app.py

import gradio as gr
import os
from PIL import Image, ImageDraw, ImageFont, ImageEnhance
import requests
import io
import json

# Définition des styles
# Styles optimisés et stabilisés
ART_STYLES = {
    "Art Moderne": {
        "prompt_prefix": "modern art style poster, professional design",
        "text_style": "modern clean typography, geometric style",
        "guidance": 9.0,  # Réduit pour plus de stabilité
        "steps": 55,
        "negative_prompt": "traditional, photorealistic, cluttered, busy design"
    },
    "Neo Vintage": {
        "prompt_prefix": "vintage style advertising poster, retro design",
        "text_style": "retro typography, vintage lettering",
        "guidance": 8.5,
        "steps": 50,
        "negative_prompt": "modern, digital, contemporary style"
    },
    "Pop Art": {
        "prompt_prefix": "pop art style poster, bold design",
        "text_style": "bold typography, comic book style text",
        "guidance": 8.0,
        "steps": 45,
        "negative_prompt": "subtle, realistic, traditional art"
    },
    "Minimaliste": {
        "prompt_prefix": "minimalist design poster, clean composition",
        "text_style": "clean minimal typography, simple text layout",
        "guidance": 7.5,
        "steps": 40,
        "negative_prompt": "complex, detailed, ornate, busy"
    }
}
ART_STYLES = {
    # Styles Photoréalistes
    "Photo HDR": {
        "prompt_prefix": "ultra realistic photograph, professional HDR photography, extremely detailed, 8k uhd",
        "text_style": "photographic text overlay",
        "guidance": 9.0,
        "steps": 60,
        "negative_prompt": "illustration, painting, drawing, cartoon, blurry, low quality, artistic"
    },
    "Portrait Studio": {
        "prompt_prefix": "professional studio photography, high end photoshoot, perfect lighting, sharp focus",
        "text_style": "elegant text overlay, magazine style typography",
        "guidance": 8.5,
        "steps": 55,
        "negative_prompt": "illustration, drawing, cartoon, painting, low quality"
    },
    "Nature Pro": {
        "prompt_prefix": "professional nature photography, national geographic style, perfect natural lighting",
        "text_style": "outdoor photography text style",
        "guidance": 8.0,
        "steps": 50,
        "negative_prompt": "illustration, artificial, cartoon, painting"
    },
    "Urban Photo": {
        "prompt_prefix": "professional urban photography, architectural photo, perfect city shot",
        "text_style": "modern photographic typography",
        "guidance": 8.5,
        "steps": 55,
        "negative_prompt": "illustration, drawing, cartoon, unrealistic"
    },
    
    # Styles Artistiques existants
    "Art Moderne": {
        "prompt_prefix": "modern art style poster, professional design",
        "text_style": "modern clean typography, geometric style",
        "guidance": 9.0,
        "steps": 55,
        "negative_prompt": "photorealistic, traditional, cluttered"
    },
    "Neo Vintage": {
        "prompt_prefix": "vintage style advertising poster, retro design",
        "text_style": "retro typography, vintage lettering",
        "guidance": 8.5,
        "steps": 50,
        "negative_prompt": "modern, photographic, contemporary"
    },
    # ... autres styles existants ...
}

# Paramètres photo optimisés
PHOTO_PARAMS = {
    "HDR": {
        "exposure_strength": 1.2,
        "contrast": 1.1,
        "saturation": 1.05
    },
    "Portrait": {
        "skin_softening": 0.8,
        "bokeh_strength": 0.7,
        "lighting": "studio"
    },
    "Nature": {
        "sharpness": 1.2,
        "vibrance": 1.1,
        "detail_enhancement": 1.15
    }
}

def enhance_photo_prompt(subject, style, photo_type="HDR"):
    """Améliore le prompt pour un rendu plus photoréaliste"""
    base_prompt = f"highly detailed photograph of {subject}, {ART_STYLES[style]['prompt_prefix']}"
    
    photo_enhancements = {
        "HDR": ", ultra high resolution photograph, perfect exposure, dramatic lighting, professional color grading",
        "Portrait": ", professional portrait photography, perfect skin texture, studio lighting setup, shallow depth of field",
        "Nature": ", sharp nature photography, perfect natural lighting, high detail macro shot, professional outdoor photography",
        "Urban": ", professional architectural photography, perfect perspective, golden hour lighting, urban landscape"
    }
    
    return base_prompt + photo_enhancements.get(photo_type, photo_enhancements["HDR"])

def generate_image(format_size, orientation, subject, style, text_effect, collection, title, subtitle, quality, creativity):
    API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
    headers = {"Authorization": f"Bearer {os.getenv('HUGGINGFACE_TOKEN')}"}
    
    try:
        width, height = (768, 1024) if format_size == "A4" else (1024, 1024)
        if orientation == "Paysage":
            width, height = height, width
            
