配置键（支持点号表示法）
|
||||
default: 如果键未找到则返回默认值
|
||||
glist = [str(g) for g in self.get_group_list()]
|
||||
target = str(group_id_or_umo)
|
||||
|
||||
Returns:
|
||||
配置值或默认值
|
||||
"""
|
||||
try:
|
||||
keys = key.split(".")
|
||||
value = self._config
|
||||
for k in keys:
|
||||
if isinstance(value, dict):
|
||||
value = value.get(k)
|
||||
else:
|
||||
return default
|
||||
if value is None:
|
||||
return default
|
||||
return value
|
||||
except Exception:
|
||||
return default
|
||||
target_simple_id = target.split(":")[-1] if ":" in target else target
|
||||
|
||||
def set(self, key: str, value: Any) -> None:
|
||||
"""
|
||||
设置配置值。
|
||||
def _is_match(item: str, target: str, target_simple_id: str) -> bool:
|
||||
if ":" in item:
|
||||
return item == target
|
||||
return item == target_simple_id
|
||||
|
||||
Args:
|
||||
key: 配置键
|
||||
value: 要设置的值
|
||||
"""
|
||||
keys = key.split(".")
|
||||
config = self._config
|
||||
for k in keys[:-1]:
|
||||
if k not in config:
|
||||
config[k] = {}
|
||||
config = config[k]
|
||||
config[keys[-1]] = value
|
||||
is_in_list = any(_is_match(item, target, target_simple_id) for item in glist)
|
||||
|
||||
# ========================================================================
|
||||
# 群组配置
|
||||
# ========================================================================
|
||||
if mode == "whitelist":
|
||||
return is_in_list
|
||||
if mode == "blacklist":
|
||||
return not is_in_list
|
||||
|
||||
def get_enabled_groups(self) -> list[str]:
|
||||
"""获取启用的群组 ID 列表。"""
|
||||
groups = self.get("enabled_groups", [])
|
||||
return [str(g) for g in groups] if groups else []
|
||||
return True
|
||||
|
||||
def is_group_enabled(self, group_id: str) -> bool:
|
||||
"""检查群组是否启用了分析。"""
|
||||
enabled = self.get_enabled_groups()
|
||||
return str(group_id) in enabled or not enabled # 空列表意味着全部启用
|
||||
def get_max_messages(self) -> int:
|
||||
"""获取最大消息数量"""
|
||||
return self.config.get("max_messages", 1000)
|
||||
|
||||
def get_bot_qq_ids(self) -> list[str]:
|
||||
"""获取要过滤掉的机器人 QQ ID 列表。"""
|
||||
ids = self.get("bot_qq_ids", [])
|
||||
return [str(i) for i in ids] if ids else []
|
||||
def get_analysis_days(self) -> int:
|
||||
"""获取分析天数"""
|
||||
return self.config.get("analysis_days", 1)
|
||||
|
||||
# ========================================================================
|
||||
# 分析配置
|
||||
# ========================================================================
|
||||
def get_auto_analysis_time(self) -> list[str]:
|
||||
"""获取自动分析时间列表"""
|
||||
val = self.config.get("auto_analysis_time", ["09:00"])
|
||||
# 兼容旧版本字符串配置
|
||||
if isinstance(val, str):
|
||||
val_list = [val]
|
||||
# 自动修复配置格式
|
||||
try:
|
||||
self.config["auto_analysis_time"] = val_list
|
||||
self.config.save_config()
|
||||
logger.info(f"自动修复配置格式 auto_analysis_time: {val} -> {val_list}")
|
||||
except Exception as e:
|
||||
logger.warning(f"修复配置格式失败: {e}")
|
||||
return val_list
|
||||
return val if isinstance(val, list) else ["09:00"]
|
||||
|
||||
def get_enable_auto_analysis(self) -> bool:
|
||||
"""获取是否启用自动分析"""
|
||||
return self.config.get("enable_auto_analysis", False)
|
||||
|
||||
def get_output_format(self) -> str:
|
||||
"""获取输出格式"""
|
||||
return self.config.get("output_format", "image")
|
||||
|
||||
def get_min_messages_threshold(self) -> int:
|
||||
"""获取最小消息阈值"""
|
||||
return self.config.get("min_messages_threshold", 50)
|
||||
|
||||
def get_topic_analysis_enabled(self) -> bool:
|
||||
"""获取是否启用话题分析"""
|
||||
return self.config.get("topic_analysis_enabled", True)
|
||||
|
||||
def get_user_title_analysis_enabled(self) -> bool:
|
||||
"""获取是否启用用户称号分析"""
|
||||
return self.config.get("user_title_analysis_enabled", True)
|
||||
|
||||
def get_golden_quote_analysis_enabled(self) -> bool:
|
||||
"""获取是否启用金句分析"""
|
||||
return self.config.get("golden_quote_analysis_enabled", True)
|
||||
|
||||
def get_max_topics(self) -> int:
|
||||
"""获取要提取的最大话题数。"""
|
||||
return int(self.get("max_topics", 5))
|
||||
"""获取最大话题数量"""
|
||||
return self.config.get("max_topics", 5)
|
||||
|
||||
def get_max_user_titles(self) -> int:
|
||||
"""获取要生成的最大用户称号数。"""
|
||||
return int(self.get("max_user_titles", 10))
|
||||
"""获取最大用户称号数量"""
|
||||
return self.config.get("max_user_titles", 8)
|
||||
|
||||
def get_max_golden_quotes(self) -> int:
|
||||
"""获取要提取的最大金句数。"""
|
||||
return int(self.get("max_golden_quotes", 5))
|
||||
"""获取最大金句数量"""
|
||||
return self.config.get("max_golden_quotes", 5)
|
||||
|
||||
def get_min_messages_for_analysis(self) -> int:
|
||||
"""获取分析所需的最小消息数。"""
|
||||
return int(self.get("min_messages", 50))
|
||||
def get_llm_retries(self) -> int:
|
||||
"""获取LLM请求重试次数"""
|
||||
return self.config.get("llm_retries", 2)
|
||||
|
||||
# ========================================================================
|
||||
# LLM 配置
|
||||
def get_topic_provider_id(self) -> str | None:
|
||||
"""获取话题分析的提供商 ID"""
|
||||
return self.get("topic_provider_id")
|
||||
|
||||
def get_user_title_provider_id(self) -> str | None:
|
||||
"""获取用户称号分析的提供商 ID"""
|
||||
return self.get("user_title_provider_id")
|
||||
|
||||
def get_golden_quote_provider_id(self) -> str | None:
|
||||
"""获取金句分析的提供商 ID"""
|
||||
return self.get("golden_quote_provider_id")
|
||||
def get_llm_backoff(self) -> int:
|
||||
"""获取LLM请求重试退避基值（秒），实际退避会乘以尝试次数"""
|
||||
return self.config.get("llm_backoff", 2)
|
||||
|
||||
def get_topic_max_tokens(self) -> int:
|
||||
"""获取话题分析的最大 token 数"""
|
||||
return int(self.get("topic_max_tokens", 2000))
|
||||
|
||||
def get_user_title_max_tokens(self) -> int:
|
||||
"""获取用户称号分析的最大 token 数"""
|
||||
return int(self.get("user_title_max_tokens", 2000))
|
||||
"""获取话题分析最大token数"""
|
||||
return self.config.get("topic_max_tokens", 12288)
|
||||
|
||||
def get_golden_quote_max_tokens(self) -> int:
|
||||
"""获取金句分析的最大 token 数"""
|
||||
return int(self.get("golden_quote_max_tokens", 1500))
|
||||
"""获取金句分析最大token数"""
|
||||
return self.config.get("golden_quote_max_tokens", 4096)
|
||||
|
||||
# ========================================================================
|
||||
# 提示词配置
|
||||
# ========================================================================
|
||||
def get_user_title_max_tokens(self) -> int:
|
||||
"""获取用户称号分析最大token数"""
|
||||
return self.config.get("user_title_max_tokens", 4096)
|
||||
|
||||
def get_topic_analysis_prompt(self) -> str | None:
|
||||
"""获取话题分析的自定义提示词模板"""
|
||||
return self.get("prompts.topic_analysis")
|
||||
def get_debug_mode(self) -> bool:
|
||||
"""获取是否启用调试模式"""
|
||||
return self.config.get("debug_mode", False)
|
||||
|
||||
def get_user_title_analysis_prompt(self) -> str | None:
|
||||
"""获取用户称号分析的自定义提示词模板"""
|
||||
return self.get("prompts.user_title_analysis")
|
||||
def get_llm_provider_id(self) -> str:
|
||||
"""获取主 LLM Provider ID"""
|
||||
return self.config.get("llm_provider_id", "")
|
||||
|
||||
def get_golden_quote_analysis_prompt(self) -> str | None:
|
||||
"""获取金句分析的自定义提示词模板"""
|
||||
return self.get("prompts.golden_quote_analysis")
|
||||
def get_topic_provider_id(self) -> str:
|
||||
"""获取话题分析专用 Provider ID"""
|
||||
return self.config.get("topic_provider_id", "")
|
||||
|
||||
# ========================================================================
|
||||
# 调度配置
|
||||
# ========================================================================
|
||||
def get_user_title_provider_id(self) -> str:
|
||||
"""获取用户称号分析专用 Provider ID"""
|
||||
return self.config.get("user_title_provider_id", "")
|
||||
|
||||
def get_auto_analysis_enabled(self) -> bool:
|
||||
"""检查是否启用了自动分析"""
|
||||
return bool(self.get("auto_analysis_enabled", False))
|
||||
def get_golden_quote_provider_id(self) -> str:
|
||||
"""获取金句分析专用 Provider ID"""
|
||||
return self.config.get("golden_quote_provider_id", "")
|
||||
|
||||
def get_analysis_time(self) -> str:
|
||||
"""获取计划分析时间 (HH:MM 格式)"""
|
||||
return str(self.get("analysis_time", "23:00"))
|
||||
|
||||
def get_analysis_timezone(self) -> str:
|
||||
"""获取计划分析的时区"""
|
||||
return str(self.get("timezone", "Asia/Shanghai"))
|
||||
|
||||
# ========================================================================
|
||||
# 报告配置
|
||||
# ========================================================================
|
||||
|
||||
def get_report_format(self) -> str:
|
||||
"""获取报告格式 (text, markdown, image)"""
|
||||
return str(self.get("report_format", "text"))
|
||||
|
||||
def get_include_statistics(self) -> bool:
|
||||
"""检查是否在报告中包含统计信息"""
|
||||
return bool(self.get("include_statistics", True))
|
||||
|
||||
def get_include_topics(self) -> bool:
|
||||
"""检查是否在报告中包含话题"""
|
||||
return bool(self.get("include_topics", True))
|
||||
|
||||
def get_include_user_titles(self) -> bool:
|
||||
"""检查是否在报告中包含用户称号"""
|
||||
return bool(self.get("include_user_titles", True))
|
||||
|
||||
def get_include_golden_quotes(self) -> bool:
|
||||
"""检查是否在报告中包含金句"""
|
||||
return bool(self.get("include_golden_quotes", True))
|
||||
|
||||
# ========================================================================
|
||||
# 工具方法
|
||||
# ========================================================================
|
||||
|
||||
def to_dict(self) -> dict[str, Any]:
|
||||
"""获取原始配置字典"""
|
||||
return self._config.copy()
|
||||
|
||||
def update(self, updates: dict[str, Any]) -> None:
|
||||
"""
|
||||
使用新值更新配置
|
||||
|
||||
Args:
|
||||
updates: 要应用的更新字典
|
||||
"""
|
||||
self._config.update(updates)
|
||||
|
||||
def validate(self) -> list[str]:
|
||||
"""
|
||||
验证配置
|
||||
|
||||
Returns:
|
||||
验证错误消息列表（如果有效则为空）
|
||||
"""
|
||||
errors = []
|
||||
|
||||
# 验证数值范围
|
||||
if self.get_max_topics() < 1 or self.get_max_topics() > 20:
|
||||
errors.append("max_topics 必须在 1 到 20 之间")
|
||||
|
||||
if self.get_max_user_titles() < 1 or self.get_max_user_titles() > 50:
|
||||
errors.append("max_user_titles 必须在 1 到 50 之间")
|
||||
|
||||
if self.get_max_golden_quotes() < 1 or self.get_max_golden_quotes() > 20:
|
||||
errors.append("max_golden_quotes 必须在 1 到 20 之间")
|
||||
|
||||
# 验证时间格式
|
||||
time_str = self.get_analysis_time()
|
||||
def get_pdf_output_dir(self) -> str:
|
||||
"""获取PDF输出目录"""
|
||||
try:
|
||||
hours, minutes = time_str.split(":")
|
||||
if not (0 <= int(hours) <= 23 and 0 <= int(minutes) <= 59):
|
||||
errors.append("analysis_time 必须是 HH:MM 格式 (00:00-23:59)")
|
||||
except ValueError:
|
||||
errors.append("analysis_time 必须是 HH:MM 格式")
|
||||
plugin_name = "astrbot_plugin_qq_group_daily_analysis"
|
||||
data_path = get_astrbot_data_path()
|
||||
default_path = data_path / "plugin_data" / plugin_name / "reports"
|
||||
return self.config.get("pdf_output_dir", str(default_path))
|
||||
except Exception:
|
||||
return self.config.get(
|
||||
"pdf_output_dir",
|
||||
"data/plugins/astrbot_plugin_qq_group_daily_analysis/reports",
|
||||
)
|
||||
|
||||
return errors
|
||||
def get_bot_self_ids(self) -> list:
|
||||
"""获取机器人自身的 ID 列表 (兼容 bot_qq_ids)"""
|
||||
ids = self.config.get("bot_self_ids", [])
|
||||
if not ids:
|
||||
ids = self.config.get("bot_qq_ids", [])
|
||||
return ids
|
||||
|
||||
def get_pdf_filename_format(self) -> str:
|
||||
"""获取PDF文件名格式"""
|
||||
return self.config.get(
|
||||
"pdf_filename_format", "群聊分析报告_{group_id}_{date}.pdf"
|
||||
)
|
||||
|
||||
def get_topic_analysis_prompt(self, style: str = "topic_prompt") -> str:
|
||||
"""获取话题分析提示词模板"""
|
||||
prompts_config = self.config.get("topic_analysis_prompts", {})
|
||||
prompt = prompts_config.get(style, "topic_prompt")
|
||||
if prompt:
|
||||
return prompt
|
||||
return self.config.get("topic_analysis_prompt", "")
|
||||
|
||||
def get_user_title_analysis_prompt(self, style: str = "user_title_prompt") -> str:
|
||||
"""获取用户称号分析提示词模板"""
|
||||
prompts_config = self.config.get("user_title_analysis_prompts", {})
|
||||
prompt = prompts_config.get(style, "user_title_prompt")
|
||||
if prompt:
|
||||
return prompt
|
||||
return self.config.get("user_title_analysis_prompt", "")
|
||||
|
||||
def get_golden_quote_analysis_prompt(
|
||||
self, style: str = "golden_quote_prompt"
|
||||
) -> str:
|
||||
"""获取金句分析提示词模板"""
|
||||
prompts_config = self.config.get("golden_quote_analysis_prompts", {})
|
||||
prompt = prompts_config.get(style, "golden_quote_prompt")
|
||||
if prompt:
|
||||
return prompt
|
||||
return self.config.get("golden_quote_analysis_prompt", "")
|
||||
|
||||
def set_topic_analysis_prompt(self, prompt: str):
|
||||
"""设置话题分析提示词模板"""
|
||||
self.config["topic_analysis_prompt"] = prompt
|
||||
self.config.save_config()
|
||||
|
||||
def set_user_title_analysis_prompt(self, prompt: str):
|
||||
"""设置用户称号分析提示词模板"""
|
||||
self.config["user_title_analysis_prompt"] = prompt
|
||||
self.config.save_config()
|
||||
|
||||
def set_golden_quote_analysis_prompt(self, prompt: str):
|
||||
"""设置金句分析提示词模板"""
|
||||
self.config["golden_quote_analysis_prompt"] = prompt
|
||||
