In LangGraph Platform, 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¶PythonJavascriptCURL
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]'
We can see that these agents are different:
PythonJavascriptCURL
console.log(openAIAssistant);
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": {}
}
PythonJavascriptCURL
console.log(defaultAssistant);
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"
}
}
We can now run the OpenAI assistant on the thread first.
PythonJavascriptCURL
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"
}
}
'
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}]}}
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?":
PythonJavascriptCURL
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"
}
}
'
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}}]}}
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4