app.py

import gradio as gr
from transformers import pipeline

# Load an open-source model for free-tier compatibility
generator = pipeline("text-generation", model="google/flan-t5-base")

def generate_test_cases(user_story):
    prompt = f"Generate structured test cases in JSON format from this user story: {user_story}"
    
    output = generator(prompt, max_length=300, do_sample=True)[0]["generated_text"]

    return output

# Create a Gradio interface
iface = gr.Interface(
    fn=generate_test_cases,
    inputs=gr.Textbox(lines=5, placeholder="Enter your user story here..."),
    outputs="text",
    title="AI Test Case Generator",
    description="Enter a user story and get structured test cases in JSON format.",
)

if __name__ == "__main__":
    iface.launch()