app.py

import streamlit as st
from transformers import pipeline, AutoProcessor, AutoModel
import torch
from huggingface_hub import login
import os

#login
api_key = os.getenv("ACCESS_TOKEN")
login(token=api_key)


# gemma
pipe = pipeline(task="text-generation", model="google/gemma-2-2b-it")

def poet(prompt):
    messages = [{"role": "user", "content": prompt}]
    outputs = pipe(messages, max_length=80)
    return outputs[0]["generated_text"][-1]["content"].strip()
    
st.title("Shakespeare Ai")
st.write("A space made to allow people to create shakespeare like text!")

# get prompt
prompt = st.text_input("Enter your prompt: ")

# analyze prompt
shakespeare = poet(prompt)

# write content
st.write(shakespeare)