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This service provides an HTTP-based asynchronous music generation API.
Basic Workflow:
- Call
POST /release_taskto submit a task and obtain atask_id. - Call
POST /query_resultto batch query task status untilstatusis1(succeeded) or2(failed). - Download audio files via
GET /v1/audio?path=...URLs returned in the result.
- Authentication
- Response Format
- Task Status Description
- Create Generation Task
- Batch Query Task Results
- Format Input
- Get Random Sample
- List Available Models
- Server Statistics
- Download Audio Files
- Health Check
- Environment Variables
The API supports optional API key authentication. When enabled, a valid key must be provided in requests.
Two authentication methods are supported:
Method A: ai_token in request body
{
"ai_token": "your-api-key",
"prompt": "upbeat pop song",
...
}Method B: Authorization header
curl -X POST http://localhost:8001/release_task \
-H 'Authorization: Bearer your-api-key' \
-H 'Content-Type: application/json' \
-d '{"prompt": "upbeat pop song"}'Set via environment variable or command-line argument:
# Environment variable
export ACESTEP_API_KEY=your-secret-key
# Or command-line argument
python -m acestep.api_server --api-key your-secret-keyAll API responses use a unified wrapper format:
{
"data": { ... },
"code": 200,
"error": null,
"timestamp": 1700000000000,
"extra": null
}| Field | Type | Description |
|---|---|---|
data |
any | Actual response data |
code |
int | Status code (200=success) |
error |
string | Error message (null on success) |
timestamp |
int | Response timestamp (milliseconds) |
extra |
any | Extra information (usually null) |
Task status (status) is represented as integers:
| Status Code | Status Name | Description |
|---|---|---|
0 |
queued/running | Task is queued or in progress |
1 |
succeeded | Generation succeeded, result is ready |
2 |
failed | Generation failed |
- URL:
/release_task - Method:
POST - Content-Type:
application/json,multipart/form-data, orapplication/x-www-form-urlencoded
The API supports both snake_case and camelCase naming for most parameters. For example:
audio_duration/duration/audioDurationkey_scale/keyscale/keyScaletime_signature/timesignature/timeSignaturesample_query/sampleQuery/description/descuse_format/useFormat/format
Additionally, metadata can be passed in a nested object (metas, metadata, or user_metadata).
Suitable for passing only text parameters, or referencing audio file paths that already exist on the server.
Basic Parameters:
| Parameter Name | Type | Default | Description |
|---|---|---|---|
prompt |
string | "" |
Music description prompt (alias: caption) |
lyrics |
string | "" |
Lyrics content |
thinking |
bool | false |
Whether to use 5Hz LM to generate audio codes (lm-dit behavior) |
vocal_language |
string | "en" |
Lyrics language (en, zh, ja, etc.) |
audio_format |
string | "mp3" |
Output format (mp3, wav, flac) |
Sample/Description Mode Parameters:
| Parameter Name | Type | Default | Description |
|---|---|---|---|
sample_mode |
bool | false |
Enable random sample generation mode (auto-generates caption/lyrics/metas via LM) |
sample_query |
string | "" |
Natural language description for sample generation (e.g., "a soft Bengali love song"). Aliases: description, desc |
use_format |
bool | false |
Use LM to enhance/format the provided caption and lyrics. Alias: format |
Multi-Model Support:
| Parameter Name | Type | Default | Description |
|---|---|---|---|
model |
string | null | Select which DiT model to use (e.g., "acestep-v15-turbo", "acestep-v15-turbo-shift3"). Use /v1/models to list available models. If not specified, uses the default model. |
thinking Semantics (Important):
thinking=false:- The server will NOT use 5Hz LM to generate
audio_code_string. - DiT runs in text2music mode and ignores any provided
audio_code_string.
- The server will NOT use 5Hz LM to generate
thinking=true:- The server will use 5Hz LM to generate
audio_code_string(lm-dit behavior). - DiT runs with LM-generated codes for enhanced music quality.
