Create app.py

app.py

@@ -1,22 +1,22 @@
-import streamlit as st
-import joblib
-
-# Load the model and vectorizer
-model = joblib.load('svm_spam_model.pkl')
-vectorizer = joblib.load('vectorizer.pkl')
-
-st.title("Email Spam Detector 📧")
-user_input = st.text_area("Enter email text here:")
-
-if st.button("Predict"):
-    if user_input:
-        # Transform text and predict
-        data = vectorizer.transform([user_input])
-        prediction = model.predict(data)
-
-        if prediction[0] == 1:
-            st.error("🚨 This is a SPAM email.")
-        else:
-            st.success("✅ This is a legitimate (Ham) email.")
-    else:
-        st.warning("Please enter some text to analyze.")
+import gradio as gr
+from transformers import pipeline
+
+# Load a free pipeline model from Hugging Face
+generator = pipeline("text-generation", model="gpt2")
+
+def generate_text(user_input):
+    # Process the user input through the AI model
+    result = generator(user_input, max_length=50, num_return_sequences=1)
+    return result[0]['generated_text']
+
+# Build the Gradio interface
+demo = gr.Interface(
+    fn=generate_text, 
+    inputs=gr.Textbox(lines=2, placeholder="Enter a prompt here..."), 
+    outputs="text",
+    title="My First AI Assistant"
+)
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch()