app.py

import os
import time
import logging
import requests
from io import BytesIO
from PIL import Image
import gradio as gr

# ----------------------------
# Logging Configuration
# ----------------------------
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# ----------------------------
# Constants
# ----------------------------
HF_API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell"
DEFAULT_STYLES = [
    "Realistic", "Cinematic", "Cyberpunk",
    "Studio Lighting", "Highly Detailed", "4K"
]

# ----------------------------
# Utility Functions
# ----------------------------

def get_hf_token():
    """Load Hugging Face token from environment variable."""
    token = os.getenv("HF_TOKEN")
    if not token:
        raise EnvironmentError("HF_TOKEN not found in environment variables.")
    return token


def style_prompt(user_input: str, style: str = None) -> str:
    """Enhance prompt with selected style."""
    if not user_input.strip():
        raise ValueError("Prompt cannot be empty.")

    if style and style != "None":
        enhanced = f"{user_input}, {style}, ultra quality, sharp focus"
    else:
        enhanced = f"{user_input}, high quality"

    return enhanced


def query_hf_api(prompt, retries=3, timeout=60, seed=None):
    """Send request to Hugging Face Inference API with retry logic."""
    headers = {
        "Authorization": f"Bearer {get_hf_token()}",
        "Content-Type": "application/json"
    }

    payload = {
        "inputs": prompt,
        "options": {"wait_for_model": True}
    }

    if seed is not None:
        payload["parameters"] = {"seed": seed}

    for attempt in range(retries):
        try:
            response = requests.post(
                HF_API_URL,
                headers=headers,
                json=payload,
                timeout=timeout
            )

            if response.status_code == 200:
                return response.content

            elif response.status_code == 503:
                logger.warning("Model loading, retrying...")
                time.sleep(5)

            elif response.status_code == 429:
                logger.warning("Rate limit hit, retrying...")
                time.sleep(10)

            else:
                logger.error(f"API Error: {response.text}")
                raise RuntimeError(f"API Error: {response.text}")

        except requests.exceptions.Timeout:
            logger.warning("Timeout occurred, retrying...")
            time.sleep(5)

    raise RuntimeError("Failed after multiple retries.")


def generate_image(prompt, style, seed):
    """Main function for Gradio."""
    try:
        styled_prompt = style_prompt(prompt, style)
        image_bytes = query_hf_api(styled_prompt, seed=seed)

        image = Image.open(BytesIO(image_bytes)).convert("RGB")

        return image

    except Exception as e:
        logger.error(str(e))
        return f"Error: {str(e)}"


# ----------------------------
# Gradio UI
# ----------------------------

with gr.Blocks() as app:
    gr.Markdown("# 🎨 AI Image Generator (FLUX.1-schnell)")
    gr.Markdown("Generate high-quality images from text prompts using Hugging Face.")

    with gr.Row():
        prompt_input = gr.Textbox(
            label="Enter your prompt",
            placeholder="e.g., A futuristic city at sunset"
        )

    with gr.Row():
        style_dropdown = gr.Dropdown(
            ["None"] + DEFAULT_STYLES,
            label="Select Style",
            value="None"
        )
        seed_input = gr.Number(
            label="Seed (optional)",
            value=None,
            precision=0
        )

    generate_btn = gr.Button("Generate Image")

    output_image = gr.Image(label="Generated Image")
    download_btn = gr.File(label="Download Image")

    examples = gr.Examples(
        examples=[
            ["A dragon flying over mountains", "Cinematic", 42],
            ["Cyberpunk city at night", "Cyberpunk", 123],
            ["Portrait of a warrior", "Realistic", 7],
        ],
        inputs=[prompt_input, style_dropdown, seed_input],
    )

    def generate_and_download(prompt, style, seed):
        image = generate_image(prompt, style, seed)
        if isinstance(image, str):
            return None, None

        file_path = "output.png"
        image.save(file_path)
        return image, file_path

    generate_btn.click(
        fn=generate_and_download,
        inputs=[prompt_input, style_dropdown, seed_input],
        outputs=[output_image, download_btn]
    )

app.launch()