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| import gradio as gr | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| from diffusers import DiffusionPipeline | |
| import torch | |
| import re | |
| import time | |
| import soundfile as sf | |
| from qwen_tts import Qwen3TTSModel | |
| from langdetect import detect | |
| import os | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| # --- Chat Logic --- | |
| chat_models = { | |
| "Normal": "Qwen/Qwen3-0.6B", | |
| "Thinking": "Qwen/Qwen2.5-1.5B-Instruct" | |
| } | |
| loaded_chat_models = {} | |
| loaded_chat_tokenizers = {} | |
| def load_chat_model(mode): | |
| model_id = chat_models[mode] | |
| if model_id not in loaded_chat_models: | |
| gr.Info(f"Loading {mode} Brain...") | |
| tokenizer = AutoTokenizer.from_pretrained(model_id) | |
| model = AutoModelForCausalLM.from_pretrained( | |
| model_id, | |
| torch_dtype=torch.bfloat16 if device == "cuda" else torch.float32, | |
| device_map="auto" | |
| ) | |
| loaded_chat_models[model_id] = model | |
| loaded_chat_tokenizers[model_id] = tokenizer | |
| return "Status: 🟢 Loaded" | |
| return "Status: 🟢 Loaded" | |
| def chat_logic(user_input, mode): | |
| model_id = chat_models[mode] | |
| if model_id not in loaded_chat_models: | |
| return "❌ Please click 'Load Model' first!" | |
| model, tokenizer = loaded_chat_models[model_id], loaded_chat_tokenizers[model_id] | |
| messages = [{"role": "user", "content": user_input}] | |
| text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) | |
| model_inputs = tokenizer([text], return_tensors="pt").to(model.device) | |
| generated_ids = model.generate(**model_inputs, max_new_tokens=1024) | |
| response = tokenizer.batch_decode([generated_ids[0][len(model_inputs.input_ids[0]):]], skip_special_tokens=True)[0] | |
| return re.sub(r'<think>.*?</think>\s*\n?', '', response, flags=re.DOTALL).strip() | |
| # --- Image Logic --- | |
| image_model_id = "stabilityai/sdxl-turbo" | |
| image_pipe = None | |
| def load_image_model(): | |
| global image_pipe | |
| if image_pipe is None: | |
| gr.Info("Priming TNT Engine...") | |
| pipe = DiffusionPipeline.from_pretrained( | |
| image_model_id, | |
| torch_dtype=torch.float16 if device == "cuda" else torch.float32 | |
| ) | |
| pipe.to(device) | |
| image_pipe = pipe | |
| return "Status: 🟢 Loaded" | |
| return "Status: 🟢 Loaded" | |
| def image_logic(prompt, width, height, steps): | |
| if image_pipe is None: | |
| yield "❌ Load Model First", None | |
| return | |
| yield "💥 IGNITING...", None | |
| image = image_pipe( | |
| prompt=prompt, | |
| width=int(width), | |
| height=int(height), | |
| num_inference_steps=int(steps), | |
| guidance_scale=0.0 | |
| ).images[0] | |
| yield "💥 EXPLODED", image | |
| # --- TTS Logic --- | |
| tts_model_id = "Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice" | |
| SUPPORTED_VOICES = ['aiden', 'dylan', 'eric', 'ono_anna', 'ryan', 'serena', 'sohee', 'uncle_fu', 'vivian'] | |
| tts_model = None | |
| def load_tts_model(): | |
| global tts_model | |
| if tts_model is None: | |
| gr.Info("Tuning Note-Blocks...") | |
| tts_model = Qwen3TTSModel.from_pretrained( | |
| tts_model_id, | |
| device_map=device, | |
| torch_dtype=torch.bfloat16 if device == "cuda" else torch.float32 | |
