如何使用 RemoteGraph 与部署交互

:::info[先决条件]

RemoteGraph 是一个接口，允许你像与常规本地定义的 LangGraph 图（例如 CompiledGraph）一样与你的 LangGraph Platform 部署进行交互。本指南向你展示如何初始化 RemoteGraph 并与之交互。

初始化图

在初始化 RemoteGraph 时，你必须始终指定：

name：你要交互的图的名称。这与你在部署的 langgraph.json 配置文件中使用的图名称相同。
api_key：一个有效的 LangSmith API 密钥。可以作为环境变量设置（LANGSMITH_API_KEY）或通过 api_key 参数直接传递。如果 LangGraphClient / SyncLangGraphClient 是使用 api_key 参数初始化的，API 密钥也可以通过 client / sync_client 参数提供。

此外，你必须提供以下其中一项：

url：你要与之交互的部署的 URL。如果你传递 url 参数，将使用提供的 URL、headers（如果提供）和默认配置值（例如超时等）创建同步和异步客户端。
client：一个 LangGraphClient 实例，用于异步与部署交互（例如使用 .astream()、.ainvoke()、.aget_state()、.aupdate_state() 等）
sync_client：一个 SyncLangGraphClient 实例，用于同步与部署交互（例如使用 .stream()、.invoke()、.get_state()、.update_state() 等）

:::Note

如果你同时传递 client 或 sync_client 以及 url 参数，它们将优先于 url 参数。如果没有提供 client / sync_client / url 参数，RemoteGraph 将在运行时抛出 ValueError。

使用 URL

=== Python

from langgraph.pregel.remote import RemoteGraph

url = <DEPLOYMENT_URL>
graph_name = "agent"
remote_graph = RemoteGraph(graph_name, url=url)

=== JavaScript

import { RemoteGraph } from "@langchain/langgraph/remote";

const url = `<DEPLOYMENT_URL>`;
const graphName = "agent";
const remoteGraph = new RemoteGraph({ graphId: graphName, url });

使用客户端

=== Python

from langgraph_sdk import get_client, get_sync_client
from langgraph.pregel.remote import RemoteGraph

url = <DEPLOYMENT_URL>
graph_name = "agent"
client = get_client(url=url)
sync_client = get_sync_client(url=url)
remote_graph = RemoteGraph(graph_name, client=client, sync_client=sync_client)

=== JavaScript

import { Client } from "@langchain/langgraph-sdk";
import { RemoteGraph } from "@langchain/langgraph/remote";

const client = new Client({ apiUrl: `<DEPLOYMENT_URL>` });
const graphName = "agent";
const remoteGraph = new RemoteGraph({ graphId: graphName, client });

调用图

由于 RemoteGraph 是一个实现了与 CompiledGraph 相同方法的 Runnable，你可以像与编译后的图交互一样与它交互，即调用 .invoke()、.stream()、.get_state()、.update_state() 等（以及它们的异步对应方法）。

异步方式

:::Note

要异步使用图，你必须在初始化 RemoteGraph 时提供 url 或 client。

=== Python

# invoke the graph
result = await remote_graph.ainvoke({
    "messages": [{"role": "user", "content": "what's the weather in sf"}]
})

# stream outputs from the graph
async for chunk in remote_graph.astream({
    "messages": [("user", "what's the weather in la?")]
}):
    print(chunk)

=== JavaScript

// invoke the graph
const result = await remoteGraph.invoke({
    messages: [{role: "user", content: "what's the weather in sf"}]
})

// stream outputs from the graph
for await (const chunk of await remoteGraph.stream({
    messages: [{role: "user", content: "what's the weather in la"}]
})):
    console.log(chunk)

同步方式

:::Note

要同步使用图，你必须在初始化 RemoteGraph 时提供 url 或 sync_client。

=== Python

# invoke the graph
result = remote_graph.invoke({
    "messages": [{"role": "user", "content": "what's the weather in sf"}]
})

# stream outputs from the graph
for chunk in remote_graph.stream({
    "messages": [("user", "what's the weather in la?")]
}):
    print(chunk)

线程级持久化

默认情况下，图运行（即 .invoke() 或 .stream() 调用）是无状态的——检查点和最终状态不会被持久化。如果你想持久化图运行的输出（例如，启用 human-in-the-loop 功能），你可以创建一个线程并通过 config 参数提供线程 ID，就像使用常规编译后的图一样：

=== Python

from langgraph_sdk import get_sync_client
url = <DEPLOYMENT_URL>
graph_name = "agent"
sync_client = get_sync_client(url=url)
remote_graph = RemoteGraph(graph_name, url=url)

# create a thread (or use an existing thread instead)
thread = sync_client.threads.create()

# invoke the graph with the thread config
config = {"configurable": {"thread_id": thread["thread_id"]}}
result = remote_graph.invoke({
    "messages": [{"role": "user", "content": "what's the weather in sf"}], config=config
})

# verify that the state was persisted to the thread
thread_state = remote_graph.get_state(config)
print(thread_state)

=== JavaScript

import { Client } from "@langchain/langgraph-sdk";
import { RemoteGraph } from "@langchain/langgraph/remote";

const url = `<DEPLOYMENT_URL>`;
const graphName = "agent";
const client = new Client({ apiUrl: url });
const remoteGraph = new RemoteGraph({ graphId: graphName, url });

// create a thread (or use an existing thread instead)
const thread = await client.threads.create();

// invoke the graph with the thread config
const config = { configurable: { thread_id: thread.thread_id }};
const result = await remoteGraph.invoke({
  messages: [{ role: "user", content: "what's the weather in sf" }],
  config
});

// verify that the state was persisted to the thread
const threadState = await remoteGraph.getState(config);
console.log(threadState);

用作子图

:::Note

如果你需要在具有 RemoteGraph 子图节点的图中使用 checkpointer，请确保使用 UUID 作为线程 ID。

由于 RemoteGraph 的行为与常规 CompiledGraph 相同，它也可以用作另一个图中的子图。例如：

=== Python

from langgraph_sdk import get_sync_client
from langgraph.graph import StateGraph, MessagesState, START
from typing import TypedDict

url = <DEPLOYMENT_URL>
graph_name = "agent"
remote_graph = RemoteGraph(graph_name, url=url)

# define parent graph
builder = StateGraph(MessagesState)
# add remote graph directly as a node
builder.add_node("child", remote_graph)
builder.add_edge(START, "child")
graph = builder.compile()

# invoke the parent graph
result = graph.invoke({
    "messages": [{"role": "user", "content": "what's the weather in sf"}]
})
print(result)

=== JavaScript

import { MessagesAnnotation, StateGraph, START } from "@langchain/langgraph";
import { RemoteGraph } from "@langchain/langgraph/remote";

const url = `<DEPLOYMENT_URL>`;
const graphName = "agent";
const remoteGraph = new RemoteGraph({ graphId: graphName, url });

// define parent graph and add remote graph directly as a node
const graph = new StateGraph(MessagesAnnotation)
  .addNode("child", remoteGraph)
  .addEdge("START", "child")
  .compile()

// invoke the parent graph
const result = await graph.invoke({
  messages: [{ role: "user", content: "what's the weather in sf" }]
});
console.log(result);

如何使用 RemoteGraph 与部署交互

如何使用 RemoteGraph 与部署交互

初始化图

使用 URL

使用客户端

调用图

异步方式

同步方式

线程级持久化

用作子图

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