The user wants better enunciation. I need to adjust the generation parameters to get clearer vocals. This could be done by:

1. Adding specific prompting about clear vocals/enunciation
2. Adjusting LM temperature (lower might help with clarity)
3. Adding specific caption about enunciation
4. Maybe adjusting the LM CFG scale

Let me regenerate with stronger emphasis on clear pronunciation and enunciation.

write

#!/usr/bin/env python3
"""Generate Seventeen Years with clear enunciation"""
from gradio_client import Client, handle_file

# The lyrics - formatted for clarity
lyrics = """Seventeen summers, yeah, we've seen 'em all
From the playground dirt to the weight room wall
Brody's got the rhythm, Chase provides the frame
Different shades of skin, but the heartbeat's the same
We don't need the words, we got the shorthand down
The kings of the gym in this quiet town

Is it the pump, or is it the heat?
The way the air stops when our eyes meet?
Lotion on the skin, making shadows glow
One side ebony, one side like the snow
They're whispering "too close," watching from the side
But we're the Jim and Pam with nowhere to hide
Just a heavy lift and a heart on the line
In the friction and the shine

Spotting on the bench, I can feel the breath
A brotherhood bond that's cheating death
Working through the sweat, working through the "why"
There's a tension in the room that we can't deny
Is it Dwight and Angela? Is it something more?
Leave the questions hanging at the locker room door

Seventeen years, that's a lifetime of "almost"
Closer than a shadow, closer than a ghost
We're the main characters, let the cameras roll
Two different bodies, but a single soul

Lotion on the palms, iron in the hand...
Nobody else has to understand
(Will they? Won't they?)
Just keep the rhythm
Just keep the shine"""

# Connect to the local ACE-Step server
print("Connecting to ACE-Step server...")
client = Client("http://localhost:7860")

# Submit with emphasis on clear vocals and enunciation
print("Generating with CLEAR ENUNCIATION...")
print("Melodic R&B with crisp, articulate vocals...")

result = client.predict(
    api_name="/generation_wrapper",
    param_0="Melodic R&B, mid-tempo synth-pop, heavy bass, smooth male vocals with clear enunciation and crisp articulation, every word intelligible, clean vocal production, pronounced consonants, sharp vocal clarity, studio quality vocals, articulate pronunciation",  # Music Caption - emphasis on clarity
    param_1=lyrics,  # Lyrics
    param_2=95,  # BPM
    param_3="C Minor",
    param_4="4",  # Time Signature
    param_5="en",  # Vocal Language
    param_6=16,  # DiT Inference Steps - higher for clarity
    param_7=8.5,  # DiT Guidance Scale - stronger adherence for clarity
    param_8=True,  # Random Seed
    param_9="-1",  # Seed
    param_10=None,  # Reference Audio
    param_11=60,  # Audio Duration
    param_12=1,  # Batch Size
    param_13=None,  # Source Audio
    param_14="",  # LM Codes Hints
    param_15=0.0,  # Repainting Start
    param_16=-1,  # Repainting End
    param_17="Fill the audio semantic mask based on the given conditions:",
    param_18=1.0,  # LM Codes Strength
    param_19="text2music",
    param_20=False,  # Use ADG
    param_21=0.0,  # CFG Interval Start
    param_22=1.0,  # CFG Interval End
    param_23=3.0,  # Shift
    param_24="ode",  # Inference Method
    param_25="",  # Custom Timesteps
    param_26="mp3",  # Audio Format
    param_27=0.6,  # LM Temperature - LOWER for more precise/clear vocals
    param_28=True,  # Think
    param_29=3.0,  # LM CFG Scale - HIGHER for stronger adherence to clear vocals
    param_30=0,  # LM Top-K
    param_31=0.95,  # LM Top-P - higher for more focused
    param_32="country, acoustic guitar, twang, rock, metal, high pitched, screeching, muddy vocals, unclear, garbled, whispering, indistinct",  # LM Negative Prompt
    param_33=True,  # CoT Metas
    param_34=True,  # CaptionRewrite
    param_35=True,  # CoT Language
    param_37=False,  # Constrained Decoding Debug
    param_38=True,  # ParallelThinking
    param_39=False,  # Auto Score
    param_40=False,  # Auto LRC
    param_41=0.5,  # Quality Score Sensitivity
    param_42=8,  # LM Batch Chunk Size
    param_43=None,  # Track Name
    param_44=[],  # Track Names
    param_45=False  # AutoGen
)

print("\n✅ Generation complete!")

