Create app.py

Email Spam Detector using Naive Bayes and Gradio UI.

app.py

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+import pandas as pd
+import numpy as np
+from sklearn.naive_bayes import MultinomialNB
+from sklearn.feature_extraction.text import CountVectorizer
+from sklearn.model_selection import train_test_split
+from sklearn.metrics import classification_report
+import gradio as gr
+
+# -------------------------------
+# Load and preprocess the data
+# -------------------------------
+def load_data():
+    df = pd.read_csv("spam.csv", encoding="latin-1")
+    df = df[['v1', 'v2']]  # Keep only the required columns
+    df.columns = ['label', 'message']
+    df['spam'] = df['label'].apply(lambda x: 1 if x == 'spam' else 0)
+    return df
+
+# -------------------------------
+# Train the spam classifier
+# -------------------------------
+def train_model(df):
+    X_train, X_test, y_train, y_test = train_test_split(df.message, df.spam, test_size=0.2, random_state=42)
+
+    vectorizer = CountVectorizer()
+    X_train_cv = vectorizer.fit_transform(X_train)
+    X_test_cv = vectorizer.transform(X_test)
+
+    model = MultinomialNB()
+    model.fit(X_train_cv, y_train)
+
+    y_pred = model.predict(X_test_cv)
+    print("Model performance on test set:")
+    print(classification_report(y_test, y_pred))
+
+    return model, vectorizer
+
+# -------------------------------
+# Predict function for Gradio
+# -------------------------------
+def predict_spam(email_text):
+    email_count = vectorizer.transform([email_text])
+    prediction = model.predict(email_count)[0]
+    return "Spam ❌" if prediction == 1 else "Not Spam"
+
+# -------------------------------
+# Main Execution
+# -------------------------------
+df = load_data()
+model, vectorizer = train_model(df)
+
+# -------------------------------
+# Gradio Interface
+# -------------------------------
+interface = gr.Interface(
+    fn=predict_spam,
+    inputs=gr.Textbox(lines=5, placeholder="Paste your email text here..."),
+    outputs="text",
+    title="Email Spam Detector",
+    description="A machine learning model using Naive Bayes to detect whether an email is spam or not. Type or paste an email to test it!"
+)
+
+# Shareable link
+interface.launch()