Update app.py

app.py

@@ -285,9 +285,9 @@ def generate_video(model_name: str, text: str, video_path: str,
 
 # Define examples for image and video inference
 image_examples = [
-    ["fill the correct numbers", "example/image3.png"],
-    ["ocr the image", "example/image1.png"],
-    ["explain the scene", "example/image2.jpg"],
+    ["Convert this page to docling", "images/1.png", "SmolDocling-256M-preview"],
+    ["OCR the image", "images/2.jpeg"],
+    ["Convert this page to docling", "images/3.png", "SmolDocling-256M-preview"],
 ]
 
 video_examples = [
@@ -307,7 +307,7 @@ css = """
 
 # Create the Gradio Interface
 with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
-    gr.Markdown("# **[core OCR](https://huggingface.co/collections/prithivMLmods/core-and-docscope-ocr-models-6816d7f1bde3f911c6c852bc)**")
+    gr.Markdown("# **[OCR Net 4x](https://huggingface.co/collections/prithivMLmods/core-and-docscope-ocr-models-6816d7f1bde3f911c6c852bc)**")
     with gr.Row():
         with gr.Column():
             with gr.Tabs():
@@ -317,7 +317,7 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
                     image_submit = gr.Button("Submit", elem_classes="submit-btn")
                     gr.Examples(
                         examples=image_examples,
-                        inputs=[image_query, image_upload]
+                        inputs=[image_query, image_upload, model_choice]
                     )
                 with gr.TabItem("Video Inference"):
                     video_query = gr.Textbox(label="Query Input", placeholder="Enter your query here...")
@@ -336,7 +336,7 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
         with gr.Column():
             output = gr.Textbox(label="Output", interactive=False, lines=3, scale=2)
             model_choice = gr.Radio(
-                choices=["Nanonets-OCR-s", "MonkeyOCR-Recognition", "SmolDocling-256M-preview"],
+                choices=["Nanonets-OCR-s", "SmolDocling-256M-preview", "MonkeyOCR-Recognition"],
                 label="Select Model",
                 value="Nanonets-OCR-s"
             )