Update app.py

app.py

@@ -1,9 +1,16 @@
 import gradio as gr
 import random
-from diffusers import StableDiffusionPipeline
-import torch
 import os
 
+# Attempt to import required libraries
+try:
+    from diffusers import StableDiffusionPipeline
+    import torch
+    STABLE_DIFFUSION_AVAILABLE = True
+except ImportError as e:
+    print(f"Error importing Stable Diffusion dependencies: {e}")
+    STABLE_DIFFUSION_AVAILABLE = False
+
 try:
     import openai
     openai.api_key = os.environ.get("OPENAI_API_KEY")
@@ -12,7 +19,46 @@ except ImportError:
     print("OpenAI library not found. Falling back to basic responses.")
     USE_GPT = False
 
-# ... (rest of the code remains the same)
+# Quiz questions and answers
+christmas_quiz = [
+    {
+        "question": "What is the traditional Christmas flower?",
+        "options": ["Rose", "Poinsettia", "Tulip", "Daisy"],
+        "answer": "Poinsettia"
+    },
+    {
+        "question": "In which country did the tradition of putting up a Christmas tree originate?",
+        "options": ["USA", "England", "Germany", "France"],
+        "answer": "Germany"
+    },
+    {
+        "question": "What is the name of the ballet often performed at Christmas?",
+        "options": ["Swan Lake", "The Nutcracker", "Sleeping Beauty", "Giselle"],
+        "answer": "The Nutcracker"
+    },
+    {
+        "question": "Which company was the first to use Santa Claus in advertising?",
+        "options": ["Pepsi", "Coca-Cola", "McDonald's", "Walmart"],
+        "answer": "Coca-Cola"
+    },
+    {
+        "question": "What is the most popular Christmas dinner in Japan?",
+        "options": ["Turkey", "Ham", "KFC Chicken", "Roast Beef"],
+        "answer": "KFC Chicken"
+    }
+]
+
+# Initialize the Stable Diffusion pipeline if available
+if STABLE_DIFFUSION_AVAILABLE:
+    model_id = "runwayml/stable-diffusion-v1-5"
+    pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
+
+def generate_image(prompt):
+    if not STABLE_DIFFUSION_AVAILABLE:
+        return None
+    with torch.no_grad():
+        image = pipe(prompt, num_inference_steps=50).images[0]
+    return image
 
 def get_gpt_response(prompt, history):
     if not USE_GPT:
@@ -40,4 +86,71 @@ def get_gpt_response(prompt, history):
         print(f"Error in GPT response: {e}")
         return "I'm having trouble connecting to my knowledge base right now. Can I help you with the Christmas quiz or card generation instead?"
 
-# ... (rest of the code remains the same)
+def chatbot(message, history):
+    if not history:
+        return "Ho ho ho! Merry Christmas! I'm Holly, your Christmas helper. Would you like to take a Christmas quiz, create a Christmas card, or chat about the holidays?"
+
+    last_response = history[-1][1].lower()
+
+    if "quiz" in message.lower():
+        question = random.choice(christmas_quiz)
+        options_text = "\n".join([f"{i+1}. {opt}" for i, opt in enumerate(question['options'])])
+        return f"Great! Here's your Christmas quiz question:\n\n{question['question']}\n\n{options_text}\n\nPlease enter the number of your answer."
+
+    elif "card" in message.lower():
+        if STABLE_DIFFUSION_AVAILABLE:
+            return "Wonderful! Let's create a Christmas card. Please describe the scene you'd like on your card, and I'll generate it for you using AI."
+        else:
+            return "I'm sorry, but the card generation feature is currently unavailable. Would you like to take a Christmas quiz instead?"
+
+    elif any(str(i) in message for i in range(1, 5)):  # Check if the message is a quiz answer
+        for q in christmas_quiz:
+            if q['question'] in history[-2][1]:  # Find the question in the history
+                user_answer = q['options'][int(message) - 1]
+                if user_answer == q['answer']:
+                    return f"Correct! {q['answer']} is the right answer. Would you like another question, to create a Christmas card, or to chat about something else?"
+                else:
+                    return f"Sorry, that's not correct. The right answer is {q['answer']}. Would you like another question, to create a Christmas card, or to chat about something else?"
+
+    elif "card" in last_response and STABLE_DIFFUSION_AVAILABLE:
+        image = generate_image(f"Christmas card scene: {message}")
+        if image:
+            return (f"I've created a Christmas card based on your description: '{message}'. You can see it in the image box below. "
+                    f"Would you like to create another card, take a quiz, or chat about something else?", image)
+        else:
+            return "I'm sorry, I couldn't generate the image. Would you like to try again, take a quiz, or chat about something else?"
+
+    else:
+        # Use GPT-3.5 for general conversation
+        return get_gpt_response(message, history)
+
+# Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Christmas Quiz and Card Generator Chatbot")
+    gr.Markdown("""
+    Welcome to the Christmas Quiz and Card Generator Chatbot!
+    - Type 'quiz' to start a Christmas quiz.
+    - Type 'card' to create a custom Christmas card.
+    - Or just chat about anything Christmas-related!
+    """)
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox(label="Type your message here")
+    clear = gr.Button("Clear")
+
+    def user(user_message, history):
+        return "", history + [[user_message, None]]
+
+    def bot(history):
+        bot_message = chatbot(history[-1][0], history[:-1])
+        history[-1][1] = bot_message
+        if isinstance(bot_message, tuple):
+            return history, bot_message[1]
+        return history, None
+
+    image_output = gr.Image()
+    msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
+        bot, chatbot, [chatbot, image_output]
+    )
+    clear.click(lambda: None, None, chatbot, queue=False)
+
+demo.launch()