Update app.py

app.py

@@ -5,17 +5,20 @@ from scipy.io import arff
 
 rtf_model = REaLTabFormer(
     model_type="tabular",
-    gradient_accumulation_steps=4)
+    gradient_accumulation_steps=1)
 
 
 def generate_data(file):
-    data = arff.loadarff(open(file.name,'rt'))
-    df = pd.DataFrame(data[0])
+    if '.arff' in file.name:
+        data = arff.loadarff(open(file.name,'rt'))
+        df = pd.DataFrame(data[0])
+    elif '.csv' in file.name:
+        df = pd.read_csv(file.name)
     rtf_model.fit(df)
     # Generate synthetic data
     samples = rtf_model.sample(n_samples=5)
 
-    return samples
+    return df.head(),samples
     
 css = """
         .gradio-container {
@@ -114,13 +117,17 @@ with gr.Blocks(css = css) as demo:
         
         with gr.Tab("Upload Data as File"):
             data_input_u = gr.File(label = 'Upload Data File', file_types=["text", ".json", ".csv", ".arff"])
+            num_samples = gr.Slider(label="Number of Samples", minimum=5, maximum=100, value=5, step=10)
             generate_data_btn = gr.Button('Generate Synthetic Data')
 
         with gr.Row():
+            data_sample = gr.Dataframe(label = "Original Data")
             data_output = gr.Dataframe(label = "Synthetic Data")
+            
     
     
-    generate_data_btn.click(generate_data, inputs = data_input_u, outputs = [data_output])   
+    generate_data_btn.click(generate_data, inputs = [data_input_u,num_samples], outputs = [data_sample, data_output])
+    examples = gr.Examples(examples=[['diabetes.arff',5]],inputs = [data_input_u,num_samples], outputs = [data_sample, data_output], cache_examples = True, fn = process)
 
     
 demo.launch()