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count_vectorizer_spam.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ab21921805595cfe88566f589a4a6d3340ce4aa1e15928ca204a67a58ce31c9c
+size 546064

gradioapp.py

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+import pandas as pd
+import numpy as np
+import re
+import nltk
+from nltk.tokenize import word_tokenize
+from nltk.corpus import stopwords
+from nltk.stem import WordNetLemmatizer
+from sklearn.feature_extraction.text import CountVectorizer
+import pickle
+import gradio as gr
+
+# Download NLTK data
+nltk.download("punkt")
+nltk.download("stopwords")
+nltk.download("wordnet")
+
+# Load vectorizer and model
+with open("count_vectorizer_spam.pkl", "rb") as f:
+    vectorizer = pickle.load(f)
+
+with open("nb_model_spam.pkl", "rb") as f:
+    nb_model = pickle.load(f)
+
+# Preprocessing function
+def preprocess_text(text):
+    words = word_tokenize(text)
+    words_without_punct = [word for word in words if word.isalnum()]
+    clean_text = ' '.join(words_without_punct)
+    clean_text = clean_text.lower()
+    
+    stop_words = set(stopwords.words('english'))
+    words = word_tokenize(clean_text)
+    filtered_words = [word for word in words if word.lower() not in stop_words]
+    clean_text_without_stopwords = ' '.join(filtered_words)
+    
+    lemmatizer = WordNetLemmatizer()
+    words = word_tokenize(clean_text_without_stopwords)
+    lemmatized_words = [lemmatizer.lemmatize(word) for word in words]
+    lemmatized_text = ' '.join(lemmatized_words)
+    
+    text = re.sub(r'[^a-z\s]', '', lemmatized_text)
+    return text
+
+# Prediction function for Gradio
+def predict_spam(text):
+    if text.strip() == "":
+        return "Please enter an email!"
+    
+    cleaned_text = preprocess_text(text)
+    X_input = vectorizer.transform([cleaned_text])
+    prediction = nb_model.predict(X_input)[0]
+    
+    return "Spam" if prediction == 1 else "Non-Spam"
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=predict_spam,
+    inputs=gr.Textbox(lines=5, placeholder="Enter email here..."),
+    outputs="text",
+    title="Spam Detection",
+    description="Enter an email message to detect if it's Spam or Non-Spam.",
+    allow_flagging=False
+)
+
+# Launch the app
+iface.launch()

nb_model_spam.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5a35cb6fa9ca2a7195d51346b1c873f8b268ae5e587bd5aaff8d4d7e1f46eb7f
+size 1262542