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| """ | |
| FASTAPI + GRADIO SERVING APPLICATION - Production-Ready ML Model Serving | |
| ======================================================================== | |
| This application provides a complete serving solution for the PaySim model | |
| with both programmatic API access and a user-friendly web interface. | |
| Architecture: | |
| - FastAPI: High-performance REST API with automatic OpenAPI documentation | |
| - Gradio: User-friendly web UI for manual testing and demonstrations | |
| - Pydantic: Data validation and automatic API documentation | |
| """ | |
| from fastapi import FastAPI, HTTPException | |
| from pydantic import BaseModel | |
| from typing import Literal | |
| import gradio as gr | |
| from src.app.inference import predict | |
| app = FastAPI( | |
| title="PaySim Prediction API", | |
| description="ML API for predicting Transaction Fraud", | |
| version="1.0.0" | |
| ) | |
| def health_check(): | |
| """ | |
| Health check endpoint for monitoring and load balancer health checks. | |
| """ | |
| return {"status": "ok"} | |
| class TransactionData(BaseModel): | |
| """ | |
| This is the schema for PaySim prediction | |
| This schema defines the exact features required for prediction | |
| Here goes only the columns that are consumed not even the engineered ones""" | |
| step: int #Represents a unit of time in the real world, with 1 step equating to 1 hour. | |
| #The total simulation spans 744 steps, equivalent to 30 days | |
| type:str #Transaction type | |
| amount:float #The transaction amount | |
| oldbalanceOrg: float #Sender balance before transaction | |
| newbalanceOrig: float #Sender new balance after transactions | |
| oldbalanceDest: float #receiver old balance | |
| newbalanceDest: float #receiver new balance | |
| def predict_endpoint(data: TransactionData): | |
| try: | |
| return predict(data.model_dump()) # model_dump() -> plain dict | |
| except ValueError as e: | |
| raise HTTPException(status_code=400, detail=str(e)) | |
| # ---------------GRADIO-------------------- | |
| def gradio_interface(step,type,amount,oldbalanceOrg, | |
| newbalanceOrig,oldbalanceDest,newbalanceDest): | |
| """"This function: | |
| 1. Takes individual form inputs from Gradio UI | |
| 2. Constructs the data dictionary matching the API schema | |
| 3. Calls the same inference pipeline used by the API | |
| 4. Returns user-friendly prediction string""" | |
| #construct data dictionary matching the schema | |
| data = { | |
| "step":int(step), | |
| "type":type, | |
| "amount":float(amount), | |
| "oldbalanceOrg":float(oldbalanceOrg), | |
| "newbalanceOrig":float(newbalanceOrig), | |
| "oldbalanceDest": float(oldbalanceDest), | |
| "newbalanceDest":float(newbalanceDest), | |
| } | |
| #Call same inference pipeline as API endpoint | |
| result = predict(data) | |
| prob = result["fraud_probability"] | |
| label = "Fraud" if result["is_fraud"] else "Not Fraud" | |
| return f"{label} — fraud probability: {prob * 100:.2f}%" | |
| # === GRADIO UI CONFIGURATION === | |
| demo = gr.Interface( | |
| fn = gradio_interface, | |
| inputs=[ | |
| gr.Number(label="Step", value=0, minimum=0, maximum=743), | |
| gr.Dropdown(["CASH_OUT", "TRANSFER"], label="Transaction Type", value="TRANSFER"), | |
| gr.Number(label="Amount (EU)", value=0, minimum=0), | |
| gr.Number(label="Sender's Old Balance"), | |
| gr.Number(label="Sender's New Balance"), | |
| gr.Number(label="Receiver's Old Balance"), | |
| gr.Number(label="Receiver's New Balance"), | |
| ], | |
| outputs=gr.Textbox(label= "Fraud Prediction",lines=1), | |
| title= "Pay Sim transaction Fraud Prediction", | |
| description=""" | |
| Predict if the transaction is a fraud or not using Machine Learning | |
| Fill in the transaction's details below to get a prediction. The | |
| model is using a simple MLP on historical data.""", | |
| flagging_mode="never", # no writable flagged/ dir needed (HF runs non-root) | |
| theme = gr.themes.Soft() | |
| ) | |
| app = gr.mount_gradio_app( | |
| app, | |
| demo, | |
| path="/" # Gradio UI is the landing page; API still at /predict and /docs | |
| ) | |