- The server will use 5Hz LM to generate
Metadata Auto-Completion (Conditional):
When use_cot_caption=true or use_cot_language=true or metadata fields are missing, the server may call 5Hz LM to fill the missing fields based on caption/lyrics:
bpmkey_scaletime_signatureaudio_duration
User-provided values always win; LM only fills the fields that are empty/missing.
Music Attribute Parameters:
| Parameter Name | Type | Default | Description |
|---|---|---|---|
bpm |
int | null | Specify tempo (BPM), range 30-300 |
key_scale |
string | "" |
Key/scale (e.g., "C Major", "Am"). Aliases: keyscale, keyScale |
time_signature |
string | "" |
Time signature (2, 3, 4, 6 for 2/4, 3/4, 4/4, 6/8). Aliases: timesignature, timeSignature |
audio_duration |
float | null | Generation duration (seconds), range 10-600. Aliases: duration, target_duration |
Audio Codes (Optional):
| Parameter Name | Type | Default | Description |
|---|---|---|---|
audio_code_string |
string or string[] | "" |
Audio semantic tokens (5Hz) for llm_dit. Alias: audioCodeString |
Generation Control Parameters:
| Parameter Name | Type | Default | Description |
|---|---|---|---|
inference_steps |
int | 8 |
Number of inference steps. Turbo model: 1-20 (recommended 8). Base model: 1-200 (recommended 32-64). |
guidance_scale |
float | 7.0 |
Prompt guidance coefficient. Only effective for base model. |
use_random_seed |
bool | true |
Whether to use random seed |
seed |
int | -1 |
Specify seed (when use_random_seed=false) |
batch_size |
int | 2 |
Batch generation count (max 8) |
Advanced DiT Parameters:
| Parameter Name | Type | Default | Description |
|---|---|---|---|
shift |
float | 3.0 |
Timestep shift factor (range 1.0-5.0). Only effective for base models, not turbo models. |
infer_method |
string | "ode" |
Diffusion inference method: "ode" (Euler, faster) or "sde" (stochastic). |
timesteps |
string | null | Custom timesteps as comma-separated values (e.g., "0.97,0.76,0.615,0.5,0.395,0.28,0.18,0.085,0"). Overrides inference_steps and shift. |
use_adg |
bool | false |
Use Adaptive Dual Guidance (base model only) |
cfg_interval_start |
float | 0.0 |
CFG application start ratio (0.0-1.0) |
cfg_interval_end |
float | 1.0 |
CFG application end ratio (0.0-1.0) |
5Hz LM Parameters (Optional, server-side):
These parameters control 5Hz LM sampling, used for metadata auto-completion and (when thinking=true) codes generation.
| Parameter Name | Type | Default | Description |
|---|---|---|---|
lm_model_path |
string | null | 5Hz LM checkpoint dir name (e.g. acestep-5Hz-lm-0.6B) |
lm_backend |
string | "vllm" |
vllm or pt |
lm_temperature |
float | 0.85 |
Sampling temperature |
lm_cfg_scale |
float | 2.5 |
CFG scale (>1 enables CFG) |
lm_negative_prompt |
string | "NO USER INPUT" |
Negative prompt used by CFG |
lm_top_k |
int | null | Top-k (0/null disables) |
lm_top_p |
float | 0.9 |
Top-p (>=1 will be treated as disabled) |
lm_repetition_penalty |
float | 1.0 |
Repetition penalty |
LM CoT (Chain-of-Thought) Parameters:
| Parameter Name | Type | Default | Description |
|---|---|---|---|
use_cot_caption |
bool | true |
Let LM rewrite/enhance the input caption via CoT reasoning. Aliases: cot_caption, cot-caption |
use_cot_language |
bool | true |
Let LM detect vocal language via CoT. Aliases: cot_language, cot-language |
constrained_decoding |
bool | true |
Enable FSM-based constrained decoding for structured LM output. Aliases: constrainedDecoding, constrained |
constrained_decoding_debug |
bool | false |
Enable debug logging for constrained decoding |
allow_lm_batch |
bool | true |
Allow LM batch processing for efficiency |
Edit/Reference Audio Parameters (requires absolute path on server):
| Parameter Name | Type | Default | Description |
|---|---|---|---|
reference_audio_path |
string | null | Reference audio path (Style Transfer) |
src_audio_path |
string | null | Source audio path (Repainting/Cover) |
task_type |
string | "text2music" |
Task type: text2music, cover, repaint, lego, extract, complete |
instruction |
string | auto | Edit instruction (auto-generated based on task_type if not provided) |
repainting_start |
float | 0.0 |
Repainting start time (seconds) |
repainting_end |
float | null | Repainting end time (seconds), -1 for end of audio |
audio_cover_strength |
float | 1.0 |
Cover strength (0.0-1.0). Lower values (0.2) for style transfer. |
Use this when you need to upload local audio files as reference or source audio.
