| import gradio as gr |
| import random |
| import os |
| import threading |
| import gc |
| from llama_cpp import Llama |
|
|
| |
| |
| |
| model_versions = { |
| "WizzGPTv3": "model/WizzGPTv3-q8_0.gguf", |
| "WizzGPTv6": "model/WizzGPTv6-q8_0.gguf", |
| "WizzGPTv7": "model/WizzGPTv7-q8_0.gguf", |
| "WizzGPTv8": "model/WizzGPTv8-q8_0.gguf" |
| } |
|
|
| model_descriptions = { |
| "WizzGPTv3": "Tuned for SDXL. More tag-oriented, more prompt-like, more structured.", |
| "WizzGPTv6": "Tuned for Flux-style prompting. More natural language, more fluid visual phrasing.", |
| "WizzGPTv7": "Tuned for Flux.1 / Krea. More natural, weird, exploratory and surprising continuations.", |
| "WizzGPTv8": "Cinnadust Edition." |
| } |
|
|
| llm = None |
| current_model = "WizzGPTv8" |
| model_lock = threading.Lock() |
|
|
| |
| |
| |
| prompt_list = [ |
| "A beautiful sunset over", |
| "A macro shot of", |
| "Award winning photography of", |
| "Wide shot of", |
| "The intricate details of", |
| "The portrait of a", |
| "A resin figurine of", |
| "Painting of", |
| "A delicate", |
| "A rustic", |
| "A stunningly beautiful", |
| "Masterpiece, best quality", |
| "Hyperrealistic shot of a", |
| "Professional fashion shot of", |
| "Photo of a classy", |
| "Photo of a glamour", |
| "(Horror) shot of", |
| "Cinematic film still of", |
| "A (monochrome:2) photography of", |
| "A ", |
| "Masterpiece, best quality, ultra-detailed,", |
| "A hyper-realistic, cinematic shot of", |
| "An incredibly detailed, high-resolution portrait of", |
| "A breathtaking, photorealistic capture of", |
| "A vivid, intricately detailed scene of", |
| "A surreal, ultra-detailed rendering of", |
| "An exquisitely detailed, cinematic masterpiece of", |
| "A mesmerizing, hyper-detailed view of", |
| "A stunning, ultra-realistic depiction of", |
| "A visually arresting, high-definition snapshot of", |
| "The ", |
| "The (hologram) of", |
| "A surrealist art of", |
| "The (photography of a __animal__:2), (full-body),", |
| "The (photo of a (__animal__:__animal__:__weight__) hybrid), full-body,", |
| "A photo of an Eldritch abomination,", |
| "A (3D geometrically printed figurine) of", |
| "An overwhelmingly beautiful", |
| "An (eerie scene) featuring", |
| "A serene landscape showcasing", |
| "A photography of a magnificent", |
| "A bokeh effect background with", |
| "The bustling streets of", |
| "A whimsical depiction of", |
| "A dramatic aerial view of", |
| "An enchanting tableau presenting", |
| "The ancient ruins of", |
| "A night sky filled with", |
| "A macro close-up portrait of", |
| "An (abstract composition) with", |
| "A snowy scene with", |
| "The golden hour lighting up", |
| "A mystical forest where", |
| "A futuristic cityscape with", |
| "An ethereal", |
| "A whimsical", |
| "Photo of an amazingly beautiful creature with", |
| "Photo of an iridescent", |
| "Focus on", |
| "A meticulously crafted", |
| "A dramatic chiaroscuro lighting of", |
| "An artistic interpretation of", |
| "A vivid depiction of", |
| "A serene moment captured in", |
| "A richly textured", |
| "An evocative scene portraying", |
| "An epic panorama of", |
| "An iconic representation of", |
| "A minimalist composition featuring", |
| "An avant-garde portrayal of", |
| "An immersive diorama of", |
| "A time-lapse sequence showing", |
| "A haunting silhouette against", |
| "An ancient mythological scene in", |
| "A contemporary reimagining of", |
| "A hyper-detailed rendering of", |
| "A nostalgic memory preserved in", |
| "A powerful juxtaposition of", |
| "A seamless blend of", |
| "A surreal", |
| "An evocative interplay of light and shadow", |
| "A preserved fragment of", |
| "An intricate lacework of", |
| "An offbeat take on", |
