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chore: remove useless plugins

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plugins/agent/README.md
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# Agent插件
## 插件说明
基于 [AgentMesh](https://github.com/MinimalFuture/AgentMesh) 多智能体框架实现的Agent插件，可以让机器人快速获得Agent能力，通过自然语言对话来访问 **终端、浏览器、文件系统、搜索引擎** 等各类工具。
同时还支持通过 **多智能体协作** 来完成复杂任务，例如多智能体任务分发、多智能体问题讨论、协同处理等。
AgentMesh项目地址：https://github.com/MinimalFuture/AgentMesh
## 安装
1. 确保已安装依赖：
```bash
pip install agentmesh-sdk>=0.1.3
```
2. 如需使用浏览器工具，还需安装：
```bash
pip install browser-use>=0.1.40
playwright install
```
## 配置
插件配置文件是 `plugins/agent`目录下的 `config.yaml`，包含智能体团队的配置以及工具的配置，可以从模板文件 `config-template.yaml`中复制：
```bash
cp config-template.yaml config.yaml
```
说明：
- `team`配置是默认选中的 agent team
- `teams` 下是Agent团队配置，团队的model默认为`gpt-4.1-mini`，可根据需要进行修改，模型对应的 `api_key` 需要在项目根目录的 `config.json` 全局配置中进行配置。例如openai模型需要配置 `open_ai_api_key`
- 支持为 `agents` 下面的每个agent添加model字段来设置不同的模型
## 使用方法
在对机器人发送的消息中使用 `$agent` 前缀来触发插件，支持以下命令：
- `$agent [task]`: 使用默认团队执行任务 (默认团队可通 config.yaml 中的team配置修改)
- `$agent teams`: 列出可用的团队
- `$agent use [team_name] [task]`: 使用指定的团队执行任务
### 示例
```bash
$agent 帮我查看当前目录下有哪些文件夹
$agent teams
$agent use software_team 帮我写一个产品预约体验的表单页面
```
## 工具支持
目前支持多种内置工具，包括但不限于：
- `calculator`: 数学计算工具
- `current_time`: 获取当前时间
- `browser`: 浏览器操作工具，注意需安装`browser-use`依赖
- `google_search`: 搜索引擎，注意需在`config.yaml`中配置 `api_key`
- `file_save`: 文件保存工具，开启后智能体输出的内容将保存在 `workspace` 目录下
- `terminal`: 终端命令执行工具

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plugins/agent/__init__.py
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from .agent import AgentPlugin
__all__ = ["AgentPlugin"]

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plugins/agent/agent.py
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import os
import yaml
from typing import Dict, List, Optional
from agentmesh import AgentTeam, Agent, LLMModel
from agentmesh.models import ClaudeModel
from agentmesh.tools import ToolManager
from config import conf
import plugins
from plugins import Plugin, Event, EventContext, EventAction
from bridge.context import ContextType
from bridge.reply import Reply, ReplyType
from common.log import logger
@plugins.register(
name="agent",
desc="Use AgentMesh framework to process tasks with multi-agent teams",
version="0.1.0",
author="Saboteur7",
desire_priority=1,
)
class AgentPlugin(Plugin):
"""Plugin for integrating AgentMesh framework."""
def __init__(self):
super().__init__()
self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context
self.name = "agent"
self.description = "Use AgentMesh framework to process tasks with multi-agent teams"
self.config = self._load_config()
self.tool_manager = ToolManager()
self.tool_manager.load_tools(config_dict=self.config.get("tools"))
logger.debug("[agent] inited")
def _load_config(self) -> Dict:
"""Load configuration from config.yaml file."""
config_path = os.path.join(self.path, "config.yaml")
if not os.path.exists(config_path):
logger.debug(f"Config file not found at {config_path}")
return {}
with open(config_path, 'r', encoding='utf-8') as f:
return yaml.safe_load(f)
def get_help_text(self, verbose=False, **kwargs):
"""Return help message for the agent plugin."""
help_text = "通过AgentMesh实现对终端、浏览器、文件系统、搜索引擎等工具的执行，并支持多智能体协作。"
trigger_prefix = conf().get("plugin_trigger_prefix", "$")
if not verbose:
return help_text
teams = self.get_available_teams()
teams_str = ", ".join(teams) if teams else "未配置任何团队"
help_text += "\n\n使用说明：\n"
help_text += f"{trigger_prefix}agent [task] - 使用默认团队执行任务\n"
help_text += f"{trigger_prefix}agent teams - 列出可用的团队\n"
help_text += f"{trigger_prefix}agent use [team_name] [task] - 使用特定团队执行任务\n\n"
help_text += f"可用团队: \n{teams_str}\n\n"
help_text += f"示例:\n"
help_text += f"{trigger_prefix}agent 帮我查看当前文件夹路径\n"
help_text += f"{trigger_prefix}agent use software_team 帮我写一个产品预约体验的表单页面"
return help_text
def get_available_teams(self) -> List[str]:
"""Get list of available teams from configuration."""
teams_config = self.config.get("teams", {})
return list(teams_config.keys())
def create_team_from_config(self, team_name: str) -> Optional[AgentTeam]:
"""Create a team from configuration."""