In addition to supporting all the above fields as Form Fields, the following file fields are also supported:
reference_audioorref_audio: (File) Upload reference audio filesrc_audioorctx_audio: (File) Upload source audio file
Note: After uploading files, the corresponding
_pathparameters will be automatically ignored, and the system will use the temporary file path after upload.
{
"data": {
"task_id": "550e8400-e29b-41d4-a716-446655440000",
"status": "queued",
"queue_position": 1
},
"code": 200,
"error": null,
"timestamp": 1700000000000,
"extra": null
}Basic JSON Method:
curl -X POST http://localhost:8001/release_task \
-H 'Content-Type: application/json' \
-d '{
"prompt": "upbeat pop song",
"lyrics": "Hello world",
"inference_steps": 8
}'With thinking=true (LM generates codes + fills missing metas):
curl -X POST http://localhost:8001/release_task \
-H 'Content-Type: application/json' \
-d '{
"prompt": "upbeat pop song",
"lyrics": "Hello world",
"thinking": true,
"lm_temperature": 0.85,
"lm_cfg_scale": 2.5
}'Description-driven generation (sample_query):
curl -X POST http://localhost:8001/release_task \
-H 'Content-Type: application/json' \
-d '{
"sample_query": "a soft Bengali love song for a quiet evening",
"thinking": true
}'With format enhancement (use_format=true):
curl -X POST http://localhost:8001/release_task \
-H 'Content-Type: application/json' \
-d '{
"prompt": "pop rock",
"lyrics": "[Verse 1]\nWalking down the street...",
"use_format": true,
"thinking": true
}'Select specific model:
curl -X POST http://localhost:8001/release_task \
-H 'Content-Type: application/json' \
-d '{
"prompt": "electronic dance music",
"model": "acestep-v15-turbo",
"thinking": true
}'With custom timesteps:
curl -X POST http://localhost:8001/release_task \
-H 'Content-Type: application/json' \
-d '{
"prompt": "jazz piano trio",
"timesteps": "0.97,0.76,0.615,0.5,0.395,0.28,0.18,0.085,0",
"thinking": true
}'File Upload Method:
curl -X POST http://localhost:8001/release_task \
-F "prompt=remix this song" \
-F "src_audio=@/path/to/local/song.mp3" \
-F "task_type=repaint"- URL:
/query_result - Method:
POST - Content-Type:
application/jsonorapplication/x-www-form-urlencoded
| Parameter Name | Type | Description |
|---|---|---|
task_id_list |
string (JSON array) or array | List of task IDs to query |
{
"data": [
{
"task_id": "550e8400-e29b-41d4-a716-446655440000",
"status": 1,
"result": "[{\"file\": \"/v1/audio?path=...\", \"wave\": \"\", \"status\": 1, \"create_time\": 1700000000, \"env\": \"development\", \"prompt\": \"upbeat pop song\", \"lyrics\": \"Hello world\", \"metas\": {\"bpm\": 120, \"duration\": 30, \"genres\": \"\", \"keyscale\": \"C Major\", \"timesignature\": \"4\"}, \"generation_info\": \"...\", \"seed_value\": \"12345,67890\", \"lm_model\": \"acestep-5Hz-lm-0.6B\", \"dit_model\": \"acestep-v15-turbo\"}]"
}
],
"code": 200,
"error": null,
"timestamp": 1700000000000,
"extra": null
}Result Field Description (result is a JSON string, after parsing contains):
| Field | Type | Description |
|---|---|---|
file |
string | Audio file URL (use with /v1/audio endpoint) |
wave |
string | Waveform data (usually empty) |
status |
int | Status code (0=in progress, 1=success, 2=failed) |
create_time |