| "A reflective surface capturing", |
| "A slow-motion capture of", |
| "A stunning vista showcasing", |
| "A timeless black-and-white portrait of", |
| "A twisted version of", |
| "A dynamic motion blur effect in", |
| "A geometric pattern inspired by", |
| "A moody fog enveloping", |
| "A textured overlay on", |
| "A vibrant explosion of color", |
| "A carefully orchestrated symmetry in", |
| "A kaleidoscopic arrangement of", |
| "A subtle gradation of color in", |
| "The raw grandeur of", |
| "A whirlwind of movement in", |
| "A conceptual representation of", |
| "An experimental take on", |
| "A harmonious blend of", |
| "A poetic rendering of", |
| "An organic flow of", |
| "An understated elegance in", |
| "An unassuming grace in", |
| "A dynamic shift in", |
| "A gentle harmony of", |
| "A graceful curve in", |
| "A heightened sense of", |
| "A radiant glow surrounding", |
| "A resonant soundscape in visual form", |
| "A strong focal point in", |
| "An angular perspective on", |
| "A fleeting moment of", |
| "A playful interaction between", |
| "A stark minimalist design featuring", |
| "A whimsical journey through", |
| "An organic structure evolving from", |
| "A visual metaphor for", |
| "A window into another world through a Stable-Diffusion of", |
| "A delicate balance between", |
| "A seamless transition from", |
| "A tranquil scene", |
| "The vibrant colors of", |
| "A peaceful countryside morning in", |
| "An underwater world revealing", |
| "The photography of", |
| "A (2000s vintage RAW photo) of", |
| "Photoshoot of", |
| "A breathtaking", |
| "An extremely detailed", |
| "An establishing shot of", |
| "A concept art of", |
| "A breathtaking portrait of a majestic", |
| "A charcoal sketch of", |
| "A dramatic scene of", |
| "A painting in the style of", |
| "An isolated", |
| "An (upper angle shot) of", |
| "An (aerial perspective photo) of a", |
| "A high contrast side light scene", |
| "A dark And mysterious ", |
| "A clay sculpture of", |
| "A digital illustration featuring", |
| "A graffiti art piece depicting", |
| "A historical reenactment of", |
| "A leading lines shot of", |
| "A low angle view of", |
| "A misty dawn over", |
| "A mixed media collage showcasing", |
| "A panoramic view of", |
| "A pastel portrait of", |
| "A pencil drawing of", |
| "A tight shot of", |
| "A watercolor painting of", |
| "A National Geographic wildlife photographer capturing", |
| "A worm's eye view of", |
| "An ink drawing depicting", |
| "Masterpiece,", |
| "A mesmerizing glimpse of", |
| "A captivating display of", |
| "A dynamic interplay of", |
| "A sublime vision of", |
| "A breathtaking portrayal of", |
| "A poetic interpretation of", |
| "A striking composition of", |
| "A vivid tapestry of", |
| "An enigmatic depiction of", |
| "A remarkable fusion of", |
| "A stunning perspective of", |
| "A harmonious blend of", |
| "A radical reinterpretation of", |
| "A delicate sketch of", |
| "A vibrant composition of", |
| "A richly textured portrayal of", |
| "A pioneering outlook of", |
| "A refined portrait of", |
| "A sharp focus on", |
| "A monumental depiction of", |
| "A fluid rendering of", |
| "A kinetic expression of", |
| "A graceful outline of", |
| "A provocative framework of", |
| "A subtle balance of", |
| "A minimalist construction of", |
| "A dramatic evolution of", |
| "A whimsical abstraction of", |
| "A poignant reflection of", |
| "A pioneering illustration of", |
| "A sophisticated visualization of", |
| "An exuberant composition of", |
| "A bold expression of", |
| "A lavish interpretation of", |
| "A masterful arrangement of", |
| "A futuristic vision of", |
| "A radiant convergence of", |
| "A surrealist portrayal of", |