# Get teams configuration
teams_config = self.config.get("teams", {})
# Check if the specified team exists
if team_name not in teams_config:
logger.error(f"Team '{team_name}' not found in configuration.")
available_teams = list(teams_config.keys())
logger.info(f"Available teams: {', '.join(available_teams)}")
return None
# Get team configuration
team_config = teams_config[team_name]
# Get team's model
team_model_name = team_config.get("model", "gpt-4.1-mini")
team_model = self.create_llm_model(team_model_name)
# Get team's max_steps (default to 20 if not specified)
team_max_steps = team_config.get("max_steps", 20)
# Create team with the model
team = AgentTeam(
name=team_name,
description=team_config.get("description", ""),
rule=team_config.get("rule", ""),
model=team_model,
max_steps=team_max_steps
)
# Create and add agents to the team
agents_config = team_config.get("agents", [])
for agent_config in agents_config:
# Check if agent has a specific model
if agent_config.get("model"):
agent_model = self.create_llm_model(agent_config.get("model"))
else:
agent_model = team_model
# Get agent's max_steps
agent_max_steps = agent_config.get("max_steps")
agent = Agent(
name=agent_config.get("name", ""),
system_prompt=agent_config.get("system_prompt", ""),
model=agent_model, # Use agent's model if specified, otherwise will use team's model
description=agent_config.get("description", ""),
max_steps=agent_max_steps
)
# Add tools to the agent if specified
tool_names = agent_config.get("tools", [])
for tool_name in tool_names:
tool = self.tool_manager.create_tool(tool_name)
if tool:
agent.add_tool(tool)
else:
if tool_name == "browser":
logger.warning(
"Tool 'Browser' loaded failed, "
"please install the required dependency with: \n"
"'pip install browser-use>=0.1.40' or 'pip install agentmesh-sdk[full]'\n"
)
else:
logger.warning(f"Tool '{tool_name}' not found for agent '{agent.name}'\n")
# Add agent to team
team.add(agent)
return team
def on_handle_context(self, e_context: EventContext):
"""Handle the message context."""
if e_context['context'].type != ContextType.TEXT:
return
content = e_context['context'].content
trigger_prefix = conf().get("plugin_trigger_prefix", "$")
if not content.startswith(f"{trigger_prefix}agent "):
e_context.action = EventAction.CONTINUE
return
if not self.config:
reply = Reply()
reply.type = ReplyType.ERROR
reply.content = "未找到插件配置，请在 plugins/agent 目录下创建 config.yaml 配置文件，可根据 config-template.yml 模板文件复制"
e_context['reply'] = reply
e_context.action = EventAction.BREAK_PASS
return
# Extract the actual task
task = content[len(f"{trigger_prefix}agent "):].strip()
# If task is empty, return help message
if not task:
reply = Reply()
reply.type = ReplyType.TEXT
reply.content = self.get_help_text(verbose=True)
e_context['reply'] = reply
e_context.action = EventAction.BREAK_PASS
return
# Check if task is asking for available teams
if task.lower() in ["teams", "list teams", "show teams"]:
teams = self.get_available_teams()
reply = Reply()
reply.type = ReplyType.TEXT
if not teams:
reply.content = "未配置任何团队。请检查 config.yaml 文件。"
else:
reply.content = f"可用团队: {', '.join(teams)}"
e_context['reply'] = reply
e_context.action = EventAction.BREAK_PASS
return
# Check if task specifies a team
team_name = None
if task.startswith("use "):
parts = task[4:].split(" ", 1)
if len(parts) > 0:
team_name = parts[0]
if len(parts) > 1:
task = parts[1].strip()
else:
reply = Reply()
reply.type = ReplyType.TEXT
reply.content = f"已选择团队 '{team_name}'。请输入您想执行的任务。"
e_context['reply'] = reply
e_context.action = EventAction.BREAK_PASS
return
if not team_name:
team_name = self.config.get("team")
# If no team specified, use default or first available
if not team_name:
teams = self.configself.get_available_teams()
if not teams:
reply = Reply()
reply.type = ReplyType.TEXT
reply.content = "未配置任何团队。请检查 config.yaml 文件。"
e_context['reply'] = reply
e_context.action = EventAction.BREAK_PASS
return
team_name = teams[0]
# Create team
team = self.create_team_from_config(team_name)
if not team:
reply = Reply()
reply.type = ReplyType.TEXT
reply.content = f"创建团队 '{team_name}' 失败。请检查配置。"
