Huggface/app.py

import gradio as gr
import os
from dotenv import load_dotenv

load_dotenv()
import tempfile
from backend.converter import convert_code
from backend.deployer import deploy_to_space
from backend.utils import create_zip_archive, extract_code_from_ipynb
import json

# Load CSS
with open("assets/style.css", "r") as f:
    custom_css = f.read()

def process_and_deploy(
    input_text, 
    input_file, 
    hf_token, 
    space_name, 
    deploy_mode
):
    try:
        # 1. Get Source Code
        code_content = ""
        if input_file is not None:
            # Determine file type
            if input_file.name.endswith('.ipynb'):
                with open(input_file.name, 'r', encoding='utf-8') as f:
                    content = f.read()
                code_content = extract_code_from_ipynb(content)
            else:
                with open(input_file.name, 'r', encoding='utf-8') as f:
                    code_content = f.read()
        elif input_text.strip():
            code_content = input_text
        else:
            return None, "Please provide either a file or paste code."

        if not code_content.strip():
            return None, "No code found to convert."

        # 2. Convert Code using AI Agent
        # Note: We expect GROQ_API_KEY to be set in the environment.
        # If not, we could ask user, but requirements said "place to enter HF tokens", didn't specify Groq key user input.
        # Assuming env var is present or handled globally.
        try:
             conversion_result = convert_code(code_content)
        except Exception as e:
            return None, f"AI Conversion Failed: {str(e)}"

        files_dict = {
            "app.py": conversion_result["app_py"],
            "requirements.txt": conversion_result["requirements_txt"],
            "README.md": conversion_result["readme_md"]
        }

        # 3. Create Zip
        zip_bytes = create_zip_archive(files_dict)
        
        # Create a temp file for the zip output
        # Gradio File component needs a real path
        temp_dir = tempfile.mkdtemp()
        zip_path = os.path.join(temp_dir, "huggingface_space_files.zip")
        with open(zip_path, "wb") as f:
            f.write(zip_bytes)
            
        status_msg = "Conversion Successful! Download the zip below."
        
        # 4. Deploy if requested
        deploy_url = ""
        if deploy_mode == "Convert & Deploy to HF Space":
            if not hf_token or not space_name:
                status_msg += "\n\nDeployment Skipped: Missing HF Token or Space Name."
            else:
                try:
                    deploy_url = deploy_to_space(hf_token, space_name, files_dict)
                    status_msg += f"\n\nSuccessfully Deployed to: {deploy_url}"
                except Exception as e:
                    status_msg += f"\n\nDeployment Failed: {str(e)}"

        return zip_path, status_msg

    except Exception as e:
        return None, f"An unexpected error occurred: {str(e)}"


with gr.Blocks(css=custom_css, title="HF Agent Creator") as demo:
    
    with gr.Row(elem_id="header-title"):
        gr.Markdown("# 🐝 Hugging Face Space Creator Agent")
    
    gr.Markdown("Transform your local Python scripts or Jupyter Notebooks into ready-to-deploy Hugging Face Spaces instantly.")
    
    with gr.Row():
        with gr.Column(scale=1):
            with gr.Group(elem_classes="panel-container"):
                gr.Markdown("### 1. Source Code")
                input_tab = gr.Tabs()
                with input_tab:
                    with gr.TabItem("Upload File"):
                        file_input = gr.File(
                            label="Upload .py or .ipynb file", 
                            file_types=[".py", ".ipynb"]
                        )
                    with gr.TabItem("Paste Code"):
                        text_input = gr.Code(
                            label="Paste your Python code", 
                            language="python"
                        )
        
        with gr.Column(scale=1):
             with gr.Group(elem_classes="panel-container"):
                gr.Markdown("### 2. Deployment Details")
                hf_token = gr.Textbox(
                    label="Hugging Face Access Token (Write)", 
                    type="password",
                    placeholder="hf_..."
                )
                space_name = gr.Textbox(
                    label="New Space Name", 
                    placeholder="my-awesome-agent"
                )
                action_radio = gr.Radio(
                    ["Convert Only", "Convert & Deploy to HF Space"], 
                    label="Action", 
                    value="Convert Only"
                )
                submit_btn = gr.Button("Generate Agent", variant="primary", size="lg")

    with gr.Row():
        with gr.Group(elem_classes="panel-container"):
            gr.Markdown("### 3. Results")
            status_output = gr.Markdown(label="Status Console")
            zip_output = gr.File(label="Download Generated Files")

    submit_btn.click(
        fn=process_and_deploy,
        inputs=[text_input, file_input, hf_token, space_name, action_radio],
        outputs=[zip_output, status_output]
    )

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