app.py

import gradio as gr
import random
import json
import os
import re
from datetime import datetime
from openai import OpenAI
import subprocess
import torch
from PIL import Image
from transformers import AutoProcessor, AutoModelForCausalLM, pipeline

# Skip installation process if not needed
try:
    subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True)
except:
    print("Flash attention installation skipped")

# Initialize OpenAI client (API key from environment variable)
openai_api_key = os.getenv("OPENAI_API")
if openai_api_key:
    client = OpenAI(api_key=openai_api_key)
else:
    print("Warning: OPENAI_API key not found in environment variables")
    client = None

# Add translation model
translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")

# Initialize Florence model
device = "cuda" if torch.cuda.is_available() else "cpu"
florence_model = AutoModelForCausalLM.from_pretrained('microsoft/Florence-2-base', trust_remote_code=True).to(device).eval()
florence_processor = AutoProcessor.from_pretrained('microsoft/Florence-2-base', trust_remote_code=True)

# Korean prompt translation function
def translate_prompt(prompt):
    if any("\uAC00" <= char <= "\uD7A3" for char in prompt):  # If Korean is included
        translated = translator(prompt, max_length=512)[0]['translation_text']
        return translated
    return prompt

# Florence caption function
def florence_caption(image):
    if not isinstance(image, Image.Image):
        image = Image.fromarray(image)
    
    inputs = florence_processor(text="<MORE_DETAILED_CAPTION>", images=image, return_tensors="pt").to(device)
    generated_ids = florence_model.generate(
        input_ids=inputs["input_ids"],
        pixel_values=inputs["pixel_values"],
        max_new_tokens=1024,
        early_stopping=False,
        do_sample=False,
        num_beams=3,
    )
    generated_text = florence_processor.batch_decode(generated_ids, skip_special_tokens=False)[0]
    parsed_answer = florence_processor.post_process_generation(
        generated_text,
        task="<MORE_DETAILED_CAPTION>",
        image_size=(image.width, image.height)
    )
    return parsed_answer["<MORE_DETAILED_CAPTION>"]

# JSON file load function
def load_json_file(file_name):
    file_path = os.path.join("data", file_name)
    try:
        with open(file_path, "r") as file:
            return json.load(file)
    except:
        print(f"Warning: Could not load {file_name}. Using empty list.")
        return []

# Load JSON data
ARTFORM = load_json_file("artform.json")
PHOTO_TYPE = load_json_file("photo_type.json")
BODY_TYPES = load_json_file("body_types.json")
DEFAULT_TAGS = load_json_file("default_tags.json")
ROLES = load_json_file("roles.json")
HAIRSTYLES = load_json_file("hairstyles.json")
ADDITIONAL_DETAILS = load_json_file("additional_details.json")
PHOTOGRAPHY_STYLES = load_json_file("photography_styles.json")
DEVICE = load_json_file("device.json")
PHOTOGRAPHER = load_json_file("photographer.json")
ARTIST = load_json_file("artist.json")
DIGITAL_ARTFORM = load_json_file("digital_artform.json")
PLACE = load_json_file("place.json")
LIGHTING = load_json_file("lighting.json")
CLOTHING = load_json_file("clothing.json")
COMPOSITION = load_json_file("composition.json")
POSE = load_json_file("pose.json")
BACKGROUND = load_json_file("background.json")

# Prompt generation class
class PromptGenerator:
    def __init__(self, seed=None):
        self.rng = random.Random(seed)

    def split_and_choose(self, input_str):
        choices = [choice.strip() for choice in input_str.split(",")]
        return self.rng.choices(choices, k=1)[0]

    def get_choice(self, input_str, default_choices):
        if input_str.lower() == "disabled":
            return ""
        elif "," in input_str:
            return self.split_and_choose(input_str)
        elif input_str.lower() == "random":
            return self.rng.choices(default_choices, k=1)[0]
        else:
            return input_str

    def clean_consecutive_commas(self, input_string):
        cleaned_string = re.sub(r',\s*,', ',', input_string)
        return cleaned_string

    def process_string(self, replaced, seed):
        replaced = re.sub(r'\s*,\s*', ',', replaced)
        replaced = re.sub(r',+', ',', replaced)
        original = replaced
        
        first_break_clipl_index = replaced.find("BREAK_CLIPL")
        second_break_clipl_index = replaced.find("BREAK_CLIPL", first_break_clipl_index + len("BREAK_CLIPL"))
        
        if first_break_clipl_index != -1 and second_break_clipl_index != -1:
            clip_content_l = replaced[first_break_clipl_index + len("BREAK_CLIPL"):second_break_clipl_index]
            replaced = replaced[:first_break_clipl_index].strip(", ") + replaced[second_break_clipl_index + len("BREAK_CLIPL"):].strip(", ")
            clip_l = clip_content_l
        else:
            clip_l = ""
        
        first_break_clipg_index = replaced.find("BREAK_CLIPG")
        second_break_clipg_index = replaced.find("BREAK_CLIPG", first_break_clipg_index + len("BREAK_CLIPG"))
        
        if first_break_clipg_index != -1 and second_break_clipg_index != -1:
            clip_content_g = replaced[first_break_clipg_index + len("BREAK_CLIPG"):second_break_clipg_index]
            replaced = replaced[:first_break_clipg_index].strip(", ") + replaced[second_break_clipg_index + len("BREAK_CLIPG"):].strip(", ")
            clip_g = clip_content_g
        else:
            clip_g = ""
        
        t5xxl = replaced
        
        original = original.replace("BREAK_CLIPL", "").replace("BREAK_CLIPG", "")
        original = re.sub(r'\s*,\s*', ',', original)
        original = re.sub(r',+', ',', original)
        clip_l = re.sub(r'\s*,\s*', ',', clip_l)
        clip_l = re.sub(r',+', ',', clip_l)
        clip_g = re.sub(r'\s*,\s*', ',', clip_g)
        clip_g = re.sub(r',+', ',', clip_g)
        if clip_l.startswith(","):
            clip_l = clip_l[1:]
        if clip_g.startswith(","):
            clip_g = clip_g[1:]
        if original.startswith(","):
            original = original[1:]
        if t5xxl.startswith(","):
            t5xxl = t5xxl[1:]

        return original, seed, t5xxl, clip_l, clip_g

    def generate_prompt(self, seed, custom, subject, artform, photo_type, body_types, default_tags, roles, hairstyles,
                        additional_details, photography_styles, device, photographer, artist, digital_artform,
                        place, lighting, clothing, composition, pose, background, input_image):
        kwargs = locals()
        del kwargs['self']
        
        seed = kwargs.get("seed", 0)
        if seed is not None:
            self.rng = random.Random(seed)
        components = []
        custom = kwargs.get("custom", "")
        if custom:
            custom = translate_prompt(custom)  # Apply translation
            components.append(custom)
        is_photographer = kwargs.get("artform", "").lower() == "photography" or (
            kwargs.get("artform", "").lower() == "random"
            and self.rng.choice([True, False])
        )

        subject = kwargs.get("subject", "")

        if is_photographer:
            selected_photo_style = self.get_choice(kwargs.get("photography_styles", ""), PHOTOGRAPHY_STYLES)
            if not selected_photo_style:
                selected_photo_style = "photography"
            components.append(selected_photo_style)
            if kwargs.get("photography_style", "") != "disabled" and kwargs.get("default_tags", "") != "disabled" or subject != "":
                components.append(" of")
        
