Documentation Index
Fetch the complete documentation index at: https://docs.langchain.com/llms.txt
Use this file to discover all available pages before exploring further.
Most of the time, you provide a thread_id to your client when you run your graph in order to keep track of prior runs through the persistent state implemented in LangSmith Deployment. However, if you don’t need to persist the runs you don’t need to use the built-in persistent state and can create stateless runs.
Setup
First, let’s setup our client:
from langgraph_sdk import get_client
client = get_client(url=<DEPLOYMENT_URL>)
# Using the graph deployed with the name "agent"
assistant_id = "agent"
import { Client } from "@langchain/langgraph-sdk";
const client = new Client({ apiUrl: <DEPLOYMENT_URL> });
// Using the graph deployed with the name "agent"
const assistantId = "agent";
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 '{}'
Stateless streaming
We can stream the results of a stateless run in an almost identical fashion to how we stream from a run with the state attribute, but instead of passing a value to the thread_id parameter, we pass 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'
{'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}]}}
Waiting for stateless results
In addition to streaming, you can also wait for a stateless result by using the .wait function like follows:
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>,
}'
{
'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
}
]
}
