import gradio as gr
import os
from huggingface_hub import login
from transformers import AutoModelForCausalLM, AutoTokenizer

login(os.getenv("Write"))

# Load your model and tokenizer
model_name = "distilgpt2"  # Change to your model
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Function to generate SEO-optimized content
def generate_content(prompt):
    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(**inputs)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

# Set up the Gradio interface
iface = gr.Interface(fn=generate_content, inputs="text", outputs="text")
iface.launch()