self.config.save_config()
|
||||
|
||||
def set_output_format(self, format_type: str):
|
||||
"""设置输出格式"""
|
||||
self.config["output_format"] = format_type
|
||||
self.config.save_config()
|
||||
|
||||
def set_group_list_mode(self, mode: str):
|
||||
"""设置群组列表模式"""
|
||||
self.config["group_list_mode"] = mode
|
||||
self.config.save_config()
|
||||
|
||||
def set_group_list(self, groups: list[str]):
|
||||
"""设置群组列表"""
|
||||
self.config["group_list"] = groups
|
||||
self.config.save_config()
|
||||
|
||||
def get_max_concurrent_tasks(self) -> int:
|
||||
"""获取自动分析最大并发数"""
|
||||
return self.config.get("max_concurrent_tasks", 3)
|
||||
|
||||
def set_max_concurrent_tasks(self, count: int):
|
||||
"""设置自动分析最大并发数"""
|
||||
self.config["max_concurrent_tasks"] = count
|
||||
self.config.save_config()
|
||||
|
||||
def set_max_messages(self, count: int):
|
||||
"""设置最大消息数量"""
|
||||
self.config["max_messages"] = count
|
||||
self.config.save_config()
|
||||
|
||||
def set_analysis_days(self, days: int):
|
||||
"""设置分析天数"""
|
||||
self.config["analysis_days"] = days
|
||||
self.config.save_config()
|
||||
|
||||
def set_auto_analysis_time(self, time_val: str | list[str]):
|
||||
"""设置自动分析时间"""
|
||||
self.config["auto_analysis_time"] = time_val
|
||||
self.config.save_config()
|
||||
|
||||
def set_enable_auto_analysis(self, enabled: bool):
|
||||
"""设置是否启用自动分析"""
|
||||
self.config["enable_auto_analysis"] = enabled
|
||||
self.config.save_config()
|
||||
|
||||
def set_min_messages_threshold(self, threshold: int):
|
||||
"""设置最小消息阈值"""
|
||||
self.config["min_messages_threshold"] = threshold
|
||||
self.config.save_config()
|
||||
|
||||
def set_topic_analysis_enabled(self, enabled: bool):
|
||||
"""设置是否启用话题分析"""
|
||||
self.config["topic_analysis_enabled"] = enabled
|
||||
self.config.save_config()
|
||||
|
||||
def set_user_title_analysis_enabled(self, enabled: bool):
|
||||
"""设置是否启用用户称号分析"""
|
||||
self.config["user_title_analysis_enabled"] = enabled
|
||||
self.config.save_config()
|
||||
|
||||
def set_golden_quote_analysis_enabled(self, enabled: bool):
|
||||
"""设置是否启用金句分析"""
|
||||
self.config["golden_quote_analysis_enabled"] = enabled
|
||||
self.config.save_config()
|
||||
|
||||
def set_max_topics(self, count: int):
|
||||
"""设置最大话题数量"""
|
||||
self.config["max_topics"] = count
|
||||
self.config.save_config()
|
||||
|
||||
def set_max_user_titles(self, count: int):
|
||||
"""设置最大用户称号数量"""
|
||||
self.config["max_user_titles"] = count
|
||||
self.config.save_config()
|
||||
|
||||
def set_max_golden_quotes(self, count: int):
|
||||
"""设置最大金句数量"""
|
||||
self.config["max_golden_quotes"] = count
|
||||
self.config.save_config()
|
||||
|
||||
def set_pdf_output_dir(self, directory: str):
|
||||
"""设置PDF输出目录"""
|
||||
self.config["pdf_output_dir"] = directory
|
||||
self.config.save_config()
|
||||
|
||||
def set_pdf_filename_format(self, format_str: str):
|
||||
"""设置PDF文件名格式"""
|
||||
self.config["pdf_filename_format"] = format_str
|
||||
self.config.save_config()
|
||||
|
||||
def get_report_template(self) -> str:
|
||||
"""获取报告模板名称"""
|
||||
return self.config.get("report_template", "scrapbook")
|
||||
|
||||
def set_report_template(self, template_name: str):
|
||||
"""设置报告模板名称"""
|
||||
self.config["report_template"] = template_name
|
||||
self.config.save_config()
|
||||
|
||||
def get_enable_user_card(self) -> bool:
|
||||
"""获取是否使用用户群名片"""
|
||||
return self.config.get("enable_user_card", False)
|
||||
|
||||
@property
|
||||
def playwright_available(self) -> bool:
|
||||
"""检查playwright是否可用"""
|
||||
return self._playwright_available
|
||||
|
||||
@property
|
||||
def playwright_version(self) -> str | None:
|
||||
"""获取playwright版本"""
|
||||
return self._playwright_version
|
||||
|
||||
def _check_playwright_availability(self):
|
||||
"""检查 playwright 可用性"""
|
||||
try:
|
||||
import importlib.util
|
||||
|
||||
if importlib.util.find_spec("playwright") is None:
|
||||
raise ImportError
|
||||
|
||||
import playwright
|
||||
from playwright.async_api import async_playwright # noqa: F401
|
||||
|
||||
self._playwright_available = True
|
||||
|
||||
try:
|
||||
self._playwright_version = playwright.__version__
|
||||
logger.info(f"使用 playwright {self._playwright_version} 作为 PDF 引擎")
|
||||
except AttributeError:
|
||||
self._playwright_version = "unknown"
|
||||
logger.info("使用 playwright (版本未知) 作为 PDF 引擎")
|
||||
|
||||
except ImportError:
|
||||
self._playwright_available = False
|
||||
self._playwright_version = None
|
||||
logger.warning(
|
||||
"playwright 未安装，PDF 功能将不可用。请使用 pip install playwright 安装，并运行 playwright install chromium"
|
||||
)
|
||||
|
||||
def get_browser_path(self) -> str:
|
||||
"""获取自定义浏览器路径"""
|
||||
return self.config.get("browser_path", "")
|
||||
|
||||
def set_browser_path(self, path: str):
|
||||
"""设置自定义浏览器路径"""
|
||||
self.config["browser_path"] = path
|
||||
self.config.save_config()
|
||||
|
||||
def reload_playwright(self) -> bool:
|
||||
"""重新加载 playwright 模块"""
|
||||
try:
|
||||
logger.info("开始重新加载 playwright 模块...")
|
||||
|
||||
modules_to_remove = [
|
||||
mod for mod in sys.modules.keys() if mod.startswith("playwright")
|
||||
]
|
||||
logger.info(f"移除模块: {modules_to_remove}")
|
||||
for mod in modules_to_remove:
|
||||
del sys.modules[mod]
|
||||
|
||||
try:
|
||||
import playwright
|
||||
|
||||
self._playwright_available = True
|
||||
try:
|
||||
self._playwright_version = playwright.__version__
|
||||
logger.info(
|
||||
f"重新加载成功，playwright 版本: {self._playwright_version}"
|
||||
)
|
||||
except AttributeError:
|
||||
self._playwright_version = "unknown"
|
||||
logger.info("重新加载成功，playwright 版本未知")
|
||||
|
||||
return True
|
||||
|
||||
except ImportError:
|
||||
logger.info("playwright 重新导入可能需要重启 AstrBot")
|
||||
self._playwright_available = False
|
||||
self._playwright_version = None
|
||||
return False
|
||||
except Exception:
|
||||
logger.info("playwright 重新导入失败")
|
||||
self._playwright_available = False
|
||||
self._playwright_version = None
|
||||
return False
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"重新加载 playwright 时出错: {e}")
|
||||
return False
|
||||
|
||||
def save_config(self):
|
||||
"""保存配置到AstrBot配置系统"""
|
||||
try:
|
||||
self.config.save_config()
|
||||
logger.info("配置已保存")
|
||||
except Exception as e:
|
||||
logger.error(f"保存配置失败: {e}")
|
||||
|
||||
def reload_config(self):
|
||||
"""重新加载配置"""
|
||||
try:
|
||||
logger.info("重新加载配置...")
