如何向预构建的 ReAct 智能体添加内存¶

先决条件

本指南假设您熟悉以下内容

• LangGraph 持久性
• Checkpointer 接口
• 智能体架构
• 聊天模型
• 工具

本指南将演示如何向预构建的 ReAct 智能体添加内存。有关如何开始使用预构建的 ReAct 智能体的更多信息，请参阅本教程

我们可以通过将检查点传递给create_react_agent 函数来向智能体添加内存。

设置¶

首先，让我们安装所需的软件包并设置 API 密钥

在 [1]

%%capture --no-stderr
%pip install -U langgraph langchain-openai

%%capture --no-stderr %pip install -U langgraph langchain-openai

在 [2]

import getpass
import os


def _set_env(var: str):
    if not os.environ.get(var):
        os.environ[var] = getpass.getpass(f"{var}: ")


_set_env("OPENAI_API_KEY")

import getpass import os def _set_env(var: str): if not os.environ.get(var): os.environ[var] = getpass.getpass(f"{var}: ") _set_env("OPENAI_API_KEY")

为 LangGraph 开发设置 LangSmith

注册 LangSmith 以快速发现问题并提高 LangGraph 项目的性能。LangSmith 允许您使用跟踪数据来调试、测试和监控使用 LangGraph 构建的 LLM 应用程序 - 了解有关如何开始的更多信息此处。

代码¶

在 [3]

# First we initialize the model we want to use.
from langchain_openai import ChatOpenAI

model = ChatOpenAI(model="gpt-4o", temperature=0)


# For this tutorial we will use custom tool that returns pre-defined values for weather in two cities (NYC & SF)

from typing import Literal

from langchain_core.tools import tool


@tool
def get_weather(city: Literal["nyc", "sf"]):
    """Use this to get weather information."""
    if city == "nyc":
        return "It might be cloudy in nyc"
    elif city == "sf":
        return "It's always sunny in sf"
    else:
        raise AssertionError("Unknown city")


tools = [get_weather]

# We can add "chat memory" to the graph with LangGraph's checkpointer
# to retain the chat context between interactions
from langgraph.checkpoint.memory import MemorySaver

memory = MemorySaver()

# Define the graph

from langgraph.prebuilt import create_react_agent

graph = create_react_agent(model, tools=tools, checkpointer=memory)

# 首先，我们初始化要使用的模型。 from langchain_openai import ChatOpenAI model = ChatOpenAI(model="gpt-4o", temperature=0) # 对于本教程，我们将使用自定义工具，该工具返回两个城市（纽约和旧金山）的天气预定义值 from typing import Literal from langchain_core.tools import tool @tool def get_weather(city: Literal["nyc", "sf"]): """使用此工具获取天气信息。""" if city == "nyc": return "纽约的天气可能多云" elif city == "sf": return "旧金山总是阳光明媚" else: raise AssertionError("未知城市") tools = [get_weather] # 我们可以使用 LangGraph 的检查点将“聊天内存”添加到图中 # 以在交互之间保留聊天上下文 from langgraph.checkpoint.memory import MemorySaver memory = MemorySaver() # 定义图 from langgraph.prebuilt import create_react_agent graph = create_react_agent(model, tools=tools, checkpointer=memory)

用法¶

让我们多次与它交互以显示它可以记住信息

在 [5]

def print_stream(stream):
    for s in stream:
        message = s["messages"][-1]
        if isinstance(message, tuple):
            print(message)
        else:
            message.pretty_print()

def print_stream(stream): for s in stream: message = s["messages"][-1] if isinstance(message, tuple): print(message) else: message.pretty_print()

在 [6]

config = {"configurable": {"thread_id": "1"}}
inputs = {"messages": [("user", "What's the weather in NYC?")]}

print_stream(graph.stream(inputs, config=config, stream_mode="values"))

config = {"configurable": {"thread_id": "1"}} inputs = {"messages": [("user", "纽约的天气怎么样？")]} print_stream(graph.stream(inputs, config=config, stream_mode="values"))

================================ Human Message =================================

What's the weather in NYC?
================================== Ai Message ==================================
Tool Calls:
  get_weather (call_xM1suIq26KXvRFqJIvLVGfqG)
 Call ID: call_xM1suIq26KXvRFqJIvLVGfqG
  Args:
    city: nyc
================================= Tool Message =================================
Name: get_weather

It might be cloudy in nyc
================================== Ai Message ==================================

The weather in NYC might be cloudy.

请注意，当我们传递相同的线程 ID 时，聊天历史记录会保留下来

在 [7]

inputs = {"messages": [("user", "What's it known for?")]}
print_stream(graph.stream(inputs, config=config, stream_mode="values"))

inputs = {"messages": [("user", "它以什么而闻名？")]} print_stream(graph.stream(inputs, config=config, stream_mode="values"))

================================ Human Message =================================

What's it known for?
================================== Ai Message ==================================

New York City (NYC) is known for a variety of iconic landmarks, cultural institutions, and vibrant neighborhoods. Some of the most notable aspects include:

1. **Statue of Liberty**: A symbol of freedom and democracy.
2. **Times Square**: Known for its bright lights, Broadway theaters, and bustling atmosphere.
3. **Central Park**: A large urban park offering a green oasis in the middle of the city.
4. **Empire State Building**: An iconic skyscraper with an observation deck offering panoramic views of the city.
5. **Broadway**: Famous for its world-class theater productions.
6. **Wall Street**: The financial hub of the United States.
7. **Museums**: Including the Metropolitan Museum of Art, the Museum of Modern Art (MoMA), and the American Museum of Natural History.
8. **Diverse Cuisine**: A melting pot of culinary experiences from around the world.
9. **Cultural Diversity**: A rich tapestry of cultures, languages, and traditions.
10. **Fashion**: A global fashion capital, home to New York Fashion Week.

These are just a few highlights of what makes NYC a unique and vibrant city.

在 []

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