        # Détection du style photo et optimisation du prompt
        is_photo_style = any(photo_style in style for photo_style in ["Photo", "Portrait", "Nature Pro", "Urban Photo"])
        
        if is_photo_style:
            prompt = enhance_photo_prompt(subject, style)
            guidance_scale = 8.0  # Optimisé pour le photoréalisme
            steps = 55
        else:
            prompt = f"{ART_STYLES[style]['prompt_prefix']}, {subject}"
            guidance_scale = ART_STYLES[style]['guidance']
            steps = ART_STYLES[style]['steps']
        
        if text_effect != "Standard":
            prompt += f", {TEXT_EFFECTS[text_effect]['prompt_suffix']}"
            
        if title:
            prompt += f", with text '{title}'"
            
        payload = {
            "inputs": prompt,
            "parameters": {
                "negative_prompt": ART_STYLES[style]['negative_prompt'],
                "num_inference_steps": min(int(steps * (quality/100)), 60),
                "guidance_scale": min(guidance_scale * (creativity/10), 10.0),
                "width": width,
                "height": height
            }
        }
        
        print(f"Prompt: {prompt}")  # Debug
        print(f"Paramètres: {payload}")  # Debug
        
        response = requests.post(API_URL, headers=headers, json=payload, timeout=30)
        
        if response.status_code == 200:
            image = Image.open(io.BytesIO(response.content))
            
            # Post-traitement pour styles photo
            if is_photo_style:
                image = enhance_photo(image, style)
                
            return image, "✨ Photo créée avec succès!"
        else:
            return None, f"⚠️ Erreur {response.status_code}: Essayez de modifier les paramètres"
            
    except Exception as e:
        print(f"Exception: {str(e)}")
        return None, f"⚠️ Erreur: {str(e)}"

def enhance_photo(image, style):
    """Améliore la photo selon le style"""
    try:
        enhancer = ImageEnhance.Contrast(image)
        image = enhancer.enhance(1.1)
        
        enhancer = ImageEnhance.Color(image)
        image = enhancer.enhance(1.05)
        
        enhancer = ImageEnhance.Sharpness(image)
        image = enhancer.enhance(1.15)
        
        return image
    except:
        return image
# Effets de texte stabilisés
TEXT_EFFECTS = {
    "Standard": {
        "prompt_suffix": "with clear readable text",
        "text_params": {"weight": 1.0}
    },
    "Graffiti": {
        "prompt_suffix": "with urban graffiti style text",
        "text_params": {"weight": 0.8}
    },
    "Néon": {
        "prompt_suffix": "with glowing neon text",
        "text_params": {"weight": 0.9}
    },
    "3D": {
        "prompt_suffix": "with 3D style text",
        "text_params": {"weight": 0.85}
    }
}

# Collections optimisées
THEME_COLLECTIONS = {
    "Tech": {
        "prompts": ["technology inspired", "digital aesthetic"],
        "styles": ["modern tech elements", "futuristic design"],
        "negative": "organic, rustic, natural"
    },
    "Nature": {
        "prompts": ["natural elements", "organic design"],
        "styles": ["flowing shapes", "natural textures"],
        "negative": "artificial, geometric"
    },
    "Urbain": {
        "prompts": ["urban style", "city aesthetic"],
        "styles": ["street art influence", "urban textures"],
        "negative": "rural, natural"
    }
}

def generate_image(format_size, orientation, subject, style, text_effect, collection, title, subtitle, quality, creativity):
    API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
    headers = {"Authorization": f"Bearer {os.getenv('HUGGINGFACE_TOKEN')}"}
    
    try:
        # Dimensions optimisées
        width, height = (768, 1024) if format_size == "A4" else (1024, 1024)
        if orientation == "Paysage":
            width, height = height, width
            
        # Construction du prompt optimisée
        style_config = ART_STYLES[style]
        text_config = TEXT_EFFECTS[text_effect]
        
        prompt = f"{style_config['prompt_prefix']}, {subject}"
        
        # Ajout des éléments de style et texte de manière plus stable
        if text_effect != "Standard":
            prompt += f", {text_config['prompt_suffix']}"
        
        if collection and collection in THEME_COLLECTIONS:
            coll = THEME_COLLECTIONS[collection]
            prompt += f", {', '.join(coll['prompts'][:1])}"  # Limite à un prompt pour stabilité
        
        if title:
            prompt += f", with text '{title}'"
            
