Bytedance Uso API Documentation
Playground
Try it on WaveSpeedAI!USO (Unified Style-Subject Optimized) by unifies style-driven and subject-driven generation to produce consistent outputs that blend artistic style with subject fidelity. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Features
USO combines subject and style references to generate images that follow your prompt while preserving visual qualities from the supplied references.
Why Choose This?
-
Subject and style guidance
Use reference images to guide the subject, identity, appearance, or visual style of the generated image. -
Multi-reference input
Provide up to four reference images in a single request. -
Prompt-guided generation
Add a prompt to describe the desired image, or leave it empty for reference-driven generation. -
Reproducible results
Set a seed to make generations easier to reproduce.
Parameters
| Parameter | Required | Description |
|---|---|---|
reference_images | Yes | One to four reference images. The first image is used as the content reference; following images provide style or additional visual references. |
prompt | No | Text instructions for the generated image. May be left empty for reference-driven generation. |
seed | No | Random seed for reproducible generation. Use -1 for a random seed. |
sync_model | No | Sync the model to the latest version. Default: false. |
How to Use
- Add one to four images to
reference_images. - Put the main content reference first, followed by any style or additional references.
- Add a prompt to describe the desired result, or leave it empty for reference-driven generation.
- Set a seed for reproducible results, or use
-1for a random seed. - Submit the request and retrieve the generated image URL from the result.
Pricing
Pricing is $0.50 per generated image, based on an output limit of up to 4 MP.
| Output size | Price |
|---|---|
| Up to 4 MP | $0.50 |
Best Use Cases
- Consistent subject generation — Guide the result with one or more subject references.
- Style transfer — Apply a visual style from reference images to a new composition.
- Creative exploration — Combine visual references with a prompt to explore different directions.
- Marketing and concept art — Create images that follow a consistent subject or visual identity.
Pro Tips
- Put the most important content or subject image first.
- Use clear reference images with minimal compression artifacts.
- Add a concise prompt when you need to specify how the references should be combined.
- Use a fixed seed when comparing prompt changes.
Notes
- Provide between one and four reference images.
- The output-size limit for this pricing is 4 MP.
seedandsync_modeldo not add separate charges.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
set -euo pipefail
export WAVESPEED_API_KEY="your-api-key"
REQUEST_BODY=$(cat <<'JSON'
{
"reference_images": [
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
]
}
JSON
)
# 1. Submit the prediction once. Never retry this request automatically:
# a retry after an unclear failure can create a second, billed task.
CHECK='The task may already exist. Check History or the predictions list before submitting again.'
if ! SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
--connect-timeout 10 --max-time 60 \
-X POST "https://api.wavespeed.ai/api/v3/bytedance/uso" \
-H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
-H "Content-Type: application/json" \
-d "${REQUEST_BODY}"); then
printf 'Submit failed. %s\n' "${CHECK}" >&2
exit 1
fi
TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
printf 'Submission response did not contain a prediction id. %s\n' "${CHECK}" >&2
exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"
# 2. Poll until the prediction reaches a final status.
BODY_FILE=$(mktemp)
trap 'rm -f "${BODY_FILE}"' EXIT
while true; do
# Transient errors (429, 5xx) are retried, honoring Retry-After.
HTTP_CODE=$(curl --silent --show-error --fail-with-body \
--connect-timeout 10 --max-time 60 --retry 5 --retry-delay 2 \
--output "${BODY_FILE}" --write-out '%{http_code}' \
"${RESULT_URL}" \
-H "Authorization: Bearer ${WAVESPEED_API_KEY}" || true)
case "${HTTP_CODE}" in
2??) ;;
000|429|5??) # dropped connection or temporary error: keep polling
printf 'Task %s: HTTP %s, polling again in 10s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
sleep 10; continue ;;
*) printf 'Task %s: HTTP %s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
cat "${BODY_FILE}" >&2; exit 1 ;;
esac
RESULT=$(jq 'if type == "object" and has("data") then .data else . end' "${BODY_FILE}")
STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')
case "${STATUS}" in
completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
failed|cancelled|timeout|deleted)
printf 'Task %s ended with status %s\n' "${PREDICTION_ID}" "${STATUS}" >&2
printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
*) sleep 2 ;;
esac
doneRetry temporary errors only while polling, never the submit request. Errors, retries and timeouts
Parameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| reference_images | array<string> | Yes | - | 0 ~ 4 items | A list of images to use as style references. At least 1 image is required. max 4 images. |
| prompt | string | No | - | The positive prompt for the generation. | |
| seed | integer | No | - | - | The random seed to use for the generation. -1 means a random seed will be used. |
Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data.id | string | Unique identifier for the prediction, Task Id |
| data.model | string | Model ID used for the prediction |
| data.outputs | array | Output values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed) |
| data.urls | object | Object containing related API endpoints |
| data.status | string | Task status. completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses. |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |
Result Request Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| id | string | Yes | - | Task ID |
Result Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data | object | The prediction data object containing all details |
| data.id | string | Unique identifier for the prediction |
| data.model | string | Model ID used for the prediction |
| data.outputs | array<string | object> | Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model. |
| data.urls | object | Object containing related API endpoints |
| data.status | string | Status: completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses |
| data.created_at | string | ISO timestamp of when the request was created |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |