app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline

# Load the model
model_id = "HuggingFaceH4/zephyr-7b-alpha"  # or another instruct-tuned model
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", torch_dtype="auto")
generator = pipeline("text-generation", model=model, tokenizer=tokenizer)

# AI Function
def generate_json(prompt):
    system_prompt = "You are an AI that generates valid and clean JSON objects based on descriptions."
    input_prompt = f"{system_prompt}\n\nDescription:\n{prompt}\n\nJSON:\n"
    output = generator(input_prompt, max_new_tokens=256, do_sample=False)[0]["generated_text"]

    # Remove original prompt from generated text
    json_part = output.replace(input_prompt, "").strip()
    return json_part

# Gradio UI
gr.Interface(
    fn=generate_json,
    inputs=gr.Textbox(label="Describe the JSON you want", lines=4),
    outputs=gr.Textbox(label="Generated JSON", lines=20),
    title="🧠 JSON Generator with LLM",
    description="Enter a plain language description and get a structured JSON output."
).launch()