app.py

import gradio as gr
import torch
from transformers import pipeline

MODEL_ID = "Amitesh007/text_generation-finetuned-gpt2"

# ✅ Load PyTorch model explicitly
generator = pipeline(
    task="text-generation",
    model=MODEL_ID,
    framework="pt",     # 🔑 FIX
    device=-1           # CPU (use 0 for GPU)
)

def generate(text):
    if not text or not text.strip():
        return "Please enter some text.", ""

    outputs = generator(
        text,
        max_length=120,
        num_return_sequences=2,
        do_sample=True,
        temperature=0.8,
        top_p=0.95
    )
    return outputs[0]["generated_text"], outputs[1]["generated_text"]


with gr.Blocks(title="GPT-2 Text Generator") as demo:
    gr.Markdown(
        """
        # ✍️ GPT-2 Text Generator  
        Fine-tuned GPT-2 model trained on a *Game of Thrones* dataset.
        """
    )

    with gr.Row():
        with gr.Column():
            input_text = gr.Textbox(
                lines=5,
                label="Input Prompt",
                placeholder="Type a sentence to start generating text..."
            )
            generate_button = gr.Button("Generate 🚀")

        with gr.Column():
            output_text1 = gr.Textbox(label="Generated Text 1", lines=6)
            output_text2 = gr.Textbox(label="Generated Text 2", lines=6)

    gr.Examples(
        examples=[
            "A light snow had fallen the night before, and there were",
            "The pig face had been smashed in with a mace, but Tyrion"
        ],
        inputs=input_text
    )

    generate_button.click(
        fn=generate,
        inputs=input_text,
        outputs=[output_text1, output_text2]
    )

demo.queue(concurrency_count=2)
demo.launch()