app.py

# storyverse_weaver/app.py
import gradio as gr
import os
import time
import json 
from PIL import Image, ImageDraw, ImageFont 
import random
import traceback 

# --- Core Logic Imports ---
from core.llm_services import initialize_text_llms, is_gemini_text_ready, is_hf_text_ready, generate_text_gemini, generate_text_hf
from core.image_services import initialize_image_llms, is_dalle_ready, is_hf_image_api_ready, generate_image_dalle, generate_image_hf_model, ImageGenResponse 
from core.story_engine import Story, Scene # CRITICAL: Ensure this is your updated Story class
from prompts.narrative_prompts import get_narrative_system_prompt, format_narrative_user_prompt
from prompts.image_style_prompts import STYLE_PRESETS, COMMON_NEGATIVE_PROMPTS, format_image_generation_prompt
from core.utils import basic_text_cleanup

# --- Initialize Services ---
initialize_text_llms()
initialize_image_llms() 

# --- Get API Readiness Status ---
GEMINI_TEXT_IS_READY = is_gemini_text_ready()
HF_TEXT_IS_READY = is_hf_text_ready()
DALLE_IMAGE_IS_READY = is_dalle_ready() 
HF_IMAGE_IS_READY = is_hf_image_api_ready()

# --- Application Configuration (Models, Defaults) ---
# (This section remains the same - ensure TEXT_MODELS, UI_DEFAULT_TEXT_MODEL_KEY, etc. are defined)
TEXT_MODELS = {}
UI_DEFAULT_TEXT_MODEL_KEY = None
if GEMINI_TEXT_IS_READY:
    TEXT_MODELS["✨ Gemini 1.5 Flash (Narrate)"] = {"id": "gemini-1.5-flash-latest", "type": "gemini"}
if HF_TEXT_IS_READY:
    TEXT_MODELS["Mistral 7B (Narrate via HF)"] = {"id": "mistralai/Mistral-7B-Instruct-v0.2", "type": "hf_text"}
if TEXT_MODELS: 
    UI_DEFAULT_TEXT_MODEL_KEY = list(TEXT_MODELS.keys())[0]
    if GEMINI_TEXT_IS_READY and "✨ Gemini 1.5 Flash (Narrate)" in TEXT_MODELS: UI_DEFAULT_TEXT_MODEL_KEY = "✨ Gemini 1.5 Flash (Narrate)"
    elif HF_TEXT_IS_READY and "Mistral 7B (Narrate via HF)" in TEXT_MODELS: UI_DEFAULT_TEXT_MODEL_KEY = "Mistral 7B (Narrate via HF)"
else:
    TEXT_MODELS["No Text Models Configured"] = {"id": "dummy_text_error", "type": "none"}
    UI_DEFAULT_TEXT_MODEL_KEY = "No Text Models Configured"

IMAGE_PROVIDERS = {} 
UI_DEFAULT_IMAGE_PROVIDER_KEY = None
if DALLE_IMAGE_IS_READY: 
    IMAGE_PROVIDERS["🖼️ OpenAI DALL-E 3"] = "dalle_3" 
    UI_DEFAULT_IMAGE_PROVIDER_KEY = "🖼️ OpenAI DALL-E 3"
elif HF_IMAGE_IS_READY: 
    IMAGE_PROVIDERS["🎡 HF - SDXL Base"] = "hf_sdxl_base" 
    UI_DEFAULT_IMAGE_PROVIDER_KEY = "🎡 HF - SDXL Base"
if not IMAGE_PROVIDERS: 
    IMAGE_PROVIDERS["No Image Providers Configured"] = "none"
    UI_DEFAULT_IMAGE_PROVIDER_KEY = "No Image Providers Configured"