| "A fragmented mosaic of", |
| "A cryptic collage of", |
| "A crystalline perspective on", |
| "A dreamlike rendition of", |
| "A kinetic study of", |
| "A spontaneous capture of", |
| "A reflective moment of", |
| "An intense interplay of", |
| "A layered narrative of", |
| "A refined synthesis of", |
| "A chiaroscuro play of", |
| "A poetic exploration of", |
| "A reimagined concept of", |
| "A vigorous depiction of", |
| "A textured cascade of", |
| "A visionary abstraction of", |
| "A monumental snapshot of", |
| "A scintillating vignette of", |
| "A graceful melding of", |
| "A spectral composition of", |
| "A radiant interplay of", |
| "A striking juxtaposition of", |
| "A refined montage of", |
| "A nuanced portrayal of", |
| "A visionary construct of", |
| "An evocative snapshot of", |
| "A bold fusion of", |
| "A delicate overlay of", |
| "A complex layering of", |
| "A vivid gradient of", |
| "A kinetic cascade of", |
| "A luminous texture of", |
| "A bold silhouette of", |
| "A high-resolution photographic capture of", |
| "A sharply focused photographic study of", |
| "A meticulously framed photographic moment of", |
| "An ultra-detailed photographic exploration of", |
| "A dynamic high-contrast photographic depiction of", |
| "A bold, hyper-realistic photographic rendering of", |
| "An intimate photographic snapshot of", |
| "A vividly composed photographic portrayal of", |
| "A crisp, professional photographic impression of", |
| "A timeless black-and-white photographic record of", |
| "A vividly detailed photographic vignette of", |
| "A dynamic, low-key photographic interpretation of", |
| "A refined photographic montage of", |
| "A compelling photographic narrative of", |
| "A striking high-key photographic expression of", |
| "A meticulously captured photographic scene of", |
| "A visionary photographic perspective on", |
| "An innovative photographic framing of", |
| "A sophisticated photographic series of", |
| "A powerful photographic study of", |
| "A radiant photographic tableau of", |
| "A minimalist photographic composition of", |
| "An edgy photographic take on", |
| "A vibrant photographic freeze-frame of", |
| "A kinetic photographic capture of", |
| "A meticulously arranged photographic display of", |
| "A dramatic photographic snapshot of", |
| "A crisp, color-rich photographic impression of", |
| "A bold photographic experiment capturing", |
| "An avant-garde photographic reinterpretation of", |
| "A sharply rendered photographic moment of", |
| "A compelling photographic sequence of", |
| "A profound photographic observation of", |
| "A refined photographic layering of", |
| "A spontaneous photographic capture of", |
| "A surreal photographic juxtaposition of", |
| "A masterfully composed photographic glimpse of", |
| "A radiant photographic slice of", |
| "A detailed photographic capture of", |
| "A visually arresting photographic study of" |
| ] |
|
|
| |
| |
| |
| def sanitize_prompt(prompt: str) -> str: |
| prompt = (prompt or "").replace("\r", " ").replace("\n", " ").strip() |
| return " ".join(prompt.split()) |
|
|
| def lightly_clean_completion(text: str) -> str: |
| text = (text or "").strip().replace("\r", " ").replace("\n", " ") |
| text = " ".join(text.split()) |
| while text.startswith((",", ".", ";", ":", "-", "_")): |
| text = text[1:].strip() |
| return text |
|
|
| def trim_to_sentence_boundary(text: str, max_chars: int = 240) -> str: |
| text = text.strip() |
| if len(text) <= max_chars: |
| return text |
| trimmed = text[:max_chars].rstrip() |
| last_stop = max(trimmed.rfind("."), trimmed.rfind(","), trimmed.rfind(";"), trimmed.rfind(":")) |
| if last_stop > 80: |
| trimmed = trimmed[:last_stop].rstrip() |
