| import gradio as gr |
| from agents.chat import chat_with_gemini |
| from agents.compare import compare_selected_cards |
| from data import all_card_names,all_card_lookup |
| from recommender.recommender import recommend_cards_gradio |
|
|
| |
| with gr.Blocks() as demo: |
| gr.Markdown("# Credit Card Recommender") |
| gr.Markdown("Get personalized credit card suggestions based on your lifestyle and eligibility.") |
|
|
| with gr.Tabs(): |
| |
| with gr.Tab(" Get Recommendations"): |
| with gr.Row(): |
| user_query = gr.Textbox( |
| label="Enter your query", |
| info="E.g., 'Best cards for international travel' or 'I want cashback cards with lounge access'" |
| ) |
| preferences = gr.CheckboxGroup( |
| choices=["Cashback", "Travel", "Fuel", "Airport Lounge access", |
| "Railways", "Dining", "Online Spends", "Grocery"], |
| label="Credit card categories:", |
| info="Select the features or benefits you want from your credit card" |
| ) |
|
|
| with gr.Accordion("Eligibility filters menu", open=False): |
| with gr.Row(): |
| income = gr.Slider( |
| minimum=1, maximum=60, step=1, |
| label="Annual Income (LPA) Minimum requirement is 2.5", |
| info="Helps filter cards based on your income eligibility (in Lakhs Per Annum)" |
| ) |
| cibil = gr.Slider( |
| minimum=300, maximum=900, step=10, |
| label="CIBIL Score", |
| info="Most of the cards requires a credit score of 700+" |
| ) |
| age = gr.Slider( |
| minimum=18, maximum=75, step=1, |
| label="Age", |
| info="Some cards have minimum and maximum age eligibility" |
| ) |
|
|
| with gr.Row(): |
| min_joining_fee = gr.Number( |
| label="Min Joining Fee (₹)", value=0, |
| info="Minimum one-time fee to get the card" |
| ) |
| max_joining_fee = gr.Number( |
| label="Max Joining Fee (₹)", value=150000, |
| info="Maximum one-time fee to get the card" |
| ) |
|
|
| with gr.Row(): |
| min_annual_fee = gr.Number( |
| label="Min Annual Fee (₹)", value=0, |
| info="Minimum yearly fee to be paid" |
| ) |
| max_annual_fee = gr.Number( |
| label="Max Annual Fee (₹)", value=150000, |
| info="Maximum yearly fee to be paid" |
| ) |
|
|
| with gr.Row(): |
| use_eligibility = gr.Checkbox( |
| label="Apply Eligibility Filter", value=False, |
| info="Enable this to get recommendations of the cards only for which you are eligible for" |
| ) |
| submit_btn = gr.Button("Recommend Cards", variant='primary') |
|
|
| top_card_html = gr.HTML() |
| card_df = gr.Dataframe(headers=["Card Name", "Matched Features", "Description"]) |
| card_file = gr.File(label="Download Full Recommendations (CSV)") |
|
|
| with gr.Tab(" Compare Cards"): |
| gr.Markdown("### Compare Recommended Cards") |
| compare_checkboxes = gr.CheckboxGroup( |
| choices=[], label="Select 2 or more cards to compare", |
| info="Pick 2+ cards from the recommended list to see a comparison" |
| ) |
| compare_output = gr.HTML(value="<div style='min-height:100px'></div>", visible=True) |
| compare_btn = gr.Button("Compare Selected Cards", variant='primary') |
| |
|
|
| gr.Markdown("### Compare Any Cards from Full List") |
| full_compare_dropdown = gr.Dropdown( |
| choices=all_card_names, multiselect=True, label="Select any 2+ cards", |
| info="Manually compare any cards from the full database" |
| ) |
| full_compare_btn = gr.Button("Compare Selected Cards", variant='primary') |
| full_compare_output = gr.HTML(value="<div style='min-height:100px'></div>", visible=True) |
|
|
| with gr.Tab(" Ask Follow-up Questions"): |
| gr.Markdown("### Ask any follow-up question ") |
| chatbot = gr.Chatbot(type='messages') |
| user_query_for_chat = gr.Textbox( |
| label="Enter your question", |
| info="Ask follow-ups like 'Which card has better travel insurance?' or 'Which card has less annual fee'", |
| ) |
| submit_query_btn = gr.Button("Submit Query", variant='primary') |
|
|
| card_names_state = gr.State() |
| card_lookup_state = gr.State() |
| chat_history = gr.State([]) |
| query = gr.State([]) |
|
|
| def wrapped_recommend_cards(user_query, preferences, income, cibil, age, min_joining_fee, max_joining_fee, |
| min_annual_fee, max_annual_fee, use_eligibility): |
| top_html, df, file, card_names, card_lookup, direct_query = recommend_cards_gradio( |
| user_query, preferences, income, cibil, age, min_joining_fee, max_joining_fee, |
| min_annual_fee, max_annual_fee, use_eligibility |
| ) |
| df_label = f"Found {len(card_names)} cards" |
| return top_html, gr.update(value=df, label=df_label), file, card_names, card_lookup, gr.update(choices=card_names, value=[]), direct_query |
|
|
| submit_btn.click( |
| fn=wrapped_recommend_cards, |
| inputs=[user_query, preferences, income, cibil, age, min_joining_fee, max_joining_fee, |
| min_annual_fee, max_annual_fee, use_eligibility], |
| outputs=[top_card_html, card_df, card_file, card_names_state, card_lookup_state, compare_checkboxes,query] |
| ) |
|
|
| compare_btn.click( |
| fn=compare_selected_cards, |
| inputs=[compare_checkboxes, card_lookup_state], |
| outputs=compare_output, |
| show_progress=True |
| ) |
| full_compare_btn.click( |
| fn=lambda selected: compare_selected_cards(selected, all_card_lookup), |
| inputs=[full_compare_dropdown], |
| outputs=full_compare_output |
| ) |
|
|
| submit_query_btn.click( |
| fn=chat_with_gemini, |
| inputs=[query,user_query_for_chat, chat_history, card_lookup_state], |
| outputs=[chatbot, chat_history] |
| ).then( |
| lambda: gr.update(value=""), |
| inputs=[], |
| outputs=[user_query_for_chat] |
| ) |
| |
| |
| user_query_for_chat.submit( |
| fn=chat_with_gemini, |
| inputs=[query, user_query_for_chat, chat_history, card_lookup_state], |
| outputs=[chatbot, chat_history], |
| show_progress=True |
| ).then( |
| lambda: gr.update(value=""), |
| inputs=[], |
| outputs=[user_query_for_chat] |
| ) |
|
|
