420 lines
15 KiB
Python
420 lines
15 KiB
Python
from Plugins.WPSAPI import *
|
||
from datetime import datetime
|
||
from llama_index.llms.ollama import Ollama
|
||
from llama_index.core.llms import ChatMessage
|
||
from typing import List, Dict, Optional
|
||
|
||
logger: ProjectConfig = Architecture.Get(ProjectConfig)
|
||
OLLAMA_URL = logger.FindItem("ollama_url", "http://ollama.liubai.site")
|
||
OLLAMA_MODEL = logger.FindItem("ollama_model", "qwen3:0.6b")
|
||
MAX_HISTORY = logger.FindItem("chat_ai_max_history", 20)
|
||
logger.SaveProperties()
|
||
|
||
|
||
class ChatAIAgent:
|
||
"""AI 对话智能体 - 维护全局会话历史"""
|
||
|
||
_instance: Optional['ChatAIAgent'] = None
|
||
|
||
def __init__(self, ollama_url: str = OLLAMA_URL, max_history: int = MAX_HISTORY):
|
||
"""初始化 AI 智能体
|
||
|
||
Args:
|
||
ollama_url: Ollama 服务地址
|
||
max_history: 最大历史消息数量
|
||
"""
|
||
self.ollama_url = ollama_url
|
||
self.max_history = max_history
|
||
self.llm = Ollama(model=OLLAMA_MODEL, base_url=ollama_url, request_timeout=600.0)
|
||
|
||
# 全局消息历史列表
|
||
self.global_history: List[Dict[str, any]] = []
|
||
|
||
# 系统提示词
|
||
self.system_prompt = """你是一个友好的AI助手，能够同时在多个群聊中与不同用户对话。
|
||
|
||
重要规则：
|
||
- 你能看到所有群聊的对话历史，每条消息都标注了时间、群聊ID和用户ID
|
||
- 当你需要特指某个用户或专门回复某个用户时，必须在回复中使用以下格式：<at user_id="用户ID"></at>
|
||
- 禁止直接输出用户ID数字，始终使用 <at> 标签包裹
|
||
- 注意区分不同群聊和不同用户的对话上下文
|
||
|
||
示例对话：
|
||
[2025-11-20 10:00:00] [群聊#12345] [用户#11111]: 你好
|
||
你的回复: 你好！有什么可以帮助你的吗？
|
||
|
||
[2025-11-20 10:01:00] [群聊#67890] [用户#22222]: 刚刚谁在说话, 说了什么？
|
||
你的回复: 刚刚群聊12345的用户<at user_id="11111"></at>在说话, 他说了你好。"""
|
||
|
||
logger.Log("Info", f"{ConsoleFrontColor.GREEN}ChatAIAgent 初始化完成{ConsoleFrontColor.RESET}")
|
||
logger.Log("Info", f"模型: {OLLAMA_MODEL}, 最大历史: {max_history}")
|
||
|
||
@classmethod
|
||
def get_instance(cls) -> 'ChatAIAgent':
|
||
"""获取单例实例"""
|
||
if cls._instance is None:
|
||
cls._instance = cls()
|
||
return cls._instance
|
||
|
||
def _add_message(self, chat_id: int, user_id: int, role: str, content: str) -> None:
|
||
"""添加消息到全局历史
|
||
|
||
Args:
|
||
chat_id: 群聊ID
|
||
user_id: 用户ID
|
||
role: 角色 (user/assistant)
|
||
content: 消息内容
|
||
"""
|
||
timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
||
message = {
|
||
"timestamp": timestamp,
|
||
"chat_id": chat_id,
|
||
"user_id": user_id,
|
||
"role": role,
|
||
"content": content
|
||
}
|
||
self.global_history.append(message)
|
||
self._trim_history()
|
||
|
||
def _trim_history(self) -> None:
|
||
"""裁剪历史消息到最大长度"""
|
||
if len(self.global_history) > self.max_history:
|
||
# 保留最新的 max_history 条消息
|
||
self.global_history = self.global_history[-self.max_history:]
|
||
logger.Log("Info", f"历史消息已裁剪到 {self.max_history} 条")
|
||
|
||