|
||||
logger.info("配置重载完成")
|
||||
except Exception as e:
|
||||
logger.error(f"重新加载配置失败: {e}")
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
"""
|
||||
历史记录管理器模块
|
||||
历史记录管理器模块 - 基础设施持久化层
|
||||
负责存储和查询群聊分析报告的摘要信息
|
||||
使用 AstrBot 的 put_kv_data/get_kv_data 实现
|
||||
"""
|
||||
@@ -7,7 +7,7 @@
|
||||
import datetime
|
||||
from typing import Any
|
||||
|
||||
from ..utils.logger import logger
|
||||
from ...utils.logger import logger
|
||||
|
||||
|
||||
class HistoryManager:
|
||||
@@ -90,16 +90,7 @@ class HistoryManager:
|
||||
) -> dict[str, Any] | None:
|
||||
"""
|
||||
根据群组、日期和时间点检索一份历史摘要。
|
||||
|
||||
Args:
|
||||
group_id (str): 群组 ID
|
||||
date_str (str): 日期 (YYYY-MM-DD)
|
||||
time_str (str): 时间点 (HH-MM)
|
||||
|
||||
Returns:
|
||||
dict[str, Any] | None: 历史摘要字典，未找到返回 None
|
||||
"""
|
||||
# 对齐存储时的 Key 规范
|
||||
time_str = time_str.replace(":", "-")
|
||||
key = f"analysis_{group_id}_{date_str}_{time_str}"
|
||||
return await self.plugin.get_kv_data(key, None)
|
||||
@@ -107,14 +98,6 @@ class HistoryManager:
|
||||
async def has_history(self, group_id: str, date_str: str, time_str: str) -> bool:
|
||||
"""
|
||||
快速判定是否存在指定时间点的历史分析记录。
|
||||
|
||||
Args:
|
||||
group_id (str): 群组 ID
|
||||
date_str (str): 日期
|
||||
time_str (str): 时间点
|
||||
|
||||
Returns:
|
||||
bool: 是否存在记录
|
||||
"""
|
||||
history = await self.get_history(group_id, date_str, time_str)
|
||||
return history is not None
|
||||
@@ -474,6 +474,53 @@ class DiscordAdapter(PlatformAdapter):
|
||||
logger.error(f"Discord 文件发送失败: {e}")
|
||||
return False
|
||||
|
||||
async def send_forward_msg(
|
||||
self,
|
||||
group_id: str,
|
||||
nodes: list[dict],
|
||||
) -> bool:
|
||||
"""
|
||||
在 Discord 模拟合并转发。
|
||||
|
||||
由于 Discord 没有原生节点转发 API，我们将其转换为一组文本消息发送。
|
||||
"""
|
||||
if not discord:
|
||||
return False
|
||||
|
||||
try:
|
||||
channel_id = int(group_id)
|
||||
channel = self._discord_client.get_channel(channel_id)
|
||||
if not channel:
|
||||
channel = await self._discord_client.fetch_channel(channel_id)
|
||||
|
||||
if not hasattr(channel, "send"):
|
||||
return False
|
||||
|
||||
# 将节点汇总为美化的文本块
|
||||
lines = ["📊 **结构化报告摘要 (Structured Report)**\n"]
|
||||
for node in nodes:
|
||||
data = node.get("data", node) # 兼容不同格式
|
||||
name = data.get("name", "AstrBot")
|
||||
content = data.get("content", "")
|
||||
lines.append(f"**[{name}]**:\n{content}\n")
|
||||
|
||||
full_text = "\n".join(lines)
|
||||
|
||||
# 分段处理大消息
|
||||
if len(full_text) > 1900:
|
||||
parts = [
|
||||
full_text[i : i + 1900] for i in range(0, len(full_text), 1900)
|
||||
]
|
||||
for part in parts:
|
||||
await channel.send(content=part)
|
||||
else:
|
||||
await channel.send(content=full_text)
|
||||
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.error(f"Discord 模拟转发失败: {e}")
|
||||
return False
|
||||
|
||||
# ==================== IGroupInfoRepository 实现 ====================
|
||||
|
||||
async def get_group_info(self, group_id: str) -> UnifiedGroup | None:
|
||||
|
||||
@@ -418,6 +418,41 @@ class OneBotAdapter(PlatformAdapter):
|
||||
logger.error(f"OneBot 文件发送失败: {e}")
|
||||
return False
|
||||
|
||||
async def send_forward_msg(
|
||||
self,
|
||||
group_id: str,
|
||||
nodes: list[dict],
|
||||
) -> bool:
|
||||
"""
|
||||
发送群合并转发消息。
|
||||
|
||||
Args:
|
||||
group_id (str): 目标群号
|
||||
nodes (list[dict]): 转发节点列表
|
||||
|
||||
Returns:
|
||||
bool: 是否发送成功
|
||||
"""
|
||||
if not hasattr(self.bot, "call_action"):
|
||||
return False
|
||||
|
||||
try:
|
||||
# 兼容处理节点中的 uin -> user_id (有些后端偏好 uin)
|
||||
for node in nodes:
|
||||
if "data" in node:
|
||||
if "user_id" in node["data"] and "uin" not in node["data"]:
|
||||
node["data"]["uin"] = node["data"]["user_id"]
|
||||
|
||||
await self.bot.call_action(
|
||||
"send_group_forward_msg",
|
||||
group_id=int(group_id),
|
||||
messages=nodes,
|
||||
)
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.warning(f"OneBot 发送合并转发消息失败: {e}")
|
||||
return False
|
||||
|
||||
# ==================== IGroupInfoRepository 实现 ====================
|
||||
|
||||
async def get_group_info(self, group_id: str) -> UnifiedGroup | None:
|
||||
|
||||
@@ -1,14 +1,12 @@
|
||||
"""
|
||||
Bot实例管理模块
|
||||
Bot实例管理模块 - 基础设施层
|
||||
统一管理bot实例的获取、设置和使用
|
||||
|
||||
已重构以集成 DDD PlatformAdapter 架构，支持多平台扩展。
|
||||
"""
|
||||
|
||||
from typing import Any
|
||||
|
||||
from ..infrastructure.platform import PlatformAdapter, PlatformAdapterFactory
|
||||
from ..utils.logger import logger
|
||||
from ...utils.logger import logger
|
||||
from . import PlatformAdapter, PlatformAdapterFactory
|
||||
|
||||
|
||||
class BotManager:
|
||||
@@ -146,6 +144,14 @@ class BotManager:
|
||||
"""获取所有已加载的bot实例 {platform_id: bot_instance}"""
|
||||
return self._bot_instances.copy()
|
||||
|
||||
def get_platform_count(self) -> int:
|
||||
"""获取当前已加载的平台数量"""
|
||||
return len(self._bot_instances)
|
||||
|
||||
def get_platform_ids(self) -> list[str]:
|
||||
"""获取所有已加载的平台 ID 列表"""
|
||||
return list(self._bot_instances.keys())
|
||||
|
||||
def has_bot_instance(self) -> bool:
|
||||
"""检查是否有可用的bot实例"""
|
||||
return bool(self._bot_instances)
|
||||
@@ -169,11 +175,6 @@ class BotManager:
|
||||
从 bot 实例检测平台名称，用于创建适配器。
|
||||
|
||||
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）
|
||||
"""
|
||||
# 优先使用 platform 属性
|
||||
if hasattr(bot_instance, "platform"):
|
||||
@@ -304,10 +305,6 @@ class BotManager:
|
||||
elif isinstance(metadata, dict) and "name" in metadata:
|
||||
platform_name = metadata["name"]
|
||||
|
||||
logger.info(
|
||||
f"[群分析插件 BotManager] Initial platform_name detection: {platform_name}"
|
||||
)
|
||||
|
||||
# 验证此平台名称是否受支持，如果不支持，尝试从bot实例检测（如果可用）
|
||||
if (
|
||||
not platform_name
|
||||
@@ -332,22 +329,7 @@ class BotManager:
|
||||
f"发现平台 {platform_id} 但客户端未就绪。将进行懒加载。"
|
||||
)
|
||||
discovered[platform_id] = platform
|
||||
else:
|
||||
# 后备方案：如果元数据丢失/损坏但我们有客户端，尝试使用它
|
||||
if bot_client:
|
||||
platform_name = self._detect_platform_name(bot_client)
|
||||
if platform_name:
|
||||
# 生成临时ID或使用名称
|
||||
platform_id = platform_name
|
||||
logger.warning(
|
||||
f"平台元数据丢失，使用检测到的类型 '{platform_name}' 作为 ID。"
|
||||
)
|
||||
|
||||
self._platforms[platform_id] = platform
|
||||
self.set_bot_instance(bot_client, platform_id, platform_name)
|
||||
discovered[platform_id] = bot_client
|
||||
|
||||
# 记录适配器创建结果
|
||||
if self._adapters:
|
||||
logger.info(
|
||||
f"已创建 {len(self._adapters)} 个 PlatformAdapter: "
|
||||
@@ -367,7 +349,6 @@ class BotManager:
|
||||
discovered = await self.auto_discover_bot_instances()
|
||||
self._is_initialized = True
|
||||
|
||||
# 返回发现的实例字典
|
||||
return discovered
|
||||
|
||||
def get_status_info(self) -> dict[str, Any]:
|
||||
@@ -392,9 +373,6 @@ class BotManager:
|
||||
|
||||
def update_from_event(self, event):
|
||||
"""从事件更新bot实例（用于手动命令）"""
|
||||
# 检查是否为 QQ 平台事件 (兼容性检查)
|
||||
# 注意: 非 aiocqhttp 平台也可以使用，只要适配器已注册
|
||||
|
||||
if hasattr(event, "bot") and event.bot:
|
||||
# 从事件中获取平台ID
|
||||
platform_id = None
|
||||
@@ -449,8 +427,6 @@ class BotManager:
|
||||
def is_plugin_enabled(self, platform_id: str, plugin_name: str) -> bool:
|
||||
"""检查指定平台是否启用了该插件"""
|
||||
if platform_id not in self._platforms:
|
||||
# 如果找不到平台对象（例如是手动添加的），默认认为启用
|
||||
# 或者可以返回 True，因为无法进行否定检查
|
||||
return True
|
||||
|
||||
platform = self._platforms[platform_id]
|
||||
@@ -460,7 +436,7 @@ class BotManager:
|
||||
plugin_set = platform.config.get("plugin_set", ["*"])
|
||||
|
||||
if plugin_set is None:
|
||||
return False # 如果明确为 None, 视为都不启用? 或者默认? Default is ["*"] usually.
