app.py

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from transformers import AutoModelForCausalLM, AutoTokenizer

# Load model and tokenizer
model = AutoModelForCausalLM.from_pretrained(
    "microsoft/phi-3-mini-4k-instruct",
    device_map="cpu",
    torch_dtype="auto",
    trust_remote_code=True
)
tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-3-mini-4k-instruct")

# Test generation
prompt = "Compose a captivating poem in 8-9 lines about the beauty of structured poetry. Begin with a vivid image to draw the reader in, explore emotions and metaphors in the middle, and end with a resonant and thought-provoking conclusion. Use poetic devices like rhyme, alliteration, and rhythm to enhance the flow and make the poem memorable."
# Tokenize the input
input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to("cpu")
outputs = model.generate(input_ids=input_ids, max_new_tokens=300, temperature=0.8)
poem = tokenizer.decode(outputs[0], skip_special_tokens=True)

print(poem)


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import gradio as gr
from transformers import pipeline

# Load model and tokenizer using pipeline for more efficient memory management
pipe = pipeline(
    "text-generation",
    model="microsoft/phi-3-mini-4k-instruct",
    tokenizer="microsoft/phi-3-mini-4k-instruct",
    device_map="auto",  # Let Transformers automatically choose the best device
    torch_dtype="float16",  # Use half-precision for faster inference
    trust_remote_code=True
)

# Predefined conversation responses
conversations = {
    "who built this": "This application was built by Adewuyi Ayomide, a passionate Machine Learning Engineer and Computer Science student at the University of Ibadan. He specializes in Natural Language Processing and has a keen interest in making AI more accessible and creative.",
    "who built this application": "This application was built by Adewuyi Ayomide, a passionate Machine Learning Engineer and Computer Science student at the University of Ibadan. He specializes in Natural Language Processing and has a keen interest in making AI more accessible and creative.",
    "who built this?": "This application was built by Adewuyi Ayomide, a passionate Machine Learning Engineer and Computer Science student at the University of Ibadan. He specializes in Natural Language Processing and has a keen interest in making AI more accessible and creative.",
    "who built this application?": "This application was built by Adewuyi Ayomide, a passionate Machine Learning Engineer and Computer Science student at the University of Ibadan. He specializes in Natural Language Processing and has a keen interest in making AI more accessible and creative.",
    "who created you": "I was created by Adewuyi Ayomide, a talented Machine Learning Engineer and Computer Science student at the University of Ibadan. He developed me to help people explore the beauty of poetry through AI.",
    "who created you?": "I was created by Adewuyi Ayomide, a talented Machine Learning Engineer and Computer Science student at the University of Ibadan. He developed me to help people explore the beauty of poetry through AI.",
    "hey": "Hello! 👋 I'm your AI poetry companion. Would you like me to create a poem for you?",
    "hi": "Hi there! 👋 Ready to explore the world of poetry together?",
    "hello": "Hello! 👋 I'm excited to create some poetry with you today!",
    "help": "I can help you create beautiful poems! Just share a topic, emotion, or idea, and I'll craft a unique poem for you. You can also ask me about who created me or just chat casually.",
    "wow": "Thank you! I'm glad you're impressed. Would you like me to create another poem for you? Just share any topic that interests you!",
    "amazing": "I'm delighted you think so! Would you like to explore more poetry together? Just give me a theme or emotion to work with!",
    "awesome": "Thank you for the kind words! I enjoy creating poems. What topic would you like me to write about next?",
    "beautiful": "I'm happy you enjoyed it! Poetry is a beautiful way to express emotions. Would you like another poem?",
    "nice": "Thank you! I'm here to create more poems whenever you're ready. Just share a topic with me!",
    "great": "I'm glad you liked it! Ready for another poetic journey? Just give me a theme to work with!",
    "good": "Thank you! I enjoy crafting poems. Would you like to try another topic?",
    "thank you": "You're welcome! It's my pleasure to create poems. Feel free to request another one whenever you'd like!",
    "thanks": "You're welcome! Ready for another poem whenever you are!"
}

def generate_poem(prompt, history=None):
    if history is None:
        history = []  # Initialize history as an empty list if None is passed

    # Check for predefined conversation responses
    prompt_lower = prompt.strip().lower()
    if prompt_lower in conversations:
        response = conversations[prompt_lower]
        history.append(("You", prompt))
        history.append(("AI", response))
        return history, history

    # Ensure the prompt is not empty
    if not prompt.strip():
        return history + [("You", "Please provide a topic or idea for the poem.")], history

    try:
        # Generate the poem using the pipeline with optimized parameters
        outputs = pipe(prompt, max_new_tokens=500, temperature=0.7, do_sample=True)
        poem = outputs[0]['generated_text']  # Extract generated text from pipeline output
    except Exception as e:
        poem = f"An error occurred: {e}"

    # Add the user prompt and the poem response to the history
    history.append(("You", prompt))
    history.append(("AI", poem))

    return history, history

# Create the Gradio interface
interface = gr.Interface(
    fn=generate_poem,
    inputs=["text", "state"],
    outputs=["chatbot", "state"],
    title="Love Poem Generator Chatbot",
    description="Chat with the AI, and it will generate love poems for you!"
)


# Launch the Gradio interface
interface.launch(share=True)  # Use share=True to get a public link