Merge branch 'afc' of https://github.com/MoFox-Studio/MoFox_Bot into afc
This commit is contained in:
@@ -4,6 +4,7 @@ PlanExecutor: 接收 Plan 对象并执行其中的所有动作。
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"""
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import asyncio
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import re
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import time
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from typing import Dict, List
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@@ -83,11 +84,11 @@ class PlanExecutor:
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execution_results.extend(reply_result["results"])
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self.execution_stats["reply_executions"] += len(reply_actions)
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# 并行执行其他动作
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# 将其他动作放入后台任务执行,避免阻塞主流程
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if other_actions:
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other_result = await self._execute_other_actions(other_actions, plan)
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execution_results.extend(other_result["results"])
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self.execution_stats["other_action_executions"] += len(other_actions)
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asyncio.create_task(self._execute_other_actions(other_actions, plan))
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logger.info(f"已将 {len(other_actions)} 个其他动作放入后台任务执行。")
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# 注意:后台任务的结果不会立即计入本次返回的统计数据
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# 更新总体统计
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self.execution_stats["total_executed"] += len(plan.decided_actions)
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@@ -216,12 +217,35 @@ class PlanExecutor:
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try:
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logger.info(f"执行其他动作: {action_info.action_type} (原因: {action_info.reasoning})")
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action_data = action_info.action_data or {}
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# 针对 poke_user 动作,特殊处理
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if action_info.action_type == "poke_user":
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target_message = action_info.action_message
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if target_message:
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# 优先直接获取 user_id,这才是最可靠的信息
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user_id = target_message.get("user_id")
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if user_id:
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action_data["user_id"] = user_id
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logger.info(f"检测到戳一戳动作,目标用户ID: {user_id}")
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else:
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# 如果没有 user_id,再尝试用 user_nickname 作为备用方案
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user_name = target_message.get("user_nickname")
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if user_name:
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action_data["user_name"] = user_name
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logger.info(f"检测到戳一戳动作,目标用户: {user_name}")
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else:
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logger.warning("无法从戳一戳消息中获取用户ID或昵称。")
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# 传递原始消息ID以支持引用
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action_data["target_message_id"] = target_message.get("message_id")
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# 构建动作参数
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action_params = {
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"chat_id": plan.chat_id,
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"target_message": action_info.action_message,
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"reasoning": action_info.reasoning,
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"action_data": action_info.action_data or {},
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"action_data": action_data,
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}
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# 通过动作管理器执行动作
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@@ -699,7 +699,32 @@ class DefaultReplyer:
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)
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read_history_prompt = f"这是已读历史消息,仅作为当前聊天情景的参考:\n{read_content}"
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else:
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read_history_prompt = "暂无已读历史消息"
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# 如果没有已读消息,则从数据库加载最近的上下文
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logger.info("暂无已读历史消息,正在从数据库加载上下文...")
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fallback_messages = get_raw_msg_before_timestamp_with_chat(
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chat_id=chat_id,
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timestamp=time.time(),
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limit=global_config.chat.max_context_size,
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)
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if fallback_messages:
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# 从 unread_messages 获取 message_id 列表,用于去重
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unread_message_ids = {msg.message_id for msg in unread_messages}
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filtered_fallback_messages = [
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msg for msg in fallback_messages if msg.get("message_id") not in unread_message_ids
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]
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if filtered_fallback_messages:
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read_content = build_readable_messages(
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filtered_fallback_messages,
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replace_bot_name=True,
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timestamp_mode="normal_no_YMD",
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truncate=True,
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)
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read_history_prompt = f"这是已读历史消息,仅作为当前聊天情景的参考:\n{read_content}"
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else:
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read_history_prompt = "暂无已读历史消息"
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else:
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read_history_prompt = "暂无已读历史消息"
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# 构建未读历史消息 prompt(包含兴趣度)
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unread_history_prompt = ""
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@@ -747,7 +747,7 @@ class VideoAnalyzer:
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os.unlink(temp_path)
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# 保存分析结果到数据库(仅保存成功的结果)
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if success:
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if success and not result.startswith("❌"):
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metadata = {"filename": filename, "file_size": len(video_bytes), "analysis_timestamp": time.time()}
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self._store_video_result(video_hash=video_hash, description=result, metadata=metadata)
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logger.info("✅ 分析结果已保存到数据库")
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@@ -152,10 +152,10 @@ class EmojiAction(BaseAction):
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# 调用LLM
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models = llm_api.get_available_models()
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chat_model_config = models.get("planner")
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chat_model_config = models.get("utils")
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if not chat_model_config:
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logger.error(f"{self.log_prefix} 未找到'planner'模型配置,无法调用LLM")
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return False, "未找到'planner'模型配置"
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logger.error(f"{self.log_prefix} 未找到'utils'模型配置,无法调用LLM")
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return False, "未找到'utils'模型配置"
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success, chosen_emotion, _, _ = await llm_api.generate_with_model(
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prompt, model_config=chat_model_config, request_type="emoji"
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@@ -212,10 +212,10 @@ class EmojiAction(BaseAction):
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# 调用LLM
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models = llm_api.get_available_models()
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chat_model_config = models.get("planner")
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chat_model_config = models.get("utils")
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if not chat_model_config:
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logger.error(f"{self.log_prefix} 未找到'planner'模型配置,无法调用LLM")
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return False, "未找到'planner'模型配置"
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logger.error(f"{self.log_prefix} 未找到'utils'模型配置,无法调用LLM")
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return False, "未找到'utils'模型配置"
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success, chosen_description, _, _ = await llm_api.generate_with_model(
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prompt, model_config=chat_model_config, request_type="emoji"
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@@ -30,7 +30,8 @@ class PokeAction(BaseAction):
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# === 功能描述(必须填写)===
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action_parameters = {
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"user_name": "需要戳一戳的用户的名字",
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"user_name": "需要戳一戳的用户的名字 (可选)",
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"user_id": "需要戳一戳的用户的ID (可选,优先级更高)",
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"times": "需要戳一戳的次数 (默认为 1)",
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}
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action_require = ["当需要戳某个用户时使用", "当你想提醒特定用户时使用"]
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@@ -46,32 +47,38 @@ class PokeAction(BaseAction):
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async def execute(self) -> Tuple[bool, str]:
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"""执行戳一戳的动作"""
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user_id = self.action_data.get("user_id")
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user_name = self.action_data.get("user_name")
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try:
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times = int(self.action_data.get("times", 1))
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except (ValueError, TypeError):
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times = 1
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if not user_name:
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logger.warning("戳一戳动作缺少 'user_name' 参数。")
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return False, "缺少 'user_name' 参数"
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user_info = await get_person_info_manager().get_person_info_by_name(user_name)
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if not user_info or not user_info.get("user_id"):
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logger.info(f"找不到名为 '{user_name}' 的用户。")
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return False, f"找不到名为 '{user_name}' 的用户"
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user_id = user_info.get("user_id")
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# 优先使用 user_id
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if not user_id:
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if not user_name:
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logger.warning("戳一戳动作缺少 'user_id' 或 'user_name' 参数。")
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return False, "缺少用户标识参数"
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# 备用方案:通过 user_name 查找
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user_info = await get_person_info_manager().get_person_info_by_name(user_name)
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if not user_info or not user_info.get("user_id"):
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logger.info(f"找不到名为 '{user_name}' 的用户。")
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return False, f"找不到名为 '{user_name}' 的用户"
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user_id = user_info.get("user_id")
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display_name = user_name or user_id
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for i in range(times):
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logger.info(f"正在向 {user_name} ({user_id}) 发送第 {i + 1}/{times} 次戳一戳...")
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logger.info(f"正在向 {display_name} ({user_id}) 发送第 {i + 1}/{times} 次戳一戳...")
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await self.send_command(
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"SEND_POKE", args={"qq_id": user_id}, display_message=f"戳了戳 {user_name} ({i + 1}/{times})"
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"SEND_POKE", args={"qq_id": user_id}, display_message=f"戳了戳 {display_name} ({i + 1}/{times})"
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)
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# 添加一个小的延迟,以避免发送过快
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await asyncio.sleep(0.5)
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success_message = f"已向 {user_name} 发送 {times} 次戳一戳。"
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success_message = f"已向 {display_name} 发送 {times} 次戳一戳。"
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await self.store_action_info(
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action_build_into_prompt=True, action_prompt_display=success_message, action_done=True
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)
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