|
||||
return False
|
||||
|
||||
if "*" in plugin_set:
|
||||
return True
|
||||
@@ -10,12 +10,13 @@ from pathlib import Path
|
||||
|
||||
import aiohttp
|
||||
|
||||
from ..utils.logger import logger
|
||||
from ...domain.repositories.report_repository import IReportGenerator
|
||||
from ...utils.logger import logger
|
||||
from ..visualization.activity_charts import ActivityVisualizer
|
||||
from .templates import HTMLTemplates
|
||||
|
||||
|
||||
class ReportGenerator:
|
||||
class ReportGenerator(IReportGenerator):
|
||||
"""报告生成器"""
|
||||
|
||||
def __init__(self, config_manager):
|
||||
@@ -9,7 +9,7 @@ import threading
|
||||
|
||||
from jinja2 import Environment, FileSystemLoader, select_autoescape
|
||||
|
||||
from ..utils.logger import logger
|
||||
from ...utils.logger import logger
|
||||
|
||||
|
||||
class HTMLTemplates:
|
||||
@@ -8,10 +8,10 @@ import weakref
|
||||
|
||||
from apscheduler.triggers.cron import CronTrigger
|
||||
|
||||
from ...utils.logger import logger
|
||||
from ..core.message_sender import MessageSender
|
||||
from ..infrastructure.platform.factory import PlatformAdapterFactory
|
||||
from ..reports.dispatcher import ReportDispatcher
|
||||
from ..utils.logger import logger
|
||||
from ..platform.factory import PlatformAdapterFactory
|
||||
from ..reporting.dispatcher import ReportDispatcher
|
||||
from ..utils.trace_context import TraceContext
|
||||
|
||||
|
||||
@@ -21,27 +21,21 @@ class AutoScheduler:
|
||||
def __init__(
|
||||
self,
|
||||
config_manager,
|
||||
message_handler,
|
||||
analyzer,
|
||||
report_generator,
|
||||
analysis_service,
|
||||
bot_manager,
|
||||
retry_manager,
|
||||
history_manager,
|
||||
html_render_func=None,
|
||||
):
|
||||
self.config_manager = config_manager
|
||||
self.message_handler = message_handler
|
||||
self.analyzer = analyzer
|
||||
self.report_generator = report_generator
|
||||
self.analysis_service = analysis_service
|
||||
self.bot_manager = bot_manager
|
||||
self.retry_manager = retry_manager # 保存引用
|
||||
self.history_manager = history_manager
|
||||
self.retry_manager = retry_manager
|
||||
self.html_render_func = html_render_func
|
||||
|
||||
# Initialize Core Components
|
||||
self.message_sender = MessageSender(bot_manager, config_manager, retry_manager)
|
||||
self.report_dispatcher = ReportDispatcher(
|
||||
config_manager, report_generator, self.message_sender, retry_manager
|
||||
config_manager, None, self.message_sender, retry_manager
|
||||
)
|
||||
if html_render_func:
|
||||
self.report_dispatcher.set_html_render(html_render_func)
|
||||
@@ -74,50 +68,26 @@ class AutoScheduler:
|
||||
and self.bot_manager._bot_instances
|
||||
):
|
||||
# 如果只有一个实例，直接返回
|
||||
if len(self.bot_manager._bot_instances) == 1:
|
||||
platform_id = list(self.bot_manager._bot_instances.keys())[0]
|
||||
if self.bot_manager.get_platform_count() == 1:
|
||||
platform_id = self.bot_manager.get_platform_ids()[0]
|
||||
logger.debug(f"只有一个适配器，使用平台: {platform_id}")
|
||||
return platform_id
|
||||
|
||||
# 如果有多个实例，尝试通过API检查群属于哪个适配器
|
||||
# 如果有多个实例，尝试通过适配器检查群属于哪个平台
|
||||
logger.info(f"检测到多个适配器，正在验证群 {group_id} 属于哪个平台...")
|
||||
for platform_id in self.bot_manager.get_all_bot_instances().keys():
|
||||
for platform_id in self.bot_manager.get_platform_ids():
|
||||
try:
|
||||
# 优先使用 Adapter (DDD)
|
||||
adapter = self.bot_manager.get_adapter(platform_id)
|
||||
if adapter:
|
||||
# 通过统一接口尝试获取群信息，如果能获取到则说明属于该平台
|
||||
info = await adapter.get_group_info(str(group_id))
|
||||
if info:
|
||||
logger.info(f"✅ 群 {group_id} 属于平台 {platform_id}")
|
||||
return platform_id
|
||||
else:
|
||||
logger.debug(
|
||||
f"平台 {platform_id} 无法获取群 {group_id} 信息 (返回None)"
|
||||
f"平台 {platform_id} 无法获取群 {group_id} 信息"
|
||||
)
|
||||
continue
|
||||
|
||||
# 回退到原始逻辑 (Legacy)
|
||||
bot_instance = self.bot_manager.get_bot_instance(platform_id)
|
||||
if hasattr(bot_instance, "call_action"):
|
||||
result = await bot_instance.call_action(
|
||||
"get_group_info", group_id=int(group_id)
|
||||
)
|
||||
if result and result.get("group_id"):
|
||||
logger.info(f"✅ 群 {group_id} 属于平台 {platform_id}")
|
||||
return platform_id
|
||||
except Exception as e:
|
||||
logger.debug(f"平台 {platform_id} 验证群 {group_id} 失败: {e}")
|
||||
continue
|
||||
|
||||
# 回退到原始逻辑 (Legacy)
|
||||
bot_instance = self.bot_manager.get_bot_instance(platform_id)
|
||||
if hasattr(bot_instance, "call_action"):
|
||||
result = await bot_instance.call_action(
|
||||
"get_group_info", group_id=int(group_id)
|
||||
)
|
||||
if result and result.get("group_id"):
|
||||
logger.info(f"✅ 群 {group_id} 属于平台 {platform_id}")
|
||||
return platform_id
|
||||
except Exception as e:
|
||||
logger.debug(f"平台 {platform_id} 验证群 {group_id} 失败: {e}")
|
||||
continue
|
||||
@@ -311,7 +281,7 @@ class AutoScheduler:
|
||||
async def _perform_auto_analysis_for_group(
|
||||
self, group_id: str, target_platform_id: str = None
|
||||
):
|
||||
"""为指定群执行自动分析（核心逻辑）"""
|
||||
"""为指定群执行自动分析（业务逻辑委派给 AnalysisApplicationService）"""
|
||||
# 为每个群聊使用独立的锁
|
||||
group_lock_key = f"analysis_{group_id}"
|
||||
if not hasattr(self, "_group_locks"):
|
||||
@@ -324,189 +294,51 @@ class AutoScheduler:
|
||||
|
||||
async with lock:
|
||||
try:
|
||||
start_time = asyncio.get_event_loop().time()
|
||||
|
||||
# 设置 TraceID
|
||||
trace_id = TraceContext.generate(prefix=f"group_{group_id}")
|
||||
TraceContext.set(trace_id)
|
||||
|
||||
import datetime
|
||||
|
||||
now = datetime.datetime.now()
|
||||
date_str = now.strftime("%Y-%m-%d")
|
||||
time_str = now.strftime("%H-%M")
|
||||
|
||||
if await self.history_manager.has_history(group_id, date_str, time_str):
|
||||
logger.info(
|
||||
f"群 {group_id} 在 {date_str} {time_str} 已有分析记录，跳过自动分析"
|
||||
)
|
||||
return
|
||||
|
||||
logger.info(f"开始为群 {group_id} 执行自动分析（并发任务）")
|
||||
logger.info(
|
||||
f"开始为群 {group_id} 执行自动分析 (Platform: {target_platform_id or 'Auto'})"
|
||||
)
|
||||
|
||||
# 检查平台状态 (BotManager 为基础设施层，用于获取平台就绪状态)
|
||||
if not self.bot_manager.is_ready_for_auto_analysis():
|
||||
status = self.bot_manager.get_status_info()
|
||||
logger.warning(
|
||||
f"群 {group_id} 自动分析跳过：bot管理器未就绪 - {status}"
|
||||
)
|
||||
logger.warning(f"群 {group_id} 自动分析跳过：bot管理器未就绪")
|
||||
return
|
||||
|
||||
messages = None
|
||||
platform_id = None
|
||||
bot_instance = None
|
||||
|
||||
# 1. 优先使用指定的 platform_id (如果有)
|
||||
if target_platform_id:
|
||||
if self.bot_manager.is_plugin_enabled(
|
||||
target_platform_id, "astrbot_plugin_qq_group_daily_analysis"
|
||||
):
|
||||
try:
|
||||
logger.info(
|
||||
f"使用指定平台 {target_platform_id} 获取群 {group_id} 的消息..."
