import gradio as gr
from transformers import pipeline
import torch
import random

# Pipeline optimizado para CPU
generator = pipeline(
    "text-generation",
    model="gpt2",
    max_new_tokens=100,
    device=-1,  # CPU
    torch_dtype=torch.float32
)

# Plantilla base y listas
base_template = """
A hyper-realistic full-body portrait of {subject}, embodying the essence of {theme}. Rendered in {style} style with anatomical accuracy and lifelike skin texture.

The subject wears {outfit}, showing realistic fabric weave and soft transparency. Posing {pose}, {expression}. Gaze directed {gaze}. Set in {environment}, with {mood}. Cinematic lighting, HDR tone mapping, subsurface scattering, and fine material rendering.

**TECHNICAL SPECS:**
- Camera: {camera}
- Lens: {lens}
- Settings: {aperture}, {iso}, {shutter}
- Rendering: Unreal Engine 5.4, path tracing, PBR materials, micro-displacement
- Post-processing: Film color grading, subtle grain, HDR finish

**KEYWORDS:** ultra-detailed, photorealistic, cinematic, accurate anatomy, depth of field, realistic reflections, 8K resolution --ar 9:16 --style raw
"""

subjects = [
    "a sensual fitness instructor with honey-blonde wavy hair",
    "a young woman with freckles and emerald eyes",
    "an elegant secretary in a white silk blouse",
    "a confident dancer in sheer black outfit",
    "a seductive nurse with soft brown curls"
]

themes = ["serene confidence", "alluring mystery", "quiet elegance", "sensual focus", "feminine power"]
styles = ["cinematic realism", "hyperrealistic photography", "studio portrait lighting"]
outfits = [
    "semi-transparent white lycra sportswear revealing a black lace thong",
    "delicate lace corset and silk robe",
    "tight pencil skirt and satin blouse",
    "black sheer bodysuit with lace trim",
    "minimal athletic top and form-fitting shorts"
]
poses = [
    "stretching arms overhead, body slightly arched",
    "leaning on a desk gracefully",
    "sitting with crossed legs and soft posture",
    "standing confidently with hands on hips",
    "gently turning, one hand adjusting hair"
]
expressions = [
    "a calm, inviting smile",
    "a confident and alluring stare",
    "a subtle, dreamy look",
    "a playful smirk",
    "a serene, introspective expression"
]
gazes = ["towards camera", "slightly to the side", "downwards softly", "upwards in thought"]
environments = [
    "a modern gym with mirrored walls",
    "a sunlit luxury bedroom",
    "a high-end studio with soft backlight",
    "a minimalist white room with reflections",
    "a cinematic loft with ambient glow"
]
moods = ["peaceful and sensual", "intimate and cinematic", "warm and inviting", "bold and elegant"]
cameras = ["Canon EOS R5", "Sony α7R V", "Nikon Z9", "Fujifilm GFX 100S"]
lenses = ["RF 85mm f/1.2L", "FE 50mm f/1.4 GM", "Nikkor Z 70-200mm f/2.8"]
apertures = ["f/1.4", "f/1.8", "f/2.2"]
isos = ["ISO 100", "ISO 400", "ISO 800"]
shutters = ["1/200s", "1/250s", "1/320s"]

def generate_prompts_list(count, user_input=""):
    count = max(1, min(int(count), 10))
    prompts = []
    subject = user_input.strip() if user_input else random.choice(subjects)
    
    for i in range(count):
        filled = base_template.format(
            subject=subject,
            theme=random.choice(themes),
            style=random.choice(styles),
            outfit=random.choice(outfits),
            pose=random.choice(poses),
            expression=random.choice(expressions),
            gaze=random.choice(gazes),
            environment=random.choice(environments),
            mood=random.choice(moods),
            camera=random.choice(cameras),
            lens=random.choice(lenses),
            aperture=random.choice(apertures),
            iso=random.choice(isos),
            shutter=random.choice(shutters)
        )
        try:
            with torch.no_grad():
                ai_output = generator(
                    f"Refine this prompt in natural English tone:\n{filled}",
                    do_sample=True,
                    temperature=0.7
                )[0]["generated_text"]
        except Exception as e:
            ai_output = f"Error: {str(e)}\nOriginal: {filled}"
        prompts.append(ai_output.strip())
    return prompts