def clear_history(self) -> bool:
|
||
"""清空全局历史
|
||
|
||
Returns:
|
||
是否成功
|
||
"""
|
||
try:
|
||
old_count = len(self.global_history)
|
||
self.global_history.clear()
|
||
logger.Log("Info", f"已清空全局历史，共删除 {old_count} 条消息")
|
||
return True
|
||
except Exception as e:
|
||
logger.Log("Error", f"清空历史失败: {e}")
|
||
return False
|
||
|
||
def _format_message_with_context(self, msg: Dict[str, any]) -> str:
|
||
"""格式化单条消息，包含上下文信息
|
||
|
||
Args:
|
||
msg: 消息字典
|
||
|
||
Returns:
|
||
格式化后的消息字符串
|
||
"""
|
||
timestamp = msg.get("timestamp", "")
|
||
chat_id = msg.get("chat_id", "")
|
||
user_id = msg.get("user_id", "")
|
||
role = msg.get("role", "")
|
||
content = msg.get("content", "")
|
||
|
||
if role == "user":
|
||
return f"[{timestamp}] [群聊#{chat_id}] [用户#{user_id}]: {content}"
|
||
else: # assistant
|
||
return f"[{timestamp}] [AI助手]: {content}"
|
||
|
||
def _format_history_for_llm(self) -> str:
|
||
"""格式化全局历史为 LLM 输入
|
||
|
||
Returns:
|
||
格式化后的历史字符串
|
||
"""
|
||
if not self.global_history:
|
||
return ""
|
||
|
||
formatted_messages = [
|
||
self._format_message_with_context(msg)
|
||
for msg in self.global_history
|
||
]
|
||
return "\n".join(formatted_messages)
|
||
|
||
async def chat(self, message: str, chat_id: int, user_id: int) -> str:
|
||
"""处理对话
|
||
|
||
Args:
|
||
message: 用户消息
|
||
chat_id: 群聊ID
|
||
user_id: 用户ID
|
||
|
||
Returns:
|
||
AI 回复
|
||
"""
|
||
try:
|
||
# 添加用户消息到历史
|
||
self._add_message(chat_id, user_id, "user", message)
|
||
|
||
# 格式化历史消息（不包括刚添加的用户消息）
|
||
history_without_last = self.global_history[:-1] if len(self.global_history) > 1 else []
|
||
history_text = "\n".join([
|
||
self._format_message_with_context(msg)
|
||
for msg in history_without_last
|
||
]) if history_without_last else "（这是第一条对话）"
|
||
|
||
# 构建当前用户消息的格式化版本
|
||
current_msg = f"[{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}] [群聊#{chat_id}] [用户#{user_id}]: {message}"
|
||
|
||
# 构建对话提示
|
||
conversation_prompt = f"""以下是历史对话记录：
|
||
{history_text}
|
||
|
||
当前消息：
|
||
{current_msg}
|
||
|
||
请作为AI助手回复当前用户。记住：
|
||
1. 使用 <at user_id="{user_id}"></at> 格式来提到任意你想提及的用户
|
||
2. 根据对话历史和当前消息，给出有意义的回复
|
||
3. 如果历史中有其他群聊或用户的信息，你可以引用它们"""
|
||
|
||
logger.Log("Info", f"处理对话 - 群聊#{chat_id} 用户#{user_id}")
|
||
logger.Log("Info", f"当前历史消息数: {len(self.global_history)}")
|
||
|
||
# 使用 achat 方法进行对话
|
||
messages = [
|
||
ChatMessage(role="system", content=self.system_prompt),
|
||
ChatMessage(role="user", content=conversation_prompt)
|
||
]
|
||
|
||
response = await self.llm.achat(messages)
|
||
answer = str(response.message.content)
|
||
|
||
# 添加 AI 回复到历史
|
||
self._add_message(chat_id, user_id, "assistant", answer)
|
||
|
||
logger.Log("Info", f"AI 回复长度: {len(answer)} 字符")
|
||
|
||
return answer
|
||
|
||
except Exception as e:
|
||
logger.Log("Error", f"对话处理失败: {e}")
|
||
import traceback
|
||
error_trace = traceback.format_exc()
|
||
logger.Log("Error", f"详细错误:\n{error_trace}")
|
||
return f"处理对话时出错: {str(e)}"
|
||
|
||
|
||
class ChatAIPlugin(WPSAPI):
|
||
"""AI 对话插件"""
|
||
|
||
def __init__(self):
|
||
super().__init__()
|
||
self.ai_agent = ChatAIAgent.get_instance()
|
||
|
||
@override
|
||
def dependencies(self) -> List[Type]:
|
||
return [WPSAPI]
|
||
|
||
@override
|
||
def is_enable_plugin(self) -> bool:
|
||
return True
|
||
|
||
def get_guide_title(self) -> str:
|
||
return "AI 智能对话"
|
||
|
||
def get_guide_subtitle(self) -> str:
|
||
return "基于 LlamaIndex + Ollama 的多群聊 AI 对话系统"
|
||
|
||
def get_guide_metadata(self) -> Dict[str, str]:
|
||
return {
|
||
"AI模型": OLLAMA_MODEL,
|
||
"最大历史": str(MAX_HISTORY),
|
||
"功能": "跨群聊智能对话",
|
||
}
|
||
|
||
def collect_command_entries(self) -> Sequence[GuideEntry]:
|
||
return (
|
||
{
|
||
"title": "AI对话",
|
||
"identifier": "ai_chat",
|
||
"description": "与AI助手对话，AI能看到所有群聊的历史消息并智能回复。",
|
||
"metadata": {"模型": OLLAMA_MODEL},
|
||
"icon": "🤖",
|
||
"badge": "AI",
|
||
"details": [
|
||
{
|
||
"type": "list",
|
||
"items": [
|
||
"AI 维护全局会话历史，能看到所有群聊的对话",
|
||
"每条消息包含时间戳、群聊ID、用户ID",
|
||
f"最多保留最近 {MAX_HISTORY} 条消息",
|
||
"AI 会使用 @用户 格式回复",
|
||
"示例：ai_chat 你好",
|
||
"示例：ai_chat 刚才其他群聊说了什么？",
|
||
]
|
||
}
|
||
]
|
||
},
|
||
)
|
||
|
||
def collect_guide_entries(self) -> Sequence[GuideEntry]:
|
||
return (
|
||
{
|
||
"title": "全局会话",
|
||
"description": (
|
||
"AI 维护一个全局的对话历史，能够跨群聊、跨用户理解上下文。"
|
||
"所有群聊的对话都在同一个历史中，AI 能够关联不同群聊的信息。"
|
||
),
|
||
"icon": "🌐",
|
||
},
|
||
{
|
||
"title": "智能回复",
|
||
"description": (
|
||
"AI 能够识别消息来源（群聊、用户、时间），并使用 @ 格式回复特定用户。"
|
||
),
|
||
"icon": "💬",
|
||
},
|
||
{
|
||
"title": "历史管理",
|
||
"description": (
|
||
f"自动保留最近 {MAX_HISTORY} 条消息，超出部分自动清理。"
|
||
"可使用 ai_chat_clear 指令手动清空所有历史。"
|
||
),
|
||
"icon": "📝",
|
||
},
|
||
)
|
||
|
||
@override
|
||
def wake_up(self) -> None:
|
||
logger.Log("Info", f"{ConsoleFrontColor.GREEN}ChatAIPlugin AI对话插件已加载{ConsoleFrontColor.RESET}")
|
||
self.register_plugin("ai_chat")
|
||
self.register_plugin("default")
|
||
|
||
@override
|
||
async def callback(self, message: str, chat_id: int, user_id: int) -> str|None:
|
||
"""处理用户对话"""
|
||
try:
|
||
if not message or message.strip() == "":
|
||
help_text = f"""# 🤖 AI 智能对话使用帮助
|
||
|
||
**直接发送消息即可与 AI 对话**
|
||
|
||
**特性：**
|
||
- ✨ AI 能看到所有群聊的对话历史
|
||
- 🌐 跨群聊智能理解上下文
|
||
- 💬 自动使用 @ 格式回复用户
|
||
- 📝 保留最近 {MAX_HISTORY} 条消息
|
||
|
||
**示例：**
|
||
- `ai_chat 你好`
|
||
- `ai_chat 今天天气怎么样？`
|
||
- `ai_chat 刚才其他群聊说了什么？`
|
||
- `ai_chat 请总结一下最近的对话`