int | Creation time (Unix timestamp) |
env |
string | Environment identifier |
prompt |
string | Prompt used |
lyrics |
string | Lyrics used |
metas |
object | Metadata (bpm, duration, genres, keyscale, timesignature) |
generation_info |
string | Generation info summary |
seed_value |
string | Seed values used (comma-separated) |
lm_model |
string | LM model name used |
dit_model |
string | DiT model name used |
curl -X POST http://localhost:8001/query_result \
-H 'Content-Type: application/json' \
-d '{
"task_id_list": ["550e8400-e29b-41d4-a716-446655440000"]
}'- URL:
/format_input - Method:
POST
This endpoint uses LLM to enhance and format user-provided caption and lyrics.
| Parameter Name | Type | Default | Description |
|---|---|---|---|
prompt |
string | "" |
Music description prompt |
lyrics |
string | "" |
Lyrics content |
temperature |
float | 0.85 |
LM sampling temperature |
param_obj |
string (JSON) | "{}" |
JSON object containing metadata (duration, bpm, key, time_signature, language) |
{
"data": {
"caption": "Enhanced music description",
"lyrics": "Formatted lyrics...",
"bpm": 120,
"key_scale": "C Major",
"time_signature": "4",
"duration": 180,
"vocal_language": "en"
},
"code": 200,
"error": null,
"timestamp": 1700000000000,
"extra": null
}curl -X POST http://localhost:8001/format_input \
-H 'Content-Type: application/json' \
-d '{
"prompt": "pop rock",
"lyrics": "Walking down the street",
"param_obj": "{\"duration\": 180, \"language\": \"en\"}"
}'- URL:
/create_random_sample - Method:
POST
This endpoint returns random sample parameters from pre-loaded example data for form filling.
| Parameter Name | Type | Default | Description |
|---|---|---|---|
sample_type |
string | "simple_mode" |
Sample type: "simple_mode" or "custom_mode" |
{
"data": {
"caption": "Upbeat pop song with guitar accompaniment",
"lyrics": "[Verse 1]\nSunshine on my face...",
"bpm": 120,
"key_scale": "G Major",
"time_signature": "4",
"duration": 180,
"vocal_language": "en"
},
"code": 200,
"error": null,
"timestamp": 1700000000000,
"extra": null
}curl -X POST http://localhost:8001/create_random_sample \
-H 'Content-Type: application/json' \
-d '{"sample_type": "simple_mode"}'- URL:
/v1/models - Method:
GET
Returns a list of available DiT models loaded on the server.
{
"data": {
"models": [
{
"name": "acestep-v15-turbo",
"is_default": true
},
{
"name": "acestep-v15-turbo-shift3",
"is_default": false
}
],
"default_model": "acestep-v15-turbo"
},
"code": 200,
"error": null,
"timestamp": 1700000000000,
"extra": null
}curl http://localhost:8001/v1/models- URL:
/v1/stats - Method:
GET
Returns server runtime statistics.
{
"data": {
"jobs": {
"total": 100,
"queued": 5,
"running": 1,
"succeeded": 90,
"failed": 4
},
"queue_size": 5,
"queue_maxsize": 200,
"avg_job_seconds": 8.5
},
"code": 200,
"error": null,
"timestamp": 1700000000000,
"extra": null
}curl http://localhost:8001/v1/stats- URL:
/v1/audio - Method:
GET
Download generated audio files by path.
| Parameter Name | Type | Description |
|---|---|---|
path |
string | URL-encoded path to the audio file |
# Download using the URL from task result
curl "http://localhost:8001/v1/audio?path=%2Ftmp%2Fapi_audio%2Fabc123.mp3" -o output.mp3- URL:
/health - Method:
GET
Returns service health status.