        default_tags = kwargs.get("default_tags", "random")
        body_type = kwargs.get("body_types", "")
        if not subject:
            if default_tags == "random":
                if body_type != "disabled" and body_type != "random":
                    selected_subject = self.get_choice(kwargs.get("default_tags", ""), DEFAULT_TAGS).replace("a ", "").replace("an ", "")
                    components.append("a ")
                    components.append(body_type)
                    components.append(selected_subject)
                elif body_type == "disabled":
                    selected_subject = self.get_choice(kwargs.get("default_tags", ""), DEFAULT_TAGS)
                    components.append(selected_subject)
                else:
                    body_type = self.get_choice(body_type, BODY_TYPES)
                    components.append("a ")
                    components.append(body_type)
                    selected_subject = self.get_choice(kwargs.get("default_tags", ""), DEFAULT_TAGS).replace("a ", "").replace("an ", "")
                    components.append(selected_subject)
            elif default_tags == "disabled":
                pass
            else:
                components.append(default_tags)
        else:
            if body_type != "disabled" and body_type != "random":
                components.append("a ")
                components.append(body_type)
            elif body_type == "disabled":
                pass
            else:
                body_type = self.get_choice(body_type, BODY_TYPES)
                components.append("a ")
                components.append(body_type)
            components.append(subject)

        params = [
            ("roles", ROLES),
            ("hairstyles", HAIRSTYLES),
            ("additional_details", ADDITIONAL_DETAILS),
        ]
        for param in params:
            components.append(self.get_choice(kwargs.get(param[0], ""), param[1]))
        for i in reversed(range(len(components))):
            if components[i] in PLACE:
                components[i] += ","
                break
        if kwargs.get("clothing", "") != "disabled" and kwargs.get("clothing", "") != "random":
            components.append(", dressed in ")
            clothing = kwargs.get("clothing", "")
            components.append(clothing)
        elif kwargs.get("clothing", "") == "random":
            components.append(", dressed in ")
            clothing = self.get_choice(kwargs.get("clothing", ""), CLOTHING)
            components.append(clothing)

        if kwargs.get("composition", "") != "disabled" and kwargs.get("composition", "") != "random":
            components.append(",")
            composition = kwargs.get("composition", "")
            components.append(composition)
        elif kwargs.get("composition", "") == "random": 
            components.append(",")
            composition = self.get_choice(kwargs.get("composition", ""), COMPOSITION)
            components.append(composition)
        
        if kwargs.get("pose", "") != "disabled" and kwargs.get("pose", "") != "random":
            components.append(",")
            pose = kwargs.get("pose", "")
            components.append(pose)
        elif kwargs.get("pose", "") == "random":
            components.append(",")
            pose = self.get_choice(kwargs.get("pose", ""), POSE)
            components.append(pose)
        components.append("BREAK_CLIPG")
        if kwargs.get("background", "") != "disabled" and kwargs.get("background", "") != "random":
            components.append(",")
            background = kwargs.get("background", "")
            components.append(background)
        elif kwargs.get("background", "") == "random": 
            components.append(",")
            background = self.get_choice(kwargs.get("background", ""), BACKGROUND)
            components.append(background)

        if kwargs.get("place", "") != "disabled" and kwargs.get("place", "") != "random":
            components.append(",")
            place = kwargs.get("place", "")
            components.append(place)
        elif kwargs.get("place", "") == "random": 
            components.append(",")
            place = self.get_choice(kwargs.get("place", ""), PLACE)
            components.append(place + ",")

        lighting = kwargs.get("lighting", "").lower()
        if lighting == "random":
            selected_lighting = ", ".join(self.rng.sample(LIGHTING, self.rng.randint(2, 5)))
            components.append(",")
            components.append(selected_lighting)
        elif lighting == "disabled":
            pass
        else:
            components.append(", ")
            components.append(lighting)
        components.append("BREAK_CLIPG")
        components.append("BREAK_CLIPL")
        if is_photographer:
            if kwargs.get("photo_type", "") != "disabled":
                photo_type_choice = self.get_choice(kwargs.get("photo_type", ""), PHOTO_TYPE)
                if photo_type_choice and photo_type_choice != "random" and photo_type_choice != "disabled":
                    random_value = round(self.rng.uniform(1.1, 1.5), 1)
                    components.append(f", ({photo_type_choice}:{random_value}), ")

