无状态运行¶

大多数情况下，当你运行图时，你会向客户端提供一个 thread_id，以便通过 LangGraph 平台中实现的持久状态来跟踪之前的运行。但是，如果你不需要持久化运行，则无需使用内置的持久状态，并且可以创建无状态运行。

设置¶

首先，让我们设置客户端

PythonJavascriptCURL

from langgraph_sdk import get_client

client = get_client(url=<DEPLOYMENT_URL>)
# Using the graph deployed with the name "agent"
assistant_id = "agent"
# create thread
thread = await client.threads.create()

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

const client = new Client({ apiUrl: <DEPLOYMENT_URL> });
// Using the graph deployed with the name "agent"
const assistantId = "agent";
// create thread
const thread = await client.threads.create();

curl --request POST \
    --url <DEPLOYMENT_URL>/assistants/search \
    --header 'Content-Type: application/json' \
    --data '{
        "limit": 10,
        "offset": 0
    }' | jq -c 'map(select(.config == null or .config == {})) | .[0].graph_id' && \
curl --request POST \
    --url <DEPLOYMENT_URL>/threads \
    --header 'Content-Type: application/json' \
    --data '{}'

无状态流式处理¶

我们可以以与从具有状态属性的运行进行流式处理几乎相同的方式流式传输无状态运行的结果，但不是向 thread_id 参数传递值，而是传递 None

PythonJavascriptCURL

input = {
    "messages": [
        {"role": "user", "content": "Hello! My name is Bagatur and I am 26 years old."}
    ]
}

async for chunk in client.runs.stream(
    # Don't pass in a thread_id and the stream will be stateless
    None,
    assistant_id,
    input=input,
    stream_mode="updates",
):
    if chunk.data and "run_id" not in chunk.data:
        print(chunk.data)

let input = {
  messages: [
    { role: "user", content: "Hello! My name is Bagatur and I am 26 years old." }
  ]
};

const streamResponse = client.runs.stream(
  // Don't pass in a thread_id and the stream will be stateless
  null,
  assistantId,
  {
    input,
    streamMode: "updates"
  }
);
for await (const chunk of streamResponse) {
  if (chunk.data && !("run_id" in chunk.data)) {
    console.log(chunk.data);
  }
}

curl --request POST \
    --url <DEPLOYMENT_URL>/runs/stream \
    --header 'Content-Type: application/json' \
    --data "{
        \"assistant_id\": \"agent\",
        \"input\": {\"messages\": [{\"role\": \"human\", \"content\": \"Hello! My name is Bagatur and I am 26 years old.\"}]},
        \"stream_mode\": [
            \"updates\"
        ]
    }" | jq -c 'select(.data and (.data | has("run_id") | not)) | .data'

输出

{'agent': {'messages': [{'content': "Hello Bagatur! It's nice to meet you. Thank you for introducing yourself and sharing your age. Is there anything specific you'd like to know or discuss? I'm here to help with any questions or topics you're interested in.", 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-489ec573-1645-4ce2-a3b8-91b391d50a71', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]}}

等待无状态结果¶

除了流式处理之外，你还可以通过使用 .wait 函数来等待无状态结果，如下所示：

PythonJavascriptCURL

stateless_run_result = await client.runs.wait(
    None,
    assistant_id,
    input=input,
)
print(stateless_run_result)

let statelessRunResult = await client.runs.wait(
  null,
  assistantId,
  { input: input }
);
console.log(statelessRunResult);

curl --request POST \
    --url <DEPLOYMENT_URL>/runs/wait \
    --header 'Content-Type: application/json' \
    --data '{
        "assistant_id": <ASSISTANT_IDD>,
    }'

输出

{
    'messages': [
        {
            'content': 'Hello! My name is Bagatur and I am 26 years old.',
            'additional_kwargs': {},
            'response_metadata': {},
            'type': 'human',
            'name': None,
            'id': '5e088543-62c2-43de-9d95-6086ad7f8b48',
            'example': False}
        ,
        {
            'content': "Hello Bagatur! It's nice to meet you. Thank you for introducing yourself and sharing your age. Is there anything specific you'd like to know or discuss? I'm here to help with any questions or topics you'd like to explore.",
            'additional_kwargs': {},
            'response_metadata': {},
            'type': 'ai',
            'name': None,
            'id': 'run-d6361e8d-4d4c-45bd-ba47-39520257f773',
            'example': False,
            'tool_calls': [],
            'invalid_tool_calls': [],
            'usage_metadata': None
        }
    ]
}