| return trimmed.rstrip(",;:- ") |
|
|
| def prepare_full_prompt(prompt: str, completion: str) -> str: |
| prompt = prompt.strip() |
| completion = lightly_clean_completion(completion) |
| completion = trim_to_sentence_boundary(completion, 240) |
| if not completion: |
| return prompt |
| if completion.lower().startswith(prompt.lower()): |
| return completion |
| if prompt.endswith((" ", ",", ":", ";")): |
| return f"{prompt}{completion}" |
| return f"{prompt} {completion}" |
|
|
| def dedupe_preserve_order(items): |
| seen = set() |
| out = [] |
| for item in items: |
| key = item.strip().lower() |
| if key and key not in seen: |
| seen.add(key) |
| out.append(item) |
| return out |
|
|
| def get_available_models(): |
| return [name for name, path in model_versions.items() if os.path.exists(path)] |
|
|
| |
| |
| |
| def load_model(model_name): |
| global llm, current_model |
| with model_lock: |
| if llm is not None and current_model == model_name: |
| print(f"[MODEL] Already loaded: {model_name}") |
| return |
|
|
| model_path = model_versions[model_name] |
| if not os.path.exists(model_path): |
| raise FileNotFoundError(f"Model file not found at {model_path}") |
|
|
| print("\n" + "=" * 60) |
| print(f"[MODEL] Loading model: {model_name}") |
| print(f"[MODEL] Path: {model_path}") |
|
|
| llm = None |
| gc.collect() |
|
|
| llm_local = Llama( |
| model_path=model_path, |
| n_ctx=1024, |
| n_threads=2, |
| n_batch=256, |
| verbose=False |
| ) |
|
|
| llm = llm_local |
| current_model = model_name |
|
|
| print(f"[MODEL] Loaded successfully: {model_name}") |
| print("=" * 60 + "\n") |
|
|
| |
| |
| |
| def generate_completions(prompt, n_responses, max_tokens, temperature, top_p, top_k, repeat_penalty): |
| global llm, current_model |
|
|
| prompt = sanitize_prompt(prompt) |
|
|
| if not prompt: |
| return "Please enter a prompt." |
| if len(prompt) > 420: |
| return "Prompt too long. Please keep it under 420 characters." |
|
|
| if llm is None: |
| try: |
| load_model(current_model) |
| except Exception as e: |
| return f"Error while loading model: {e}" |
|
|
| print("\n" + "=" * 60) |
| print(f"[PROMPT] {prompt}") |
| print(f"[MODEL] {current_model}") |
| print(f"[PARAMS] completions={n_responses}, max_tokens={max_tokens}, temp={temperature}, top_p={top_p}, top_k={top_k}, penalty={repeat_penalty}") |
|
|
| results = [] |
|
|
| try: |
| with model_lock: |
| for i in range(n_responses): |
| temp_i = temperature |
| top_p_i = top_p |
| top_k_i = top_k |
|
|
| if n_responses > 1: |
| temp_i = min(2.0, max(0.1, temperature + random.uniform(-0.08, 0.10))) |
| top_p_i = min(1.0, max(0.15, top_p + random.uniform(-0.04, 0.04))) |
| top_k_i = max(1, min(128, int(top_k + random.randint(-4, 4)))) |
|
|
| output = llm( |
| prompt, |
| max_tokens=max_tokens, |
| temperature=temp_i, |
| top_p=top_p_i, |
| top_k=top_k_i, |
| repeat_penalty=repeat_penalty, |
| echo=False, |
| stop=["\n", "\n\n", "Prompt:", "Explanation:", "This image", "In this image"] |
| ) |
|
|
| text = output["choices"][0]["text"].strip() |
| full = prepare_full_prompt(prompt, text) |
|
|
| if full: |
| results.append(full) |
| print(f"[RESPONSE {i+1}] {full}") |
| else: |
| print(f"[RESPONSE {i+1}] skipped empty result") |
|
|
| except Exception as e: |
| print(f"[ERROR] Generation failed: {e}") |
| print("=" * 60 + "\n") |
| return f"Generation error: {e}" |
|
|
| results = dedupe_preserve_order(results) |
|
|
| print("=" * 60 + "\n") |
|
|
| if not results: |
| return "No valid completion generated." |
|
|
| return "\n\n".join(results) |
|
|
| |
| |
| |
| def set_random_prompt(n): |
| selected = random.choice(prompt_list) |
| return ( |
| selected, |
| selected, |
| f"🎲 Random Prompt{'s' if n > 1 else ''}", |
| f"✨ Generate Prompt{'s' if n > 1 else ''}" |
| ) |
|
|
| def set_prompt_from_dropdown(choice, n): |
| if not choice: |
| return gr.update(), f"🎲 Random Prompt{'s' if n > 1 else ''}", f"✨ Generate Prompt{'s' if n > 1 else ''}" |
| return choice, f"🎲 Random Prompt{'s' if n > 1 else ''}", f"✨ Generate Prompt{'s' if n > 1 else ''}" |
|
|
| def on_model_change(model_name): |
| try: |
| load_model(model_name) |
| return ( |
| f"Model loaded: {model_name}", |
| f"<div class='model-note'>{model_descriptions.get(model_name, 'Experimental visual prompt continuation model.')}</div>" |
| ) |
| except Exception as e: |
| return ( |
| f"Model load error: {e}", |
| "<div class='model-note'>Unable to load the selected model.</div>" |
| ) |
|
|
| def clear_all(n): |
| return "", "", f"🎲 Random Prompt{'s' if n > 1 else ''}", f"✨ Generate Prompt{'s' if n > 1 else ''}" |
|
|
| |
| |
| |
| available_models = get_available_models() |
| if not available_models: |
| raise RuntimeError("No model files were found in the model/ directory.") |
|
|
| if current_model not in available_models: |
| current_model = available_models[0] |
|
|
| load_model(current_model) |
| default_prompt = random.choice(prompt_list) |
|
|
| |
| |
| |
| theme = gr.themes.Base( |
| primary_hue="indigo", |
| secondary_hue="slate", |
| neutral_hue="slate", |
| radius_size="lg", |
| text_size="md", |
| spacing_size="md" |
| ) |
|
|
| custom_css = """ |
| html, body, .gradio-container { |
| background: |
| radial-gradient(circle at 8% 10%, rgba(91, 76, 255, 0.22), transparent 24%), |
| radial-gradient(circle at 92% 8%, rgba(0, 180, 255, 0.14), transparent 22%), |
| linear-gradient(180deg, #070b14 0%, #0b1020 100%) !important; |
| color: #eef2ff !important; |
| min-height: 100vh; |
| } |
| |
| .gradio-container { |
| width: 100% !important; |
| max-width: min(1680px, 100vw) !important; |
| margin: 0 auto !important; |
| padding-left: clamp(14px, 2vw, 28px) !important; |
| padding-right: clamp(14px, 2vw, 28px) !important; |
| } |
| |
| footer { |
| display: none !important; |
| } |
| |
| .app-shell { |
| width: 100%; |
| padding-top: 20px; |
| padding-bottom: 24px; |
| } |
| |
| .hero { |
| width: 100%; |
| margin-bottom: 18px; |
| border: 1px solid rgba(255,255,255,0.08); |
| background: linear-gradient(135deg, rgba(110, 86, 255, 0.16), rgba(0, 194, 255, 0.08)); |
| border-radius: 24px; |
| padding: 20px 24px; |
| box-shadow: 0 14px 40px rgba(0, 0, 0, 0.24); |
| backdrop-filter: blur(10px); |
| } |
| |
| .main-grid { |
| gap: 18px !important; |
| align-items: stretch !important; |
| } |
| |
| .panel { |
| background: rgba(12, 17, 30, 0.82) !important; |
| border: 1px solid rgba(255,255,255,0.07) !important; |
| border-radius: 22px !important; |
| box-shadow: 0 14px 34px rgba(0,0,0,0.18) !important; |
| backdrop-filter: blur(10px); |
| padding: 16px !important; |
| } |
| |
| .left-stack, .right-stack { |
| gap: 14px !important; |
| } |
| |
| .model-note { |
| margin-top: 8px; |
| font-size: 13px; |
| color: #a5b4fc; |
| line-height: 1.45; |
| } |
| |
| .output-panel { |
| height: 100%; |
| min-height: 520px; |
| } |
| |
| .block-label, label, .gr-form > label, .wrap > label { |
| color: #dbe7ff !important; |
| } |
| |
| .gradio-textbox textarea, |
| .gradio-textbox input, |
| .gradio-dropdown input, |
| .gradio-dropdown textarea, |
| .gradio-dropdown .secondary-wrap input, |
| .gradio-dropdown .wrap-inner input, |
| .gradio-number input, |
| .gradio-multimodal-textbox textarea { |
| background: rgba(255,255,255,0.06) !important; |
| border: 1px solid rgba(255,255,255,0.10) !important; |
| color: #f8fbff !important; |
| -webkit-text-fill-color: #f8fbff !important; |
| border-radius: 16px !important; |
| opacity: 1 !important; |
| } |
| |
| .gradio-textbox textarea::placeholder, |
| .gradio-textbox input::placeholder, |
| .gradio-dropdown input::placeholder { |
| color: #9fb0cb !important; |
| -webkit-text-fill-color: #9fb0cb !important; |
| opacity: 1 !important; |
| } |
| |
| .gradio-dropdown .wrap-inner, |
| .gradio-dropdown .wrap, |
| .gradio-dropdown .secondary-wrap { |
| color: #f8fbff !important; |
| } |
| |
| .gradio-dropdown .token, |
| .gradio-dropdown .selected, |
| .gradio-dropdown [data-testid="dropdown"] input, |
| .gradio-dropdown [data-testid="dropdown"] span { |
| color: #f8fbff !important; |
| -webkit-text-fill-color: #f8fbff !important; |
| } |
| |
| .gradio-dropdown .options, |
| .gradio-dropdown .options *, |
| .gradio-dropdown ul, |
| .gradio-dropdown li { |
| background: #111827 !important; |
| color: #f8fbff !important; |
| } |
| |
| .gradio-textbox textarea:disabled, |
| .gradio-textbox input:disabled, |
| .gradio-dropdown input:disabled, |
| .gradio-number input:disabled { |
| color: #d9e3f3 !important; |
| -webkit-text-fill-color: #d9e3f3 !important; |
| opacity: 1 !important; |
| } |
| |
| .statusbox textarea, |
| .statusbox input { |
| color: #86efac !important; |
| -webkit-text-fill-color: #86efac !important; |
| font-weight: 700 !important; |
| opacity: 1 !important; |
| } |
| |
| button { |
| border-radius: 16px !important; |
| border: 1px solid rgba(255,255,255,0.08) !important; |
| font-weight: 700 !important; |
| transition: all 0.18s ease !important; |
| } |
| |
| button:hover { |
| transform: translateY(-1px); |
| filter: brightness(1.05); |
| } |
| |
| .generate-btn button { |
| background: linear-gradient(135deg, #6d5dfc 0%, #21c7ff 100%) !important; |
| color: #ffffff !important; |
| box-shadow: 0 10px 30px rgba(70, 110, 255, 0.25); |
| } |
| |
| .secondary-btn button { |
| background: rgba(255,255,255,0.07) !important; |
| color: #eef2ff !important; |
| } |
| |
| .slim-btn button { |
| min-height: 48px !important; |
| } |
| |
| .output-panel textarea { |
| font-size: 15px !important; |
| line-height: 1.65 !important; |
| min-height: 420px !important; |
| } |
| |
| .copy-note { |
| color: #94a3b8; |
| font-size: 12px; |
| margin-top: 8px; |
| } |
| |
| .gradio-textbox, .gradio-dropdown, .gradio-slider, .gradio-accordion { |
| --block-background-fill: rgba(12, 17, 30, 0.62) !important; |
| --input-background-fill: rgba(255,255,255,0.04) !important; |
| } |
| |
| .gradio-accordion { |
| background: rgba(12, 17, 30, 0.72) !important; |
| border: 1px solid rgba(255,255,255,0.07) !important; |
| border-radius: 18px !important; |
| } |
| |
| textarea { |
| scrollbar-color: rgba(255,255,255,0.24) transparent; |
| } |
| |
| .btn-row { |
| gap: 10px !important; |
| } |
| |
| .compact-row { |
| gap: 12px !important; |
| } |
| |
| @media (max-width: 1200px) { |
| .output-panel { |
| min-height: 460px; |
| } |
| } |
| |
| @media (max-width: 900px) { |
| .panel { |
| border-radius: 18px !important; |
| padding: 14px !important; |
| } |
| |
| .output-panel { |
| min-height: 360px; |
| } |
| } |
| |
| @media (max-width: 768px) { |
| .gradio-container { |
| padding-left: 12px !important; |
| padding-right: 12px !important; |
| } |
| |
| .output-panel { |
| min-height: 280px; |
| } |
| |
| .output-panel textarea { |
| min-height: 280px !important; |
| } |
| |
| .btn-row { |
| flex-direction: column !important; |
| } |
| |
| .btn-row > * { |
| width: 100% !important; |
| } |
| } |
| """ |
|
|
| |
| |
| |
| with gr.Blocks(theme=theme, css=custom_css, title="WizzGPT Prompt Generator") as demo: |
| with gr.Column(elem_classes=["app-shell"]): |
| with gr.Column(elem_classes=["hero"]): |
| gr.Markdown("## ✨ WizzGPT — Forget logic. Embrace surprise. This model creates visual wonder, not narrative clarity.") |
|
|
| with gr.Row(equal_height=True, elem_classes=["main-grid"]): |
| with gr.Column(scale=7, min_width=420, elem_classes=["left-stack"]): |
| with gr.Column(elem_classes=["panel"]): |
| with gr.Row(elem_classes=["compact-row"]): |
| model_selector = gr.Dropdown( |
| choices=available_models, |
| value=current_model, |
| label="🧠 Select Model", |
| interactive=True |
| ) |
| model_status = gr.Textbox( |
| value=f"Model loaded: {current_model}", |
| label="Status", |
| interactive=False, |
| elem_classes=["statusbox"] |
| ) |
|
|
| model_hint = gr.HTML( |
| f"<div class='model-note'>{model_descriptions.get(current_model, '')}</div>" |
| ) |
|
|
| prompt_input = gr.Textbox( |
| label="📝 Prompt", |
| lines=4, |
| value=default_prompt, |
| placeholder="Type a prompt start or pick one below..." |
| ) |
|
|
| with gr.Row(elem_classes=["compact-row"]): |
| prompt_dropdown = gr.Dropdown( |
| choices=prompt_list, |
| value=default_prompt, |
| label="📌 Prompt Examples", |
| scale=4 |
| ) |
| random_button = gr.Button( |
| "🎲 Random", |
| scale=1, |
| elem_classes=["secondary-btn", "slim-btn"] |
| ) |
|
|
| n_responses = gr.Slider( |
| 1, 7, value=3, step=1, |
| label="Number of Completions" |
| ) |
|
|
| with gr.Accordion("⚙️ Advanced Settings", open=False): |
| max_tokens = gr.Slider(10, 140, value=55, step=5, label="Max Tokens") |
| temperature = gr.Slider(0.1, 2.0, value=1.25, step=0.05, label="Temperature") |
| top_p = gr.Slider(0.0, 1.0, value=0.90, step=0.05, label="Top-p") |
| top_k = gr.Slider(0, 128, value=40, step=1, label="Top-k") |
| repeat_penalty = gr.Slider(0.5, 2.0, value=1.35, step=0.05, label="Repeat Penalty") |
|
|
| with gr.Row(elem_classes=["btn-row"]): |
| generate_button = gr.Button( |
| "✨ Generate Prompt(s)", |
| elem_classes=["generate-btn", "slim-btn"] |
| ) |
| reroll_button = gr.Button( |
| "🔄 Reroll", |
| elem_classes=["secondary-btn", "slim-btn"] |
| ) |
| clear_button = gr.Button( |
| "🧹 Clear", |
| elem_classes=["secondary-btn", "slim-btn"] |
| ) |
|
|
| with gr.Column(scale=8, min_width=420, elem_classes=["right-stack"]): |
| with gr.Column(elem_classes=["panel", "output-panel"]): |
| output = gr.Textbox( |
| label="📄 Generated Completions", |
| lines=20, |
| max_lines=28, |
| show_copy_button=True, |
| placeholder="Your generated prompt continuations will appear here..." |
| ) |
| gr.HTML('<div class="copy-note">Tip: V3 is more SDXL-like, V6/V7 are more natural and exploratory. Lower Max Tokens for tighter results.</div>') |
|
|
| prompt_dropdown.change( |
| set_prompt_from_dropdown, |
| [prompt_dropdown, n_responses], |
| [prompt_input, random_button, generate_button] |
| ) |
|
|
| random_button.click( |
| set_random_prompt, |
| inputs=n_responses, |
| outputs=[prompt_input, prompt_dropdown, random_button, generate_button] |
| ) |
|
|
| n_responses.change( |
| lambda n: ( |
| f"🎲 Random Prompt{'s' if n > 1 else ''}", |
| f"✨ Generate Prompt{'s' if n > 1 else ''}" |
| ), |
| inputs=n_responses, |
| outputs=[random_button, generate_button] |
| ) |
|
|
| generate_button.click( |
| fn=generate_completions, |
| inputs=[prompt_input, n_responses, max_tokens, temperature, top_p, top_k, repeat_penalty], |
| outputs=output |
| ) |
|
|
| reroll_button.click( |
| fn=generate_completions, |
| inputs=[prompt_input, n_responses, max_tokens, temperature, top_p, top_k, repeat_penalty], |
| outputs=output |
| ) |
|
|
| model_selector.change( |
| on_model_change, |
| inputs=model_selector, |
| outputs=[model_status, model_hint] |
| ) |
|
|
| clear_button.click( |
| clear_all, |
| inputs=n_responses, |
| outputs=[prompt_input, output, random_button, generate_button] |
| ) |
|
|
| demo.queue().launch() |