            params = [
                ("device", DEVICE),
                ("photographer", PHOTOGRAPHER),
            ]
            components.extend([self.get_choice(kwargs.get(param[0], ""), param[1]) for param in params])
            if kwargs.get("device", "") != "disabled":
                components[-2] = f", shot on {components[-2]}"
            if kwargs.get("photographer", "") != "disabled":
                components[-1] = f", photo by {components[-1]}"
        else:
            digital_artform_choice = self.get_choice(kwargs.get("digital_artform", ""), DIGITAL_ARTFORM)
            if digital_artform_choice:
                components.append(f"{digital_artform_choice}")
            if kwargs.get("artist", "") != "disabled":
                components.append(f"by {self.get_choice(kwargs.get('artist', ''), ARTIST)}")
        components.append("BREAK_CLIPL")

        prompt = " ".join(components)
        prompt = re.sub(" +", " ", prompt)
        replaced = prompt.replace("of as", "of")
        replaced = self.clean_consecutive_commas(replaced)

        return self.process_string(replaced, seed)
    
    def add_caption_to_prompt(self, prompt, caption):
        if caption:
            return f"{prompt}, {caption}"
        return prompt

class OpenAIGenerationNode:
    def __init__(self):
        self.client = client
        self.prompts_dir = "./prompts"
        os.makedirs(self.prompts_dir, exist_ok=True)

    def save_prompt(self, prompt):
        filename_text = "openai_" + prompt.split(',')[0].strip()
        filename_text = re.sub(r'[^\w\-_\. ]', '_', filename_text)
        filename_text = filename_text[:30]  
        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
        base_filename = f"{filename_text}_{timestamp}.txt"
        filename = os.path.join(self.prompts_dir, base_filename)
        
        with open(filename, "w") as file:
            file.write(prompt)
        
        print(f"Prompt saved to {filename}")

    def generate(self, input_text, happy_talk, compress, compression_level, poster, custom_base_prompt=""):
        try:
            if not self.client:
                return "Error: OpenAI API key not found. Please set OPENAI_API environment variable."
                
            # Fixed model: gpt-4.1-mini
            openai_model = "gpt-4.1-mini"

            default_happy_prompt = """Create a detailed visually descriptive caption of this description, which will be used as a prompt for a text to image AI system (caption only, no instructions like "create an image").Remove any mention of digital artwork or artwork style. Give detailed visual descriptions of the character(s), including ethnicity, skin tone, expression etc. Imagine using keywords for a still for someone who has aphantasia. Describe the image style, e.g. any photographic or art styles / techniques utilized. Make sure to fully describe all aspects of the cinematography, with abundant technical details and visual descriptions. If there is more than one image, combine the elements and characters from all of the images creatively into a single cohesive composition with a single background, inventing an interaction between the characters. Be creative in combining the characters into a single cohesive scene. Focus on two primary characters (or one) and describe an interesting interaction between them, such as a hug, a kiss, a fight, giving an object, an emotional reaction / interaction. If there is more than one background in the images, pick the most appropriate one. Your output is only the caption itself, no comments or extra formatting. The caption is in a single long paragraph. If you feel the images are inappropriate, invent a new scene / characters inspired by these. Additionally, incorporate a specific movie director's visual style and describe the lighting setup in detail, including the type, color, and placement of light sources to create the desired mood and atmosphere. Always frame the scene, including details about the film grain, color grading, and any artifacts or characteristics specific."""

            default_simple_prompt = """Create a brief, straightforward caption for this description, suitable for a text-to-image AI system. Focus on the main elements, key characters, and overall scene without elaborate details. Provide a clear and concise description in one or two sentences."""

            poster_prompt = """Analyze the provided description and extract key information to create a movie poster style description. Format the output as follows:
Title: A catchy, intriguing title that captures the essence of the scene, place the title in "".
Main character: Give a description of the main character.
Background: Describe the background in detail.
Supporting characters: Describe the supporting characters
Branding type: Describe the branding type
Tagline: Include a tagline that captures the essence of the movie.
Visual style: Ensure that the visual style fits the branding type and tagline.
You are allowed to make up film and branding names, and do them like 80's, 90's or modern movie posters."""

            if poster:
                base_prompt = poster_prompt
            elif custom_base_prompt.strip():
                base_prompt = custom_base_prompt
            else:
                base_prompt = default_happy_prompt if happy_talk else default_simple_prompt

            if compress and not poster:
                compression_chars = {
                    "soft": 600 if happy_talk else 300,
                    "medium": 400 if happy_talk else 200,
                    "hard": 200 if happy_talk else 100
                }
                char_limit = compression_chars[compression_level]
                base_prompt += f" Compress the output to be concise while retaining key visual details. MAX OUTPUT SIZE no more than {char_limit} characters."