|
||||
)
|
||||
bot_instance = self.bot_manager.get_bot_instance(
|
||||
target_platform_id
|
||||
)
|
||||
if bot_instance:
|
||||
analysis_days = self.config_manager.get_analysis_days()
|
||||
messages = (
|
||||
await self.message_handler.fetch_group_messages(
|
||||
bot_instance,
|
||||
group_id,
|
||||
analysis_days,
|
||||
target_platform_id,
|
||||
)
|
||||
)
|
||||
if messages:
|
||||
platform_id = target_platform_id
|
||||
logger.info(
|
||||
f"✅ 群 {group_id} 成功通过平台 {platform_id} 获取到 {len(messages)} 条消息"
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
f"指定平台 {target_platform_id} 获取消息失败: {e}"
|
||||
)
|
||||
|
||||
# 2. 如果指定平台失败或没有指定，尝试自动检测 (原有逻辑)
|
||||
if not messages:
|
||||
# 获取所有可用的平台ID和bot实例
|
||||
if (
|
||||
hasattr(self.bot_manager, "_bot_instances")
|
||||
and self.bot_manager._bot_instances
|
||||
):
|
||||
available_platforms = list(
|
||||
self.bot_manager._bot_instances.items()
|
||||
)
|
||||
logger.info(
|
||||
f"群 {group_id} 检测到 {len(available_platforms)} 个可用平台，开始依次尝试..."
|
||||
)
|
||||
|
||||
for test_platform_id, test_bot_instance in available_platforms:
|
||||
# 如果已经试过 target_platform_id，跳过
|
||||
if (
|
||||
target_platform_id
|
||||
and test_platform_id == target_platform_id
|
||||
):
|
||||
continue
|
||||
|
||||
# 检查该平台是否启用了此插件
|
||||
if not self.bot_manager.is_plugin_enabled(
|
||||
test_platform_id,
|
||||
"astrbot_plugin_qq_group_daily_analysis",
|
||||
):
|
||||
logger.debug(
|
||||
f"平台 {test_platform_id} 未启用此插件，跳过"
|
||||
)
|
||||
continue
|
||||
|
||||
try:
|
||||
logger.info(
|
||||
f"尝试使用平台 {test_platform_id} 获取群 {group_id} 的消息..."
|
||||
)
|
||||
analysis_days = self.config_manager.get_analysis_days()
|
||||
test_messages = (
|
||||
await self.message_handler.fetch_group_messages(
|
||||
test_bot_instance,
|
||||
group_id,
|
||||
analysis_days,
|
||||
test_platform_id,
|
||||
)
|
||||
)
|
||||
|
||||
if test_messages and len(test_messages) > 0:
|
||||
# 成功获取到消息，使用这个平台
|
||||
messages = test_messages
|
||||
platform_id = test_platform_id
|
||||
bot_instance = test_bot_instance
|
||||
logger.info(
|
||||
f"✅ 群 {group_id} 成功通过平台 {platform_id} 获取到 {len(messages)} 条消息"
|
||||
)
|
||||
break
|
||||
else:
|
||||
logger.debug(
|
||||
f"平台 {test_platform_id} 未获取到消息，继续尝试下一个平台"
|
||||
)
|
||||
except Exception as e:
|
||||
logger.debug(
|
||||
f"平台 {test_platform_id} 获取消息失败: {e}，继续尝试下一个平台"
|
||||
)
|
||||
continue
|
||||
|
||||
if not messages:
|
||||
logger.warning(
|
||||
f"群 {group_id} 所有平台都尝试失败，未获取到足够的消息记录"
|
||||
)
|
||||
return
|
||||
else:
|
||||
# 回退到原来的逻辑（单个平台）- 几乎不会走到这里，除非 _bot_instances 为空
|
||||
pass # 省略 legacy 逻辑，因为 _bot_instances 为空在上面 is_ready 检查了
|
||||
|
||||
if not messages:
|
||||
# 最后尝试 legacy get_platform_id_for_group
|
||||
# ... (Keep existing fallback if needed, but the loop above covers most cases)
|
||||
pass
|
||||
|
||||
# 检查消息数量
|
||||
min_threshold = self.config_manager.get_min_messages_threshold()
|
||||
if not messages or len(messages) < min_threshold:
|
||||
logger.warning(
|
||||
f"群 {group_id} 消息数量不足（{len(messages) if messages else 0}条），跳过分析"
|
||||
)
|
||||
return
|
||||
|
||||
logger.info(f"群 {group_id} 获取到 {len(messages)} 条消息，开始分析")
|
||||
|
||||
# 进行分析 - 构造正确的 unified_msg_origin
|
||||
# platform_id 已经在前面获取，直接使用
|
||||
umo = f"{platform_id}:GroupMessage:{group_id}" if platform_id else None
|
||||
analysis_result = await self.analyzer.analyze_messages(
|
||||
messages, group_id, umo
|
||||
# 委派给应用层服务执行核心用例
|
||||
result = await self.analysis_service.execute_daily_analysis(
|
||||
group_id=group_id, platform_id=target_platform_id, manual=False
|
||||
)
|
||||
if not analysis_result:
|
||||
logger.error(f"群 {group_id} 分析失败")
|
||||
|
||||
if not result.get("success"):
|
||||
reason = result.get("reason")
|
||||
logger.info(f"群 {group_id} 自动分析跳过: {reason}")
|
||||
return
|
||||
|
||||
# 生成并发送报告
|
||||
# 获取分析结果及适配器
|
||||
analysis_result = result["analysis_result"]
|
||||
adapter = result["adapter"]
|
||||
|
||||
# 调度导出并发送报告 (由 ReportDispatcher 协调)
|
||||
# 注意：ReportDispatcher 可能也需要轻微重构以接收 adapter
|
||||
# 但目前为了最小化改动，我们仍然使用 dispatcher 逻辑
|
||||
# 传入 platform_id 以便其能正确路由
|
||||
await self.report_dispatcher.dispatch(
|
||||
group_id, analysis_result, platform_id
|
||||
group_id,
|
||||
analysis_result,
|
||||
adapter.platform_id
|
||||
if hasattr(adapter, "platform_id")
|
||||
else target_platform_id,
|
||||
)
|
||||
|
||||
# 保存到历史记录
|
||||
await self.history_manager.save_analysis(
|
||||
group_id, analysis_result, date_str, time_str
|
||||
)
|
||||
|
||||
# 记录执行时间
|
||||
end_time = asyncio.get_event_loop().time()
|
||||
execution_time = end_time - start_time
|
||||
logger.info(f"群 {group_id} 分析完成，耗时: {execution_time:.2f}秒")
|
||||
logger.info(f"群 {group_id} 自动分析任务执行成功")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"群 {group_id} 自动分析执行失败: {e}", exc_info=True)
|
||||
|
||||
finally:
|
||||
# 锁资源由 WeakValueDictionary 自动管理，无需手动清理
|
||||
logger.info(f"群 {group_id} 自动分析完成")
|
||||
logger.debug(f"群 {group_id} 自动分析流程结束")
|
||||
|
||||
async def _get_all_groups(self) -> list[tuple[str, str]]:
|
||||
"""
|
||||
@@ -7,7 +7,7 @@ from dataclasses import dataclass
|
||||
|
||||
import aiohttp
|
||||
|
||||
from ..utils.logger import logger
|
||||
from ...utils.logger import logger
|
||||
|
||||
|
||||
@dataclass
|
||||
@@ -194,73 +194,27 @@ class RetryManager:
|
||||
logger.error(f"[RetryManager] Base64编码失败: {e}")
|
||||
return False
|
||||
|
||||
# 2. 获取 Bot 实例
|
||||
bot = self.bot_manager.get_bot_instance(task.platform_id)
|
||||
if not bot:
|
||||
# 2. 获取适配器 (DDD 基础设施层)
|
||||
adapter = self.bot_manager.get_adapter(task.platform_id)
|
||||
if not adapter:
|
||||
logger.error(
|
||||
f"[RetryManager] 平台 {task.platform_id} 的 Bot 实例未找到，无法重试"
|
||||
f"[RetryManager] 平台 {task.platform_id} 的适配器未找到，无法重试"
|
||||
)
|
||||
return False # 无法重试，因为 Bot 已离线
|
||||
return False
|
||||
|
||||
# 3. 发送图片
|
||||
# 3. 发送图片 (通过统一适配器接口)
|
||||
logger.info(
|
||||
f"[RetryManager] 正在向群 {task.group_id} 发送重试图片 (Base64模式)..."
