Prompt Optimizer API Documentation

Prompt Optimizer API Documentation

Playground

Advanced Prompt Optimizer for image and video generation. Automatically enhances prompts for clarity, structure, composition, motion dynamics, and style control—producing significantly better outputs across models like FLUX, Wan, Kling, Veo, Seedance, and more. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Overview

The WaveSpeedAI Prompt Optimizer enhances prompts specifically for image and video generation workflows. It restructures and enriches your input prompt to improve visual clarity, composition, cinematic framing, lighting, camera movement, and style consistency.

Designed for models such as Nano Banana, Seedream, FLUX, Wan, Kling, Veo, Seedance, Hailuo, and other leading visual-generation systems.

Key Features

• Improves visual composition (lighting, framing, perspective)
• Expands prompts with cinematic and artistic attributes
• Enhances style, mood, and motion for video models
• Reduces ambiguity and ensures consistent reproducible outputs
• Works seamlessly in automated pipelines and API workflows

Why Use It?

Raw user prompts often produce unstable or low-quality visual outputs. The Prompt Optimizer standardizes and enriches prompts, leading to:

• Better image detail and fidelity
• More stable, coherent video motion
• Consistent art direction across batches
• Improved adherence to user intent

Usage

Send any raw text prompt to the /v1/prompt/optimize endpoint and receive a fully optimized version ready for visual generation models.

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'
{
  "style": "default",
  "mode": "image"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/prompt-optimizer" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

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 "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "${TASK}" | jq -r '.urls.get // empty')
if [ -z "${RESULT_URL}" ]; then RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"; fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body \
    "${RESULT_URL}" \
    -H "Authorization: Bearer ${WAVESPEED_API_KEY}")
  RESULT=$(printf '%s' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  case "${STATUS}" in
    completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "${STATUS}" >&2; exit 1 ;;
  esac
done

Parameters

Task Submission Parameters

Request Parameters

Response Parameters

Result Request Parameters

Result Response Parameters