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App

docs/docs/api/app.md

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App

Get started with the App API

Chat App

python
POST /api/v2/chat/completions

Examples

import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';

Stream Chat App

<Tabs defaultValue="python" groupId="chat" values={[ {label: 'Curl', value: 'curl'}, {label: 'Python', value: 'python'}, ] }>

<TabItem value="curl">
shell
 DBGPT_API_KEY=dbgpt
 APP_ID={YOUR_APP_ID}

 curl -X POST "http://localhost:5670/api/v2/chat/completions" \
    -H "Authorization: Bearer $DBGPT_API_KEY" \
    -H "accept: application/json" \
    -H "Content-Type: application/json" \
    -d "{\"messages\":\"Hello\",\"model\":\"gpt-4o\", \"chat_mode\": \"chat_app\", \"chat_param\": \"$APP_ID\"}"
</TabItem> <TabItem value="python">
python
from dbgpt_client import Client

DBGPT_API_KEY = "dbgpt"
APP_ID="{YOUR_APP_ID}"

client = Client(api_key=DBGPT_API_KEY)

async for data in client.chat_stream(
    messages="Introduce AWEL", 
    model="gpt-4o", 
    chat_mode="chat_app", 
    chat_param=APP_ID
):
    print(data)
</TabItem> </Tabs>

Chat Completion Stream Response

commandline
data: {"id": "109bfc28-fe87-452c-8e1f-d4fe43283b7d", "created": 1710919480, "model": "gpt-4o", "choices": [{"index": 0, "delta": {"role": "assistant", "content": "```agent-plans\n[{\"name\": \"Introduce Awel\", \"num\": 2, \"status\": \"complete\", \"agent\": \"Human\", \"markdown\": \"```agent-messages\\n[{\\\"sender\\\": \\\"Summarizer\\\", \\\"receiver\\\": \\\"Human\\\", \\\"model\\\": \\\"gpt-4o\\\", \\\"markdown\\\": \\\"Agentic Workflow Expression Language (AWEL) is a specialized language designed for developing large model applications with intelligent agent workflows. It offers flexibility and functionality, allowing developers to focus on business logic for LLMs applications without getting bogged down in model and environment details. AWEL uses a layered API design architecture, making it easier to work with. You can find examples and source code to get started with AWEL, and it supports various operators and environments. AWEL is a powerful tool for building native data applications through workflows and agents.\"}]\n```"}}]}

data: [DONE]

Get App

python
GET /api/v2/serve/apps/{app_id}

<Tabs defaultValue="curl_get_app" groupId="chat1" values={[ {label: 'Curl', value: 'curl_get_app'}, {label: 'Python', value: 'python_get_app'}, ] }>

<TabItem value="curl_get_app">
shell
DBGPT_API_KEY=dbgpt
APP_ID={YOUR_APP_ID}
curl -X GET "http://localhost:5670/api/v2/serve/apps/$APP_ID" -H "Authorization: Bearer $DBGPT_API_KEY"
</TabItem> <TabItem value="python_get_app">
python
from dbgpt_client import Client
from dbgpt_client.app import get_app

DBGPT_API_KEY = "dbgpt"
app_id = "{your_app_id}"

client = Client(api_key=DBGPT_API_KEY)
res = await get_app(client=client, app_id=app_id)
</TabItem> </Tabs>

Query Parameters

<b>app_id</b> <font color="gray"> string </font> <font color="red"> Required </font>

app id

Response body

Return <a href="#the-app-object">App Object</a>

List App

python
GET /api/v2/serve/apps

<Tabs defaultValue="curl_list_app" groupId="chat1" values={[ {label: 'Curl', value: 'curl_list_app'}, {label: 'Python', value: 'python_list_app'}, ] }>

<TabItem value="curl_list_app">
shell
DBGPT_API_KEY=dbgpt

curl -X GET 'http://localhost:5670/api/v2/serve/apps' -H "Authorization: Bearer $DBGPT_API_KEY"
</TabItem> <TabItem value="python_list_app">
python
from dbgpt_client import Client
from dbgpt_client.app import list_app

DBGPT_API_KEY = "dbgpt"
app_id = "{your_app_id}"

client = Client(api_key=DBGPT_API_KEY)
res = await list_app(client=client)
</TabItem> </Tabs>

Response body

Return <a href="#the-app-object">App Object</a> List

The App Model

<b>app_code</b> <font color="gray"> string </font>

unique app id

<b>app_name</b> <font color="gray"> string </font>

app name

<b>app_describe</b> <font color="gray"> string </font>

app describe

<b>team_mode</b> <font color="gray"> string </font>

team mode

<b>language</b> <font color="gray"> string </font>

language

<b>team_context</b> <font color="gray"> string </font>

team context

<b>user_code</b> <font color="gray"> string </font>

user code

<b>sys_code</b> <font color="gray"> string </font>

sys code

<b>is_collected</b> <font color="gray"> string </font>

is collected

<b>icon</b> <font color="gray"> string </font>

icon

<b>created_at</b> <font color="gray"> string </font>

created at

<b>updated_at</b> <font color="gray"> string </font>

updated at

<b>details</b> <font color="gray"> string </font>

app details List[AppDetailModel]

The App Detail Model

<b>app_code</b> <font color="gray"> string </font>

app code

<b>app_name</b> <font color="gray"> string </font>

app name

<b>agent_name</b> <font color="gray"> string </font>

agent name

<b>node_id</b> <font color="gray"> string </font>

node id

<b>resources</b> <font color="gray"> string </font>

resources

<b>prompt_template</b> <font color="gray"> string </font>

prompt template

<b>llm_strategy</b> <font color="gray"> string </font>

llm strategy

<b>llm_strategy_value</b> <font color="gray"> string </font>

llm strategy value

<b>created_at</b> <font color="gray"> string </font>

created at

<b>updated_at</b> <font color="gray"> string </font>

updated at