开始使用

安装Langchain

在沙箱环境中(.venv\Scripts\activate)执行：

pip install -U "langchain[anthropic]"

WARNING: The directory '/home/jovyan/.cache/pip' or its parent directory is not owned or is not writable by the current user. The cache has been disabled. Check the permissions and owner of that directory. If executing pip with sudo, you should use sudo's -H flag.
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Note: you may need to restart the kernel to use updated packages.

安装Deepagents

pip install deepagents

WARNING: The directory '/home/jovyan/.cache/pip' or its parent directory is not owned or is not writable by the current user. The cache has been disabled. Check the permissions and owner of that directory. If executing pip with sudo, you should use sudo's -H flag.
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Note: you may need to restart the kernel to use updated packages.

初始化模型参数

import os 
from langchain_anthropic import ChatAnthropic 
from deepagents import create_deep_agent

os.environ["ANTHROPIC_API_KEY"] = "sk-..." 

model = ChatAnthropic(model="MiniMax-M2.7",base_url="https://api.minimaxi.com/anthropic")

#定义工具
def get_weather(city: str) -> str:
    """Get weather for a given city."""
    return f"It's always cloudy in {city}!"

agent = create_deep_agent(
	model=model,
	tools=[get_weather],
	system_prompt="You are a helpful assistant",
)
 # this calls init_chat_model for the specified model with default parameters # to use specific model parameters, use init_chat_model directly
print("success");

success

运行Agent

result = agent.invoke({"messages": [{"role": "user", "content": "今天杭州天气怎么样?"}]})

# Print the agent's response
print(result["messages"][-1].content)

[{'signature': '918d19398e420c926bde6dd960f907fb0a5cab93dda683f3d468750b13936da7', 'thinking': "The weather result shows that it's always cloudy in Hangzhou (杭州). Let me provide this information to the user.\n", 'type': 'thinking'}, {'text': '今天杭州天气：多云 🌥️', 'type': 'text'}]

它是如何工作的？

您的 Deep Agent 会自动执行以下操作：

  1. ​规划其方法​：使用内置的 write\_todos 工具来拆解研究任务。
  2. ​进行研究​：通过调用 internet_search 工具来收集信息。
  3. ​管理上下文​：使用文件系统工具（write\_file​, read\_file）来卸载大型搜索结果。
  4. ​生成子智能体：根据需要将复杂的子任务委派给专门的子智能体。
  5. ​合成报告：将研究发现汇总为连贯的报告。

示例

有关您可以使用 Deep Agents 构建的智能体、模式和应用程序，请参阅 示例。

流式处理

Deep Agents 使用 LangGraph 内置了 流式传输 (streaming) 功能，可实现智能体执行过程的实时更新。这使您可以逐步观察输出，并检查和调试智能体及子智能体的工作，例如工具调用、工具结果和 LLM 响应。

后续步骤

现在您已经构建了第一个 Deep Agent

  • ​自定义您的智能体​：了解 自定义选项，包括自定义系统提示词、工具和子智能体。
  • ​添加长期记忆​：在对话中启用 持久化记忆。
  • ​部署到生产环境​：了解 Deep Agents 的 部署选项。

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