#!/usr/bin/env python3 import gradio as gr import numpy as np from PIL import Image, ImageDraw, ImageFont import cv2 import os import json import hashlib import time import random from datetime import datetime from pathlib import Path import warnings warnings.filterwarnings("ignore") # All heavy imports happen inside button handlers print("App loaded successfully") class SafetyFramework: BLOCKED = ["child","minor","underage","kid","children","non-consensual","revenge", "hidden camera","spy","torture","gore","snuff","beheading","execution", "terrorist","bomb making","how to kill"] WARN = ["real person","celebrity","famous","actor","actress","public figure","politician","named individual"] def check_prompt(self, text): if not text: return True, "ok", "" text_lower = text.lower() for kw in self.BLOCKED: if kw in text_lower: return False, "blocked", f"Blocked term: '{kw}'" wf = [k for k in self.WARN if k in text_lower] if wf: return True, "warning", f"Warning: references real individuals ({', '.join(wf)})" return True, "ok", "" def watermark(self, image, meta=None): if image is None: return image img = image.copy().convert("RGBA") w, h = img.size overlay = Image.new("RGBA", img.size, (0,0,0,0)) draw = ImageDraw.Draw(overlay) try: font = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf", max(10, h//80)) except: font = ImageFont.load_default() wm = "AI GENERATED - Fictional Content" ts = datetime.utcnow().strftime("%Y-%m-%d %H:%M UTC") try: bx = draw.textbbox((0,0), wm, font=font) tw, th = bx[2]-bx[0], bx[3]-bx[1] except: tw, th = len(wm)*6, 12 x, y = w-tw-15, h-th-15 draw.rectangle([x-5, y-5, x+tw+5, y+th+5], fill=(0,0,0,80)) draw.text((x,y), wm, fill=(255,255,255,180), font=font) draw.rectangle([x-5, y-th-7, x+len(ts)*6+5, y-5], fill=(0,0,0,80)) draw.text((x, y-th-5), ts, fill=(200,200,200,150), font=font) return Image.alpha_composite(img, overlay).convert("RGB") SAFETY = SafetyFramework() def placeholder(prompt, w, h, label="", sub=""): img = Image.new("RGB", (int(w), int(h)), (30,30,40)) d = ImageDraw.Draw(img) try: fl = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf", 24) fs = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf", 14) except: fl = fs = ImageFont.load_default() t = "AI Creative Suite" d.text(((int(w)-len(t)*14)//2, 20), t, fill=(200,200,255), font=fl) p = prompt[:60] + "..." if len(prompt)>60 else prompt d.text(((int(w)-len(p)*8)//2, int(h)//2-30), p, fill=(180,180,200), font=fs) if sub: d.text(((int(w)-len(sub)*8)//2, int(h)//2), sub, fill=(150,150,180), font=fs) if label: d.text(((int(w)-len(label)*8)//2, int(h)//2+30), label, fill=(150,150,180), font=fs) return SAFETY.watermark(img) class ImageGen: def __init__(self): self._pipe = None def _init(self): if self._pipe is not None: return True try: import torch from diffusers import DiffusionPipeline dev = "cuda" if torch.cuda.is_available() else "cpu" self._pipe = DiffusionPipeline.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16 if dev=="cuda" else torch.float32, use_safetensors=True, variant="fp16" if dev=="cuda" else None) if dev=="cuda": self._pipe = self._pipe.to(dev) self._pipe.enable_model_cpu_offload() self._dev = dev return True except Exception as e: self._err = str(e) return False def generate(self, prompt, neg, width, height, steps, guidance, seed, num): ok, lvl, msg = SAFETY.check_prompt(prompt) if not ok: return [placeholder(prompt, width, height, "BLOCKED", msg)]*int(num), msg if not self._init(): return [placeholder(prompt, width, height, "LOADING", self._err)]*int(num), f"Model not ready: {self._err}" import torch s = int(seed) if int(seed)!