Create app.py

app.py

@@ -0,0 +1,101 @@
+import gradio as gr
+import random
+from diffusers import StableDiffusionPipeline
+import torch
+
+# 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
+model_id = "runwayml/stable-diffusion-v1-5"
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+pipe = pipe.to("cuda")
+
+def generate_image(prompt):
+    image = pipe(prompt).images[0]
+    return image
+
+def chatbot(message, history):
+    if not history:
+        return "Ho ho ho! Merry Christmas! I'm Santa's helper. Would you like to take a Christmas quiz or create a Christmas card?"
+
+    last_response = history[-1][1].lower()
+
+    if "quiz" in last_response:
+        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 last_response:
+        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."
+
+    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 or to create a Christmas card?"
+                else:
+                    return f"Sorry, that's not correct. The right answer is {q['answer']}. Would you like another question or to create a Christmas card?"
+
+    else:
+        image = generate_image(f"Christmas card scene: {message}")
+        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 or take a quiz?", image)
+
+# 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 say hello to get started!
+    """)
+    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, image = chatbot(history[-1][0], history[:-1])
+        history[-1][1] = bot_message
+        if image:
+            return history, image
+        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()