Create app.py

app.py

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+import pandas as pd
+import gradio as gr
+
+# Initial data
+data = {
+    'Name': ['Alice', 'Bob', 'Charlie'],
+    'Age': [25, 30, 35],
+    'City': ['New York', 'Los Angeles', 'Chicago'],
+    'Feedback': [None, None, None]
+}
+df = pd.DataFrame(data)
+
+# Function to add feedback
+def add_feedback(name, feedback):
+    global df
+    df.loc[df['Name'] == name, 'Feedback'] = feedback
+    return df
+
+# Function to get a response from GPT (placeholder for actual GPT call)
+def get_gpt_response(question):
+    # Convert DataFrame to CSV string
+    csv_data = df.to_csv(index=False)
+    # Create context with feedback
+    context = f"""
+    Here is the data of people including their names, ages, cities they live in, and feedback:
+
+    {csv_data}
+
+    Question: {question}
+    """
+    # Placeholder for GPT call
+    response = "Charlie, 35 years old, from Chicago is the oldest person."
+    return response
+
+def ask_question(question):
+    response = get_gpt_response(question)
+    return response
+
+def submit_feedback(name, feedback):
+    updated_df = add_feedback(name, feedback)
+    return updated_df
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Data Inquiry and Feedback System")
+
+    with gr.Row():
+        with gr.Column():
+            question_input = gr.Textbox(label="Ask a Question")
+            response_output = gr.Textbox(label="GPT Response", interactive=False)
+            ask_button = gr.Button("Ask")
+
+        with gr.Column():
+            name_input = gr.Textbox(label="Name for Feedback")
+            feedback_input = gr.Textbox(label="Feedback")
+            submit_button = gr.Button("Submit Feedback")
+            feedback_df = gr.Dataframe(label="Updated DataFrame", interactive=False)
+    
+    ask_button.click(fn=ask_question, inputs=question_input, outputs=response_output)
+    submit_button.click(fn=submit_feedback, inputs=[name_input, feedback_input], outputs=feedback_df)
+
+demo.launch()