Create main.py

main.py

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+import threading
+import uvicorn
+import pandas as pd
+import pickle
+from fastapi import FastAPI
+
+# Initialize FastAPI app
+app = FastAPI()
+
+# Load the saved model
+def load_model():
+    try:
+        with open('model.pkl', 'rb') as file:
+            model = pickle.load(file)
+        return model
+    except Exception as e:
+        raise RuntimeError(f"Error loading model: {e}")
+
+model = load_model()
+
+# Define the FastAPI endpoint
+@app.post("/predict")
+async def predict_transaction(data: dict):
+    try:
+        # Convert the input data to a DataFrame
+        transaction_data = pd.DataFrame([data])
+        prediction = model.predict(transaction_data)
+
+        result = "Fraudulent transaction" if prediction[0] == 1 else "Acceptable transaction"
+        return {"prediction": result}
+    except Exception as e:
+        return {"error": str(e)}
+
+# Function to run the FastAPI server
+def run_fastapi():
+    uvicorn.run(app, host="0.0.0.0", port=8000)
+
+# Start the FastAPI server in a separate thread
+thread = threading.Thread(target=run_fastapi, daemon=True)
+thread.start()
+