{
"data": {
"status": "ok",
"service": "ACE-Step API",
"version": "1.0"
},
"code": 200,
"error": null,
"timestamp": 1700000000000,
"extra": null
}The API server can be configured using environment variables:
| Variable | Default | Description |
|---|---|---|
ACESTEP_API_HOST |
127.0.0.1 |
Server bind host |
ACESTEP_API_PORT |
8001 |
Server bind port |
ACESTEP_API_KEY |
(empty) | API authentication key (empty disables auth) |
ACESTEP_API_WORKERS |
1 |
API worker thread count |
| Variable | Default | Description |
|---|---|---|
ACESTEP_CONFIG_PATH |
acestep-v15-turbo |
Primary DiT model path |
ACESTEP_CONFIG_PATH2 |
(empty) | Secondary DiT model path (optional) |
ACESTEP_CONFIG_PATH3 |
(empty) | Third DiT model path (optional) |
ACESTEP_DEVICE |
auto |
Device for model loading |
ACESTEP_USE_FLASH_ATTENTION |
true |
Enable flash attention |
ACESTEP_OFFLOAD_TO_CPU |
false |
Offload models to CPU when idle |
ACESTEP_OFFLOAD_DIT_TO_CPU |
false |
Offload DiT specifically to CPU |
| Variable | Default | Description |
|---|---|---|
ACESTEP_INIT_LLM |
auto | Whether to initialize LM at startup (auto determines based on GPU) |
ACESTEP_LM_MODEL_PATH |
acestep-5Hz-lm-0.6B |
Default 5Hz LM model |
ACESTEP_LM_BACKEND |
vllm |
LM backend (vllm or pt) |
ACESTEP_LM_DEVICE |
(same as ACESTEP_DEVICE) | Device for LM |
ACESTEP_LM_OFFLOAD_TO_CPU |
false |
Offload LM to CPU |
| Variable | Default | Description |
|---|---|---|
ACESTEP_QUEUE_MAXSIZE |
200 |
Maximum queue size |
ACESTEP_QUEUE_WORKERS |
1 |
Number of queue workers |
ACESTEP_AVG_JOB_SECONDS |
5.0 |
Initial average job duration estimate |
ACESTEP_AVG_WINDOW |
50 |
Window for averaging job duration |
| Variable | Default | Description |
|---|---|---|
ACESTEP_TMPDIR |
.cache/acestep/tmp |
Temporary file directory |
TRITON_CACHE_DIR |
.cache/acestep/triton |
Triton cache directory |
TORCHINDUCTOR_CACHE_DIR |
.cache/acestep/torchinductor |
TorchInductor cache directory |
HTTP Status Codes:
200: Success400: Invalid request (bad JSON, missing fields)401: Unauthorized (missing or invalid API key)404: Resource not found415: Unsupported Content-Type429: Server busy (queue is full)500: Internal server error
Error Response Format:
{
"detail": "Error message describing the issue"
}-
Use
thinking=truefor best quality results with LM-enhanced generation. -
Use
sample_query/descriptionfor quick generation from natural language descriptions. -
Use
use_format=truewhen you have caption/lyrics but want LM to enhance them. -
Batch query task status using the
/query_resultendpoint to query multiple tasks at once. -
Check
/v1/statsto understand server load and average job time. -
Use multi-model support by setting
ACESTEP_CONFIG_PATH2andACESTEP_CONFIG_PATH3environment variables, then select with themodelparameter. -
For production, set
ACESTEP_API_KEYto enable authentication and secure your API. -
For low VRAM environments, enable
ACESTEP_OFFLOAD_TO_CPU=trueto support longer audio generation.