Create app.py

app.py

@@ -0,0 +1,49 @@
+import gradio as gr
+import pandas as pd
+import json
+
+# --- Your custom function ---
+def my_function(data_list):
+    # Example transformation – replace this with your logic
+    df = pd.DataFrame(data_list)
+    df["new_col"] = df.index + 1
+    return df
+
+# --- Wrapper for Gradio ---
+def process_json_list(json_text):
+    try:
+        # Parse JSON list input
+        data = json.loads(json_text)
+        if not isinstance(data, list):
+            return None, "Error: Input must be a JSON list of objects"
+        
+        # Apply your function
+        df = my_function(data)
+        
+        # Save to CSV
+        csv_path = "output.csv"
+        df.to_csv(csv_path, index=False)
+        
+        return df, csv_path
+    except Exception as e:
+        return None, f"Error: {str(e)}"
+
+# --- Gradio Interface ---
+with gr.Blocks() as demo:
+    gr.Markdown("## 🧠 JSON → DataFrame → CSV Converter")
+    gr.Markdown("Paste your JSON list below and get both a table and downloadable CSV.")
+    
+    json_input = gr.Code(
+        label="Input JSON List",
+        language="json",
+        value='[{"name": "Alice", "age": 25}, {"name": "Bob", "age": 30}]'
+    )
+
+    run_btn = gr.Button("Convert")
+
+    df_output = gr.Dataframe(label="Processed DataFrame", interactive=False)
+    file_output = gr.File(label="Download CSV")
+
+    run_btn.click(fn=process_json_list, inputs=json_input, outputs=[df_output, file_output])
+
+demo.launch()