|
||
|
||
**清空历史：**
|
||
使用 `ai_chat_clear` 指令清空所有历史消息
|
||
|
||
**技术：**
|
||
基于 LlamaIndex + Ollama ({OLLAMA_MODEL})"""
|
||
return await self.send_markdown_message(help_text, chat_id, user_id)
|
||
|
||
# 使用智能体处理对话
|
||
answer = await self.ai_agent.chat(message, chat_id, user_id)
|
||
|
||
# 格式化返回结果
|
||
formatted_answer = answer
|
||
|
||
return await self.send_markdown_message(formatted_answer, chat_id, user_id)
|
||
|
||
except Exception as e:
|
||
logger.Log("Error", f"AI对话异常: {e}")
|
||
import traceback
|
||
error_detail = traceback.format_exc()
|
||
logger.Log("Error", f"详细错误: {error_detail}")
|
||
error_msg = f"""❌ **处理对话时出错**
|
||
|
||
错误信息：{str(e)}
|
||
|
||
请稍后重试或联系管理员。"""
|
||
return await self.send_markdown_message(error_msg, chat_id, user_id)
|
||
|
||
|
||
class ChatAIClearPlugin(WPSAPI):
|
||
"""清空 AI 对话历史插件"""
|
||
|
||
def __init__(self):
|
||
super().__init__()
|
||
|
||
@override
|
||
def dependencies(self) -> List[Type]:
|
||
return [ChatAIPlugin]
|
||
|
||
@override
|
||
def is_enable_plugin(self) -> bool:
|
||
return True
|
||
|
||
def get_guide_title(self) -> str:
|
||
return "清空 AI 对话历史"
|
||
|
||
def get_guide_subtitle(self) -> str:
|
||
return "清空全局 AI 对话历史记录"
|
||
|
||
def get_guide_metadata(self) -> Dict[str, str]:
|
||
return {
|
||
"功能": "历史管理",
|
||
"作用范围": "全局",
|
||
}
|
||
|
||
def collect_command_entries(self) -> Sequence[GuideEntry]:
|
||
return (
|
||
{
|
||
"title": "清空历史",
|
||
"identifier": "ai_chat_clear",
|
||
"description": "清空 AI 的全局对话历史记录。",
|
||
"icon": "🗑️",
|
||
"badge": "管理",
|
||
"details": [
|
||
{
|
||
"type": "list",
|
||
"items": [
|
||
"清空所有群聊的对话历史",
|
||
"AI 将不再记得之前的对话",
|
||
"不影响 AI 的基础功能",
|
||
"示例：ai_chat_clear",
|
||
]
|
||
}
|
||
]
|
||
},
|
||
)
|
||
|
||
@override
|
||
def wake_up(self) -> None:
|
||
logger.Log("Info", f"{ConsoleFrontColor.GREEN}ChatAIClearPlugin 清空历史插件已加载{ConsoleFrontColor.RESET}")
|
||
self.register_plugin("ai_chat_clear")
|
||
|
||
@override
|
||
async def callback(self, message: str, chat_id: int, user_id: int) -> str|None:
|
||
"""清空对话历史"""
|
||
try:
|
||
# 获取 AI Agent 实例
|
||
ai_agent = ChatAIAgent.get_instance()
|
||
|
||
# 清空历史
|
||
success = ai_agent.clear_history()
|
||
|
||
if success:
|
||
result_msg = """✅ **历史已清空**
|
||
|
||
AI 的全局对话历史已成功清空。
|
||
|
||
AI 将不再记得之前的对话内容。"""
|
||
else:
|
||
result_msg = """❌ **清空失败**
|
||
|
||
清空历史时出现错误，请稍后重试。"""
|
||
|
||
return await self.send_markdown_message(result_msg, chat_id, user_id)
|
||
|
||
except Exception as e:
|
||
logger.Log("Error", f"清空历史异常: {e}")
|
||
error_msg = f"""❌ **清空历史时出错**
|
||
|
||
错误信息：{str(e)}
|
||
|
||
请稍后重试或联系管理员。"""
|
||
return await self.send_markdown_message(error_msg, chat_id, user_id)
|
||
|