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import gradio as gr
import database
import app_logic
import visualization
# 1. Initialize Database Schema and Sample Data on startup
database.init_db()
# --- Helper Functions for UI Logic ---
def update_dropdown(category):
"""
Triggered when Category changes.
Updates the Product list and clears the review textbox.
"""
names = app_logic.get_products_by_category(category)
return gr.Dropdown(choices=names, value=names[0] if names else None), ""
def refresh_owner_dashboard():
"""
Fetches the latest data for the Table and the latest Plotly Chart.
Used by the Refresh button and automatic updates.
"""
table_data = app_logic.get_all_reviews()
chart_figure = visualization.generate_sentiment_pie_chart()
return table_data, chart_figure
def validate_input(text):
"""
Real-time 'Sense Check'.
Disables the Submit button unless at least 3 words are typed.
"""
word_count = len(text.strip().split())
if word_count >= 3:
# Enable button and make it primary (colored)
return gr.update(interactive=True, variant="primary")
else:
# Disable button and make it secondary (gray)
return gr.update(interactive=False, variant="secondary")
# --- UI Layout using Gradio Blocks ---
with gr.Blocks(theme=gr.themes.Soft()) as demo:
gr.Markdown("# 👗 Women's Clothing Portal")
gr.Markdown("### AI-Powered Customer Feedback & Business Intelligence")
with gr.Tabs():
# TAB 1: CUSTOMER INTERFACE
with gr.TabItem("Customer"):
gr.Markdown("#### Submit your Review")
with gr.Row():
with gr.Column():
category_input = gr.Dropdown(
choices=["Jeans", "Tops", "Kurti", "Leggings"],
value="Jeans",
label="Category"
)
product_input = gr.Dropdown(choices=[], label="Product Name")
rating_input = gr.Slider(1, 5, step=1, value=5, label="Rating (1-5)")
review_input = gr.Textbox(
label="Review Text",
placeholder="Please write at least 3 words about the fit or quality...",
lines=4
)
# Submit button starts as DISABLED
submit_btn = gr.Button("Submit Review", variant="secondary", interactive=False)
status_output = gr.Textbox(label="Submission Status")
# TAB 2: OWNER DASHBOARD
with gr.TabItem("Owner Dashboard"):
gr.Markdown("#### Live Sentiment Analytics")
with gr.Row():
with gr.Column(scale=2):
# Plotly Chart from visualization.py
sentiment_plot = gr.Plot(label="Sentiment Distribution")
with gr.Column(scale=1):
refresh_btn = gr.Button("🔄 Refresh Database", variant="secondary")
gr.Markdown("Updates the chart and table with the latest customer entries.")
data_table = gr.Dataframe(label="Detailed Customer Feedback Log", interactive=False)
# TAB 3: AI BUSINESS INSIGHTS
with gr.TabItem("📈 AI Insights"):
gr.Markdown("#### Strategic Business Analysis")
gr.Markdown("Generate a deep-dive report based on all current customer feedback using Generative AI.")
generate_report_btn = gr.Button("Generate AI Strategy Report", variant="primary")
report_output = gr.Markdown(value="*Report will appear here after clicking the button...*")
# --- UI Event Listeners ---
# 1. Real-time Word Count Validation
review_input.change(
fn=validate_input,
inputs=review_input,
outputs=submit_btn
)
# 2. Category -> Product Dropdown Sync
category_input.change(
fn=update_dropdown,
inputs=category_input,
outputs=[product_input, review_input]
)
# 3. Clear review text when product changes
product_input.change(lambda: "", outputs=review_input)
# 4. Main Submission Logic (Saves to DB, Updates Chart, Resets UI)
submit_btn.click(
fn=app_logic.save_review,
inputs=[product_input, rating_input, review_input],
outputs=status_output
).then(
# Auto-update the dashboard
fn=refresh_owner_dashboard,
outputs=[data_table, sentiment_plot]
).then(
# Clear the text box
fn=lambda: "", outputs=review_input
).then(
# Re-disable the button
fn=lambda: gr.update(interactive=False, variant="secondary"),
outputs=submit_btn
)
# 5. Manual Dashboard Refresh
refresh_btn.click(
fn=refresh_owner_dashboard,
outputs=[data_table, sentiment_plot]
)
# 6. AI Report Generation
generate_report_btn.click(
fn=app_logic.generate_business_report,
outputs=report_output
)
# 7. Initial Load (Ensures data is visible when the page first opens)
demo.load(refresh_owner_dashboard, outputs=[data_table, sentiment_plot])
demo.load(
fn=update_dropdown,
inputs=category_input,
outputs=[product_input, review_input]
)
# --- Launch the Application ---
if __name__ == "__main__":
# Use share=True if you want to create a public link
demo.launch() |