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"""A gradio app for credit card approval prediction using FHE.""" |
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import subprocess |
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import time |
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import gradio as gr |
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from settings import ( |
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REPO_DIR, |
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ACCOUNT_MIN_MAX, |
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CHILDREN_MIN_MAX, |
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INCOME_MIN_MAX, |
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AGE_MIN_MAX, |
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EMPLOYED_MIN_MAX, |
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FAMILY_MIN_MAX, |
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INCOME_TYPES, |
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OCCUPATION_TYPES, |
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HOUSING_TYPES, |
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EDUCATION_TYPES, |
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FAMILY_STATUS, |
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) |
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from backend import ( |
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pre_process_keygen_encrypt_send_user, |
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pre_process_keygen_encrypt_send_bank, |
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pre_process_keygen_encrypt_send_third_party, |
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run_fhe, |
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get_output, |
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decrypt_output, |
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) |
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subprocess.Popen(["uvicorn", "server:app"], cwd=REPO_DIR) |
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time.sleep(3) |
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demo = gr.Blocks() |
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print("Starting the demo...") |
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with demo: |
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gr.Markdown( |
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""" |
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<h1 align="center">Credit Card Approval Prediction Using Fully Homomorphic Encryption</h1> |
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""" |
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) |
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gr.Markdown("## Client side") |
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gr.Markdown("### Step 1: Infos. ") |
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with gr.Row(): |
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with gr.Column(): |
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gr.Markdown("### User") |
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gender = gr.Radio(["Female", "Male"], label="Gender") |
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bool_inputs = gr.CheckboxGroup(["Car", "Property", "Work phone", "Phone", "Email"], label="What do you own ?") |
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num_children = gr.Slider(**CHILDREN_MIN_MAX, step=1, label="Number of children", info="How many children do you have (0 to 19) ?") |
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num_family = gr.Slider(**FAMILY_MIN_MAX, step=1, label="Family", info="How many members does your family have? (1 to 20) ?") |
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total_income = gr.Slider(**INCOME_MIN_MAX, label="Income", info="What's you total yearly income (in euros, 3780 to 220500) ?") |
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age = gr.Slider(**AGE_MIN_MAX, step=1, label="Age", info="How old are you (20 to 68) ?") |
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income_type = gr.Dropdown(choices=INCOME_TYPES, label="Income type", info="What is your main type of income ?") |
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education_type = gr.Dropdown(choices=EDUCATION_TYPES, label="Education", info="What is your education background ?") |
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family_status = gr.Dropdown(choices=FAMILY_STATUS, label="Family", info="What is your family status ?") |
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occupation_type = gr.Dropdown(choices=OCCUPATION_TYPES, label="Occupation", info="What is your main occupation ?") |
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housing_type = gr.Dropdown(choices=HOUSING_TYPES, label="Housing", info="In what type of housing do you live ?") |
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with gr.Column(): |
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gr.Markdown("### Bank ") |
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account_length = gr.Slider(**ACCOUNT_MIN_MAX, step=1, label="Account length", info="How long have this person had this account (in months, 0 to 60) ?") |
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with gr.Column(): |
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gr.Markdown("### Third party ") |
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employed = gr.Radio(["Yes", "No"], label="Is the person employed ?") |
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years_employed = gr.Slider(**EMPLOYED_MIN_MAX, step=1, label="Years of employment", info="How long have this person been employed (in years, 0 to 43) ?") |
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gr.Markdown("### Step 2: Keygen, encrypt using FHE and send the inputs to the server.") |
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with gr.Row(): |
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with gr.Column(): |
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gr.Markdown("### User") |
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encrypt_button_user = gr.Button("Encrypt the inputs and send to server.") |
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user_id = gr.Textbox(label="", max_lines=2, interactive=False, visible=False) |
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encrypted_input_user = gr.Textbox( |
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label="Encrypted input representation:", max_lines=2, interactive=False |
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) |
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with gr.Column(): |
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gr.Markdown("### Bank ") |
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encrypt_button_bank = gr.Button("Encrypt the inputs and send to server.") |
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bank_id = gr.Textbox(label="", max_lines=2, interactive=False, visible=False) |
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encrypted_input_bank = gr.Textbox( |
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label="Encrypted input representation:", max_lines=2, interactive=False |
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) |
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with gr.Column(): |
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gr.Markdown("### Third Party ") |
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encrypt_button_third_party = gr.Button("Encrypt the inputs and send to server.") |
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third_party_id = gr.Textbox(label="", max_lines=2, interactive=False, visible=False) |
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encrypted_input_third_party = gr.Textbox( |
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label="Encrypted input representation:", max_lines=2, interactive=False |
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) |
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gr.Markdown("## Server side") |
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gr.Markdown( |
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"The encrypted values are received by the server. The server can then compute the prediction " |
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"directly over them. Once the computation is finished, the server returns " |
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"the encrypted result to the client." |
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) |
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gr.Markdown("### Step 6: Run FHE execution.") |
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execute_fhe_button = gr.Button("Run FHE execution.") |
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fhe_execution_time = gr.Textbox( |
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label="Total FHE execution time (in seconds):", max_lines=1, interactive=False |
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) |
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gr.Markdown("## Client side") |
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gr.Markdown( |
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"The encrypted output is sent back to the client, who can finally decrypt it with the " |
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"private key." |
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) |
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gr.Markdown("### Step 7: Receive the encrypted output from the server.") |
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gr.Markdown( |
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"The output displayed here is the encrypted result sent by the server, which has been " |
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"decrypted using a different private key. This is only used to visually represent an " |
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"encrypted output." |
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) |
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get_output_button = gr.Button("Receive the encrypted output from the server.") |
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gr.Markdown("### Step 8: Decrypt the output.") |
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decrypt_button = gr.Button("Decrypt the output") |
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prediction_output = gr.Textbox( |
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label="Credit card approval decision: ", max_lines=1, interactive=False |
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) |
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encrypt_button_user.click( |
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pre_process_keygen_encrypt_send_user, |
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inputs=[gender, bool_inputs, num_children, num_family, total_income, age, income_type, \ |
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education_type, family_status, occupation_type, housing_type], |
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outputs=[user_id, encrypted_input_user], |
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) |
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encrypt_button_bank.click( |
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pre_process_keygen_encrypt_send_bank, |
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inputs=[account_length], |
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outputs=[bank_id, encrypted_input_bank], |
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) |
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encrypt_button_third_party.click( |
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pre_process_keygen_encrypt_send_third_party, |
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inputs=[employed, years_employed], |
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outputs=[third_party_id, encrypted_input_third_party], |
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) |
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execute_fhe_button.click(run_fhe, inputs=[user_id, bank_id, third_party_id], outputs=[fhe_execution_time]) |
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get_output_button.click( |
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get_output, |
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inputs=[user_id, bank_id, third_party_id], |
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) |
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decrypt_button.click( |
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decrypt_output, |
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inputs=[user_id, bank_id, third_party_id], |
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outputs=[prediction_output], |
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) |
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gr.Markdown( |
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"The app was built with [Concrete-ML](https://github.com/zama-ai/concrete-ml), a " |
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"Privacy-Preserving Machine Learning (PPML) open-source set of tools by [Zama](https://zama.ai/). " |
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"Try it yourself and don't forget to star on Github ⭐." |
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) |
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demo.launch(share=False) |
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