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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()
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