=-1 else random.randint(0, 2**32) gen = torch.Generator(device=self._dev).manual_seed(s) out = [] for i in range(int(num)): g = gen.manual_seed(s+i) try: r = self._pipe(prompt=prompt, negative_prompt=neg, width=int(width), height=int(height), num_inference_steps=int(steps), guidance_scale=float(guidance), generator=g).images[0] out.append(SAFETY.watermark(r, {"seed": s+i})) except Exception as e: out.append(placeholder(prompt, width, height, "ERROR", str(e)[:50])) return out, msg if lvl=="warning" else "" class VideoGen: def __init__(self): self._pipe = None def _init(self): if self._pipe is not None: return True try: import torch from diffusers import CogVideoXPipeline self._pipe = CogVideoXPipeline.from_pretrained("THUDM/CogVideoX-2b", torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32) if torch.cuda.is_available(): self._pipe.enable_model_cpu_offload() return True except Exception as e: self._err = str(e) return False def generate(self, prompt, num_frames, fps, seed): ok, lvl, msg = SAFETY.check_prompt(prompt) if not ok: return self._fallback(prompt, num_frames, fps, "BLOCKED"), msg if self._init(): try: import torch s = int(seed) if int(seed)!=-1 else random.randint(0, 2**32) gen = torch.Generator(device="cuda" if torch.cuda.is_available() else "cpu").manual_seed(s) v = self._pipe(prompt=prompt, num_frames=int(num_frames), num_inference_steps=50, guidance_scale=6.0, generator=gen).frames[0] path = f"/tmp/video_{int(time.time())}.mp4" from diffusers.utils import export_to_video export_to_video(v, path, fps=int(fps)) return path, msg if lvl=="warning" else "" except Exception as e: return self._fallback(prompt, num_frames, fps, str(e)[:50]), str(e) return self._fallback(prompt, num_frames, fps, self._err), self._err def _fallback(self, prompt, nf, fps, status=""): path = f"/tmp/vid_{int(time.time())}.mp4" frames = [] w, h = 512, 512 try: f = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf", 20) fs = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf", 14) except: f = fs = ImageFont.load_default() for i in range(int(nf)): img = Image.new("RGB", (w,h), (20,20,30)) d = ImageDraw.Draw(img) off = int(15*np.sin(i*2*3.14159/max(nf,1))) d.text((w//2-100+off, 30), "AI Creative Suite - Video", fill=(200,200,255), font=f) p = prompt[:50]+"..." if len(prompt)>50 else prompt d.text((w//2-len(p)*4, h//2-20), p, fill=(180,180,200), font=fs) if status: d.text((20, h//2+10), f"Status: {status}", fill=(255,100,100), font=fs) bw = 300; bx = (w-bw)//2; by = h//2+40 pr = (i+1)/max(nf,1); fw = int(bw*pr) d.rectangle([bx,by,bx+bw,by+20], outline=(100,100,150), width=2) d.rectangle([bx+2,by+2,bx+fw-2,by+18], fill=(100,150,255)) frames.append(np.array(img)) try: import imageio imageio.mimsave(path, frames, fps=int(fps)) except: img = Image.new("RGB",(w,h),(20,20,30)); ImageDraw.Draw(img).text((50,200),"Video error",fill=(200,200,255)); img.save(path) return path class AudioGen: def __init__(self): self._music = None; self._sfx = None def _init_music(self, size): try: from transformers import AutoProcessor, MusicgenForConditionalGeneration p = AutoProcessor.from_pretrained(f"facebook/musicgen-{size}") m = MusicgenForConditionalGeneration.from_pretrained(f"facebook/musicgen-{size}") self._music = (p, m); return True except Exception as e: self._music_err = str(e); return False def _init_sfx(self): try: from transformers import AutoProcessor, AutoModelForTextToWaveform p = AutoProcessor.from_pretrained("facebook/audiogen-medium") m = AutoModelForTextToWaveform.from_pretrained("facebook/audiogen-medium") self._sfx = (p, m); return True except Exception as e: self._sfx_err = str(e); return False def generate_music(self, prompt, duration, seed, size): ok, lvl, msg = SAFETY.check_prompt(prompt) if not ok: return self._placeholder(float(duration), "BLOCKED"), msg if not self._music and not self._init_music(size): return self._placeholder(float(duration), self._music_err), self._music_err try: import torch p, m = self._music inputs = p(text=[prompt], padding=True, return_tensors="pt") mt = min(int(float(duration)*50), 1500) av = m.generate(**inputs, max_new_tokens=mt, do_sample=True, guidance_scale=3.0) path = f"/tmp/mus_{int(time.time())}.wav" import scipy.io.wavfile scipy.io.wavfile.write(path, rate=m.config.audio_encoder.sampling_rate, data=av[0,0].cpu().numpy()) return path, msg if lvl=="warning" else "" except Exception as e: return self._placeholder(float(duration), str(e)[:60]), str(e) def generate_sfx(self, prompt, duration, seed): ok, lvl, msg = SAFETY.check_prompt(prompt) if not ok: return self._placeholder(float(duration), "BLOCKED"), msg if not self._sfx and not self._init_sfx(): return self._placeholder(float(duration), self._sfx_err), self._sfx_err try: p, m = self._sfx inputs = p(text=[prompt], return_tensors="pt") mt = min(int(float(duration)*50), 1000) av = m.generate(**inputs, max_new_tokens=mt, do_sample=True) path = f"/tmp/sfx_{int(time.time())}.wav" import scipy.io.wavfile scipy.io.wavfile.write(path, rate=16000, data=av[0,0].cpu().numpy()) return path, msg if lvl=="warning" else "" except Exception as e: return self._placeholder(float(duration), str(e)[:60]), str(e) def _placeholder(self, dur, label=""): sr = 16000; s = np.zeros(int(sr*dur), np.float32) t = np.linspace(0,dur,len(s)) s += 0.1*np.sin(2*3.14159*440*t)*(t<0.5) s += 0.05*np.sin(2*3.14159*880*t)*((t>0.5)&(t<1.0)) path = f"/tmp/ph_{int(time.time())}.wav" try: import scipy.io.wavfile scipy.io.wavfile.write(path, rate=sr, data=s) except: with open(path, "wb") as f: pass return path class Enhancer: def upscale(self, image, scale): if image is None: return None w, h = image.size ns = (int(w*float(scale)), int(h*float(scale))) return SAFETY.watermark(image.resize(ns, Image.Resampling.LANCZOS)) def skin(self, image, strength): if image is None: return None img = np.array(image).astype(np.float32) sm = cv2.bilateralFilter(img.astype(np.uint8), 9, 75, 75) en = img*(1-float(strength)) + sm.astype(np.float32)*float(strength) k = np.array([[-1,-1,-1],[-1,9,-1],[-1,-1,-1]])*0.3 + np.array([[0,0,0],[0,1,0],[0,0,0]])*0.7 en = cv2.filter2D(en.astype(np.uint8), -1, k) return SAFETY.watermark(Image.fromarray(en)) class PlotGen: def __init__(self): self.tmpl = { "romance": {"scenes":["Meeting","Connection","Conflict","Resolution","Intimacy"], "beats":["first glance","shared secret","external obstacle","emotional