| ) | |
| return "Status: 🟢 Loaded" | |
| return "Status: 🟢 Loaded" | |
| def tts_logic(text, voice, inst, auto): | |
| if tts_model is None: | |
| return None, "Status: ❌ Not Loaded" | |
| try: | |
| wavs, sr = tts_model.generate_custom_voice( | |
| language="English", | |
| speaker=voice, | |
| instruct=inst, | |
| text=text | |
| ) | |
| output_path = "creeper_voice.wav" | |
| sf.write(output_path, wavs[0], sr) | |
| return output_path, "Status: 🟢 Audio Generated" | |
| except Exception as e: | |
| return None, f"Status: ❌ Error: {str(e)}" | |
| # --- UI Styles --- | |
| creeper_css = """ | |
| body { background-color: #000000; } | |
| .gradio-container { background-color: #1e1e1e; border: 8px solid #2e8b57; color: #00ff00; } | |
| .small-status { font-size: 0.8em; color: #2e8b57; margin-top: -10px; } | |
| .gr-button-primary { background-color: #4A7023 !important; border: 2px solid #000 !important; } | |
| """ | |
| with gr.Blocks(css=creeper_css, title="CREEPER AI HUB") as demo: | |
| gr.Markdown("# 🟩 CREEPER AI HUB 🟩") | |
| with gr.Tabs(): | |
| # --- Chat Tab --- | |
| with gr.TabItem("SSSSS-CHAT"): | |
| with gr.Row(): | |
| chat_status = gr.Markdown("Status: 🔴 Not Loaded", elem_classes=["small-status"]) | |
| with gr.Row(): | |
| mode_radio = gr.Radio(["Normal", "Thinking"], value="Normal", label="Brain Mode") | |
| load_chat_btn = gr.Button("Load Model") | |
| chat_in = gr.Textbox(label="Message", lines=3) | |
| chat_out = gr.Textbox(label="Creeper Says") | |
| chat_btn = gr.Button("EXPLODE TEXT", variant="primary") | |
| load_chat_btn.click(load_chat_model, mode_radio, chat_status) | |
| chat_btn.click(chat_logic, [chat_in, mode_radio], chat_out) | |
| # --- Image Tab --- | |
| with gr.TabItem("TNT-IMAGE"): | |
| with gr.Row(): | |
| img_status = gr.Markdown("Status: 🔴 Not Loaded", elem_classes=["small-status"]) | |
| with gr.Row(): | |
| img_prompt = gr.Textbox(label="Visual Idea", placeholder="Pixel art forest...") | |
| load_img_btn = gr.Button("Load Model") | |
| with gr.Row(): | |
| w_s = gr.Slider(256, 1024, 512, step=64, label="Width") | |
| h_s = gr.Slider(256, 1024, 512, step=64, label="Height") | |
| s_s = gr.Slider(1, 10, 4, step=1, label="Steps") | |
| img_btn = gr.Button("EXPLODE IMAGE", variant="primary") | |
| img_out = gr.Image(label="Output") | |
| load_img_btn.click(load_image_model, None, img_status) | |
| img_btn.click(image_logic, [img_prompt, w_s, h_s, s_s], [img_status, img_out]) | |
| # --- TTS Tab --- | |
| with gr.TabItem("NOTE-BLOCK"): | |
| with gr.Row(): | |
| tts_status = gr.Markdown("Status: 🔴 Not Loaded", elem_classes=["small-status"]) | |
| with gr.Row(): | |
| voice_sel = gr.Dropdown(SUPPORTED_VOICES, value="vivian", label="Speaker") | |
| load_tts_btn = gr.Button("Load Model") | |
| tts_in = gr.Textbox(label="Text to Speak") | |
| style_in = gr.Textbox("Speak naturally", label="Instructions") | |
| tts_btn = gr.Button("EXPLODE AUDIO", variant="primary") | |
| aud_out = gr.Audio(label="Audio Output") | |
| load_tts_btn.click(load_tts_model, None, tts_status) | |
| tts_btn.click(tts_logic, [tts_in, voice_sel, style_in, gr.State(True)], [aud_out, tts_status]) | |
| if __name__ == "__main__": | |
| demo.launch(mcp_server=False) | |