        # Configuration optimisée
        payload = {
            "inputs": prompt,
            "parameters": {
                "negative_prompt": style_config['negative_prompt'],
                "num_inference_steps": min(style_config['steps'], 50),  # Limite pour stabilité
                "guidance_scale": min(style_config['guidance'] * (creativity/10), 10.0),  # Limite max
                "width": width,
                "height": height
            }
        }
        
        print(f"Prompt: {prompt}")  # Debug
        print(f"Paramètres: {payload}")  # Debug
        
        response = requests.post(API_URL, headers=headers, json=payload, timeout=30)
        
        if response.status_code == 200:
            image = Image.open(io.BytesIO(response.content))
            return image, "✨ Création réussie!"
        else:
            print(f"Erreur API: {response.text}")  # Debug
            return None, f"⚠️ Erreur {response.status_code}: Essayez de modifier les paramètres"
            
    except Exception as e:
        print(f"Exception: {str(e)}")  # Debug
        return None, f"⚠️ Erreur: {str(e)}"

# Effets de texte
TEXT_EFFECTS = {
    "Standard": {
        "prompt_suffix": "with clear readable text",
        "text_params": {"weight": 1.0}
    },
    "Néon": {
        "prompt_suffix": "with glowing neon text effect",
        "text_params": {"weight": 1.2}
    },
    "3D": {
        "prompt_suffix": "with 3D text effect, depth and shadows",
        "text_params": {"weight": 1.3}
    },
    "Métallique": {
        "prompt_suffix": "with metallic text effect, reflective surface",
        "text_params": {"weight": 1.1}
    },
    "Graffiti": {
        "prompt_suffix": "with graffiti style text, urban art typography",
        "text_params": {"weight": 1.2}
    }
}

# Collections thématiques
THEME_COLLECTIONS = {
    "Nature": {
        "prompts": ["natural elements", "organic composition"],
        "styles": ["flowing lines", "natural textures"],
        "negative": "artificial, synthetic"
    },
    "Urbain": {
        "prompts": ["urban landscape", "city elements"],
        "styles": ["street art", "architectural elements"],
        "negative": "rural, natural"
    },
    "Tech": {
        "prompts": ["technological elements", "digital aesthetic"],
        "styles": ["circuit patterns", "tech elements"],
        "negative": "organic, traditional"
    }
}

# CSS personnalisé
CUSTOM_CSS = """
.container { max-width: 1200px; margin: auto; }
.welcome { text-align: center; margin: 20px 0; padding: 20px; background: #1e293b; border-radius: 10px; }
.quality-controls { margin: 10px 0; padding: 10px; background: #2d3748; border-radius: 5px; }
.style-group { background: #2d3748; padding: 15px; border-radius: 5px; margin: 10px 0; }
.text-effects { background: #374151; padding: 12px; border-radius: 5px; margin: 8px 0; }
.preview-panel { position: relative; }
.parameters { display: flex; gap: 10px; }
"""

def enhance_prompt(subject, style, text_effect, collection=None, additional_details=""):
    """Génération de prompt optimisée"""
    style_config = ART_STYLES[style]
    text_config = TEXT_EFFECTS[text_effect]
    
    base_prompt = f"{style_config['prompt_prefix']}, {subject}"
    
    if text_effect != "Standard":
        base_prompt += f", {text_config['prompt_suffix']}"
    
    if collection and collection in THEME_COLLECTIONS:
        collection_data = THEME_COLLECTIONS[collection]
        collection_elements = collection_data["prompts"] + collection_data["styles"]
        base_prompt += f", {', '.join(collection_elements)}"
        
    if additional_details:
        base_prompt += f", {additional_details}"
    
    negative_prompt = style_config['negative_prompt']
    if collection:
        negative_prompt += f", {THEME_COLLECTIONS[collection]['negative']}"
    
    return base_prompt, negative_prompt

def generate_image(format_size, orientation, subject, style, text_effect, collection, 
                  title, subtitle, quality, creativity, additional_details=""):
    """Fonction de génération d'image"""
    API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
    headers = {"Authorization": f"Bearer {os.getenv('HUGGINGFACE_TOKEN')}"}
    
    try:
        base_width = 1024
        base_height = 1024
        if orientation == "Portrait":
            if format_size in ["A4", "A3"]:
                base_width = 768
                base_height = 1024
        else:
            if format_size in ["A4", "A3"]:
                base_width = 1024
                base_height = 768

