app.py

import gradio as gr
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

# Load your pretrained model and tokenizer
model_name = "your-model-name"  # Replace with your model's name
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

# Define the Gradio interface
iface = gr.Interface(
    fn=generate_answer,
    inputs=[gr.Textbox(lines=5, placeholder="Ask a question")],
    outputs="textbox",
    title="AI Answer Generator",
)

# Function to generate an answer using your model
def generate_answer(question):
    inputs = tokenizer([question], return_tensors="pt")
    outputs = model.generate(**inputs)
    answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return answer

# Launch the interface
iface.launch()