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1 Parent(s): 9369d0f

Revert to working version from commit 49b987b

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  1. app.py +16 -48
app.py CHANGED
@@ -6,9 +6,6 @@ from einops import rearrange
6
  import gradio as gr
7
  from stable_audio_tools import get_pretrained_model
8
  from stable_audio_tools.inference.generation import generate_diffusion_cond
9
- from diffusers import DiffusionPipeline
10
- from PIL import Image
11
- from moviepy.editor import AudioFileClip, ImageClip
12
 
13
  # Authenticate
14
  token = os.getenv("HUGGINGFACE_TOKEN")
@@ -16,25 +13,19 @@ if not token:
16
  raise RuntimeError("HUGGINGFACE_TOKEN not set")
17
  login(token=token, add_to_git_credential=False)
18
 
19
- # Load audio model
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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- audio_model, audio_config = get_pretrained_model("stabilityai/stable-audio-open-small")
22
- audio_model = audio_model.to(device)
23
- sample_rate = audio_config["sample_rate"]
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- sample_size = audio_config["sample_size"]
25
 
26
- # Load image model (Kandinsky)
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- image_pipe = DiffusionPipeline.from_pretrained(
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- "kandinsky-community/kandinsky-3",
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- torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32
30
- ).to(device)
31
-
32
- # Generate audio
33
  def generate_audio(prompt):
34
  conditioning = [{"prompt": prompt, "seconds_total": 11}]
35
  with torch.no_grad():
36
  output = generate_diffusion_cond(
37
- audio_model,
38
  steps=8,
39
  conditioning=conditioning,
40
  sample_size=sample_size,
@@ -46,45 +37,22 @@ def generate_audio(prompt):
46
  torchaudio.save(path, output, sample_rate)
47
  return path
48
 
49
- # Generate image
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- def generate_image(prompt):
51
- image = image_pipe(prompt=prompt, height=500, width=500).images[0]
52
- image_path = "output.png"
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- image.save(image_path)
54
- return image_path
55
-
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- # Combine audio + image into mp4
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- def combine_to_video(image_path, audio_path, output_path="output.mp4"):
58
- clip = ImageClip(image_path).set_duration(12).set_audio(AudioFileClip(audio_path))
59
- clip = clip.set_fps(1)
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- clip.write_videofile(output_path, codec="libx264", audio_codec="aac", fps=1)
61
- return output_path
62
-
63
- # Unified generation
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- def generate_av(prompt):
65
- audio_path = generate_audio(prompt)
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- image_path = generate_image(prompt)
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- video_path = combine_to_video(image_path, audio_path)
68
- return video_path
69
-
70
- # UI
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- interface = gr.Interface(
72
- fn=generate_av,
73
  inputs=gr.Textbox(
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  label="🎀 Prompt your sonic art here",
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  placeholder="e.g. 'drunk driving with mario and yung lean'"
76
  ),
77
- outputs=gr.Video(
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- label="🧠 Generated Audiovisual Clip"
 
79
  ),
80
  title='🌐 Hot Prompts in Your Area: "My Husband Is Dead"',
81
- description="Enter a fun sound idea for music art. Returns a synced image + audio mp4.",
82
  examples=[
83
  "ghosts peeing in a server room",
84
  "tech startup boss villain entrance music",
85
  "AI doing acid in a technofeudalist dystopia"
86
- ],
87
- css="style.css"
88
- )
89
-
90
- interface.launch()
 
6
  import gradio as gr
7
  from stable_audio_tools import get_pretrained_model
8
  from stable_audio_tools.inference.generation import generate_diffusion_cond
 
 
 
9
 
10
  # Authenticate
11
  token = os.getenv("HUGGINGFACE_TOKEN")
 
13
  raise RuntimeError("HUGGINGFACE_TOKEN not set")
14
  login(token=token, add_to_git_credential=False)
15
 
16
+ # Load model
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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+ model, config = get_pretrained_model("stabilityai/stable-audio-open-small")
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+ model = model.to(device)
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+ sample_rate = config["sample_rate"]
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+ sample_size = config["sample_size"]
22
 
23
+ # Inference function
 
 
 
 
 
 
24
  def generate_audio(prompt):
25
  conditioning = [{"prompt": prompt, "seconds_total": 11}]
26
  with torch.no_grad():
27
  output = generate_diffusion_cond(
28
+ model,
29
  steps=8,
30
  conditioning=conditioning,
31
  sample_size=sample_size,
 
37
  torchaudio.save(path, output, sample_rate)
38
  return path
39
 
40
+ # πŸŒ€ Hot Prompt Club UI
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+ gr.Interface(
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+ fn=generate_audio,
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
43
  inputs=gr.Textbox(
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  label="🎀 Prompt your sonic art here",
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  placeholder="e.g. 'drunk driving with mario and yung lean'"
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  ),
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+ outputs=gr.Audio(
48
+ type="filepath",
49
+ label="🧠 Generated Audio"
50
  ),
51
  title='🌐 Hot Prompts in Your Area: "My Husband Is Dead"',
52
+ description="Enter a fun sound idea for music art.",
53
  examples=[
54
  "ghosts peeing in a server room",
55
  "tech startup boss villain entrance music",
56
  "AI doing acid in a technofeudalist dystopia"
57
+ ]
58
+ ).launch()