            # Correct OpenAI API call format
            response = self.client.chat.completions.create(
                model=openai_model,
                messages=[
                    {
                        "role": "system",
                        "content": "You are a helpful assistant. Try your best to give best response possible to user."
                    },
                    {
                        "role": "user",
                        "content": f"{base_prompt}\nDescription: {input_text}"
                    }
                ],
                temperature=1,
                max_tokens=2048,
                top_p=1
            )
            
            # Extract response
            output = response.choices[0].message.content
            
            # Clean output
            if ": " in output:
                output = output.split(": ", 1)[1].strip()
            elif output.lower().startswith("here"):
                sentences = output.split(". ")
                if len(sentences) > 1:
                    output = ". ".join(sentences[1:]).strip()
            
            # Save prompt
            self.save_prompt(output)
            
            return output

        except Exception as e:
            print(f"An error occurred: {e}")
            return f"Error occurred while processing the request: {str(e)}"

# Enhanced CSS
css = """
footer {
    visibility: hidden;
}
.main-title {
    text-align: center;
    margin: 20px 0;
}
.main-title h1 {
    color: #2c3e50;
    font-size: 2.5em;
}
.badge-container {
    display: flex;
    justify-content: center;
    gap: 15px;
    margin: 20px auto;
    max-width: 100%;
}
.prompt-generator-container {
    background: #f8f9fa;
    border-radius: 10px;
    padding: 20px;
    margin: 10px 0;
}
.settings-container {
    background: #ffffff;
    border-radius: 8px;
    padding: 15px;
    margin: 10px 0;
    box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
.output-container {
    background: #e8f4f8;
    border-radius: 8px;
    padding: 15px;
    margin: 10px 0;
}
.generate-button {
    background: #3498db !important;
    color: white !important;
    font-size: 1.1em !important;
    padding: 12px 24px !important;
    margin: 10px 0 !important;
}
.openai-button {
    background: #27ae60 !important;
    color: white !important;
    font-size: 1.1em !important;
    padding: 12px 24px !important;
}
.section-header {
    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
    color: white;
    padding: 10px 15px;
    border-radius: 8px;
    margin-bottom: 15px;
    font-weight: bold;
}
"""

def create_interface():
    prompt_generator = PromptGenerator()
    openai_node = OpenAIGenerationNode()
    
    with gr.Blocks(theme="soft", css=css) as demo:
        # Header
        with gr.Row(elem_classes="main-title"):
            gr.HTML("""
                <h1>🎨 Flux Prompt Generator</h1>
                <p style="text-align: center; color: #7f8c8d; font-size: 1.1em;">
                    Korean Input Support | AI-Based Prompt Generator
                </p>
            """)
        
        # Badges
        with gr.Row(elem_classes="badge-container"):
            gr.HTML("""
                <a href="https://huggingface.co/spaces/openfree/Best-AI" target="_blank">
                    <img src="https://img.shields.io/static/v1?label=OpenFree&message=BEST%20AI%20Services&color=%230000ff&labelColor=%23000080&logo=huggingface&logoColor=%23ffa500&style=for-the-badge" alt="OpenFree badge">
                </a>
                <a href="https://discord.gg/openfreeai" target="_blank">
                    <img src="https://img.shields.io/static/v1?label=Discord&message=Openfree%20AI&color=%230000ff&labelColor=%23800080&logo=discord&logoColor=white&style=for-the-badge" alt="Discord badge">
                </a>
            """)
        
        # Main container
        with gr.Row():
            # Left panel - Settings
            with gr.Column(scale=2):
                gr.HTML('<div class="section-header">🎯 Basic Settings</div>')
                seed = gr.Slider(0, 30000, label='Seed Value', step=1, value=random.randint(0,30000))
                custom = gr.Textbox(label="✏️ Custom Prompt (Korean Available)", placeholder="Enter your description...")
                subject = gr.Textbox(label="🎭 Subject (Optional)", placeholder="e.g., beautiful woman, cute cat, etc...")
                