breakthrough","physical closeness"]}, "adventure": {"scenes":["Departure","Trials","Discovery","Confrontation","Return"], "beats":["call to action","overcoming fear","hidden truth","final battle","changed perspective"]}, "mystery": {"scenes":["Incident","Investigation","Twist","Confrontation","Revelation"], "beats":["unexplained event","clue gathering","false lead","accusation","truth uncovered"]}, "fantasy": {"scenes":["Ordinary World","Crossing","Allies","Ordeal","Mastery"], "beats":["mundane life","portal opens","unlikely friendship","greatest fear","new power"]}, "thriller": {"scenes":["Calm","Disturbance","Escalation","Crisis","Aftermath"], "beats":["peaceful moment","unusual detail","stakes rise","point of no return","new normal"]}, "sci-fi": {"scenes":["Present","Anomaly","Exploration","Revelation","Transformation"], "beats":["technological world","strange signal","unknown territory","alien truth","human evolution"]} } self.emos = {"passionate":["intense gaze","trembling touch","racing heartbeats","heated whisper","burning desire"], "tense":["clenched jaw","narrowed eyes","heavy silence","shallow breathing","coiled energy"], "joyful":["bright laughter","warm embrace","sparkling eyes","relaxed posture","genuine smile"], "mysterious":["shadowed face","half-smile","glance over shoulder","unspoken knowledge","concealed intention"], "dark":["haunted expression","clenched fists","distant stare","sharp movements","controlled rage"]} def generate(self, genre, theme, tone, num_scenes, setting, chars): t = self.tmpl.get(genre, self.tmpl["romance"]) e = self.emos.get(tone, self.emos["passionate"]) n = min(int(num_scenes), len(t["scenes"])) out = f"# {genre.upper()} PLOT: {theme or 'Untitled'}\n\n" out += f"**Tone:** {tone} | **Setting:** {setting or 'Various'} | **Characters:** {chars or '2'}\n\n---\n\n" for i in range(n): sn = t["scenes"][i]; bt = t["beats"][i] if i ⚠️ Safety: Watermarked outputs. Fictional characters only. No face-swap or voice cloning. """) with gr.Tab("Image Generator"): with gr.Row(): with gr.Column(scale=2): gp = gr.Textbox(label="Prompt", placeholder="cinematic portrait of a fantasy warrior, dramatic lighting", lines=3) gn = gr.Textbox(label="Negative Prompt", value="blurry, low quality, distorted, deformed, extra limbs", lines=2) with gr.Row(): gw = gr.Slider(512, 1536, 1024, 64, label="Width") gh = gr.Slider(512, 1536, 1024, 64, label="Height") with gr.Row(): gs = gr.Slider(10, 100, 30, 1, label="Steps") gg = gr.Slider(1, 20, 7.5, 0.5, label="Guidance") with gr.Row(): gd = gr.Number(-1, label="Seed (-1=random)", precision=0) gn_img = gr.Slider(1, 4, 1, 1, label="Num Images") gb = gr.Button("Generate", variant="primary") gw_txt = gr.Textbox(label="Safety Check", interactive=False) with gr.Column(scale=3): go = gr.Gallery(label="Generated Images", columns=2, rows=2) with gr.Tab("Image Enhancer"): with gr.Row(): with gr.Column(): ei = gr.Image(label="Input Image", type="pil") es = gr.Slider(1, 4, 2, 0.5, label="Upscale Factor") esk = gr.Slider(0, 1, 0.5, 0.1, label="Skin Texture Strength") with gr.Row(): ebu = gr.Button("Upscale") ebs = gr.Button("Enhance Texture") with gr.Column(): eo = gr.Image(label="Enhanced Result") with gr.Tab("Pose Editor"): with gr.Row(): with gr.Column(): pi = gr.Image(label="Character Reference", type="pil") pp = gr.Textbox(label="Character Description", placeholder="female warrior with silver armor", lines=2) pn = gr.Slider(1, 8, 4, 1, label="Number of Views") with gr.Row(): pbx = gr.Button("Extract Pose") pbg = gr.Button("Generate Views", variant="primary") pw = gr.Textbox(label="Safety Check", interactive=False) with gr.Column(): po = gr.Gallery(label="Generated Views", columns=2, rows=2) with gr.Tab("Image Variations"): with gr.Row(): with gr.Column(): vi = gr.Image(label="Reference Image", type="pil") vp = gr.Textbox(label="Base Prompt", placeholder="portrait of a character", lines=2) vn = gr.Slider(1, 8, 4, 1, label="Variations") vs = gr.Number(-1, label="Seed", precision=0) vb = gr.Button("Generate Variations", variant="primary") vw = gr.Textbox(label="Safety Check", interactive=False) with gr.Column(): vo = gr.Gallery(label="Style Variations", columns=2, rows=2) with gr.Tab("Video Generator"): with gr.Row(): with gr.Column(): vdp = gr.Textbox(label="Video Prompt", placeholder="slow motion ocean waves, golden hour, cinematic", lines=3) with gr.Row(): vdf = gr.Slider(16, 49, 25, 1, label="Frames") vdfps = gr.Slider(4, 30, 8, 1, label="FPS") vds = gr.Number(-1, label="Seed", precision=0) vdb = gr.Button("Generate Video", variant="primary") vdw = gr.Textbox(label="Safety Check", interactive=False) with gr.Column(): vdo = gr.Video(label="Generated Video") with gr.Tab("Audio Generator"): with gr.Row(): with gr.Column(): gr.Markdown("#### Music") amp = gr.Textbox(label="Music Prompt", placeholder="romantic orchestral music, soft piano", lines=2) with gr.Row(): amd = gr.Slider(5, 60, 10, 5, label="Duration (s)") amsz = gr.Radio(["small","medium","large"], value="small", label="Size") ams = gr.Number(-1, label="Seed", precision=0) amb = gr.Button("Generate Music", variant="primary") amw = gr.Textbox(label="Safety Check", interactive=False) with gr.Column(): amo = gr.Audio(label="Generated Music", type="filepath") with gr.Row(): with gr.Column(): gr.Markdown("#### Sound Effects") asp = gr.Textbox(label="SFX Prompt", placeholder="rain on window, footsteps on gravel", lines=2) with gr.Row(): asd = gr.Slider(1, 30, 5, 1, label="Duration (s)") ass = gr.Number(-1, label="Seed", precision=0) asb = gr.Button("Generate SFX") asw = gr.Textbox(label="Safety Check", interactive=False) with gr.Column(): aso = gr.Audio(label="Generated SFX", type="filepath") gr.Markdown("
⚠️ Instrumental music and environmental sounds only. No voice cloning.
") with gr.Tab("Plot Generator"): with gr.Row(): with gr.Column(): plg = gr.Dropdown(["romance","adventure","mystery","fantasy","thriller","sci-fi"], value="romance", label="Genre") plt = gr.Textbox(label="Theme/Topic", placeholder="forbidden love, time travel") plto = gr.Dropdown(["passionate","tense","joyful","mysterious","dark"], value="passionate", label="Tone") with gr.Row(): pln = gr.Slider(3, 10, 5, 1, label="Scenes") plc = gr.Textbox(label="Characters", value="2") pls = gr.Textbox(label="Setting", placeholder="Victorian mansion, futuristic city") plb = gr.Button("Generate Plot", variant="primary") with gr.Column(scale=2): plo = gr.Textbox(label="Generated Plot", lines=40) with gr.Tab("Film Editor"): with gr.Row(): with gr.Column(): gr.Markdown("#### Project") fpn = gr.Textbox(label="Project Name", value="my_film") with gr.Row(): fpc = gr.Button("Create Project") fps = gr.Textbox(label="Status", interactive=False) gr.Markdown("---") gr.Markdown("#### Add Scene") fsi = gr.Image(label="Scene Image", type="pil") with gr.Row(): fsd = gr.Slider(1, 30, 5, 1, label="Duration (s)") fsa = gr.Audio(label="Audio (optional)", type="filepath") fpa = gr.Button("Add Scene") gr.Markdown("---") gr.Markdown("#### Render") with gr.Row(): fpf = gr.Slider(12, 60, 24, 1, label="FPS") fpt = gr.Dropdown(["none","fade","cut","wipe"], value="fade", label="Transition") fpr = gr.Button("Render Film", variant="primary") with gr.Column(): fpo = gr.Video(label="Rendered Film") fprs = gr.Textbox(label="Render Status", interactive=False) with gr.Tab("Prompt Helper"): with gr.Row(): with gr.Column(): phb = gr.Textbox(label="Basic Prompt", placeholder="portrait of a warrior", lines=2) with gr.Row(): phst = gr.Dropdown(["cinematic","oil painting","digital art","anime","photorealistic","fantasy art","watercolor","film noir"], value="cinematic", label="Style") phl = gr.Dropdown(["golden hour","dramatic lighting","soft natural","neon","moonlight","studio lighting","volumetric fog"], value="dramatic lighting", label="Lighting") phq = gr.Dropdown(["masterpiece","highly detailed","8k resolution","concept art","trending on artstation","award winning"], value="masterpiece, highly detailed", label="Quality") phc = gr.Dropdown(["close-up portrait","wide shot","medium shot","extreme close-up","overhead shot","low angle"], value="close-up portrait", label="Camera") phbtn = gr.Button("Enhance Prompt", variant="primary") with gr.Column(): pho = gr.Textbox(label="Enhanced Prompt", lines=6) phn = gr.Textbox(label="Negative Prompt", value="blurry, low quality, distorted, deformed, bad anatomy, extra limbs, watermark, signature, amateur, worst quality, low resolution", lines=2) # Handlers ig = ImageGen() gb.click(fn=lambda *a: (ig.generate(*a)[0], ig.generate(*a)[1]), inputs=[gp,gn,gw,gh,gs,gg,gd,gn_img], outputs=[go,gw_txt]) en = Enhancer() ebu.click(fn=en.upscale, inputs=[ei,es], outputs=eo) ebs.click(fn=en.skin, inputs=[ei,esk], outputs=eo) pe = PoseEd() pbx.click(fn=pe.extract, inputs=pi, outputs=po) pbg.click(fn=lambda i,p,n: pe.views(i,p,n), inputs=[pi,pp,pn], outputs=[po,pw]) vg = VarGen() vb.click(fn=lambda i,p,n,s: vg.gen(i,p,n,s), inputs=[vi,vp,vn,vs], outputs=[vo,vw]) vdg = VideoGen() vdb.click(fn=vdg.generate, inputs=[vdp,vdf,vdfps,vds], outputs=[vdo,vdw]) ag = AudioGen() amb.click(fn=ag.generate_music, inputs=[amp,amd,ams,amsz], outputs=[amo,amw]) asb.click(fn=ag.generate_sfx, inputs=[asp,asd,ass], outputs=[aso,asw]) pg = PlotGen() plb.click(fn=pg.generate, inputs=[plg,plt,plto,pln,pls,plc], outputs=plo) fe = FilmEd() fpc.click(fn=fe.create, inputs=fpn, outputs=fps) fpa.click(fn=fe.add, inputs=[fpn,fsi,fsd,fsa], outputs=fps) fpr.click(fn=lambda p,f,t: fe.render(p,f,t), inputs=[fpn,fpf,fpt], outputs=[fpo,fprs]) def ph_enh(basic, style, lighting, quality, camera): if not basic: return "","" return f"{camera}, {basic}, {style}, {lighting}, {quality}, best quality, sharp focus", "blurry, low quality, distorted, deformed, bad anatomy, extra limbs, watermark, signature, amateur, worst quality, low resolution" phbtn.click(fn=ph_enh, inputs=[phb,phst,phl,phq,phc], outputs=[pho,phn]) return demo if __name__ == "__main__": demo = build_ui() demo.launch(server_name="0.0.0.0", server_port=7860)