Update app.py

app.py

@@ -1,7 +1,43 @@
+# Step 6.1: Define different input components
 import gradio as gr
 
-def caption(image):
-    return "I have the input!!"
-input_module = gr.inputs.Image(label = "Input Image")
-output_module = gr.outputs.Textbox(label = "Output Text")
-gr.Interface(fn=caption, inputs=input_module, outputs=output_module).launch()
+# a. define text data type
+input_module1 = gr.inputs.Textbox(label = "Input Text")
+
+# b. define image data type
+input_module2 = gr.inputs.Image(label = "Input Image")
+
+# c. define Number data type
+input_module3 = gr.inputs.Number(label = "Input Number")
+
+# d. define Slider data type
+input_module4 = gr.inputs.Slider(1, 100, step=5, label = "Input Slider")
+
+# e. define Checkbox data type
+input_module5 = gr.inputs.Checkbox(label = "Does it work?")
+
+# f. define Radio data type
+input_module6 = gr.inputs.Radio(choices=["park", "zoo", "road"], label = "Input Radio")
+
+# g. define Dropdown data type
+input_module7 = gr.inputs.Dropdown(choices=["park", "zoo", "road"], label = "Input Dropdown")
+# Step 6.2: Define different output components
+# a. define text data type
+output_module1 = gr.outputs.Textbox(label = "Output Text")
+
+# b. define image data type
+output_module2 = gr.outputs.Image(label = "Output Image")
+def multi_inputs(input1, input2, input3, input4, input5, input6, input7 ):
+    import numpy as np
+    ## processing inputs
+
+    ## return outputs
+    output1 = "Processing inputs and return outputs" # text output example
+    output2 = np.random.rand(6,6) # image-like array output example
+    return output1,output2
+gr.Interface(fn=multi_inputs, 
+             inputs=[input_module1, input_module2, input_module3,
+                     input_module4, input_module5, input_module6,
+                     input_module7], 
+             outputs=[output_module1, output_module2]
+            ).launch()