                # Global option settings
                gr.HTML('<div class="section-header">⚡ Quick Settings</div>')
                global_option = gr.Radio(
                    ["Disabled", "Random", "No Figure Rand"],
                    label="Apply All Options at Once:",
                    value="Disabled",
                    info="Change all settings at once"
                )
                
                # Detailed settings
                with gr.Accordion("🎨 Artform & Photo Type", open=False):
                    artform = gr.Dropdown(["disabled", "random"] + ARTFORM, label="Artform", value="disabled")
                    photo_type = gr.Dropdown(["disabled", "random"] + PHOTO_TYPE, label="Photo Type", value="disabled")
            
                with gr.Accordion("👤 Character Settings", open=False):
                    body_types = gr.Dropdown(["disabled", "random"] + BODY_TYPES, label="Body Type", value="disabled")
                    default_tags = gr.Dropdown(["disabled", "random"] + DEFAULT_TAGS, label="Default Tags", value="disabled")
                    roles = gr.Dropdown(["disabled", "random"] + ROLES, label="Role", value="disabled")
                    hairstyles = gr.Dropdown(["disabled", "random"] + HAIRSTYLES, label="Hairstyle", value="disabled")
                    clothing = gr.Dropdown(["disabled", "random"] + CLOTHING, label="Clothing", value="disabled")
            
                with gr.Accordion("🏞️ Scene Settings", open=False):
                    place = gr.Dropdown(["disabled", "random"] + PLACE, label="Place", value="disabled")
                    lighting = gr.Dropdown(["disabled", "random"] + LIGHTING, label="Lighting", value="disabled")
                    composition = gr.Dropdown(["disabled", "random"] + COMPOSITION, label="Composition", value="disabled")
                    pose = gr.Dropdown(["disabled", "random"] + POSE, label="Pose", value="disabled")
                    background = gr.Dropdown(["disabled", "random"] + BACKGROUND, label="Background", value="disabled")
            
                with gr.Accordion("🎭 Style & Artist", open=False):
                    additional_details = gr.Dropdown(["disabled", "random"] + ADDITIONAL_DETAILS, label="Additional Details", value="disabled")
                    photography_styles = gr.Dropdown(["disabled", "random"] + PHOTOGRAPHY_STYLES, label="Photography Style", value="disabled")
                    device = gr.Dropdown(["disabled", "random"] + DEVICE, label="Camera/Device", value="disabled")
                    photographer = gr.Dropdown(["disabled", "random"] + PHOTOGRAPHER, label="Photographer", value="disabled")
                    artist = gr.Dropdown(["disabled", "random"] + ARTIST, label="Artist", value="disabled")
                    digital_artform = gr.Dropdown(["disabled", "random"] + DIGITAL_ARTFORM, label="Digital Artform", value="disabled")
                
                generate_button = gr.Button("🚀 Generate Prompt", variant="primary", elem_classes="generate-button")

            # Middle panel - Image and output
            with gr.Column(scale=2):
                with gr.Accordion("🖼️ Image Caption Generation", open=False):
                    input_image = gr.Image(label="Upload Image (Optional)", type="pil")
                    caption_output = gr.Textbox(label="Generated Caption", lines=3)
                    with gr.Row():
                        create_caption_button = gr.Button("📝 Generate Caption", variant="secondary")
                        add_caption_button = gr.Button("➕ Add to Prompt", variant="secondary")

                gr.HTML('<div class="section-header">📋 Generated Prompts</div>')
                output = gr.Textbox(label="Main Prompt", lines=4)
                with gr.Accordion("Advanced Output Options", open=False):
                    t5xxl_output = gr.Textbox(label="T5XXL", lines=2)
                    clip_l_output = gr.Textbox(label="CLIP L", lines=2)
                    clip_g_output = gr.Textbox(label="CLIP G", lines=2)
            
