app.py

import gradio as gr
import subprocess
import os
import torch
from model import GPTLanguageModel, decode, context

# Clone the repository if not already cloned
REPO_URL = "https://huggingface.co/TharunSivamani/tiny-shakespeare"
REPO_NAME = "tiny-shakespeare"

if not os.path.exists(REPO_NAME):
    subprocess.run(["git", "clone", REPO_URL])

# Set the device
DEVICE = "cuda" if torch.cuda.is_available() else "cpu"

# Load the model
model = GPTLanguageModel().to(DEVICE)
model.load_state_dict(torch.load(f"{REPO_NAME}/model.pth", map_location=DEVICE), strict=False)
model.eval()

# Define the display function
def display(text, number):
    answer = decode(model.generate(context, max_new_tokens=number)[0].tolist())
    return text + " \n" + answer

# Gradio app interface
input_box = gr.Textbox(label="Story Lines", value="Once Upon a Time")
input_slider = gr.Slider(
    minimum=200, maximum=500, label="Select the maximum number of tokens/words:", step=100
)
output_text = gr.Textbox()

gr.Interface(
    fn=display,
    inputs=[input_box, input_slider],
    outputs=output_text,
    examples=[["Shakespeare Once Said", 500], ["A Long Time Ago", 300]]
).launch()