#!/usr/bin/env python3
"""
Minimal A1D MCP Server with Gradio - Ultra-simple version to avoid all compatibility issues
"""

import gradio as gr
import os
from utils import A1DAPIClient, prepare_request_data, format_response_with_preview
from config import TOOLS_CONFIG

def get_api_client():
    """Get API client with current API key"""
    api_key = os.getenv("A1D_API_KEY")
    if not api_key:
        raise ValueError("A1D_API_KEY environment variable is required")
    return A1DAPIClient(api_key)

def process_remove_bg(image_url):
    """Remove background from images using AI"""
    try:
        if not image_url or not image_url.strip():
            return "❌ Error: Please provide an image URL"
        
        client = get_api_client()
        data = prepare_request_data("remove_bg", image_url=image_url)
        response = client.make_request_with_result(
            TOOLS_CONFIG["remove_bg"]["api_endpoint"],
            data,
            timeout=120
        )
        message, media_url = format_response_with_preview(response, "remove_bg")
        return f"{message}\n\nResult URL: {media_url}" if media_url else message
    except Exception as e:
        return f"❌ Error: {str(e)}"

def process_upscale(image_url, scale):
    """Upscale images using AI"""
    try:
        if not image_url or not image_url.strip():
            return "❌ Error: Please provide an image URL"
        
        client = get_api_client()
        data = prepare_request_data("image_upscaler", image_url=image_url, scale=int(scale))
        response = client.make_request_with_result(
            TOOLS_CONFIG["image_upscaler"]["api_endpoint"],
            data,
            timeout=120
        )
        message, media_url = format_response_with_preview(response, "image_upscaler")
        return f"{message}\n\nResult URL: {media_url}" if media_url else message
    except Exception as e:
        return f"❌ Error: {str(e)}"

def process_generate(prompt):
    """Generate images using AI from text prompts"""
    try:
        if not prompt or not prompt.strip():
            return "❌ Error: Please provide a text prompt"
        
        client = get_api_client()
        data = prepare_request_data("image_generator", prompt=prompt)
        response = client.make_request_with_result(
            TOOLS_CONFIG["image_generator"]["api_endpoint"],
            data,
            timeout=120
        )
        message, media_url = format_response_with_preview(response, "image_generator")
        return f"{message}\n\nResult URL: {media_url}" if media_url else message
    except Exception as e:
        return f"❌ Error: {str(e)}"

# Create the minimal Gradio interface
def create_minimal_interface():
    """Create minimal interface with basic components only"""
    
    # Background Removal Interface
    bg_interface = gr.Interface(
        fn=process_remove_bg,
        inputs=gr.Textbox(label="Image URL", placeholder="https://example.com/image.jpg"),
        outputs=gr.Textbox(label="Result"),
        title="🎭 Background Removal",
        description="Remove background from images using AI"
    )
    
    # Image Upscaler Interface  
    upscale_interface = gr.Interface(
        fn=process_upscale,
        inputs=[
            gr.Textbox(label="Image URL", placeholder="https://example.com/image.jpg"),
            gr.Radio(choices=["2", "4", "8", "16"], value="2", label="Scale Factor")
        ],
        outputs=gr.Textbox(label="Result"),
        title="🔍 Image Upscaler",
        description="Upscale images using AI"
    )
    
    # Image Generator Interface
    gen_interface = gr.Interface(
        fn=process_generate,
        inputs=gr.Textbox(label="Text Prompt", placeholder="A beautiful sunset over mountains...", lines=3),
        outputs=gr.Textbox(label="Result"),
        title="🎨 Image Generator", 
        description="Generate images using AI from text prompts"
    )
    
    # Create tabbed interface
    demo = gr.TabbedInterface(
        [bg_interface, upscale_interface, gen_interface],
        ["Background Removal", "Image Upscaler", "Image Generator"],
        title="🤖 A1D MCP Server - Universal AI Tools"
    )
    
    return demo

if __name__ == "__main__":
    # Check for API key
    if not os.getenv("A1D_API_KEY"):
        print("❌ Error: A1D_API_KEY environment variable is required")
        print("Please set your API key in the Space settings")
        exit(1)
    
    print("🚀 Starting A1D MCP Server (Minimal Version)...")
    print("✅ API key found")
    print("🌐 Server will be available at: http://0.0.0.0:7860")
    
    # Create and launch the minimal app
    demo = create_minimal_interface()
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=False
    )