            # Right panel - OpenAI
            with gr.Column(scale=2):
                gr.HTML('<div class="section-header">🤖 OpenAI Prompt Enhancement</div>')
                gr.HTML("<p style='text-align: center; color: #95a5a6;'>Model Used: gpt-4.1-mini</p>")
                
                with gr.Row():
                    happy_talk = gr.Checkbox(label="😊 Happy Talk", value=True, info="More detailed description")
                    compress = gr.Checkbox(label="🗜️ Compress", value=True, info="Limit output length")
                
                compression_level = gr.Radio(
                    ["soft", "medium", "hard"], 
                    label="Compression Strength", 
                    value="hard",
                    visible=True
                )
                
                poster = gr.Checkbox(label="🎬 Movie Poster Style", value=False)
                
                custom_base_prompt = gr.Textbox(
                    label="🛠️ Custom Base Prompt", 
                    lines=5,
                    placeholder="Enter special instructions for OpenAI..."
                )
                
                generate_text_button = gr.Button("✨ Enhance with AI", variant="primary", elem_classes="openai-button")
                
                text_output = gr.Textbox(
                    label="🎯 AI Enhanced Result", 
                    lines=10,
                    elem_classes="output-container"
                )

        # Event handlers
        def create_caption(image):
            if image is not None:
                return florence_caption(image)
            return ""

        create_caption_button.click(
            create_caption,
            inputs=[input_image],
            outputs=[caption_output]
        )

        generate_button.click(
            prompt_generator.generate_prompt,
            inputs=[seed, custom, subject, artform, photo_type, body_types, default_tags, roles, hairstyles,
                    additional_details, photography_styles, device, photographer, artist, digital_artform,
                    place, lighting, clothing, composition, pose, background, input_image],
            outputs=[output, gr.Number(visible=False), t5xxl_output, clip_l_output, clip_g_output]
        )

        add_caption_button.click(
            prompt_generator.add_caption_to_prompt,
            inputs=[output, caption_output],
            outputs=[output]
        )

        generate_text_button.click(
            lambda input_text, happy_talk, compress, compression_level, poster, custom_base_prompt: 
                openai_node.generate(input_text, happy_talk, compress, compression_level, poster, custom_base_prompt),
            inputs=[output, happy_talk, compress, compression_level, poster, custom_base_prompt],
            outputs=text_output
        )

        # Show/hide compression strength based on compress checkbox
        compress.change(
            lambda x: gr.update(visible=x),
            inputs=[compress],
            outputs=[compression_level]
        )

        # Global option change function
        def update_all_options(choice):
            updates = []
            dropdown_list = [
                artform, photo_type, body_types, default_tags, roles, hairstyles, clothing,
                place, lighting, composition, pose, background, additional_details,
                photography_styles, device, photographer, artist, digital_artform
            ]
            
            if choice == "Disabled":
                updates = [gr.update(value="disabled") for _ in dropdown_list]
            elif choice == "Random":
                updates = [gr.update(value="random") for _ in dropdown_list]
            else:  # No Figure Random
                updates = []
                # Character-related settings are disabled
                character_dropdowns = [photo_type, body_types, default_tags, roles, hairstyles, clothing, pose, additional_details]
                other_dropdowns = [artform, place, lighting, composition, background, photography_styles, device, photographer, artist, digital_artform]
                
                for dropdown in dropdown_list:
                    if dropdown in character_dropdowns:
                        updates.append(gr.update(value="disabled"))
                    else:
                        updates.append(gr.update(value="random"))
            
            return updates
        
        global_option.change(
            update_all_options,
            inputs=[global_option],
            outputs=[
                artform, photo_type, body_types, default_tags, roles, hairstyles, clothing,
                place, lighting, composition, pose, background, additional_details,
                photography_styles, device, photographer, artist, digital_artform
            ]
        )

    return demo

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