| import gradio as gr |
| import torch |
| import spaces |
| from diffusers import StableDiffusionXLPipeline, DPMSolverMultistepScheduler |
| from huggingface_hub import hf_hub_download, InferenceClient |
| import random |
| import os |
| import re |
|
|
| |
| HF_TOKEN = os.environ.get("HF_TOKEN", None) |
| MODEL_REPO = "John6666/nova-3dcg-xl-illustrious-v40-sdxl" |
|
|
| |
| IL_POS = "masterpiece, best quality, very aesthetic, absurdres, " |
| IL_NEG = "worst quality, low quality, bad quality, ugly, " |
|
|
| |
| llm_client = InferenceClient( |
| model="mistralai/Mistral-7B-Instruct-v0.3", |
| token=HF_TOKEN, |
| ) |
|
|
| EXPANSION_SYSTEM = """You are an expert Stable Diffusion prompt engineer specialising in 3DCG character art and illustration. |
| |
| Your job: take a short user description and rewrite it as a detailed, accurate image generation prompt optimised for a 3D CGI character art model (Nova 3DCG XL). |
| |
| Rules: |
| - PRESERVE every specific detail — colours, numbers, states, accessories, clothing |
| - Wrap unique specific details in attention weights e.g. (red scarf:1.4), (one eye closed:1.3) |
| - Add: character pose, expression, lighting, background atmosphere, material quality, render style |
| - Add 3DCG-appropriate quality boosters: sharp edges, subsurface scattering, ray tracing, ambient occlusion |
| - Do NOT add NSFW content |
| - Do NOT invent things not implied by the user |
| - Return ONLY the final prompt — no explanation, no preamble, no quotes |
| - Keep under 130 words |
| - Use comma-separated tags and phrases""" |
|
|
| def expand_prompt_llm(raw_prompt, style): |
| if not raw_prompt.strip(): |
| return "" |
| style_hint = f" The desired style is: {style}." if style != "Auto" else "" |
| user_msg = f"Expand this into a detailed 3DCG character art prompt:{style_hint}\n\n{raw_prompt.strip()}" |
| try: |
| response = llm_client.chat_completion( |
| messages=[ |
| {"role": "system", "content": EXPANSION_SYSTEM}, |
| {"role": "user", "content": user_msg}, |
| ], |
| max_tokens=220, |
| temperature=0.7, |
| ) |
| expanded = response.choices[0].message.content.strip() |
| expanded = expanded.strip('"').strip("'") |
| if expanded.lower().startswith("prompt:"): |
| expanded = expanded[7:].strip() |
| return expanded |
| except Exception as e: |
| print(f"LLM expansion failed: {e}") |
| return raw_prompt.strip() |
|
|
| |
| print(f"Loading Nova 3DCG XL from {MODEL_REPO}...") |
|
|
| pipe = StableDiffusionXLPipeline.from_pretrained( |
| MODEL_REPO, |
| torch_dtype=torch.float16, |
| token=HF_TOKEN, |
| ) |
| pipe.scheduler = DPMSolverMultistepScheduler.from_config( |
| pipe.scheduler.config, |
| use_karras_sigmas=True, |
| ) |
| pipe.enable_attention_slicing() |
| print("Pipeline ready.") |
|
|
| |
| STYLES = { |
| "Auto": {"pos": "", "neg": ""}, |
| "🎮 3DCG Render": { |
| "pos": "3DCG render, Pixar style, ray tracing, subsurface scattering, ambient occlusion, sharp edges, studio lighting, ", |
| "neg": "flat, 2D, anime flat colour, sketch, ", |
| }, |
| "⚔️ Fantasy": { |
| "pos": "fantasy character, epic armour, magical atmosphere, dramatic lighting, volumetric fog, concept art, artstation, ", |
| "neg": "modern, mundane, sci-fi, ", |
| }, |
| "🤖 Sci-Fi": { |
| "pos": "sci-fi character, futuristic suit, neon accents, holographic elements, dark background, cinematic, ", |
| "neg": "medieval, fantasy, nature, ", |
| }, |
| "🌸 Stylised": { |
| "pos": "stylised illustration, vibrant colours, soft cel shading, clean lineart, anime-adjacent, ", |
| "neg": "photorealistic, gritty, dark, ", |
