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.
In LangSmith Deployment, a thread is not explicitly associated with a particular agent.
This means that you can run multiple agents on the same thread, which allows a different agent to continue from an initial agent’s progress.
In this example, we will create two agents and then call them both on the same thread.
You’ll see that the second agent will respond using information from the checkpoint generated in the thread by the first agent as context.
Setup
from langgraph_sdk import get_client
client = get_client(url=<DEPLOYMENT_URL>)
openai_assistant = await client.assistants.create(
graph_id="agent", config={"configurable": {"model_name": "openai"}}
)
# There should always be a default assistant with no configuration
assistants = await client.assistants.search()
default_assistant = [a for a in assistants if not a["config"]][0]
import { Client } from "@langchain/langgraph-sdk";
const client = new Client({ apiUrl: <DEPLOYMENT_URL> });
const openAIAssistant = await client.assistants.create(
{ graphId: "agent", config: {"configurable": {"model_name": "openai"}}}
);
const assistants = await client.assistants.search();
const defaultAssistant = assistants.find(a => !a.config);
curl --request POST \
--url <DEPLOYMENT_URL>/assistants \
--header 'Content-Type: application/json' \
--data '{
"graph_id": "agent",
"config": { "configurable": { "model_name": "openai" } }
}' && \
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]'
console.log(openAIAssistant);
curl --request GET \
--url <DEPLOYMENT_URL>/assistants/<OPENAI_ASSISTANT_ID>
{
"assistant_id": "db87f39d-b2b1-4da8-ac65-cf81beb3c766",
"graph_id": "agent",
"created_at": "2024-08-30T21:18:51.850581+00:00",
"updated_at": "2024-08-30T21:18:51.850581+00:00",
"config": {
"configurable": {
"model_name": "openai"
}
},
"metadata": {}
}
console.log(defaultAssistant);
curl --request GET \
--url <DEPLOYMENT_URL>/assistants/<DEFAULT_ASSISTANT_ID>
{
"assistant_id": "fe096781-5601-53d2-b2f6-0d3403f7e9ca",
"graph_id": "agent",
"created_at": "2024-08-08T22:45:24.562906+00:00",
"updated_at": "2024-08-08T22:45:24.562906+00:00",
"config": {},
"metadata": {
"created_by": "system"
}
}
Run assistants on thread
Run OpenAI assistant
We can now run the OpenAI assistant on the thread first.
thread = await client.threads.create()
input = {"messages": [{"role": "user", "content": "who made you?"}]}
async for event in client.runs.stream(
thread["thread_id"],
openai_assistant["assistant_id"],
input=input,
stream_mode="updates",
):
print(f"Receiving event of type: {event.event}")
print(event.data)
print("\n\n")
const thread = await client.threads.create();
let input = {"messages": [{"role": "user", "content": "who made you?"}]}
const streamResponse = client.runs.stream(
thread["thread_id"],
openAIAssistant["assistant_id"],
{
input,
streamMode: "updates"
}
);
for await (const event of streamResponse) {
console.log(`Receiving event of type: ${event.event}`);
console.log(event.data);
console.log("\n\n");
}
thread_id=$(curl --request POST \
--url <DEPLOYMENT_URL>/threads \
--header 'Content-Type: application/json' \
--data '{}' | jq -r '.thread_id') && \
curl --request POST \
--url "<DEPLOYMENT_URL>/threads/${thread_id}/runs/stream" \
--header 'Content-Type: application/json' \
--data '{
"assistant_id": <OPENAI_ASSISTANT_ID>,
"input": {
"messages": [
{
"role": "user",
"content": "who made you?"
}
]
},
"stream_mode": [
"updates"
]
}' | \
sed 's/\r$//' | \
awk '
/^event:/ {
if (data_content != "") {
print data_content "\n"
}
sub(/^event: /, "Receiving event of type: ", $0)
printf "%s...\n", $0
data_content = ""
}
/^data:/ {
sub(/^data: /, "", $0)
data_content = $0
}
END {
if (data_content != "") {
print data_content "\n\n"
}
}
'
Receiving event of type: metadata
{'run_id': '1ef671c5-fb83-6e70-b698-44dba2d9213e'}
Receiving event of type: updates
{'agent': {'messages': [{'content': 'I was created by OpenAI, a research organization focused on developing and advancing artificial intelligence technology.', 'additional_kwargs': {}, 'response_metadata': {'finish_reason': 'stop', 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_157b3831f5'}, 'type': 'ai', 'name': None, 'id': 'run-f5735b86-b80d-4c71-8dc3-4782b5a9c7c8', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]}}
Run default assistant
Now, we can run it on the default assistant and see that this second assistant is aware of the initial question, and can answer the question, “and you?”:
input = {"messages": [{"role": "user", "content": "and you?"}]}
async for event in client.runs.stream(
thread["thread_id"],
default_assistant["assistant_id"],
input=input,
stream_mode="updates",
):
print(f"Receiving event of type: {event.event}")
print(event.data)
print("\n\n")
let input = {"messages": [{"role": "user", "content": "and you?"}]}
const streamResponse = client.runs.stream(
thread["thread_id"],
defaultAssistant["assistant_id"],
{
input,
streamMode: "updates"
}
);
for await (const event of streamResponse) {
console.log(`Receiving event of type: ${event.event}`);
console.log(event.data);
console.log("\n\n");
}
curl --request POST \
--url <DEPLOYMENT_URL>/threads/<THREAD_ID>/runs/stream \
--header 'Content-Type: application/json' \
--data '{
"assistant_id": <DEFAULT_ASSISTANT_ID>,
"input": {
"messages": [
{
"role": "user",
"content": "and you?"
}
]
},
"stream_mode": [
"updates"
]
}' | \
sed 's/\r$//' | \
awk '
/^event:/ {
if (data_content != "") {
print data_content "\n"
}
sub(/^event: /, "Receiving event of type: ", $0)
printf "%s...\n", $0
data_content = ""
}
/^data:/ {
sub(/^data: /, "", $0)
data_content = $0
}
END {
if (data_content != "") {
print data_content "\n\n"
}
}
'
Receiving event of type: metadata
{'run_id': '1ef6722d-80b3-6fbb-9324-253796b1cd13'}
Receiving event of type: updates
{'agent': {'messages': [{'content': [{'text': 'I am an artificial intelligence created by Anthropic, not by OpenAI. I should not have stated that OpenAI created me, as that is incorrect. Anthropic is the company that developed and trained me using advanced language models and AI technology. I will be more careful about providing accurate information regarding my origins in the future.', 'type': 'text', 'index': 0}], 'additional_kwargs': {}, 'response_metadata': {'stop_reason': 'end_turn', 'stop_sequence': None}, 'type': 'ai', 'name': None, 'id': 'run-ebaacf62-9dd9-4165-9535-db432e4793ec', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': {'input_tokens': 302, 'output_tokens': 72, 'total_tokens': 374}}]}}
