Upload app.py

app.py

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+import joblib
+import re
+import pandas as pd
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.naive_bayes import MultinomialNB
+from fastapi import FastAPI
+from pydantic import BaseModel
+
+# Load the model and vectorizer
+vectorizer = joblib.load("vectorizer.joblib")
+model = joblib.load("naive_bayes_model.joblib")
+
+app = FastAPI()
+
+class URLInput(BaseModel):
+    url: str
+
+def preprocess_url(url):
+    url = re.sub(r"http\S+", "", url)
+    url = re.sub(r"\d+", "", url)
+    url = re.sub(r"\W", " ", url)
+    url = url.lower()
+    return url
+
+@app.post("/predict")
+def predict_url(url_input: URLInput):
+    processed_url = preprocess_url(url_input.url)
+    vectorized_url = vectorizer.transform([processed_url])
+    prediction = model.predict(vectorized_url)
+    return {"prediction": prediction[0]}
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)