Update app.py

app.py

@@ -1,7 +1,68 @@
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+def main():
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+    def generate_predictions(image_input, text_input, do_sample, sampling_topp, sampling_temperature)
+
+        return None, None
+
+    term_of_use = """
+    ### Terms of use  
+    By using this model, users are required to agree to the following terms:  
+    The model is intended for academic and research purposes. 
+    The utilization of the model to create unsuitable material is strictly forbidden and not endorsed by this work. 
+    The accountability for any improper or unacceptable application of the model rests exclusively with the individuals who generated such content. 
+    
+    ### License
+    This project is licensed under the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct).
+    """
+
+    with gr.Blocks(title="Kosmos-2", theme=gr.themes.Base()).queue() as demo:
+        gr.Markdown(("""
+            # Kosmos-2: Grounding Multimodal Large Language Models to the World
+            [[Paper]](https://arxiv.org/abs/2306.14824) [[Code]](https://github.com/microsoft/unilm/blob/master/kosmos-2)
+            """))
+        with gr.Row():
+            with gr.Column():
+                image_input = gr.Image(type="pil", label="Test Image")
+                text_input = gr.Radio(["Brief", "Detailed"], label="Description Type", value="Brief")
+                do_sample = gr.Checkbox(label="Enable Sampling", info="(Please enable it before adjusting sampling parameters below)", value=False)
+                with gr.Accordion("Sampling parameters", open=False) as sampling_parameters:
+                    sampling_topp = gr.Slider(minimum=0.1, maximum=1, step=0.01, value=0.9, label="Sampling: Top-P")
+                    sampling_temperature = gr.Slider(minimum=0.1, maximum=1, step=0.01, value=0.7, label="Sampling: Temperature")
+
+                run_button = gr.Button(label="Run", visible=True)
+
+            with gr.Column():
+                image_output = gr.Image(type="pil")
+                text_output1 = gr.HighlightedText(
+                                    label="Generated Description",
+                                    combine_adjacent=False,
+                                    show_legend=True,
+                                ).style(color_map={"box": "red"})
+
+        with gr.Row():
+            with gr.Column():
+                gr.Examples(examples=[
+                            ["demo/images/two_dogs.jpg", "Detailed", False],
+                            ["demo/images/snowman.png", "Brief", False],
+                            ["demo/images/man_ball.png", "Detailed", False],
+                        ], inputs=[image_input, text_input, do_sample])
+            with gr.Column():
+                gr.Examples(examples=[
+                            ["demo/images/six_planes.png", "Brief", False],
+                            ["demo/images/quadrocopter.jpg", "Brief", False],
+                            ["demo/images/carnaby_street.jpg", "Brief", False],
+                        ], inputs=[image_input, text_input, do_sample])
+        gr.Markdown(term_of_use)
+
+        run_button.click(fn=generate_predictions,
+                         inputs=[image_input, text_input, do_sample, sampling_topp, sampling_temperature],
+                         outputs=[image_output, text_output1],
+                         show_progress=True, queue=True)
+
+    demo.launch(share=True)
+
+
+if __name__ == "__main__":
+    main()