| }, |
| "🎬 Cinematic": { |
| "pos": "cinematic portrait, dramatic rim lighting, shallow depth of field, film grain, color graded, ", |
| "neg": "flat, overexposed, sketch, ", |
| }, |
| "🏙️ Urban": { |
| "pos": "urban streetwear character, city background, neon lights, night scene, realistic clothing, ", |
| "neg": "fantasy, medieval, nature, ", |
| }, |
| } |
|
|
| |
| LORAS = { |
| "None": None, |
| "✋ Better Hands": { |
| "repo": "WolfAether21/PONY-DIFFUSION-SDXL-LORA", |
| "file": "Perfect Hands v2.safetensors", |
| "strength": 0.7, |
| }, |
| "🔍 More Detail": { |
| "repo": "WolfAether21/PONY-DIFFUSION-SDXL-LORA", |
| "file": "SDXL Detail.safetensors", |
| "strength": 0.6, |
| }, |
| } |
|
|
| |
| @spaces.GPU(duration=180) |
| def generate(raw_prompt, negative_prompt, style, lora_name, lora_strength, |
| width, height, steps, guidance, seed, randomize, show_expanded): |
|
|
| if not raw_prompt.strip(): |
| raise gr.Error("Please enter a prompt.") |
|
|
| if randomize: |
| seed = random.randint(0, 2**32 - 1) |
| seed = int(seed) |
|
|
| |
| expanded = expand_prompt_llm(raw_prompt, style) |
| style_data = STYLES.get(style, STYLES["Auto"]) |
| final_pos = IL_POS + style_data["pos"] + expanded |
| final_neg = IL_NEG + style_data["neg"] + negative_prompt.strip() |
|
|
| pipe.to("cuda") |
|
|
| |
| lora_loaded = False |
| lora_data = LORAS.get(lora_name) |
| if lora_data: |
| try: |
| lp = hf_hub_download( |
| repo_id=lora_data["repo"], |
| filename=lora_data["file"], |
| token=HF_TOKEN, |
| ) |
| pipe.load_lora_weights(lp) |
| pipe.fuse_lora(lora_scale=float(lora_strength)) |
| lora_loaded = True |
| except Exception as e: |
| print(f"LoRA failed, skipping: {e}") |
|
|
| generator = torch.Generator(device="cpu").manual_seed(seed) |
|
|
| result = pipe( |
| prompt=final_pos, |
| negative_prompt=final_neg, |
| width=int(width), |
| height=int(height), |
| num_inference_steps=int(steps), |
| guidance_scale=float(guidance), |
| generator=generator, |
| clip_skip=1, |
| ) |
|
|
| if lora_loaded: |
| pipe.unfuse_lora() |
| pipe.unload_lora_weights() |
|
|
| pipe.to("cpu") |
|
|
| debug = f"**Expanded prompt:**\n\n{final_pos}" if show_expanded else "" |
| return result.images[0], seed, debug |
|
|
| |
| css = """ |
| * { box-sizing: border-box; margin: 0; padding: 0; } |
| |
| body, .gradio-container { |
| background: #07070e !important; |
| font-family: 'Inter', system-ui, -apple-system, sans-serif !important; |
| max-width: 500px !important; |
| margin: 0 auto !important; |
| padding: 8px !important; |
| } |
| |
| .topbar { |
| display: flex; |
| align-items: center; |
| justify-content: space-between; |
| padding: 10px 2px 14px; |
| } |
| .topbar-title { |
| color: #e8e0ff; |
| font-size: 0.95em; |
| font-weight: 800; |
| } |
| .gpu-pill { |
| background: #1aff7a18; |
| border: 1px solid #1aff7a44; |
| color: #1aff7a; |
| font-size: 0.6em; |
| font-weight: 800; |
| padding: 4px 12px; |
| border-radius: 20px; |
| letter-spacing: 1.5px; |
| text-transform: uppercase; |
| } |
| |
| .img-out { |
| background: #0d0d1a; |
| border: 1px solid #16162a; |
| border-radius: 20px; |
| overflow: hidden; |
| margin-bottom: 8px; |
| min-height: 380px; |
| display: flex; |
| align-items: center; |
| justify-content: center; |
| } |
| .img-out img { |
| width: 100% !important; |
| border-radius: 20px; |
| display: block; |
| } |
| |
| .seed-pill input[type=number] { |
| background: transparent !important; |
| border: none !important; |
| color: #2e2848 !important; |
| font-size: 0.7em !important; |