# --- Gradio UI Theme and CSS ---
# (omega_theme and omega_css definitions remain THE SAME as the last full app.py version)
omega_theme = gr.themes.Base(font=[gr.themes.GoogleFont("Lexend Deca")], primary_hue=gr.themes.colors.purple).set(body_background_fill="#0F0F1A", block_background_fill="#1A1A2E", slider_color="#A020F0")
omega_css = """ /* ... Paste your full omega_css string here ... 
body, .gradio-container .gr-button span { white-space: nowrap !important; overflow: hidden; text-overflow: ellipsis; display: inline-block; max-width: 90%; }
.gradio-container .gr-button { display: flex; align-items: center; justify-content: center; }
.gradio-container .gr-button svg { margin-right: 4px !important; }
*/ """


# --- Helper: Placeholder Image Creation ---
def create_placeholder_image(text="Processing...", size=(512, 512), color="#23233A", text_color="#E0E0FF"):
    img = Image.new('RGB', size, color=color); draw = ImageDraw.Draw(img)
    try: font_path = "arial.ttf" if os.path.exists("arial.ttf") else None 
    except: font_path = None 
    try: font = ImageFont.truetype(font_path, 40) if font_path else ImageFont.load_default()
    except IOError: font = ImageFont.load_default()
    if hasattr(draw, 'textbbox'): bbox = draw.textbbox((0,0), text, font=font); tw, th = bbox[2]-bbox[0], bbox[3]-bbox[1]
    else: tw, th = draw.textsize(text, font=font) 
    draw.text(((size[0]-tw)/2, (size[1]-th)/2), text, font=font, fill=text_color); return img

# --- StoryVerse Weaver Orchestrator ---
def add_scene_to_story_orchestrator(
    current_story_obj: Story, scene_prompt_text: str, image_style_dropdown: str, artist_style_text: str,
    negative_prompt_text: str, text_model_key: str, image_provider_key: str,
    narrative_length: str, image_quality: str,
    progress=gr.Progress(track_tqdm=True)
):
    start_time = time.time() 
    if not current_story_obj: current_story_obj = Story() # Ensure story object exists
    
    log_accumulator = [f"**🚀 Scene {current_story_obj.current_scene_number + 1} - {time.strftime('%H:%M:%S')}**"]
    
    # --- Initialize values for the final return tuple ---
    # These correspond to the `outputs` list of `engage_button.click()`
    # Order: story_state_output, output_gallery, output_latest_scene_image, 
    #        output_latest_scene_narrative, output_status_bar, output_interaction_log_markdown
    
    # Get initial gallery state based on current story object
    # This ensures that if we error out early, the gallery doesn't just disappear if it had items
    current_gallery_items = current_story_obj.get_all_scenes_for_gallery_display()
    if not current_gallery_items: # Handle initially empty story for gallery
        placeholder_gallery_img = create_placeholder_image("Start Weaving!", size=(180,180), color="#1A1A2E")
        current_gallery_items = [(placeholder_gallery_img, "Your StoryVerse awaits!")]

    # These will be updated and form the basis of the final 'return'
    ret_story_state = current_story_obj 
    ret_gallery = current_gallery_items 
    ret_latest_image = None
    ret_latest_narrative_md_obj = gr.Markdown(value="## Processing...\nNarrative being woven...")
    ret_status_bar_html_obj = gr.HTML(value="<p class='processing_text status_text'>Processing...</p>")
    # ret_log_md is built up

    # Initial UI update via yield (buttons disabled by .then() chain)
    yield {
        output_status_bar: gr.HTML(value=f"<p class='processing_text status_text'>🌌 Weaving Scene {current_story_obj.current_scene_number + 1}...</p>"),
        output_latest_scene_image: gr.Image(value=create_placeholder_image("🎨 Conjuring visuals...")),
        output_latest_scene_narrative: gr.Markdown(value=" Musing narrative..."),
        output_interaction_log_markdown: gr.Markdown(value="\n".join(log_accumulator))
    }

    try:
        if not scene_prompt_text.strip():
            raise ValueError("Scene prompt cannot be empty!")

        # --- 1. Generate Narrative Text ---
        progress(0.1, desc="✍️ Crafting narrative...")
        narrative_text_generated = f"Narrative Error: Init failed." # Default
        # ... (Full narrative generation logic from your previous working app.py)
        # ... (This part should call generate_text_gemini or generate_text_hf and update narrative_text_generated)
        text_model_info = TEXT_MODELS.get(text_model_key)
        if text_model_info and text_model_info["type"] != "none":
            system_p = get_narrative_system_prompt("default"); prev_narrative = current_story_obj.get_last_scene_narrative(); user_p = format_narrative_user_prompt(scene_prompt_text, prev_narrative)
            log_accumulator.append(f"  Narrative: Using {text_model_key} ({text_model_info['id']}).")
            text_response = None
            if text_model_info["type"] == "gemini": text_response = generate_text_gemini(user_p, model_id=text_model_info["id"], system_prompt=system_p, max_tokens=768 if narrative_length.startswith("Detailed") else 400)
            elif text_model_info["type"] == "hf_text": text_response = generate_text_hf(user_p, model_id=text_model_info["id"], system_prompt=system_p, max_tokens=768 if narrative_length.startswith("Detailed") else 400)
            if text_response and text_response.success: narrative_text_generated = basic_text_cleanup(text_response.text); log_accumulator.append(f"  Narrative: Success.")
            elif text_response: narrative_text_generated = f"**Narrative Error ({text_model_key}):** {text_response.error}"; log_accumulator.append(f"  Narrative: FAILED - {text_response.error}")
            else: log_accumulator.append(f"  Narrative: FAILED - No response from {text_model_key}.")
        else: narrative_text_generated = "**Narrative Error:** Text model unavailable."; log_accumulator.append(f"  Narrative: FAILED - Model '{text_model_key}' unavailable.")

        ret_latest_narrative_str_content = f"## Scene Idea: {scene_prompt_text}\n\n{narrative_text_generated}"
        ret_latest_narrative_md_obj = gr.Markdown(value=ret_latest_narrative_str_content) # Prepare for final return
        yield { output_latest_scene_narrative: ret_latest_narrative_md_obj,
                output_interaction_log_markdown: gr.Markdown(value="\n".join(log_accumulator)) }

        # --- 2. Generate Image ---
        progress(0.5, desc="🎨 Conjuring visuals...")
        image_generated_pil = None
        image_generation_error_message = None
        # ... (Full image generation logic from your previous working app.py) ...
        # ... (This part should call generate_image_dalle or generate_image_hf_model and update image_generated_pil)
        selected_image_provider_key_from_ui = image_provider_key
        selected_image_provider_type = IMAGE_PROVIDERS.get(selected_image_provider_key_from_ui)
        image_content_prompt_for_gen = narrative_text_generated if narrative_text_generated and "Error" not in narrative_text_generated else scene_prompt_text
        quality_keyword = "ultra detailed, " if image_quality == "High Detail" else ("concept sketch, " if image_quality == "Sketch Concept" else "")
        full_image_prompt = format_image_generation_prompt(quality_keyword + image_content_prompt_for_gen[:350], image_style_dropdown, artist_style_text)
        log_accumulator.append(f"  Image: Attempting with provider key '{selected_image_provider_key_from_ui}' (maps to type '{selected_image_provider_type}').")
        if selected_image_provider_type and selected_image_provider_type != "none": # Actual call logic
            image_response = None # ... (call DALL-E or HF based on selected_image_provider_type)
            if selected_image_provider_type.startswith("dalle_"):
                if DALLE_IMAGE_IS_READY: image_response = generate_image_dalle(full_image_prompt, model="dall-e-3" if selected_image_provider_type == "dalle_3" else "dall-e-2")
                else: image_generation_error_message = "**Image Error:** DALL-E selected but not ready."
            elif selected_image_provider_type.startswith("hf_"):
                if HF_IMAGE_IS_READY: 
                    hf_model_id = "stabilityai/stable-diffusion-xl-base-1.0" # Default
                    if selected_image_provider_type == "hf_openjourney": hf_model_id = "prompthero/openjourney"
                    elif selected_image_provider_type == "hf_sd_1_5": hf_model_id = "runwayml/stable-diffusion-v1-5"
                    image_response = generate_image_hf_model(full_image_prompt, model_id=hf_model_id, negative_prompt=negative_prompt_text or COMMON_NEGATIVE_PROMPTS)
                else: image_generation_error_message = "**Image Error:** HF Image selected but not ready."
            # ... (process image_response)
            if image_response and image_response.success: image_generated_pil = image_response.image; log_accumulator.append("  Image: Success.")
            elif image_response: image_generation_error_message = f"**Image Error:** {image_response.error}"; log_accumulator.append(f"  Image: FAILED - {image_response.error}")
            elif not image_generation_error_message: image_generation_error_message = "**Image Error:** No response/unknown issue."
        else: image_generation_error_message = "**Image Error:** No valid image provider."

        ret_latest_image = image_generated_pil if image_generated_pil else create_placeholder_image("Image Gen Failed", color="#401010")
        yield { output_latest_scene_image: gr.Image(value=ret_latest_image),
                output_interaction_log_markdown: gr.Markdown(value="\n".join(log_accumulator)) }

        # --- 3. Add Scene to Story Object ---
        final_scene_error = None
        if image_generation_error_message and "**Narrative Error**" in narrative_text_generated : final_scene_error = f"Narrative: {narrative_text_generated.split('**')[-1].strip()} \nImage: {image_generation_error_message.split('**')[-1].strip()}"
        elif "**Narrative Error**" in narrative_text_generated: final_scene_error = narrative_text_generated
        elif image_generation_error_message: final_scene_error = image_generation_error_message
        
        current_story_obj.add_scene_from_elements(
            user_prompt=scene_prompt_text,
            narrative_text=narrative_text_generated if "**Narrative Error**" not in narrative_text_generated else "(Narrative generation failed, see error log)",
            image=image_generated_pil,
            image_style_prompt=f"{image_style_dropdown}{f', by {artist_style_text}' if artist_style_text and artist_style_text.strip() else ''}",
            image_provider=selected_image_provider_key_from_ui,
            error_message=final_scene_error
        )
        ret_story_state = current_story_obj 
        log_accumulator.append(f"  Scene {current_story_obj.current_scene_number} processed and added to story object.")
        
        # --- 4. Prepare Final Values for Return Tuple ---
        gallery_tuples_final = current_story_obj.get_all_scenes_for_gallery_display()
        processed_gallery_tuples = []
        if not gallery_tuples_final: # Ensure gallery is not empty for Gradio if story just started
            placeholder_gallery_img = create_placeholder_image("Your Story Begins!", size=(180,180), color="#1A1A2E")
            processed_gallery_tuples = [(placeholder_gallery_img, "First scene pending or just added!")]
        else:
            for img_item, cap_text in gallery_tuples_final:
                if img_item is None:
                    gallery_placeholder = create_placeholder_image(f"S{cap_text.split(':')[0][1:]}\nError/NoImg", size=(180,180), color="#2A2A4A")
                    processed_gallery_tuples.append((gallery_placeholder, cap_text))
                else:
                    processed_gallery_tuples.append((img_item, cap_text))
        ret_gallery = processed_gallery_tuples


        _ , latest_narr_for_display_final_str_temp = current_story_obj.get_latest_scene_details_for_display()
        ret_latest_narrative_md_obj = gr.Markdown(value=latest_narr_for_display_final_str_temp)
        
        status_html_str_temp = f"<p class='error_text status_text'>Scene {current_story_obj.current_scene_number} added with errors.</p>" if final_scene_error else f"<p class='success_text status_text'>🌌 Scene {current_story_obj.current_scene_number} woven!</p>"
        ret_status_bar_html_obj = gr.HTML(value=status_html_str_temp)
        
        progress(1.0, desc="Scene Complete!")

    except ValueError as ve:
        log_accumulator.append(f"\n**INPUT/CONFIG ERROR:** {ve}")
        ret_status_bar_html_obj = gr.HTML(value=f"<p class='error_text status_text'>❌ CONFIGURATION ERROR: {ve}</p>")
        ret_latest_narrative_md_obj = gr.Markdown(value=f"## Error\n{ve}")
    except Exception as e:
        log_accumulator.append(f"\n**UNEXPECTED RUNTIME ERROR:** {type(e).__name__} - {e}\n{traceback.format_exc()}")
        ret_status_bar_html_obj = gr.HTML(value=f"<p class='error_text status_text'>❌ UNEXPECTED ERROR: {type(e).__name__}. Check logs.</p>")
        ret_latest_narrative_md_obj = gr.Markdown(value=f"## Unexpected Error\n{type(e).__name__}: {e}\nSee log for details.")
    
    current_total_time = time.time() - start_time
    log_accumulator.append(f"  Cycle ended at {time.strftime('%H:%M:%S')}. Total time: {current_total_time:.2f}s")
    ret_log_md = gr.Markdown(value="\n".join(log_accumulator)) # Prepare final log content
    
    # Final return for the .click() handler's `outputs` list
    return (
        ret_story_state,
        ret_gallery, # This is now processed_gallery_tuples
        ret_latest_image, # This is the PIL image or placeholder
        ret_latest_narrative_md_obj, # This is a gr.Markdown object
        ret_status_bar_html_obj,     # This is a gr.HTML object
        ret_log_md                   # This is a gr.Markdown object
    )

def clear_story_state_ui_wrapper():
    print("DEBUG: clear_story_state_ui_wrapper called")
    new_story = Story()
    placeholder_img = create_placeholder_image("Your StoryVerse is a blank canvas...", color="#1A1A2E", text_color="#A0A0C0")
    cleared_gallery = [(placeholder_img, "Your StoryVerse is new and untold...")]
    initial_narrative = "## ✨ A New Story Begins ✨\nDescribe your first scene idea..."
    status_msg = "<p class='processing_text status_text'>📜 Story Cleared.</p>"
    return (new_story, cleared_gallery, None, gr.Markdown(initial_narrative), gr.HTML(status_msg), "Log Cleared.", "")

def surprise_me_func():
    print("DEBUG: surprise_me_func called")
    themes = ["Cosmic Horror", "Solarpunk Utopia", "Mythic Fantasy", "Noir Detective"]; actions = ["unearths an artifact", "negotiates"]; settings = ["on a rogue planet", "in a city in a tree"]; prompt = f"A protagonist {random.choice(actions)} {random.choice(settings)}. Theme: {random.choice(themes)}."; style = random.choice(list(STYLE_PRESETS.keys())); artist = random.choice(["H.R. Giger", "Moebius", ""]*2)
    print(f"DEBUG: surprise_me_func returning: Prompt='{prompt}', Style='{style}', Artist='{artist}'")
    return prompt, style, artist

def disable_buttons_for_processing():
    print("DEBUG: Disabling buttons")
    return gr.Button(interactive=False), gr.Button(interactive=False)

def enable_buttons_after_processing():
    print("DEBUG: Enabling buttons")
    return gr.Button(interactive=True), gr.Button(interactive=True)

# --- Gradio UI Definition ---
with gr.Blocks(theme=omega_theme, css=omega_css, title="✨ StoryVerse Omega ✨") as story_weaver_demo:
    # Define Python variables for UI components
    story_state_output = gr.State(Story()) 
    
    gr.Markdown("<div align='center'><h1>✨ StoryVerse Omega ✨</h1>\n<h3>Craft Immersive Multimodal Worlds with AI</h3></div>")
    gr.HTML("<div class='important-note'><strong>Welcome, Worldsmith!</strong> Describe your vision, choose your style, and let Omega help you weave captivating scenes with narrative and imagery. Ensure API keys (<code>STORYVERSE_...</code>) are correctly set in Space Secrets!</div>")

    with gr.Accordion("🔧 AI Services Status & Info", open=False):
        status_text_list = []; text_llm_ok = (GEMINI_TEXT_IS_READY or HF_TEXT_IS_READY); image_gen_ok = (DALLE_IMAGE_IS_READY or HF_IMAGE_IS_READY)
        if not text_llm_ok and not image_gen_ok: status_text_list.append("<p style='color:#FCA5A5;font-weight:bold;'>⚠️ CRITICAL: NO AI SERVICES CONFIGURED.</p>")
        else:
            if text_llm_ok: status_text_list.append("<p style='color:#A7F3D0;'>✅ Text Generation Ready.</p>")
            else: status_text_list.append("<p style='color:#FCD34D;'>⚠️ Text Generation NOT Ready.</p>")
            if image_gen_ok: status_text_list.append("<p style='color:#A7F3D0;'>✅ Image Generation Ready.</p>")
            else: status_text_list.append("<p style='color:#FCD34D;'>⚠️ Image Generation NOT Ready.</p>")
        gr.HTML("".join(status_text_list))

    with gr.Row(equal_height=False, variant="panel"):
        with gr.Column(scale=7, min_width=450): 
            gr.Markdown("### 💡 **Craft Your Scene**", elem_classes="input-section-header")
            with gr.Group(): scene_prompt_input = gr.Textbox(lines=7, label="Scene Vision (Description, Dialogue, Action):", placeholder="e.g., Amidst swirling cosmic dust...")
            with gr.Row(elem_classes=["compact-row"]):
                with gr.Column(scale=2): image_style_input = gr.Dropdown(choices=["Default (Cinematic Realism)"] + sorted(list(STYLE_PRESETS.keys())), value="Default (Cinematic Realism)", label="Visual Style", allow_custom_value=True)
                with gr.Column(scale=2): artist_style_input = gr.Textbox(label="Artistic Inspiration (Optional):", placeholder="e.g., Moebius...")
            negative_prompt_input = gr.Textbox(lines=2, label="Exclude from Image:", value=COMMON_NEGATIVE_PROMPTS)
            with gr.Accordion("⚙️ Advanced AI Configuration", open=False):
                 with gr.Group():
                    text_model_dropdown = gr.Dropdown(choices=list(TEXT_MODELS.keys()), value=UI_DEFAULT_TEXT_MODEL_KEY, label="Narrative AI Engine")
                    image_provider_dropdown = gr.Dropdown(choices=list(IMAGE_PROVIDERS.keys()), value=UI_DEFAULT_IMAGE_PROVIDER_KEY, label="Visual AI Engine")
                    with gr.Row():
                        narrative_length_dropdown = gr.Dropdown(["Short (1 paragraph)", "Medium (2-3 paragraphs)", "Detailed (4+ paragraphs)"], value="Medium (2-3 paragraphs)", label="Narrative Detail")
                        image_quality_dropdown = gr.Dropdown(["Standard", "High Detail", "Sketch Concept"], value="Standard", label="Image Detail/Style")
            with gr.Row(elem_classes=["compact-row"], equal_height=True):
                engage_button = gr.Button("🌌 Weave!", variant="primary", scale=3, icon="✨") # Shorter text
                surprise_button = gr.Button("🎲 Surprise!", variant="secondary", scale=1, icon="🎁")
                clear_story_button = gr.Button("🗑️ New", variant="stop", scale=1, icon="♻️") # Shorter text
            output_status_bar = gr.HTML(value="<p class='processing_text status_text'>Ready to weave your first masterpiece!</p>")
        
        with gr.Column(scale=10, min_width=700): 
            gr.Markdown("### 🖼️ **Your StoryVerse**", elem_classes="output-section-header")
            with gr.Tabs():
                with gr.TabItem("🌠 Latest Scene"): 
                    output_latest_scene_image = gr.Image(label="Latest Image", type="pil", interactive=False, height=512, show_label=False, show_download_button=True, elem_classes=["panel_image"])
                    output_latest_scene_narrative = gr.Markdown() 
                with gr.TabItem("📚 Story Scroll"): 
                    output_gallery = gr.Gallery(label="Story Scroll", show_label=False, columns=4, object_fit="cover", height=700, preview=True, allow_preview=True, elem_classes=["gallery_output"])
                with gr.TabItem("⚙️ Log"): 
                    with gr.Accordion("Interaction Log", open=False): 
                        output_interaction_log_markdown = gr.Markdown("Log...")

    # Event Handlers
    engage_button.click(fn=disable_buttons_for_processing, outputs=[engage_button, surprise_button], queue=False)\
        .then(fn=add_scene_to_story_orchestrator, 
              inputs=[story_state_output, scene_prompt_input, image_style_input, artist_style_input, negative_prompt_input, text_model_dropdown, image_provider_dropdown, narrative_length_dropdown, image_quality_dropdown], 
              outputs=[story_state_output, output_gallery, output_latest_scene_image, output_latest_scene_narrative, output_status_bar, output_interaction_log_markdown])\
        .then(fn=enable_buttons_after_processing, outputs=[engage_button, surprise_button], queue=False)
    
    clear_story_button.click(fn=clear_story_state_ui_wrapper, 
                             outputs=[story_state_output, output_gallery, output_latest_scene_image, output_latest_scene_narrative, output_status_bar, output_interaction_log_markdown, scene_prompt_input])
    
    surprise_button.click(fn=surprise_me_func, 
                            outputs=[scene_prompt_input, image_style_input, artist_style_input])
    
    gr.Examples(
        examples=[
            ["A lone, weary traveler on a mechanical steed crosses a vast, crimson desert under twin suns. Dust devils dance in the distance.", "Sci-Fi Western", "Moebius", "greenery, water, modern city"],
            ["Deep within an ancient, bioluminescent forest, a hidden civilization of sentient fungi perform a mystical ritual around a pulsating crystal.", "Psychedelic Fantasy", "Alex Grey", "technology, buildings, roads"],
            ["A child sits on a crescent moon, fishing for stars in a swirling nebula. A friendly space whale swims nearby.", "Whimsical Cosmic", "James Jean", "realistic, dark, scary"],
            ["A grand, baroque library where the books fly freely and whisper forgotten lore to those who listen closely.", "Magical Realism", "Remedios Varo", "minimalist, simple, technology"]
        ],
        inputs=[scene_prompt_input, image_style_input, artist_style_input, negative_prompt_input], 
        label="🌌 Example Universes to Weave 🌌",
    )
    gr.HTML("<div style='text-align:center; margin-top:30px; padding-bottom:20px;'><p style='font-size:0.9em; color:#8080A0;'>✨ StoryVerse Omega™ - Weaving Worlds with Words and Pixels ✨</p></div>")

# --- Entry Point ---
if __name__ == "__main__":
    print("="*80); print("✨ StoryVerse Omega (Full App with Fixes) Launching... ✨")
    print(f"  Gemini Text Ready: {GEMINI_TEXT_IS_READY}"); print(f"  HF Text Ready: {HF_TEXT_IS_READY}")
    print(f"  DALL-E Image Ready: {DALLE_IMAGE_IS_READY}"); print(f"  HF Image API Ready: {HF_IMAGE_IS_READY}")
    if not (GEMINI_TEXT_IS_READY or HF_TEXT_IS_READY) or not (DALLE_IMAGE_IS_READY or HF_IMAGE_IS_READY): 
        print("  🔴 WARNING: Not all primary/fallback AI services configured.")
    print(f"  Default Text Model: {UI_DEFAULT_TEXT_MODEL_KEY}"); print(f"  Default Image Provider: {UI_DEFAULT_IMAGE_PROVIDER_KEY}")
    print("="*80)
    story_weaver_demo.launch(debug=True, server_name="0.0.0.0", share=False)