如何在同一线程上运行多个代理¶
在 LangGraph Cloud 中，线程没有明确地与特定代理关联。这意味着您可以在同一线程上运行多个代理，这允许不同的代理从初始代理的进度继续。
在本示例中，我们将创建两个代理，然后在同一线程上调用它们。您将看到第二个代理将使用来自第一个代理在线程中生成的 checkpoint 中的信息作为上下文进行响应。
设置¶
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]'
我们可以看到这些代理是不同的
输出
{
"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": {}
}
输出
{
"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"
}
}
在线程上运行助手¶
运行 OpenAI 助手¶
我们现在可以首先在线程上运行 OpenAI 助手。
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"
}
}
'
输出
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}]}}
运行默认助手¶
现在，我们可以在默认助手上运行它，并看到第二个助手知道最初的问题，并且可以回答问题“你呢？”
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"
}
}
'
输出
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}}]}}