app.py

import gradio as gr
from transformers import pipeline
import subprocess

# Load a code-generation model with support for multiple languages
code_generator = pipeline("text2text-generation", model="bigcode/t5-code-generation")

def generate_code(description, language):
    prompt = f"Generate {language} code: {description}"
    response = code_generator(prompt, max_length=400)[0]['generated_text']
    return response.strip()

def execute_code(code, language):
    if language == "Python":
        try:
            result = subprocess.run(['python3', '-c', code], capture_output=True, text=True, timeout=5)
            return result.stdout if result.stdout else result.stderr
        except Exception as e:
            return str(e)
    return "Code execution only supported for Python."

# Create a Gradio interface with language selection and execution
iface = gr.Interface(
    fn=generate_code,
    inputs=[
        gr.Textbox(lines=5, placeholder="Describe your coding task..."),
        gr.Dropdown(choices=["Python", "JavaScript", "Java"], label="Programming Language")
    ],
    outputs=[gr.Code(), gr.Textbox(label="Execution Output")],
    title="Multi-Language Text-to-Code AI",
    description="Convert natural language descriptions into code in different programming languages! Run Python code directly in the app.",
    theme="default",
    allow_flagging="never"
)

# Launch the app
if __name__ == "__main__":
    iface.launch(share=True)