|
||||
f"[RetryManager] 正在向群 {task.group_id} 发送重试图片 (Adapter: {type(adapter).__name__})..."
|
||||
)
|
||||
|
||||
# 使用 OneBot v11 标准 API
|
||||
if hasattr(bot, "api") and hasattr(bot.api, "call_action"):
|
||||
try:
|
||||
# 构造消息
|
||||
# 使用 list 格式兼容性更好
|
||||
message = [
|
||||
{
|
||||
"type": "text",
|
||||
"data": {"text": "📊 每日群聊分析报告（重试发送）：\n"},
|
||||
},
|
||||
{"type": "image", "data": {"file": image_file_str}},
|
||||
]
|
||||
|
||||
result = await bot.api.call_action(
|
||||
"send_group_msg", group_id=int(task.group_id), message=message
|
||||
)
|
||||
|
||||
# 检查 retcode
|
||||
if isinstance(result, dict):
|
||||
retcode = result.get("retcode", 0)
|
||||
if retcode == 0:
|
||||
return True
|
||||
elif retcode == 1200:
|
||||
# 即使是 Base64 也可能超时，但概率小很多
|
||||
logger.warning(
|
||||
"[RetryManager] 发送失败 (retcode=1200): 消息可能过大或Bot连接不稳定"
|
||||
)
|
||||
return False
|
||||
else:
|
||||
logger.warning(
|
||||
f"[RetryManager] 发送失败 (retcode={retcode}): {result}"
|
||||
)
|
||||
return False
|
||||
return (
|
||||
True # 假设非 dict 类型返回即成功（某些适配器可能返回不同类型）
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[RetryManager] 发送API调用异常: {e}")
|
||||
return False
|
||||
|
||||
elif hasattr(bot, "send_msg"): # 尝试 AstrBot 抽象接口
|
||||
try:
|
||||
# 尝试直接发送
|
||||
await bot.send_msg(image_file_str, group_id=task.group_id)
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.error(f"[RetryManager] 抽象接口发送失败: {e}")
|
||||
return False
|
||||
|
||||
else:
|
||||
logger.warning(
|
||||
f"[RetryManager] 未知的 Bot 类型 {type(bot)}，无法发送消息。"
|
||||
)
|
||||
# 注意：某些适配器可能需要 URL，某些需要 Base64。
|
||||
# 适配器内部通常应处理好 bytes/base64 的发送。
|
||||
# 这里我们尝试直接传 image_file_str (base64://)
|
||||
try:
|
||||
success = await adapter.send_image(task.group_id, image_file_str)
|
||||
return success
|
||||
except Exception as e:
|
||||
logger.error(f"[RetryManager] 适配器发送图片异常: {e}")
|
||||
return False
|
||||
|
||||
except Exception as e:
|
||||
@@ -271,7 +225,7 @@ class RetryManager:
|
||||
pass
|
||||
|
||||
async def _send_fallback_text(self, task: RetryTask):
|
||||
"""发送文本回退报告（使用合并转发）"""
|
||||
"""发送文本回退报告（业务逻辑委派给适配器）"""
|
||||
if not self.report_generator:
|
||||
logger.warning("[RetryManager] 未配置 ReportGenerator，无法发送文本回退")
|
||||
return
|
||||
@@ -282,60 +236,41 @@ class RetryManager:
|
||||
task.analysis_result
|
||||
)
|
||||
|
||||
bot = self.bot_manager.get_bot_instance(task.platform_id)
|
||||
if not bot:
|
||||
# 2. 获取适配器 (DDD 基础设施层)
|
||||
adapter = self.bot_manager.get_adapter(task.platform_id)
|
||||
if not adapter:
|
||||
logger.error(
|
||||
f"[RetryManager] 无法获取适配器 {task.platform_id}，放弃发送回退文本"
|
||||
)
|
||||
return
|
||||
|
||||
# 构造合并转发节点
|
||||
# 注意：这里需要构造符合 OneBot v11 标准的节点列表
|
||||
# 即使没有 self_id，我们也可以尝试发送
|
||||
|
||||
# 获取 bot self_id (如果能获取到)
|
||||
bot_id = "10000" # fallback id
|
||||
if hasattr(bot, "self_id"):
|
||||
bot_id = str(bot.self_id)
|
||||
|
||||
nickname = "AstrBot日常分析"
|
||||
|
||||
nodes = [
|
||||
{
|
||||
"type": "node",
|
||||
"data": {
|
||||
"name": nickname,
|
||||
"uin": bot_id,
|
||||
"content": "⚠️ 图片报告多次生成失败，为您呈现文本版报告：",
|
||||
},
|
||||
},
|
||||
{
|
||||
"type": "node",
|
||||
"data": {"name": nickname, "uin": bot_id, "content": text_report},
|
||||
"data": {"name": nickname, "content": text_report},
|
||||
},
|
||||
]
|
||||
|
||||
if hasattr(bot, "api") and hasattr(bot.api, "call_action"):
|
||||
# 尝试发送群合并转发消息
|
||||
# 一般使用 send_group_forward_msg 或 send_group_msg (带 nodes)
|
||||
try:
|
||||
await bot.api.call_action(
|
||||
"send_group_forward_msg",
|
||||
group_id=int(task.group_id),
|
||||
messages=nodes,
|
||||
)
|
||||
logger.info(
|
||||
f"[RetryManager] 群 {task.group_id} 文本回退报告发送成功 (合并转发)"
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(
|
||||
f"[RetryManager] 合并转发失败，尝试直接发送文本: {e}"
|
||||
)
|
||||
# 回退到直接发送宽文本
|
||||
await bot.api.call_action(
|
||||
"send_group_msg",
|
||||
group_id=int(task.group_id),
|
||||
message=f"⚠️ 图片报告生成失败，文本报告：\n{text_report}"[
|
||||
:4500
|
||||
], # 截断防止过长
|
||||
)
|
||||
# 3. 通过适配器发送结构化消息
|
||||
success = await adapter.send_forward_msg(task.group_id, nodes)
|
||||
|
||||
if success:
|
||||
logger.info(f"[RetryManager] 群 {task.group_id} 文本回退报告发送成功")
|
||||
else:
|
||||
# 最终兜底：发送简单文本
|
||||
logger.warning("[RetryManager] 结构化发送失败，尝试直接发送文本回退")
|
||||
await adapter.send_text(
|
||||
task.group_id,
|
||||
f"⚠️ 图片报告生成失败，文本报告：\n{text_report}"[:4500],
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[RetryManager] 文本回退发送失败: {e}", exc_info=True)
|
||||
logger.error(f"[RetryManager] 文本回退流程异常: {e}", exc_info=True)
|
||||
+1
-1
@@ -6,7 +6,7 @@
|
||||
from collections import defaultdict
|
||||
from datetime import datetime
|
||||
|
||||
from ..models.data_models import ActivityVisualization
|
||||
from ...domain.models.data_models import ActivityVisualization
|
||||
|
||||
|
||||
class ActivityVisualizer:
|
||||
@@ -1,13 +0,0 @@
|
||||
"""
|
||||
数据模型模块
|
||||
"""
|
||||
|
||||
from .data_models import (
|
||||
GoldenQuote,
|
||||
GroupStatistics,
|
||||
SummaryTopic,
|
||||
TokenUsage,
|
||||
UserTitle,
|
||||
)
|
||||
|
||||
__all__ = ["SummaryTopic", "UserTitle", "GoldenQuote", "TokenUsage", "GroupStatistics"]
|
||||
@@ -1,197 +0,0 @@
|
||||
"""
|
||||
通用工具函数模块
|
||||
包含消息分析和其他通用功能
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
from typing import Any
|
||||
|
||||
from ..analysis.llm_analyzer import LLMAnalyzer
|
||||
from ..analysis.statistics import UserAnalyzer
|
||||
from ..core.message_handler import MessageHandler
|
||||
from ..models.data_models import TokenUsage
|
||||
from .logger import logger
|
||||
|
||||
|
||||
class MessageAnalyzer:
|
||||
"""
|
||||
业务逻辑：消息分析整合器
|
||||
|
||||
该类作为一个门面（Facade），将消息存储、统计计算、LLM 智能分析以及用户画像分析
|
||||
等多个底层组件整合在一起，提供统一的消息分析流程接口。
