diff --git a/projects/rtmpose/app.py b/projects/rtmpose/app.py
index 416e169e4f..6b5be8f9bb 100644
--- a/projects/rtmpose/app.py
+++ b/projects/rtmpose/app.py
@@ -3,19 +3,31 @@
 import os
 from functools import partial
 
-import gradio as gr
-
 # prepare environment
 project_path = os.path.join(os.path.dirname(os.path.abspath(__file__)))
 mmpose_path = project_path.split('/projects', 1)[0]
 
 os.system('python -m pip install Openmim')
+os.system('python -m pip install openxlab')
+os.system('python -m pip install gradio==3.38.0')
+
 os.system('python -m mim install "mmcv>=2.0.0"')
 os.system('python -m mim install "mmengine>=0.9.0"')
 os.system('python -m mim install "mmdet>=3.0.0"')
 os.system(f'python -m mim install -e {mmpose_path}')
+
+import gradio as gr  # noqa
+from openxlab.model import download  # noqa
+
 from mmpose.apis import MMPoseInferencer  # noqa
 
+# download checkpoints
+download(model_repo='mmpose/RTMPose', model_name='dwpose-l')
+download(model_repo='mmpose/RTMPose', model_name='RTMW-x')
+download(model_repo='mmpose/RTMPose', model_name='RTMO-l')
+download(model_repo='mmpose/RTMPose', model_name='RTMPose-l-body8')
+download(model_repo='mmpose/RTMPose', model_name='RTMPose-m-face6')
+
 models = [
     'rtmpose | body', 'rtmo | body', 'rtmpose | face', 'dwpose | wholebody',
     'rtmw | wholebody'
@@ -115,12 +127,7 @@ def predict(input,
         input_img = gr.Image(type='numpy')
         button = gr.Button('Inference', variant='primary')
         hm = gr.Checkbox(label='draw-heatmap', info='Whether to draw heatmap')
-        model_type = gr.Dropdown([
-            'rtmpose | body', 'rtmo | body', 'rtmpose | face',
-            'dwpose | wholebody', 'rtmw | wholebody'
-        ],
-                                 label='Model | Keypoint Type',
-                                 info='Body / Face / Wholebody')
+        model_type = gr.Dropdown(models, label='Model | Keypoint Type')
 
         gr.Markdown('## News')
         for news in news_list[::-1]:
@@ -138,12 +145,7 @@ def predict(input,
         input_img = gr.Image(source='webcam', type='numpy')
         button = gr.Button('Inference', variant='primary')
         hm = gr.Checkbox(label='draw-heatmap', info='Whether to draw heatmap')
-        model_type = gr.Dropdown([
-            'rtmpose | body', 'rtmo | body', 'rtmpose | face',
-            'dwpose | wholebody', 'rtmw | wholebody'
-        ],
-                                 label='Model | Keypoint Type',
-                                 info='Body / Face / Wholebody')
+        model_type = gr.Dropdown(models, label='Model | Keypoint Type')
 
         gr.Markdown('## News')
         for news in news_list[::-1]:
@@ -161,12 +163,7 @@ def predict(input,
         input_video = gr.Video(type='mp4')
         button = gr.Button('Inference', variant='primary')
         hm = gr.Checkbox(label='draw-heatmap', info='Whether to draw heatmap')
-        model_type = gr.Dropdown([
-            'rtmpose | body', 'rtmo | body', 'rtmpose | face',
-            'dwpose | wholebody', 'rtmw | wholebody'
-        ],
-                                 label='Model | Keypoint type',
-                                 info='Body / Face / Wholebody')
+        model_type = gr.Dropdown(models, label='Model | Keypoint type')
 
         gr.Markdown('## News')
         for news in news_list[::-1]:
@@ -184,12 +181,7 @@ def predict(input,
         input_video = gr.Video(source='webcam', format='mp4')
         button = gr.Button('Inference', variant='primary')
         hm = gr.Checkbox(label='draw-heatmap', info='Whether to draw heatmap')
-        model_type = gr.Dropdown([
-            'rtmpose | body', 'rtmo | body', 'rtmpose | face',
-            'dwpose | wholebody', 'rtmw | wholebody'
-        ],
-                                 label='Model | Keypoint Type',
-                                 info='Body / Face / Wholebody')
+        model_type = gr.Dropdown(models, label='Model | Keypoint Type')
 
         gr.Markdown('## News')
         for news in news_list[::-1]: