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无状态运行

大多数时候，当您运行图时，需要向客户端提供 thread_id，以便通过 LangGraph Cloud 中实现的持久状态跟踪先前的运行。但是，如果您不需要持久化运行，则无需使用内置的持久状态，可以创建无状态运行。

设置

首先，让我们设置客户端

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 '{}'

无状态流式传输

我们可以通过几乎与使用状态属性进行流式传输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

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

除了流式传输，您还可以使用 .wait 函数等待无状态结果，如下所示

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
        }
    ]
}

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