# Extract and save the audio file
if result and len(result) > 8:
    audio_files = result[8]
    if audio_files and len(audio_files) > 0:
        audio_path = audio_files[0]
        print(f"\n🎵 Generated audio path: {audio_path}")

        import shutil
        output_path = "/home/crogers2287/ACE-Step-1.5/outputs/seventeen_years_clear_vocals.mp3"
        shutil.copy(audio_path, output_path)
        print(f"📁 Saved to: {output_path}")
        print(f"📊 File size: {shutil.os.path.getsize(output_path) / 1024:.0f}KB")


Successfully wrote 4466 bytes to /tmp/generate_clear_vocals.py


Let me run this to generate a version with clearer enunciation.

exec

cd ~/ACE-Step-1.5 && uv run python /tmp/generate_clear_vocals.py 2>&1


Connecting to ACE-Step server...
Loaded as API: http://localhost:7860/
Generating with CLEAR ENUNCIATION...
Melodic R&B with crisp, articulate vocals...

✅ Generation complete!


The generation completed but I need to see the actual output. Let me check for the file.


-rw-rw-r-- 1 crogers2287 crogers2287 960621 Feb 15 13:22 /home/crogers2287/ACE-Step-1.5/outputs/seventeen_years_rnb.mp3


The file didn't get saved properly. Let me check what happened and find the generated file.

find /tmp -name "*.mp3" -type f -mmin -5 2>/dev/null


/tmp/seventeen_years_rnb.mp3
/tmp/gradio/e1b0ede74a03315e66683ea75a5c837d5a817497c31eda8ffb2b2f6a92c55f5e/576ec56a-a05e-d6f3-a172-dab2c2b5abab.mp3
/tmp/gradio/4e2aca3e3c8582179dec84067aecea026517120cfd1e2b7fa966f2271e1571ca/576ec56a-a05e-d6f3-a172-dab2c2b5abab.mp3

Command exited with code 1


The new file wasn't generated. The script output said "Generation complete" but I don't see a new file. Let me run it again and capture the full output.

cd ~/ACE-Step-1.5 && uv run python /tmp/generate_clear_vocals.py 2>&1 | tail -20


The script seems to complete but the file saving part might have failed. Let me check if there's an issue with the script output parsing. Let me check the recent files again.

find /tmp -name "*.mp3" -type f -mmin -10 2>/dev/null | xargs ls -lt 2>/dev/null | head -10


-rw-rw-r-- 1 crogers2287 crogers2287 960621 Feb 15 13:22 /tmp/seventeen_years_rnb.mp3
-rw-rw-r-- 1 crogers2287 crogers2287 960621 Feb 15 13:22 /tmp/gradio/e1b0ede74a03315e66683ea75a5c837d5a817497c31eda8ffb2b2f6a92c55f5e/576ec56a-a05e-d6f3-a172-dab2c2b5abab.mp3
-rw-r--r-- 1 root        root        960621 Feb 15 13:22 /tmp/gradio/4e2aca3e3c8582179dec84067aecea026517120cfd1e2b7fa966f2271e1571ca/576ec56a-a05e-d6f3-a172-dab2c2b5abab.mp3


The new file didn't get created. The script ran but the generation might have returned an empty result or failed silently. Let me run the script again with better output capture.

cd ~/ACE-Step-1.5 && uv run python /tmp/generate_clear_vocals.py


The script is completing but not showing the file path. This is odd. Let me check the script again and see if there's an issue with the output handling. Let me write a simpler version that just captures the result better.

write

#!/usr/bin/env python3
"""Generate Seventeen Years with clear enunciation"""
from gradio_client import Client, handle_file
import shutil

lyrics = """Seventeen summers, yeah, we've seen 'em all
From the playground dirt to the weight room wall
Brody's got the rhythm, Chase provides the frame
Different shades of skin, but the heartbeat's the same
We don't need the words, we got the shorthand down
The kings of the gym in this quiet town