e_context['reply'] = reply
e_context.action = EventAction.BREAK_PASS
return
# Run the task
try:
logger.info(f"[agent] Running task '{task}' with team '{team_name}', team_model={team.model.model}")
result = team.run_async(task=task)
for agent_result in result:
res_text = f"🤖 {agent_result.get('agent_name')}\n\n{agent_result.get('final_answer')}"
_send_text(e_context, content=res_text)
reply = Reply()
reply.type = ReplyType.TEXT
reply.content = ""
e_context['reply'] = reply
e_context.action = EventAction.BREAK_PASS
except Exception as e:
logger.exception(f"Error running task with team '{team_name}'")
reply = Reply()
reply.type = ReplyType.ERROR
reply.content = f"执行任务时出错: {str(e)}"
e_context['reply'] = reply
e_context.action = EventAction.BREAK_PASS
return
def create_llm_model(self, model_name) -> LLMModel:
if conf().get("use_linkai"):
api_base = "https://api.link-ai.tech/v1"
api_key = conf().get("linkai_api_key")
elif model_name.startswith(("gpt", "text-davinci", "o1", "o3")):
api_base = conf().get("open_ai_api_base") or "https://api.openai.com/v1"
api_key = conf().get("open_ai_api_key")
elif model_name.startswith("claude"):
return ClaudeModel(model=model_name, api_key=conf().get("claude_api_key"))
elif model_name.startswith("moonshot"):
api_base = "https://api.moonshot.cn/v1"
api_key = conf().get("moonshot_api_key")
elif model_name.startswith("qwen"):
api_base = "https://dashscope.aliyuncs.com/compatible-mode/v1"
api_key = conf().get("dashscope_api_key")
else:
api_base = conf().get("open_ai_api_base") or "https://api.openai.com/v1"
api_key = conf().get("open_ai_api_key")
llm_model = LLMModel(model=model_name, api_key=api_key, api_base=api_base)
return llm_model
def _send_text(e_context: EventContext, content: str):
reply = Reply(ReplyType.TEXT, content)
channel = e_context["channel"]
channel.send(reply, e_context["context"])

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plugins/agent/config-template.yaml
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# 默认选中的Agent Team名称
team: general_team
tools:
google_search:
# get your apikey from https://serper.dev/
api_key: "YOUR API KEY"
# Agent Team 配置
teams:
# 通用智能体团队
general_team:
model: "gpt-4.1-mini" # 团队使用的模型
description: "A versatile research and information agent team"
max_steps: 5
agents:
- name: "通用智能助手"
description: "Universal assistant specializing in research, information synthesis, and task execution"
system_prompt: "You are a versatile assistant who answers questions and completes tasks using available tools. Reply in a clearly structured, attractive and easy to read format."
# Agent 支持使用的工具
tools:
- time
- calculator
- google_search
- browser
- terminal
# 软件开发智能体团队
software_team:
model: "gpt-4.1-mini"
description: "A software development team with product manager, developer and tester."
rule: "A normal R&D process should be that Product Manager writes PRD, Developer writes code based on PRD, and Finally, Tester performs testing."
max_steps: 10
agents:
- name: "Product-Manager"
description: "Responsible for product requirements and documentation"
system_prompt: "You are an experienced product manager who creates concise PRDs, focusing on user needs and feature specifications. You always format your responses in Markdown."
tools:
- time
- file_save
- name: "Developer"
description: "Implements code based on PRD"
system_prompt: "You are a skilled developer. When developing web application, you creates single-page website based on user needs, you deliver HTML files with embedded JavaScript and CSS that are visually appealing, responsive, and user-friendly, featuring a grand layout and beautiful background. The HTML, CSS, and JavaScript code should be well-structured and effectively organized."
tools:
- file_save
- name: "Tester"
description: "Tests code and verifies functionality"
system_prompt: "You are a tester who validates code against requirements. For HTML applications, use browser tools to test functionality. For Python or other client-side applications, use the terminal tool to run and test. You only need to test a few core cases."
tools:
- file_save
- browser
- terminal