        enhanced_prompt, negative_prompt = enhance_prompt(
            subject, style, text_effect, collection, additional_details
        )
        
        if title:
            enhanced_prompt += f", with text: '{title}'"
        if subtitle:
            enhanced_prompt += f", subtitle: '{subtitle}'"
            
        print(f"Prompt: {enhanced_prompt}")  # Debug
        
        payload = {
            "inputs": enhanced_prompt,
            "parameters": {
                "negative_prompt": negative_prompt,
                "num_inference_steps": int(ART_STYLES[style]['steps'] * (quality/100)),
                "guidance_scale": ART_STYLES[style]['guidance'] * (creativity/10),
                "width": base_width,
                "height": base_height
            }
        }
        
        response = requests.post(API_URL, headers=headers, json=payload, timeout=60)
        
        if response.status_code == 200:
            image = Image.open(io.BytesIO(response.content))
            return image, f"✨ Création {style} avec effet {text_effect} réussie!"
        else:
            print(f"Erreur API: {response.text}")
            return None, f"⚠️ Erreur {response.status_code}: Ajustez les paramètres"
            
    except Exception as e:
        print(f"Exception: {str(e)}")
        return None, f"⚠️ Erreur: {str(e)}"

def create_interface():
    with gr.Blocks(css=CUSTOM_CSS) as app:
        gr.HTML("""
            <div class="welcome">
                <h1>🤖 Equity Artisan 3.0</h1>
                <p>Créez des affiches artistiques professionnelles avec notre assistant créatif augmenté.</p>
            </div>
        """)
        
        with gr.Column(elem_classes="container"):
            # Format
            with gr.Group(elem_classes="style-group"):
                gr.Markdown("### 📏 Format et Orientation")
                with gr.Row():
                    format_choice = gr.Dropdown(
                        choices=["A4", "A3", "A2", "A1", "A0"],
                        value="A4",
                        label="Format"
                    )
                    orientation = gr.Radio(
                        choices=["Portrait", "Paysage"],
                        value="Portrait",
                        label="Orientation"
                    )

            # Style et Contenu
            with gr.Group(elem_classes="style-group"):
                gr.Markdown("### 🎨 Style et Création")
                with gr.Row():
                    with gr.Column(scale=1):
                        style = gr.Dropdown(
                            choices=list(ART_STYLES.keys()),
                            value="Neo Vintage",
                            label="Style artistique"
                        )
                        text_effect = gr.Dropdown(
                            choices=list(TEXT_EFFECTS.keys()),
                            value="Standard",
                            label="Effet de texte"
                        )
                        collection = gr.Dropdown(
                            choices=list(THEME_COLLECTIONS.keys()),
                            label="Collection (optionnel)"
                        )
                
                    with gr.Column(scale=2):
                        subject = gr.Textbox(
                            label="Sujet principal",
                            placeholder="Ex: loup, paysage urbain..."
                        )
                        additional_details = gr.Textbox(
                            lines=2,
                            label="Détails additionnels",
                            placeholder="Ajoutez des détails..."
                        )

            # Texte
            with gr.Group(elem_classes="text-effects"):
                gr.Markdown("### ✍️ Texte")
                with gr.Row():
                    title = gr.Textbox(
                        label="Titre principal",
                        placeholder="Texte principal..."
                    )
                    subtitle = gr.Textbox(
                        label="Sous-titre",
                        placeholder="Texte secondaire..."
                    )

            # Paramètres
            with gr.Group(elem_classes="quality-controls"):
                with gr.Row():
                    quality = gr.Slider(
                        minimum=30,
                        maximum=50,
                        value=35,
                        step=5,
                        label="Qualité"
                    )
                    creativity = gr.Slider(
                        minimum=5,
                        maximum=15,
                        value=7.5,
                        step=0.5,
                        label="Créativité"
                    )

            with gr.Row():
                generate_btn = gr.Button("✨ Générer", variant="primary")
                clear_btn = gr.Button("🗑️ Effacer", variant="secondary")

            image_output = gr.Image(label="Aperçu", type="pil")
            status = gr.Textbox(label="Statut", interactive=False)

        # Events
        generate_btn.click(
            generate_image,
            inputs=[
                format_choice,
                orientation,
                subject,
                style,
                text_effect,
                collection,
                title,
                subtitle,
                quality,
                creativity,
                additional_details
            ],
            outputs=[image_output, status]
        )
        
        clear_btn.click(
            lambda: (None, "Image effacée"),
            outputs=[image_output, status]
        )

    return app

if __name__ == "__main__":
    app = create_interface()
    app.launch()