AgentScope2

1.quickstart

import asyncio
import osfrom agentscope.agent import Agentfrom agentscope.event import EventType
from agentscope.message import UserMsg
from agentscope.tool import Toolkit, Bash, Read, Write, Edit
from agentscope.model import AnthropicChatModel
from agentscope.credential import AnthropicCredentialMINIMAX_API_KEY = os.environ.get("MINIMAX_API_KEY","",
)async def main() -> None:model = AnthropicChatModel(credential=AnthropicCredential(api_key=MINIMAX_API_KEY,base_url="https://api.minimaxi.com/anthropic",),model="MiniMax-M2.5",stream=True)agent = Agent(name="Friday",system_prompt="You are a helpful assistant named Friday.",model=model,toolkit=Toolkit(tools=[Bash(), Read(), Write(), Edit()]),)user_msg = UserMsg(name="user", content="告诉斐波那契数列的前10项")# # 方式一：等待最终的助手消息。# reply_msg = await agent.reply(user_msg)# # `reply_msg` 是一个 `AssistantMsg`，其 `content` 是一组内容块。# # 可按需检查文本块、工具调用等。# 方式二：流式获取增量事件（文本片段、工具调用等）。async for event in agent.reply_stream(user_msg):print(event)# 根据 `event.type` 分发处理 —— 每个分支对应一种事件类型。match event.type:case EventType.TEXT_BLOCK_DELTA:# 模型返回的流式文本片段 —— 追加到界面或标准输出。print(event.delta)if __name__ == "__main__":asyncio.run(main())

1.消息和事件

import asyncio
import osfrom agentscope.agent import Agentfrom agentscope.event import EventType
from agentscope.tool import Toolkit, Bash, Read, Write, Edit
from agentscope.model import AnthropicChatModel
from agentscope.credential import AnthropicCredential
from agentscope.message import UserMsg, AssistantMsg, SystemMsgMINIMAX_API_KEY = os.environ.get("MINIMAX_API_KEY","sk-api-1Mk2lu1pxRcpnR2UPLWneKaI5cgPCd1nKVw5fbdTvbOWWi1P4xoKmMAdStAjEkxsxnvOmDVvYzkfh7rd1LHY1uwW8ME5WdOfvvq08MSd2Eo1O_k0qdpgV3M",
)async def main() -> None:model = AnthropicChatModel(credential=AnthropicCredential(api_key=MINIMAX_API_KEY,base_url="https://api.minimaxi.com/anthropic",),model="MiniMax-M2.5",stream=True)system_msg = SystemMsg(name="system", content="你是MegaAgent")agent = Agent(name="Friday",# 所有 TextBlock 的拼接文本system_prompt=system_msg.get_text_content(),model=model,toolkit=Toolkit(tools=[Bash(), Read(), Write(), Edit()]))user_msg = UserMsg(name="user", content="告诉我这个文件的内容D://WorkSpace//AI//megaAgent//backend//article.md")# 发送消息async for event in agent.reply_stream(user_msg):print(event)match event.type:# 生命周期case EventType.REPLY_START:print("模型开始返回结果")case EventType.REPLY_END:print("模型返回结果结束")case EventType.MODEL_CALL_START:print("模型 API 调用开始")case EventType.MODEL_CALL_END:print("模型 API 调用结束")# 思考case EventType.THINKING_BLOCK_START:print("模型开始思考")case EventType.THINKING_BLOCK_DELTA:print("模型思考内容:" + event.delta)case EventType.THINKING_BLOCK_END:print("模型结束思考")# 文本块case EventType.TEXT_BLOCK_START:print("文本块开始")case EventType.TEXT_BLOCK_DELTA:print("文本内容" + event.delta)case EventType.TEXT_BLOCK_END:print("文本块结束")# 工具调用case EventType.TOOL_CALL_START:print("工具调用开始" + event.tool_call_name)case EventType.TOOL_CALL_DELTA:print("工具调用参数内容" + event.delta)case EventType.TOOL_CALL_END:print("工具调用结束")case EventType.TOOL_RESULT_START:print("工具调用结果开始")case EventType.TOOL_RESULT_TEXT_DELTA:print("工具调用结果文本内容" + event.delta)case EventType.TOOL_RESULT_END:print("工具调用结果结束" + event.state)if __name__ == "__main__":asyncio.run(main())