def create_prompt_blocks(count, user_input):
    prompts = generate_prompts_list(count, user_input)
    
    with gr.Blocks() as blocks_ui:
        for i, prompt in enumerate(prompts, 1):
            with gr.Group():
                gr.Markdown(f"### Prompt #{i}")
                with gr.Row():
                    textbox = gr.Textbox(
                        value=prompt,
                        lines=8,
                        max_lines=12,
                        show_copy_button=True,
                        container=False,
                        show_label=False
                    )
                gr.Markdown("---")
    
    return blocks_ui

# Tema personalizado con colores oscuros y azules
custom_css = """
.dark-box textarea {
    background-color: #1a1a1a !important;
    color: #4fc3f7 !important;
    border: 1px solid #1565c0 !important;
    font-family: monospace;
}

.dark-box {
    background: #2d3748 !important;
    padding: 1.5rem;
    border-radius: 10px;
    border: 1px solid #4a5568;
    margin-bottom: 1rem;
}

.dark-box h3 {
    color: #90caf9 !important;
    margin-top: 0 !important;
}

.copy-btn {
    background: #1976d2 !important;
    color: white !important;
    border: none !important;
}

.copy-btn:hover {
    background: #1565c0 !important;
}
"""

with gr.Blocks(
    title="BATUTO - Generador de Prompts Hiperrealistas", 
    theme=gr.themes.Soft(),
    css=custom_css
) as demo:
    gr.Markdown("""
    # 🎨 BATUTO - Generador de Prompts Hiperrealistas
    Genera prompts detallados para crear imágenes hiperrealistas con IA
    """)
    
    with gr.Row():
        with gr.Column(scale=3):
            input_text = gr.Textbox(
                label="Describe tu idea o personaje",
                placeholder="Ejemplo: 'una mujer joven con cabello rojo en un estudio fotográfico'",
                lines=2
            )
        with gr.Column(scale=1):
            count_spinner = gr.Slider(
                minimum=1, 
                maximum=10, 
                step=1, 
                value=3, 
                label="Número de prompts a generar"
            )
    
    generar_btn = gr.Button("✨ Generar Prompts", variant="primary", size="lg")
    
    gr.Markdown("## 📝 Prompts Generados")
    blocks_output = gr.HTML()
    
    @generar_btn.click(inputs=[count_spinner, input_text], outputs=blocks_output)
    def update_blocks(count, user_input):
        prompts = generate_prompts_list(count, user_input)
        
        html_blocks = ""
        for i, prompt in enumerate(prompts, 1):
            html_blocks += f"""
            <div class="dark-box">
                <h3>Prompt #{i}</h3>
                <div style="position: relative;">
                    <textarea 
                        id="prompt-{i}" 
                        style="width: 100%; height: 200px; padding: 1rem; border-radius: 8px; font-family: monospace; resize: vertical; background: #1a1a1a; color: #4fc3f7; border: 1px solid #1565c0;"
                        readonly
                    >{prompt}</textarea>
                    <button 
                        onclick="copyPrompt({i})" 
                        class="copy-btn"
                        style="position: absolute; top: 0.5rem; right: 0.5rem; padding: 0.5rem 1rem; background: #1976d2; color: white; border: none; border-radius: 6px; cursor: pointer;"
                    >
                        📋 Copiar
                    </button>
                </div>
            </div>
            """
        
        # Añadir el script JavaScript para copiar
        html_blocks += """
        <script>
        function copyPrompt(id) {
            const textarea = document.getElementById('prompt-' + id);
            textarea.select();
            textarea.setSelectionRange(0, 99999);
            document.execCommand('copy');
            
            // Feedback visual
            const button = event.target;
            const originalText = button.textContent;
            button.textContent = '✅ Copiado!';
            button.style.background = '#388e3c';
            
            setTimeout(() => {
                button.textContent = originalText;
                button.style.background = '#1976d2';
            }, 2000);
        }
        </script>
        """
        
        return html_blocks

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