85 lines
2.2 KiB
Python
85 lines
2.2 KiB
Python
#!/usr/bin/env python3
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"""
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演示 thinking 输出的示例
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这个脚本展示了在 verbose 模式下，Agent 会同时输出思考过程和执行动作。
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"""
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from phone_agent import PhoneAgent
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from phone_agent.agent import AgentConfig
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from phone_agent.model import ModelConfig
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def main():
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print("=" * 60)
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print("Phone Agent - Thinking 输出演示")
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print("=" * 60)
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# 配置模型
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model_config = ModelConfig(
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base_url="http://localhost:8000/v1",
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model_name="autoglm-phone-9b",
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temperature=0.1,
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)
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# 配置 Agent (verbose=True 会输出详细信息)
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agent_config = AgentConfig(
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max_steps=10,
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verbose=True, # 开启详细输出
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)
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# 创建 Agent
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agent = PhoneAgent(
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model_config=model_config,
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agent_config=agent_config,
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)
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# 执行任务
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print("\n📱 开始执行任务...\n")
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result = agent.run("打开小红书搜索美食攻略")
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print("\n" + "=" * 60)
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print(f"📊 最终结果: {result}")
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print("=" * 60)
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if __name__ == "__main__":
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"""
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运行此脚本，你将看到如下格式的输出：
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==================================================
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💭 思考过程:
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--------------------------------------------------
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当前在系统桌面，需要先启动小红书应用，然后进行搜索
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--------------------------------------------------
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🎯 执行动作:
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{
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"_metadata": "do",
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"action": "Launch",
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"app": "小红书"
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}
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==================================================
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(执行后会继续下一步...)
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==================================================
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💭 思考过程:
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--------------------------------------------------
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小红书已打开，现在需要点击搜索框并输入关键词
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--------------------------------------------------
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🎯 执行动作:
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{
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"_metadata": "do",
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"action": "Tap",
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"element": [500, 100]
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}
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==================================================
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... (更多步骤)
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🎉 ================================================
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✅ 任务完成: 已成功搜索美食攻略
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==================================================
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"""
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main()
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