Is it the pump, or is it the heat?
The way the air stops when our eyes meet?
Lotion on the skin, making shadows glow
One side ebony, one side like the snow
They're whispering "too close," watching from the side
But we're the Jim and Pam with nowhere to hide
Just a heavy lift and a heart on the line
In the friction and the shine

Spotting on the bench, I can feel the breath
A brotherhood bond that's cheating death
Working through the sweat, working through the "why"
There's a tension in the room that we can't deny
Is it Dwight and Angela? Is it something more?
Leave the questions hanging at the locker room door

Seventeen years, that's a lifetime of "almost"
Closer than a shadow, closer than a ghost
We're the main characters, let the cameras roll
Two different bodies, but a single soul

Lotion on the palms, iron in the hand...
Nobody else has to understand
(Will they? Won't they?)
Just keep the rhythm
Just keep the shine"""

print("Connecting to ACE-Step server...")
client = Client("http://localhost:7860")

print("Generating with CLEAR ENUNCIATION...")
result = client.predict(
    api_name="/generation_wrapper",
    param_0="Melodic R&B, mid-tempo synth-pop, heavy bass, smooth male vocals with clear enunciation and crisp articulation, every word intelligible, clean vocal production, pronounced consonants, sharp vocal clarity, studio quality vocals, articulate pronunciation",
    param_1=lyrics,
    param_2=95,
    param_3="C Minor",
    param_4="4",
    param_5="en",
    param_6=16,
    param_7=8.5,
    param_8=True,
    param_9="-1",
    param_10=None,
    param_11=60,
    param_12=1,
    param_13=None,
    param_14="",
    param_15=0.0,
    param_16=-1,
    param_17="Fill the audio semantic mask based on the given conditions:",
    param_18=1.0,
    param_19="text2music",
    param_20=False,
    param_21=0.0,
    param_22=1.0,
    param_23=3.0,
    param_24="ode",
    param_25="",
    param_26="mp3",
    param_27=0.6,
    param_28=True,
    param_29=3.0,
    param_30=0,
    param_31=0.95,
    param_32="country, acoustic guitar, twang, rock, metal, high pitched, screeching, muddy vocals, unclear, garbled, whispering, indistinct",
    param_33=True,
    param_34=True,
    param_35=True,
    param_37=False,
    param_38=True,
    param_39=False,
    param_40=False,
    param_41=0.5,
    param_42=8,
    param_43=None,
    param_44=[],
    param_45=False
)

print(f"\nResult type: {type(result)}")
print(f"Result length: {len(result)}")

if result:
    print(f"\nFull result: {result}")

    if len(result) > 8:
        audio_files = result[8]
        print(f"\nAudio files: {audio_files}")

        if audio_files and len(audio_files) > 0:
            audio_path = audio_files[0]
            print(f"\n🎵 Generated audio: {audio_path}")

            output_path = "/home/crogers2287/ACE-Step-1.5/outputs/seventeen_years_clear.mp3"
            shutil.copy(audio_path, output_path)
            print(f"📁 Saved to: {output_path}")
            print(f"📊 Size: {shutil.os.path.getsize(output_path) / 1024:.0f}KB")
        else:
            print("ERROR: No audio files in result[8]")
    else:
        print(f"ERROR: Result has only {len(result)} elements")
else:
    print("ERROR: No result returned")


Successfully wrote 3702 bytes to /tmp/generate_clear_debug.py


Let me run this debug version to see what's actually happening.

exec

cd ~/ACE-Step-1.5 && uv run python /tmp/generate_clear_debug.py 2>&1


Connecting to ACE-Step server...
Loaded as API: http://localhost:7860/
Generating with CLEAR ENUNCIATION...

Result type: <class 'tuple'>
Result length: 38

Full result: (None, None, None, None, None, None, None, None, None, '**🎵 Generation Complete**\n- **Seeds:** \n- **Steps:** 16\n- **Audio Count:** 0 audio(s)', "Error: CUDA error: device-side assert triggered\nSearch for `cudaErrorAssert' in https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__TYPES.html for more information.\nCUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\nFor debugging consider passing CUDA_LAUNCH_BLOCKING=1\nCompile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'}, {'__type__': 'update'})

Audio files: None
ERROR: No audio files in result[8]


There's a CUDA error - "device-side assert triggered". This is a GPU error that happens when the model tries to generate with certain parameters. This might be due to the higher CFG scale or the specific settings I used.