|
||||
|
||||
Attributes:
|
||||
context (Any): AstrBot 上下文环境
|
||||
config_manager (Any): 配置管理者实例
|
||||
bot_manager (Any, optional): 机器人多实例管理者
|
||||
message_handler (MessageHandler): 负责消息过滤和基础统计
|
||||
llm_analyzer (LLMAnalyzer): 负责调用大模型进行语义分析
|
||||
user_analyzer (UserAnalyzer): 负责用户活跃度及角色分析
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self, context: Any, config_manager: Any, bot_manager: Any | None = None
|
||||
):
|
||||
"""
|
||||
初始化消息分析器。
|
||||
|
||||
Args:
|
||||
context (Any): AstrBot 核心上下文
|
||||
config_manager (Any): 插件配置管理器
|
||||
bot_manager (Any, optional): 多平台机器人管理器实例
|
||||
"""
|
||||
self.context = context
|
||||
self.config_manager = config_manager
|
||||
self.bot_manager = bot_manager
|
||||
self.message_handler = MessageHandler(config_manager, bot_manager)
|
||||
self.llm_analyzer = LLMAnalyzer(context, config_manager)
|
||||
self.user_analyzer = UserAnalyzer(config_manager)
|
||||
|
||||
def _extract_bot_self_id_from_instance(self, bot_instance: Any) -> str | None:
|
||||
"""
|
||||
内部方法：从不同平台的机器人实例中探测其自身 ID。
|
||||
|
||||
Args:
|
||||
bot_instance (Any): 宿主机器人实例 (如 OneBot, Discord 实例)
|
||||
|
||||
Returns:
|
||||
str | None: 探测到的用户 ID 或 None
|
||||
"""
|
||||
if hasattr(bot_instance, "self_id") and bot_instance.self_id:
|
||||
return str(bot_instance.self_id)
|
||||
elif hasattr(bot_instance, "user_id") and bot_instance.user_id:
|
||||
return str(bot_instance.user_id)
|
||||
return None
|
||||
|
||||
async def set_bot_instance(
|
||||
self, bot_instance: Any, platform_id: str | None = None
|
||||
) -> None:
|
||||
"""
|
||||
向分析组件注入当前活跃的机器人实例。
|
||||
|
||||
Args:
|
||||
bot_instance (Any): 活跃的机器人 SDK 实例
|
||||
platform_id (str, optional): 平台标识符，用于多实例路由
|
||||
"""
|
||||
if self.bot_manager:
|
||||
self.bot_manager.set_bot_instance(bot_instance, platform_id)
|
||||
else:
|
||||
# 降级逻辑：仅设置单个默认 ID
|
||||
bot_self_id = self._extract_bot_self_id_from_instance(bot_instance)
|
||||
if bot_self_id:
|
||||
await self.message_handler.set_bot_self_ids([bot_self_id])
|
||||
|
||||
async def analyze_messages(
|
||||
self, messages: list[dict], group_id: str, unified_msg_origin: str | None = None
|
||||
) -> dict | None:
|
||||
"""
|
||||
执行完整的群消息流水化分析。
|
||||
|
||||
包含：消息预处理 -> 词频统计 -> 活跃用户识别 -> LLM 摘要/金句提取。
|
||||
|
||||
Args:
|
||||
messages (list[dict]): 待处理的原始或统一格式消息字典列表
|
||||
group_id (str): 群组 ID，用于上下文标识
|
||||
unified_msg_origin (str, optional): 统一消息来源标识
|
||||
|
||||
Returns:
|
||||
dict | None: 包含 statistics, topics, user_titles, user_analysis 的字典，失败返回 None
|
||||
"""
|
||||
try:
|
||||
# 1. 基础消息统计 (耗时操作，放入线程池避免阻塞事件循环)
|
||||
statistics = await asyncio.to_thread(
|
||||
self.message_handler.calculate_statistics, messages
|
||||
)
|
||||
|
||||
# 2. 用户维度分析 (等级、发言习惯等)
|
||||
user_analysis = await asyncio.to_thread(
|
||||
self.user_analyzer.analyze_users, messages
|
||||
)
|
||||
|
||||
# 3. 筛选分析范围：提取 Top N 活跃用户用于深度称号分析
|
||||
max_user_titles = self.config_manager.get_max_user_titles()
|
||||
top_users = self.user_analyzer.get_top_users(
|
||||
user_analysis, limit=max_user_titles
|
||||
)
|
||||
logger.info(
|
||||
f"已为称号分析筛选出 {len(top_users)} 名活跃用户 (最大限制: {max_user_titles})"
|
||||
)
|
||||
|
||||
# 4. LLM 语义分析阶段
|
||||
topics = []
|
||||
user_titles = []
|
||||
golden_quotes = []
|
||||
total_token_usage = TokenUsage()
|
||||
|
||||
# 检查开关设置
|
||||
topic_enabled = self.config_manager.get_topic_analysis_enabled()
|
||||
user_title_enabled = self.config_manager.get_user_title_analysis_enabled()
|
||||
golden_quote_enabled = (
|
||||
self.config_manager.get_golden_quote_analysis_enabled()
|
||||
)
|
||||
|
||||
# 策略：如果多项功能均开启，则通过 LLMAnalyzer 并发调用，显著降低分析总时长
|
||||
if topic_enabled and user_title_enabled and golden_quote_enabled:
|
||||
(
|
||||
topics,
|
||||
user_titles,
|
||||
golden_quotes,
|
||||
total_token_usage,
|
||||
) = await self.llm_analyzer.analyze_all_concurrent(
|
||||
messages, user_analysis, umo=unified_msg_origin, top_users=top_users
|
||||
)
|
||||
else:
|
||||
# 串行降级路径：根据开关按需串行调用 (适用于 Token 敏感或单项测试)
|
||||
if topic_enabled:
|
||||
topics, topic_tokens = await self.llm_analyzer.analyze_topics(
|
||||
messages, umo=unified_msg_origin
|
||||
)
|
||||
total_token_usage.prompt_tokens += topic_tokens.prompt_tokens
|
||||
total_token_usage.completion_tokens += (
|
||||
topic_tokens.completion_tokens
|
||||
)
|
||||
total_token_usage.total_tokens += topic_tokens.total_tokens
|
||||
|
||||
if user_title_enabled:
|
||||
(
|
||||
user_titles,
|
||||
title_tokens,
|
||||
) = await self.llm_analyzer.analyze_user_titles(
|
||||
messages,
|
||||
user_analysis,
|
||||
umo=unified_msg_origin,
|
||||
top_users=top_users,
|
||||
)
|
||||
total_token_usage.prompt_tokens += title_tokens.prompt_tokens
|
||||
total_token_usage.completion_tokens += (
|
||||
title_tokens.completion_tokens
|
||||
)
|
||||
total_token_usage.total_tokens += title_tokens.total_tokens
|
||||
|
||||
if golden_quote_enabled:
|
||||
(
|
||||
golden_quotes,
|
||||
quote_tokens,
|
||||
) = await self.llm_analyzer.analyze_golden_quotes(
|
||||
messages, umo=unified_msg_origin
|
||||
)
|
||||
total_token_usage.prompt_tokens += quote_tokens.prompt_tokens
|
||||
total_token_usage.completion_tokens += (
|
||||
quote_tokens.completion_tokens
|
||||
)
|
||||
total_token_usage.total_tokens += quote_tokens.total_tokens
|
||||
|
||||
# 5. 回填分析结果并组装返回字典
|
||||
statistics.golden_quotes = golden_quotes
|
||||
statistics.token_usage = total_token_usage
|
||||
|
||||
return {
|
||||
"statistics": statistics,
|
||||
"topics": topics,
|
||||
"user_titles": user_titles,
|
||||
"user_analysis": user_analysis,
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"消息分析流水线执行失败: {e}")
|
||||
return None
|
||||
Reference in New Issue
Block a user