Seedance 2.5 Now Live | Try in Video Generator →

wavespeed-ai/

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.

llm
Input

Idle

A glamorous, confident woman with voluminous blonde curls strides down a Parisian street at dusk, exuding 1950s cinematic allure. She wears a sleek black off-the-shoulder satin gown, paired with striking red high heels and holds a sparkling silver clutch. Smoke curls from her cigarette as she gazes forward, embodying bold fashion and urban sophistication. Behind her, the neon-lit “BALAZLE” theater sign glows against the twilight sky, while a vintage blue car idles nearby. The scene is captured in a cinematic, high-contrast style with dynamic camera movement, emphasizing motion and atmosphere.

$0.001per run·~1000 / $1

ExamplesView all

Related Models

README

Image & Video Prompt Optimizer API

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.

Note:This website uses AI models provided by third parties. Documentation prices are for reference and may be outdated. The Generate button shows an estimate; the final task charge prevails.

Prompt Optimizer API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/prompt-optimizer with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Prompt Optimizer below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_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 "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; 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' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$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
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/prompt-optimizer";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "style": "default",
        "mode": "image"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "style": "default",
    "mode": "image"
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/wavespeed-ai/prompt-optimizer", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

Prompt Optimizer API — Frequently asked questions

What is the Prompt Optimizer API?

Prompt Optimizer is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. 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. You can call it programmatically or try it from the playground above.

How do I call the Prompt Optimizer API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/prompt-optimizer.

How much does Prompt Optimizer cost per run?

Prompt Optimizer starts at $0.001 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Prompt Optimizer accept?

Key inputs: `image`, `enable_sync_mode`, `mode`, `style`, `text`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/prompt-optimizer.

How long does Prompt Optimizer take to generate?

Median end-to-end generation time on WaveSpeedAI is around 5 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Prompt Optimizer outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

Prompt Optimizer | Fast LLM API on WaveSpeedAI