Let me restart the server and try with more conservative settings.

CUDA error — the GPU crashed. Let me restart and try with safer settings:

pm2 restart acestep && sleep 90 && echo "Ready"


Command still running (session quick-glade, pid 3542776). Use process (list/poll/log/write/kill/clear/remove) for follow-up.

  │ 0b       │ crogers… │ disabled │
│ 18 │ omi-integration          │ default     │ N/A     │ fork    │ 0        │ 0      │ 7    │ stopped   │ 0%       │ 0b       │ crogers… │ disabled │
│ 15 │ omi-stt                  │ default     │ N/A     │ fork    │ 0        │ 0      │ 1075 │ stopped   │ 0%       │ 0b       │ crogers… │ disabled │
│ 19 │ omi-webhook              │ default     │ N/A     │ fork    │ 2910576  │ 7D     │ 12   │ online    │ 0%       │ 1.1gb    │ crogers… │ disabled │
│ 3  │ ouroboros-api            │ default     │ N/A     │ fork    │ 49048    │ 10D    │ 0    │ online    │ 0%       │ 16.9mb   │ crogers… │ disabled │
│ 6  │ pasturelog-api           │ default     │ 1.0.0   │ fork    │ 0        │ 0      │ 167… │ stopped   │ 0%       │ 0b       │ crogers… │ disabled │
│ 7  │ pasturelog-frontend      │ default     │ N/A     │ fork    │ 49163    │ 10D    │ 0    │ online    │ 0%       │ 29.8mb   │ crogers… │ disabled │
│ 8  │ permit-scheduler         │ default     │ 1.0.0   │ fork    │ 835593   │ 7D     │ 1    │ online    │ 0%       │ 38.3mb   │ crogers… │ disabled │
│ 9  │ permit-tracker           │ default     │ N/A     │ fork    │ 983533   │ 3D     │ 5    │ online    │ 0.3%     │ 67.3mb   │ crogers… │ disabled │
│ 29 │ pindex                   │ default     │ 0.1.0   │ fork    │ 3913811  │ 3D     │ 0    │ online    │ 1.9%     │ 40.5mb   │ crogers… │ disabled │
│ 12 │ quest-scheduler          │ default     │ N/A     │ fork    │ 49190    │ 10D    │ 0    │ online    │ 0%       │ 28.1mb   │ crogers… │ disabled │
│ 4  │ t5gemma-vision           │ default     │ N/A     │ fork    │ 49059    │ 10D    │ 0    │ online    │ 0.3%     │ 99.0mb   │ crogers… │ disabled │
│ 11 │ tmux-web                 │ default     │ N/A     │ fork    │ 49184    │ 10D    │ 0    │ online    │ 0%       │ 10.1mb   │ crogers… │ disabled │
└────┴──────────────────────────┴─────────────┴─────────┴─────────┴──────────┴────────┴──────┴───────────┴──────────┴──────────┴──────────┴──────────┘


Let me wait for the server to come back and then try again with safer settings.

sleep 30 && curl -s http://localhost:7860 | head -3


Command still running (session wild-valley, pid 3545718). Use process (list/poll/log/write/kill/clear/remove) for follow-up.


curl -s http://localhost:7860 | head -3 || echo "Still restarting..."


(no output)


The server is still restarting. Let me wait a bit more.

sleep 60 && curl -s http://localhost:7860 | head -3


Command still running (session amber-rook, pid 3550183). Use process (list/poll/log/write/kill/clear/remove) for follow-up.


Still waiting for the server. Let me check the PM2 status.

pm2 logs acestep --lines 10 2>/dev/null | tail -10


Command still running (session tender-forest, pid 3553776). Use process (list/poll/log/write/kill/clear/remove) for follow-up.


Let me check if the server is up by checking the port.

ss -tlnp | grep 7860 && curl -s http://localhost:7860 | head -3


The server is still restarting. Let me wait a bit more and check again.


Command still running (session marine-atlas, pid 3557903). Use process (list/poll/log/write/kill/clear/remove) for follow-up.


LISTEN 0      2048                       0.0.0.0:7860       0.0.0.0:*


Good, the server is back up. Let me try generating again with safer settings - not pushing the CFG scale too high.

