Update app.py

app.py

@@ -1,9 +1,10 @@
+# CodeAlpha Task 2: Chatbot for FAQs
 from sklearn.feature_extraction.text import TfidfVectorizer
 from sklearn.metrics.pairwise import cosine_similarity
 import numpy as np
 import gradio as gr
 
-# Step 1: Collect FAQs - 
+# Step 1: Collect FAQs
 faqs = {
     "What is CodeAlpha?": "CodeAlpha is a tech platform offering free virtual internships in AI, Web Development, and Data Science to help students gain practical experience.",
     "How long is CodeAlpha internship?": "CodeAlpha internships last 1 month. You must complete minimum 2 out of 4 tasks to receive the completion certificate and Letter of Recommendation.",
@@ -18,7 +19,7 @@ faqs = {
 questions = list(faqs.keys())
 answers = list(faqs.values())
 
-# Step 2: Preprocess using TF-IDF -// tokenize + clean automatically
+# Step 2: Preprocess using TF-IDF
 vectorizer = TfidfVectorizer(stop_words='english')
 tfidf_matrix = vectorizer.fit_transform(questions)
 
@@ -38,13 +39,15 @@ def chatbot_response(message, history):
     else:
         return "🤖 I don't have info on that. Try asking about CodeAlpha internship, TF-IDF, or cosine similarity."
 
-# Step 5: Create simple chat UI
-demo = gr.ChatInterface(
-    fn=chatbot_response,
-    title="CodeAlpha FAQ Chatbot - Task 2",
-    description="Ask me about CodeAlpha internship or NLP concepts! Uses TF-IDF + Cosine Similarity",
-    examples=["What is CodeAlpha?", "When is submission deadline?", "What is TF-IDF?"],
-    theme=gr.themes.Soft()
-)
+# Step 5: Create Chat UI - الصيغة الصحيحة
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# CodeAlpha FAQ Chatbot - Task 2")
+    gr.Markdown("Ask me about CodeAlpha internship or NLP concepts! Uses TF-IDF + Cosine Similarity")
 
-demo.launch(share=True)
+    gr.ChatInterface(
+        fn=chatbot_response,
+        examples=["What is CodeAlpha?", "When is submission deadline?", "What is TF-IDF?"],
+        chatbot=gr.Chatbot(height=400),
+    )
+
+demo.launch()