How to run multiple agents on the same thread

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

Python

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]

Javascript

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

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]'

We can see that these agents are different:

Python

print(openai_assistant)

Javascript

console.log(openAIAssistant);

CURL

curl --request GET \
    --url <DEPLOYMENT_URL>/assistants/<OPENAI_ASSISTANT_ID>

Output:

{
"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": {}
}

Python

print(default_assistant)

Javascript

console.log(defaultAssistant);

CURL

curl --request GET \
    --url <DEPLOYMENT_URL>/assistants/<DEFAULT_ASSISTANT_ID>

Output:

{
"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.

Python

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")

Javascript

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");
}

CURL

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"
        }
    }
'

Output:

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?”:

Python

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")

Javascript

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

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"
        }
    }
'

Output:

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}}]}}

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