Firered Image Edit API Documentation

Firered Image Edit API Documentation

Playground

FireRed Image Edit enables precise image editing with natural-language instructions, supporting both English and Chinese prompts with multi-image references. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.

Features

FireRed Image Edit is a powerful AI image editing model that combines elements from multiple reference images into a single cohesive output. Upload reference images of people, objects, or styles, then describe how to combine them — the model intelligently merges elements while maintaining natural composition and lighting.

Why Choose This?

• Multi-image composition Combine elements from multiple reference images into one seamless result.

• Natural language editing Describe your edit in plain text — reference images by Figure number for precise control.

• Flexible sizing Specify custom output size, or leave blank to match the first image’s aspect ratio.

• Intelligent blending Automatically adapts lighting, perspective, and style for realistic integration.

• Prompt Enhancer Built-in tool to automatically improve your edit descriptions.

Parameters

How to Use

1. Upload reference images — add all images containing elements you want to combine.
2. Write your prompt — describe the edit using “Figure 1”, “Figure 2”, etc. to reference specific images.
3. Set size (optional) — specify output dimensions, or leave blank to use first image’s ratio.
4. Use Prompt Enhancer (optional) — click to automatically refine your description.
5. Run — submit and download your edited image.

Pricing

Best Use Cases

• Virtual Try-On — Put a person in different outfits from reference photos.
• Character Compositing — Combine character features with new environments or accessories.
• Product Visualization — Show products on different models or in various settings.
• Creative Compositing — Merge elements from multiple sources for unique imagery.
• Marketing & Ads — Create customized visuals by combining brand assets.

Pro Tips

• Use “Figure 1”, “Figure 2”, etc. in your prompt to reference images in upload order.
• Clear, front-facing reference images produce the best element extraction.
• The first image determines the default output aspect ratio when size is not specified.
• Describe the scene context (location, lighting, mood) for more cohesive results.
• For best results, use reference images with similar lighting conditions.

Notes

• Both prompt and images are required fields.
• Ensure uploaded image URLs are publicly accessible.
• Output size defaults to first image’s aspect ratio if not specified.

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'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "images": [
    "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
  ]
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/firered-image/edit" \
  -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