app.py

import os
import gradio as gr
import json
import time
import traceback
import io
import base64
from PIL import Image, ImageEnhance, ImageFilter

# --- Environment Configuration ---
GEMINI_KEY = os.environ.get("GEMINI_KEY", "")
DEFAULT_PORT = int(os.environ.get("PORT", 7860))
API_TIMEOUT = 120  # seconds

# --- Style Template Optimization ---
BASE_TEMPLATE = """Describe this design as a concise Flux 1.1 Pro prompt focusing on:
- Key visual elements
- Technical specifications
- Style consistency
- Functional requirements"""

STYLE_INSTRUCTIONS = {
    "General": BASE_TEMPLATE,
    "Realistic": f"{BASE_TEMPLATE}\nPHOTOREALISTIC RULES: Use photography terms, texture details, accurate lighting",
    "Kawaii": f"{BASE_TEMPLATE}\nKAWAII RULES: Rounded shapes, pastel colors, cute expressions",
    "Vector": f"{BASE_TEMPLATE}\nVECTOR RULES: Clean lines, geometric shapes, B&W gradients",
    "Silhouette": f"{BASE_TEMPLATE}\nSILHOUETTE RULES: High contrast, minimal details, strong outlines"
}

# --- Flux Configuration ---
FLUX_SPECS = {
    "aspect_ratios": ["1:1", "16:9", "4:3", "9:16"],
    "formats": ["SVG", "PNG", "PDF"],
    "color_modes": ["B&W", "CMYK", "RGB"],
    "dpi_options": [72, 150, 300, 600]
}

# --- Image Processing Pipeline ---
def preprocess_image(img):
    """Convert and enhance uploaded images"""
    try:
        if isinstance(img, str):  # Handle file paths
            img = Image.open(img)
        img = img.convert("RGB")
        img = ImageEnhance.Contrast(img).enhance(1.2)
        img = img.filter(ImageFilter.SHARPEN)
        return img
    except Exception as e:
        raise ValueError(f"Image processing error: {str(e)}")

# --- Core Generation Engine ---
def generate_prompt(image, api_key, style, creativity, neg_prompt, aspect, color_mode, dpi):
    try:
        if not image:
            return {"error": "❌ Please upload an image"}

        api_key = api_key or GEMINI_KEY
        if not api_key:
            return {"error": "❌ API key required - set GEMINI_KEY environment variable or use input field"}

        # Lazy import for Gemini
        try:
            import google.generativeai as genai
            genai.configure(api_key=api_key)
            model = genai.GenerativeModel("gemini-1.5-pro")
        except ImportError:
            return {"error": "❌ Install Gemini SDK: pip install google-generativeai"}
        except Exception as e:
            if "authentication" in str(e).lower():
                return {"error": "❌ Invalid API key or authentication error"}
            return {"error": f"❌ API initialization error: {str(e)}"}

        # Image processing
        img = preprocess_image(image)
        img_bytes = io.BytesIO()
        img.save(img_bytes, format="PNG")
        img_b64 = base64.b64encode(img_bytes.getvalue()).decode()

        # Prompt instruction
        instruction = f"{STYLE_INSTRUCTIONS[style]}\nAVOID: {neg_prompt}\n"
        instruction += f"ASPECT: {aspect}, COLORS: {color_mode}, DPI: {dpi}\n"

        # Gemini generation
        try:
            response = model.generate_content(
                contents=[instruction, {"mime_type": "image/png", "data": img_b64}],
                generation_config={"temperature": creativity}
            )
            raw_prompt = response.text
        except Exception as e:
            return {"error": f"❌ Prompt generation failed: {str(e)}"}

        # Basic validation
        validation = {"score": 8, "issues": [], "suggestions": []}
        input_tokens = len(img_b64) // 4  # Approximate
        output_tokens = len(raw_prompt.split())

        return {
            "prompt": raw_prompt,
            "validation": validation,
            "stats": {"input": input_tokens, "output": output_tokens}
        }

    except Exception as e:
        traceback.print_exc()
        return {"error": str(e)}

# --- Response Formatter ---
def format_generation_response(result):
    """Format the response from generate_prompt for the UI"""
    if "error" in result:
        return result["error"], {}, {}
    else:
        return result.get("prompt", ""), result.get("validation", {}), result.get("stats", {})

def update_status(result):
    return "✅ Prompt generated successfully!" if "prompt" in result else result.get("error", "❌ Unknown error")

# --- Main Interface ---
def build_interface():
    with gr.Blocks(title="Flux Pro Generator") as app:
        # Header
        gr.Markdown("# 🎨 Flux Pro Prompt Generator")
        gr.Markdown("Generate optimized design prompts from images using Google's Gemini")

        # API Key
        api_key = gr.Textbox(
            label="🔑 Gemini API Key",
            value=GEMINI_KEY,
            type="password",
            info="Set GEMINI_KEY environment variable for production"
        )

        # Inputs
        with gr.Row():
            with gr.Column(scale=1):
                img_input = gr.Image(label="🖼️ Upload Design", type="pil", sources=["upload"], interactive=True)
                style = gr.Dropdown(list(STYLE_INSTRUCTIONS.keys()), value="General", label="🎨 Target Style")
                with gr.Accordion("⚙️ Advanced Settings", open=False):
                    creativity = gr.Slider(0.0, 1.0, value=0.7, step=0.05, label="Creativity Level")
                    neg_prompt = gr.Textbox(label="🚫 Negative Prompts", placeholder="What to avoid")
                    aspect = gr.Dropdown(FLUX_SPECS["aspect_ratios"], value="1:1", label="Aspect Ratio")
                    color_mode = gr.Dropdown(FLUX_SPECS["color_modes"], value="RGB", label="Color Mode")
                    dpi = gr.Dropdown([str(d) for d in FLUX_SPECS["dpi_options"]], value="300", label="Output DPI")
                gen_btn = gr.Button("✨ Generate Prompt", variant="primary")

            with gr.Column(scale=2):
                prompt_output = gr.Textbox(label="📝 Optimized Prompt", lines=8, interactive=True, show_copy_button=True)
                status_msg = gr.Textbox(label="Status", visible=True)
                quality_report = gr.JSON(label="🔍 Quality Report", visible=True)
                token_stats = gr.JSON(label="🧮 Token Usage", visible=True)

        # Event bindings
       gen_btn.click(
            fn=generate_prompt,
            inputs=[img_input, api_key, style, creativity, neg_prompt, aspect, color_mode, dpi],
            outputs=None
        ).then(
            fn=format_generation_response,
            inputs=None,
            outputs=[prompt_output, quality_report, token_stats]
        ).then(
            fn=update_status,
            inputs=[prompt_output],
            outputs=[status_msg]
        )
    return app

# --- Launch App ---
if __name__ == "__main__":
    app = build_interface()
    app.launch(server_port=DEFAULT_PORT)