Flux Kontext Pro Text to Image
The FLUX.1 Kontext [pro] text-to-image delivers state-of-the-art image generation results with unprecedented prompt following, photorealistic rendering, and flawless typography.
Features
FLUX.1 Kontext is a state-of-the-art image editing model by Black Forest Labs that lets you edit images using text prompts. It makes editing intuitive by understanding the relationship between visuals and language. You can make precise changes to objects, scenes, and layout — all without disrupting the composition.
FLUX.1-Kontext-pro/text-to-image delivers state-of-the-art image generation results with unprecedented prompt following, photorealistic rendering, and flawless typography.
Key Features
- Context-Aware Editing: Intelligent understanding of text semantics for precise modifications that preserve natural aesthetics.
- Lightning Fast: Optimized neural architecture delivers professional results in seconds for real-time workflows.
- Precision Control: Granular control over transformations with intuitive parameters and fine-tuning capabilities.
- SOTA Quality: State-of-the-art results surpassing existing models across all quality benchmarks.
Use Cases
- Concept Art: Create characters, environments, and moodboards directly from text prompts for films, games, or animation.
- Virtual Characters: Design original characters or avatars for social media, storytelling, or digital experiences.
- Marketing Visuals: Generate branded content, ad mockups, or promotional visuals from campaign keywords.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-kontext-pro/text-to-image" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"prompt": "A grand steampunk airship soaring through the sky, with intricate brass and copper details, large propellers spinning, and a massive balloon filled with hot air. The airship is adorned with Victorian-style architecture, featuring ornate railings and decorative elements. The sky is a brilliant blue with fluffy white clouds, and the airship casts a shadow on the landscape below. The scene conveys a sense of adventure and exploration",
"aspect_ratio": "1:1",
"num_images": 1,
"guidance_scale": 3.5,
"safety_tolerance": "2"
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
Parameter | Type | Required | Default | Range | Description |
---|---|---|---|---|---|
prompt | string | Yes | A grand steampunk airship soaring through the sky, with intricate brass and copper details, large propellers spinning, and a massive balloon filled with hot air. The airship is adorned with Victorian-style architecture, featuring ornate railings and decorative elements. The sky is a brilliant blue with fluffy white clouds, and the airship casts a shadow on the landscape below. The scene conveys a sense of adventure and exploration | - | The prompt to generate an image from. |
aspect_ratio | string | No | 1:1 | - | The aspect ratio of the generated image. |
num_images | integer | No | 1 | 1 ~ 4 | The number of images to generate. |
seed | integer | No | - | -1 ~ 9999999999 | The same seed and the same prompt given to the same version of the model will output the same image every time. |
guidance_scale | number | No | 3.5 | 1.0 ~ 10.0 | The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt when looking for a related image to show you. |
safety_tolerance | string | No | 2 | - | The safety tolerance level for the generated image. 1 being the most strict and 5 being the most permissive. |
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 | Array of URLs to the generated content (empty when status is not completed ) |
data.urls | object | Object containing related API endpoints |
data.urls.get | string | URL to retrieve the prediction result |
data.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
data.status | string | Status of the task: created , processing , completed , or failed |
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 Query Parameters
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 | Array of URLs to the generated content (empty when status is not completed ) |
data.urls | object | Object containing related API endpoints |
data.urls.get | string | URL to retrieve the prediction result |
data.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
data.status | string | Status of the task: created , processing , completed , or failed |
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 |