Skip to main content
大多数情况下,在运行图时你会向客户端提供一个 thread_id,以便通过 LangSmith Deployment 中实现的持久化状态来追踪之前的运行记录。然而,如果你不需要持久化运行记录,则无需使用内置的持久化状态,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>)
# 使用名为 "agent" 的已部署图
assistant_id = "agent"

无状态流式处理

我们可以以几乎与从具有状态属性的运行中流式处理相同的方式流式处理无状态运行的结果,但不同之处在于:我们不向 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(
    # 不传入 thread_id,流式处理将是无状态的
    None,
    assistant_id,
    input=input,
    stream_mode="updates",
):
    if chunk.data and "run_id" not in chunk.data:
        print(chunk.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,你还可以使用 .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)
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
        }
    ]
}