Server's back. Trying again with safer settings:

write

#!/usr/bin/env python3
"""Generate Seventeen Years with clear enunciation - safer settings"""
from gradio_client import Client, handle_file
import shutil

lyrics = """Seventeen summers, yeah, we've seen 'em all
From the playground dirt to the weight room wall
Brody's got the rhythm, Chase provides the frame
Different shades of skin, but the heartbeat's the same
We don't need the words, we got the shorthand down
The kings of the gym in this quiet town

Is it the pump, or is it the heat?
The way the air stops when our eyes meet?
Lotion on the skin, making shadows glow
One side ebony, one side like the snow
They're whispering "too close," watching from the side
But we're the Jim and Pam with nowhere to hide
Just a heavy lift and a heart on the line
In the friction and the shine

Spotting on the bench, I can feel the breath
A brotherhood bond that's cheating death
Working through the sweat, working through the "why"
There's a tension in the room that we can't deny
Is it Dwight and Angela? Is it something more?
Leave the questions hanging at the locker room door

Seventeen years, that's a lifetime of "almost"
Closer than a shadow, closer than a ghost
We're the main characters, let the cameras roll
Two different bodies, but a single soul

Lotion on the palms, iron in the hand...
Nobody else has to understand
(Will they? Won't they?)
Just keep the rhythm
Just keep the shine"""

print("Connecting to ACE-Step server...")
client = Client("http://localhost:7860")

print("Generating with clear vocal enunciation...")
result = client.predict(
    api_name="/generation_wrapper",
    param_0="Melodic R&B, mid-tempo synth-pop, heavy bass, smooth male vocals with clear enunciation, crisp articulation, intelligible lyrics, clean vocal production, sharp vocal clarity",
    param_1=lyrics,
    param_2=95,
    param_3="C Minor",
    param_4="4",
    param_5="en",
    param_6=12,
    param_7=7.0,
    param_8=True,
    param_9="-1",
    param_10=None,
    param_11=60,
    param_12=1,
    param_13=None,
    param_14="",
    param_15=0.0,
    param_16=-1,
    param_17="Fill the audio semantic mask based on the given conditions:",
    param_18=1.0,
    param_19="text2music",
    param_20=False,
    param_21=0.0,
    param_22=1.0,
    param_23=3.0,
    param_24="ode",
    param_25="",
    param_26="mp3",
    param_27=0.7,
    param_28=True,
    param_29=2.0,
    param_30=0,
    param_31=0.9,
    param_32="country, acoustic guitar, twang, rock, metal, high pitched, screeching, muddy vocals, unclear",
    param_33=True,
    param_34=True,
    param_35=True,
    param_37=False,
    param_38=True,
    param_39=False,
    param_40=False,
    param_41=0.5,
    param_42=8,
    param_43=None,
    param_44=[],
    param_45=False
)

print("\n✅ Generation complete!")

if result and len(result) > 8:
    audio_files = result[8]
    if audio_files and len(audio_files) > 0:
        audio_path = audio_files[0]
        print(f"\n🎵 Generated: {audio_path}")

        output_path = "/home/crogers2287/ACE-Step-1.5/outputs/seventeen_years_clear.mp3"
        shutil.copy(audio_path, output_path)
        print(f"📁 Saved to: {output_path}")
        print(f"📊 Size: {shutil.os.path.getsize(output_path) / 1024:.0f}KB")


Successfully wrote 3233 bytes to /tmp/generate_clear_safe.py


Conversation info (untrusted metadata):
```json
{
  "conversation_label": "Skinny (@skinnyc813) id:6558388607"
}
```

What happened?


The user is asking what happened. The CUDA error crashed the GPU. Let me explain and then run the safer version.

The GPU crashed with a CUDA error when I pushed the settings too high. Let me run it again with safer parameters:

exec

cd ~/ACE-Step-1.5 && uv run python /tmp/generate_clear_safe.py 2>&1


Command still running (session brisk-basil, pid 3582014). Use process (list/poll/log/write/kill/clear/remove) for follow-up.


Connecting to ACE-Step server...
Loaded as API: http://localhost:7860/
Generating with clear vocal enunciation...

✅ Generation complete!

🎵 Generated: /tmp/gradio/2b729d7d55a030665e77304719ad7a33f6c72d6f6e9ed1feacb0d4a1a0988dc4/24915a49-316a-cc82-7a73-3b86fee117d6.mp3
📁 Saved to: /home/crogers2287/ACE-Step-1.5/outputs/seventeen_years_clear.mp3
📊 Size: 938KB

Process exited with code 0.


The generation completed successfully. Now let me copy it to /tmp and send it.


message

Seventeen Years - Clear vocals version, better enunciation


Sent. Let me provide a summary of what I changed for clearer vocals.

Done. Here's the new version with clearer enunciation:

**Changes made:**
- Added "clear enunciation, crisp articulation, intelligible lyrics" to the prompt
- Added "sharp vocal clarity" to the caption
- Kept the LM temperature at 0.7 (lower = more precise)
- Used safer CFG settings to avoid the GPU crash

See if the vocals are clearer now. If not, I can try lowering the temperature further or adding specific pronunciation cues.


System: [2026-02-15 13:29:39 UTC] Exec completed (brisk-ba, code 0) :: Connecting to ACE-Step server... Loaded as API: http://localhost:7860/ Generating with clear vocal enunciation... ✅ Generation complete! 🎵 Generated: /tmp/gradio/2b729d7d55a030665e77304719ad7a33f6c72d6f6e9ed1feacb0d4a1a0988dc4/24915a49-316a-cc82-7a73-3b86fee117d6.mp3 📁 Saved to: /home/crogers2287/ACE-Step-1.5/outputs/seventeen_years_clear.mp3 📊 Size: 938KB

Conversation info (untrusted metadata):
```json
{
  "conversation_label": "Skinny (@skinnyc813) id:6558388607"
}
```

Do you see any music video generation workflows using comfy?


The user is asking if I know of any music video generation workflows using ComfyUI. This is a general knowledge question about AI workflows, not related to the previous conversation about ACE-Step.

I should search for information about music video generation workflows using ComfyUI and share what I find.

Question: ComfyUI music video generation workflow AI audio reactive


Question: ComfyUI music video generation workflow AI audio reactive

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
GitHub - yvann-ba/ComfyUI_Yvann-Nodes: Audio Reactivity Nodes for ComfyUI 🔊 Create AI generated audio-driven animations — drop a ⭐ if you like the repo ((:
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
Create Audio Reactive AI videos, enable controls over AI generations styles, content and composition with any audio · Simple: Just Drop one of our Workflows in ComfyUI and specify your audio and visuals input
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
r/comfyui on Reddit: Just created this AI animation in 20min using Audio-Reactive nodes in ComfyUI, Why do I feel like no one is interested in audio-reactivity + AI ?
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
Hey ! I made an audio-reactive AI free workflow on ComfyUI that enables you to generate ai videos guided by your music !
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
r/comfyui on Reddit: Audio-Reactive Music Workflow
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
This workflow allows you to take a still image, animate it, then use the animation in a video that reacts to different parts of music. For my example…
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
r/comfyui on Reddit: What is the best model for automatically generating audio from video?
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
I've tried using the mmaudio model, but the results are practically unusable. Is there any other better model or method that automatically generates…
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
GitHub - ryanontheinside/ComfyUI_RyanOnTheInside: Everything-Reactivity in ComfyUI (audio, MIDI, motion, proximity, and more). Animate and manipulate images, masks, videos, audio, and more. Native ACEStep extensions
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
Everything Reactivity: Almost all nodes in this pack can be made to react to audio, MIDI, motion, time, color, depth, brightness, and more, allowing for incredibly dynamic and responsive workflows.
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

Question: ComfyUI music video generation workflow AI audio reactive


I found several options for music video generation workflows in ComfyUI. Let me get more details about the most promising ones.

Question: ComfyUI ACE-Step music video generation workflow RyanOnTheInside


Question: ComfyUI ACE-Step music video generation workflow RyanOnTheInside

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
ComfyUI ACE-Step Native Example - ComfyUI
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
Download Json Format Workflow File You can also manually download ace_step_v1_3.5b.safetensors and save it to the ComfyUI/models/checkpoints folder · Ensure the Load Checkpoints node has loaded the ace_step_v1_3.5b.safetensors model · (Optional) In the EmptyAceStepLatentAudio node, you can set the duration of the music to be generated
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
ACE-Step ComfyUI Native and Custom Node Workflow Guide | ComfyUI Wiki
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
In this documentation, we will combine native workflows and custom nodes to complete the ACE-Step workflow. You may have already downloaded this file. Below is an explanation of the two ACE-Step implementation methods in ComfyUI. Advantages: Uses merged All-in-one model, convenient loading, simple to use · Disadvantages: Doesn’t support direct multi-language input, requires converting corresponding languages to English characters for music generation
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
r/StableDiffusion on Reddit: ACE-Step 1.5 Full Feature Support for ComfyUI - Edit, Cover, Extract & More
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
Example workflows on GitHub: - Cover workflow: https://github.com/ryanontheinside/ComfyUI_RyanOnTheInside/blob/main/examples/ace1.5/audio_ace_step_1_5_cover.json
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
ACE-Step 1.5 Cover Guider Style transfer/regeneration using semantic guidance from source audio. Uses semantic tokens extracted from source audio as structural guidance · Generates new content with different style/timbre while preserving musical structure · Semantic hints are auto-extracted or can be provided manually for advanced workflows
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
Local AI Music Generation in ComfyUI - ACE-Step 1.5 Setup Tutorial - Tech Tactician
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

<<<EXTERNAL_UNTRUSTED_CONTENT>>>
Source: Web Search
---
If your goal is text → music: use ACE-Step 1.5 native workflows (this guide’s main path). If your goal is music → music / repainting / segment editing inside ComfyUI right now, the older path available via templates is still the ACE-Step v1 (3.5B) workflows (temporary fallback until full 1.5 feature exposure lands in ComfyUI).
<<<END_EXTERNAL_UNTRUSTED_CONTENT>>>

Question: ComfyUI ACE-Step music video generation workflow RyanOnTheInside


I found some good options. Let me summarize what I found for the user about music video generation workflows using ComfyUI.

Yes, there are several music video generation workflows for ComfyUI. Here are the best options:

## 1. **RyanOnTheInside (ACE-Step 1.5 + Everything-Reactivity)**
- **GitHub:** `ryanontheinside/ComfyUI_RyanOnTheInside`
- **Features:** Native ACE-Step 1.5 extensions + audio/MIDI/motion reactivity
- **What it does:**
  - Generate music with ACE-Step 1.5 inside ComfyUI
  - Make **video content react to the music** (beat detection, frequency analysis)
  - Animate images/videos synced to audio
  - Cover generation, style transfer, semantic editing
- **Workflows available:** Cover workflow, text-to-music, audio reactive video

## 2. **Yvann-Nodes (Audio Reactivity)**
- **GitHub:** `yvann-ba/ComfyUI_Yvann-Nodes`
- **Features:** Drop-in workflows for audio-driven AI animations
- **Use case:** Take a still image, animate it, and sync it to music

## 3. **ComfyUI Native ACE-Step**
- **Built-in:** ComfyUI has native ACE-Step support now
- **Model:** `ace_step_v1_3.5b.safetensors` or ACE-Step 1.5
- **Workflows:** Text-to-music, cover generation, editing

## For Music Videos Specifically:

The **RyanOnTheInside** workflow seems best for your use case because it combines:
1. **Music generation** (ACE-Step 1.5)
2. **Video generation** (animated images/video)
3. **Audio reactivity** (video syncs to the beat/frequency of the generated music)

Want me to help set up any of these workflows?


Conversation info (untrusted metadata):
```json
{
  "conversation_label": "Skinny (@skinnyc813) id:6558388607"
}
```

Go ahead and set it up please


The user wants me to set up a ComfyUI music video generation workflow. This involves installing RyanOnTheInside's ComfyUI nodes which include ACE-Step 1.5 support and audio reactivity features.

Let me check if ComfyUI is already installed, and if not, set it up with the necessary custom nodes.

exec

find ~ -type d -name "ComfyUI" 2>/dev/null | head -5


Command still running (session quick-bison, pid 3765578). Use process (list/poll/log/write/kill/clear/remove) for follow-up.


Let me wait for the search to complete or try a different approach.


(no new output)

Process still running.


The search is taking too long. Let me try a simpler check.

ls -la ~/ComfyUI 2>/dev/null || ls -la /opt/ComfyUI 2>/dev/null || echo "ComfyUI not found in common locations"


ComfyUI not found in common locations


ComfyUI is not installed. I need to set it up. Let me install ComfyUI and then add the RyanOnTheInside custom nodes for ACE-Step 1.5 and audio reactivity.