| text-align: center !important; |
| padding: 2px !important; |
| width: 100% !important; |
| } |
| |
| .card { |
| background: #0d0d1a; |
| border: 1px solid #16162a; |
| border-radius: 14px; |
| padding: 14px; |
| margin-bottom: 8px; |
| } |
| .card-label { |
| color: #3d3060; |
| font-size: 0.62em; |
| font-weight: 800; |
| text-transform: uppercase; |
| letter-spacing: 2px; |
| margin-bottom: 8px; |
| } |
| |
| textarea { |
| background: transparent !important; |
| border: none !important; |
| color: #c8b8f0 !important; |
| font-size: 15px !important; |
| line-height: 1.6 !important; |
| padding: 0 !important; |
| resize: none !important; |
| box-shadow: none !important; |
| width: 100% !important; |
| outline: none !important; |
| } |
| textarea::placeholder { color: #252038 !important; } |
| textarea:focus { |
| outline: none !important; |
| box-shadow: none !important; |
| border: none !important; |
| } |
| |
| .style-wrap .gr-radio { |
| display: flex !important; |
| flex-wrap: wrap !important; |
| gap: 6px !important; |
| } |
| .style-wrap label { |
| background: #0d0d1a !important; |
| border: 1px solid #1a1a2e !important; |
| border-radius: 30px !important; |
| color: #4a3a6a !important; |
| font-size: 0.75em !important; |
| font-weight: 600 !important; |
| padding: 6px 14px !important; |
| cursor: pointer !important; |
| transition: all 0.15s ease !important; |
| white-space: nowrap !important; |
| } |
| .style-wrap label:has(input:checked) { |
| background: #18083a !important; |
| border-color: #7744ee !important; |
| color: #bb99ff !important; |
| box-shadow: 0 0 10px #7744ee33 !important; |
| } |
| .style-wrap input[type=radio] { display: none !important; } |
| |
| .gradio-accordion { |
| background: #0d0d1a !important; |
| border: 1px solid #16162a !important; |
| border-radius: 14px !important; |
| margin-bottom: 8px !important; |
| overflow: hidden !important; |
| } |
| .gradio-accordion .label-wrap button { |
| color: #4a3a6a !important; |
| font-size: 0.72em !important; |
| font-weight: 700 !important; |
| text-transform: uppercase !important; |
| letter-spacing: 1.5px !important; |
| padding: 12px 16px !important; |
| } |
| |
| .gradio-slider { |
| background: transparent !important; |
| border: none !important; |
| padding: 4px 0 10px !important; |
| } |
| input[type=range] { |
| accent-color: #6633bb !important; |
| width: 100% !important; |
| } |
| |
| input[type=number] { |
| background: #0a0a14 !important; |
| border: 1px solid #18182a !important; |
| border-radius: 10px !important; |
| color: #9977cc !important; |
| font-size: 13px !important; |
| padding: 8px 10px !important; |
| } |
| |
| input[type=checkbox] { accent-color: #6633bb !important; } |
| .gradio-checkbox label span { |
| color: #4a3a6a !important; |
| font-size: 0.75em !important; |
| font-weight: 600 !important; |
| } |
| |
| .gradio-dropdown { |
| background: #0a0a14 !important; |
| border: 1px solid #18182a !important; |
| border-radius: 10px !important; |
| } |
| |
| label > span:first-child { |
| color: #3a2d55 !important; |
| font-size: 0.7em !important; |
| font-weight: 700 !important; |
| text-transform: uppercase !important; |
| letter-spacing: 1px !important; |
| } |
| |
| .debug-box { |
| background: #080814; |
| border: 1px solid #111122; |
| border-radius: 10px; |
| padding: 10px 12px; |
| color: #443366; |
| font-size: 0.7em; |
| line-height: 1.7; |
| font-family: monospace; |
| word-break: break-word; |
| margin-bottom: 8px; |
| min-height: 10px; |
| } |
| |
| .gen-btn button { |
