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%%capture --no-stderr
%pip install --quiet -U langchain_openai langchain_core langgraph langgraph-prebuilt
%%capture --no-stderr
%pip install --quiet -U langchain_openai langchain_core langgraph langgraph-prebuilt
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import os, getpass
def _set_env(var: str):
if not os.environ.get(var):
os.environ[var] = getpass.getpass(f"{var}: ")
_set_env("OPENAI_API_KEY")
import os, getpass
def _set_env(var: str):
if not os.environ.get(var):
os.environ[var] = getpass.getpass(f"{var}: ")
_set_env("OPENAI_API_KEY")
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from langchain_openai import ChatOpenAI
def multiply(a: int, b: int) -> int:
"""Multiply a and b.
Args:
a: first int
b: second int
"""
return a * b
llm = ChatOpenAI(model="gpt-4o")
llm_with_tools = llm.bind_tools([multiply])
from langchain_openai import ChatOpenAI
def multiply(a: int, b: int) -> int:
"""Multiply a and b.
Args:
a: first int
b: second int
"""
return a * b
llm = ChatOpenAI(model="gpt-4o")
llm_with_tools = llm.bind_tools([multiply])
我们使用内置的 ToolNode，只需传入工具列表即可初始化该节点。
我们采用内置的 tools_condition作为条件判断边。
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from IPython.display import Image, display
from langgraph.graph import StateGraph, START, END
from langgraph.graph import MessagesState
from langgraph.prebuilt import ToolNode
from langgraph.prebuilt import tools_condition
# Node
def tool_calling_llm(state: MessagesState):
return {"messages": [llm_with_tools.invoke(state["messages"])]}
# Build graph
builder = StateGraph(MessagesState)
builder.add_node("tool_calling_llm", tool_calling_llm)
builder.add_node("tools", ToolNode([multiply]))
builder.add_edge(START, "tool_calling_llm")
builder.add_conditional_edges(
"tool_calling_llm",
# If the latest message (result) from assistant is a tool call -> tools_condition routes to tools
# If the latest message (result) from assistant is a not a tool call -> tools_condition routes to END
tools_condition,
)
builder.add_edge("tools", END)
graph = builder.compile()
# View
display(Image(graph.get_graph().draw_mermaid_png()))
from IPython.display import Image, display
from langgraph.graph import StateGraph, START, END
from langgraph.graph import MessagesState
from langgraph.prebuilt import ToolNode
from langgraph.prebuilt import tools_condition
# Node
def tool_calling_llm(state: MessagesState):
return {"messages": [llm_with_tools.invoke(state["messages"])]}
# Build graph
builder = StateGraph(MessagesState)
builder.add_node("tool_calling_llm", tool_calling_llm)
builder.add_node("tools", ToolNode([multiply]))
builder.add_edge(START, "tool_calling_llm")
builder.add_conditional_edges(
"tool_calling_llm",
# If the latest message (result) from assistant is a tool call -> tools_condition routes to tools
# If the latest message (result) from assistant is a not a tool call -> tools_condition routes to END
tools_condition,
)
builder.add_edge("tools", END)
graph = builder.compile()
# View
display(Image(graph.get_graph().draw_mermaid_png()))
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from langchain_core.messages import HumanMessage
messages = [HumanMessage(content="Hello, what is 2 multiplied by 2?")]
messages = graph.invoke({"messages": messages})
for m in messages['messages']:
m.pretty_print()
from langchain_core.messages import HumanMessage
messages = [HumanMessage(content="Hello, what is 2 multiplied by 2?")]
messages = graph.invoke({"messages": messages})
for m in messages['messages']:
m.pretty_print()
================================ Human Message ================================= Hello world. ================================== Ai Message ================================== Hello! How can I assist you today?
现在我们可以看到图表成功运行了工具！
它返回了一个 ToolMessage 响应。
LangGraph Studio¶
⚠️ 免责声明
自这些视频录制以来，我们已更新 Studio 使其支持本地运行并在浏览器中打开。这现在是运行 Studio 的首选方式（而非视频中展示的桌面应用程序）。关于本地开发服务器的文档请参见此处，运行说明请参见此处。要启动本地开发服务器，请在本模块的 /studio 目录下运行以下终端命令：
langgraph dev
您将看到如下输出：
- 🚀 API: http://127.0.0.1:2024
- 🎨 Studio UI: https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:2024
- 📚 API Docs: http://127.0.0.1:2024/docs
打开浏览器并访问 Studio 界面：https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:2024。
在 Studio 中加载 router，该路由使用 module-1/studio/router.py 的配置，设置文件位于 module-1/studio/langgraph.json。
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if 'google.colab' in str(get_ipython()):
raise Exception("Unfortunately LangGraph Studio is currently not supported on Google Colab")
if 'google.colab' in str(get_ipython()):
raise Exception("Unfortunately LangGraph Studio is currently not supported on Google Colab")
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