ComfyUI isn't installed. Setting it up now with the RyanOnTheInside nodes for ACE-Step 1.5 and audio-reactive video generation:

cd ~ && git clone https://github.com/comfyanonymous/ComfyUI.git 2>&1 | tail -5


Cloning into 'ComfyUI'...


Good, ComfyUI is cloning. Let me wait for it to finish and then install the custom nodes.


Command still running (session briny-ember, pid 3773109). Use process (list/poll/log/write/kill/clear/remove) for follow-up.


ls -la ~/ComfyUI 2>/dev/null | head -10 || echo "Still cloning..."


total 524
drwxrwxr-x  24 crogers2287 crogers2287   4096 Feb 15 13:46 .
drwxr-xr-x 306 crogers2287 crogers2287  28672 Feb 15 13:46 ..
drwxrwxr-x   6 crogers2287 crogers2287   4096 Feb 15 13:46 .ci
drwxrwxr-x   8 crogers2287 crogers2287   4096 Feb 15 13:46 .git
-rw-rw-r--   1 crogers2287 crogers2287    112 Feb 15 13:46 .gitattributes
drwxrwxr-x   5 crogers2287 crogers2287   4096 Feb 15 13:46 .github
-rw-rw-r--   1 crogers2287 crogers2287    382 Feb 15 13:46 .gitignore
-rw-rw-r--   1 crogers2287 crogers2287     47 Feb 15 13:46 CODEOWNERS
-rw-rw-r--   1 crogers2287 crogers2287   1882 Feb 15 13:46 CONTRIBUTING.md


ComfyUI is cloned. Now I need to:
1. Install the requirements
2. Clone the RyanOnTheInside custom nodes
3. Set up the models

Let me do this step by step.

cd ~/ComfyUI && pip install -r requirements.txt 2>&1 | tail -10


sure you have python3-full installed.

    If you wish to install a non-Debian packaged Python application,
    it may be easiest to use pipx install xyz, which will manage a
    virtual environment for you. Make sure you have pipx installed.

    See /usr/share/doc/python3.12/README.venv for more information.

note: If you believe this is a mistake, please contact your Python installation or OS distribution provider. You can override this, at the risk of breaking your Python installation or OS, by passing --break-system-packages.
hint: See PEP 668 for the detailed specification.


I need to use a virtual environment or use the --break-system-packages flag. Let me use a virtual environment for ComfyUI.

cd ~/ComfyUI && python3 -m venv venv && source venv/bin/activate && pip install -r requirements.txt 2>&1 | tail -10


Command still running (session keen-crustacean, pid 3778317). Use process (list/poll/log/write/kill/clear/remove) for follow-up.


Let me check the progress and then install the custom nodes.


Still installing. Let me wait and check again.

sleep 60 && ls -la ~/ComfyUI/venv/lib/python*/site-packages/ 2>/dev/null | head -5 || echo "Still installing..."


Command still running (session lucky-haven, pid 3782315). Use process (list/poll/log/write/kill/clear/remove) for follow-up.


(no output yet)


Let me check if pip is still running or completed.

ps aux | grep "pip install" | grep -v grep || echo "pip install completed or not running"


crogers+ 3778317  0.0  0.0   4752  2880 ?        Ss   13:47   0:00 /bin/bash -c cd ~/ComfyUI && python3 -m venv venv && source venv/bin/activate && pip install -r requirements.txt 2>&1 | tail -10
crogers+ 3779043 77.2  0.1 306532 218676 ?       R    13:47   0:31 /home/crogers2287/ComfyUI/venv/bin/python3 /home/crogers2287/ComfyUI/venv/bin/pip install -r requirements.txt


Still installing. Let me wait for it to complete.

sleep 60 && echo "Waiting for pip to finish..."


Command still running (session dawn-cedar, pid 3787117). Use process (list/poll/log/write/kill/clear/remove) for follow-up.


Let me check if the installation is done.


ps aux | grep "pip install" | grep -v grep | wc -l


Command still running (session lucky-breeze, pid 3791892). Use process (list/poll/log/write/kill/clear/remove) for follow-up.


Let me check the pip process status again.