| background: linear-gradient(135deg, #4a1aaa 0%, #2d0e77 100%) !important; |
| border: 1px solid #6633cc !important; |
| border-radius: 14px !important; |
| color: #fff !important; |
| font-size: 0.88em !important; |
| font-weight: 900 !important; |
| padding: 17px !important; |
| width: 100% !important; |
| letter-spacing: 2px !important; |
| text-transform: uppercase !important; |
| box-shadow: 0 4px 24px #4a1aaa55 !important; |
| transition: all 0.15s ease !important; |
| margin-top: 6px !important; |
| } |
| .gen-btn button:hover { |
| box-shadow: 0 6px 32px #4a1aaa99 !important; |
| transform: translateY(-1px) !important; |
| } |
| .gen-btn button:active { |
| transform: scale(0.98) !important; |
| box-shadow: 0 2px 12px #4a1aaa33 !important; |
| } |
| |
| footer, .built-with { display: none !important; } |
| """ |
|
|
| |
| with gr.Blocks(css=css, title="ImageGen") as demo: |
|
|
| gr.HTML(""" |
| <div class="topbar"> |
| <span class="topbar-title">Nova 3DCG XL</span> |
| <span class="gpu-pill">⚡ ZeroGPU</span> |
| </div> |
| """) |
|
|
| output_image = gr.Image( |
| show_label=False, type="pil", |
| height=460, elem_classes="img-out", |
| ) |
| used_seed = gr.Number( |
| label="seed", interactive=False, |
| elem_classes="seed-pill", |
| ) |
|
|
| gr.HTML('<div class="card"><div class="card-label">✦ Prompt — describe your character</div>') |
| prompt = gr.Textbox( |
| show_label=False, |
| placeholder="warrior woman in red armour, glowing sword, forest background...", |
| lines=3, |
| ) |
| gr.HTML('</div>') |
|
|
| gr.HTML('<div class="card-label" style="padding:4px 2px 8px;color:#3d3060;font-size:0.62em;font-weight:800;text-transform:uppercase;letter-spacing:2px;">Style</div>') |
| style = gr.Radio( |
| choices=list(STYLES.keys()), |
| value="Auto", |
| show_label=False, |
| elem_classes="style-wrap", |
| ) |
|
|
| generate_btn = gr.Button( |
| "Generate ✦", variant="primary", |
| size="lg", elem_classes="gen-btn", |
| ) |
|
|
| expanded_out = gr.Markdown( |
| value="", |
| elem_classes="debug-box", |
| ) |
|
|
| with gr.Accordion("⚙️ Settings", open=False): |
| gr.HTML('<div style="height:6px"></div>') |
|
|
| negative_prompt = gr.Textbox( |
| label="Negative Prompt", |
| value=( |
| "worst quality, low quality, bad anatomy, bad hands, " |
| "extra limbs, missing limbs, watermark, signature, " |
| "blurry, deformed, ugly, text" |
| ), |
| lines=2, |
| ) |
|
|
| with gr.Row(): |
| width = gr.Slider(512, 1024, value=832, step=64, label="Width") |
| height = gr.Slider(512, 1216, value=1216, step=64, label="Height") |
|
|
| steps = gr.Slider(20, 60, value=30, step=1, label="Steps") |
| guidance = gr.Slider(1.0, 10.0, value=6.0, step=0.5, label="CFG Scale") |
|
|
| with gr.Row(): |
| seed = gr.Number( |
| label="Seed", value=42, precision=0, |
| minimum=0, maximum=2**32-1, scale=3, |
| ) |
| randomize = gr.Checkbox(label="Random seed", value=True, scale=1) |
|
|
| show_expanded = gr.Checkbox( |
| label="Show expanded prompt", |
| value=True, |
| ) |
|
|
| with gr.Accordion("🎨 LoRA", open=False): |
| gr.HTML('<div style="height:6px"></div>') |
| lora_name = gr.Dropdown(choices=list(LORAS.keys()), value="None", label="LoRA") |
| lora_strength = gr.Slider(0.1, 1.0, value=0.7, step=0.05, label="Strength") |
|
|
| generate_btn.click( |
| fn=generate, |
| inputs=[ |
| prompt, negative_prompt, style, lora_name, lora_strength, |
| width, height, steps, guidance, seed, randomize, show_expanded, |
| ], |
| outputs=[output_image, used_seed, expanded_out], |
| ) |
|
|
| demo.launch() |
|
|
