Generate

Text-to-image, image-to-video, text-to-speech, and image-to-3D generation. Use Generate as the starting point for most workflows.

Every endpoint returns a job_id and has a matching GET …/status/{job_id} route, see Jobs. The fields output_format (webp, jpeg, or png), callback_url (a webhook), and server_id (Enterprise: pin to a dedicated pod) are accepted by every endpoint below.

Text → Image
Image → Video
Text → Speech
Image → 3D

POST /generate/image/v1, only prompt is required.

cURL
JavaScript
Python
Java

curl -X POST https://api.imagepipeline.io/generate/image/v1 \
  -H "X-API-Key: $IMAGEPIPELINE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "prompt": "a person in a red jacket on a rooftop at golden hour",
  "width": 1024,
  "height": 1024,
  "output_format": "webp"
}'

const res = await fetch("https://api.imagepipeline.io/generate/image/v1", {
  method: "POST",
  headers: {
    "X-API-Key": process.env.IMAGEPIPELINE_API_KEY,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
  "prompt": "a person in a red jacket on a rooftop at golden hour",
  "width": 1024,
  "height": 1024,
  "output_format": "webp"
}),
});
const { job_id } = await res.json();

import requests

res = requests.post(
    "https://api.imagepipeline.io/generate/image/v1",
    headers={"X-API-Key": API_KEY},
    json={
  "prompt": "a person in a red jacket on a rooftop at golden hour",
  "width": 1024,
  "height": 1024,
  "output_format": "webp"
},
)
job_id = res.json()["job_id"]

HttpRequest req = HttpRequest.newBuilder()
    .uri(URI.create("https://api.imagepipeline.io/generate/image/v1"))
    .header("X-API-Key", System.getenv("IMAGEPIPELINE_API_KEY"))
    .header("Content-Type", "application/json")
    .POST(HttpRequest.BodyPublishers.ofString("""
{
  "prompt": "a person in a red jacket on a rooftop at golden hour",
  "width": 1024,
  "height": 1024,
  "output_format": "webp"
}
"""))
    .build();
HttpResponse<String> res = client.send(req, BodyHandlers.ofString());

Field	Type	Default	Notes
`prompt`	string	,	Required. Text prompt describing the image.
`width` / `height`	integer	`1024`	Output dimensions in pixels (max 1024).
`num_inference_steps`	integer	model	Number of denoising steps. More = more detail, slower.
`guidance_scale`	number	model	How strictly to follow the prompt. Omit for the model default.
`seed`	integer	`-1`	`-1` randomizes; set a value for reproducibility.
`enhance_prompt`	boolean	`false`	Run the prompt through a lightweight AI enhancer first.
`logo_url`	string	,	Public URL of a logo (PNG/WebP with transparency) to include.
`palette`	string[]	,	Brand colours as hex codes, e.g. `["#FF5733", "#3498DB"]`.
`output_format`	string	`webp`	`webp`, `jpeg`, or `png`.
`profile_id`	string	,	Apply an identity profile.
`callback_url`	string	,	Receive a webhook on completion.
`server_id`	string	,	Enterprise: pin to a dedicated pod.

Response — poll GET …/status/{job_id} until status is completed:

{
  "job_id": "job_8f2a3c1b",
  "status": "completed",
  "result_url": "https://cdn.imagepipeline.io/o/8f2a3c1b.webp",
  "processing_time_seconds": 7.4,
  "balance_remaining_usd": 187.52
}

POST /generate/video/v1, animate a still image (input_image required).

cURL
JavaScript
Python
Java

curl -X POST https://api.imagepipeline.io/generate/video/v1 \
  -H "X-API-Key: $IMAGEPIPELINE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "input_image": "https://.../still.webp",
  "prompt": "make this image come alive, cinematic motion",
  "duration_seconds": 2.0,
  "width": 896,
  "height": 512
}'

const res = await fetch("https://api.imagepipeline.io/generate/video/v1", {
  method: "POST",
  headers: {
    "X-API-Key": process.env.IMAGEPIPELINE_API_KEY,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
  "input_image": "https://.../still.webp",
  "prompt": "make this image come alive, cinematic motion",
  "duration_seconds": 2.0,
  "width": 896,
  "height": 512
}),
});
const { job_id } = await res.json();

import requests

res = requests.post(
    "https://api.imagepipeline.io/generate/video/v1",
    headers={"X-API-Key": API_KEY},
    json={
  "input_image": "https://.../still.webp",
  "prompt": "make this image come alive, cinematic motion",
  "duration_seconds": 2.0,
  "width": 896,
  "height": 512
},
)
job_id = res.json()["job_id"]

HttpRequest req = HttpRequest.newBuilder()
    .uri(URI.create("https://api.imagepipeline.io/generate/video/v1"))
    .header("X-API-Key", System.getenv("IMAGEPIPELINE_API_KEY"))
    .header("Content-Type", "application/json")
    .POST(HttpRequest.BodyPublishers.ofString("""
{
  "input_image": "https://.../still.webp",
  "prompt": "make this image come alive, cinematic motion",
  "duration_seconds": 2.0,
  "width": 896,
  "height": 512
}
"""))
    .build();
HttpResponse<String> res = client.send(req, BodyHandlers.ofString());

Field	Type	Default	Notes
`input_image`	string	,	Required. Public URL of the image to animate.
`prompt`	string	cinematic motion	Describe the animation style or motion.
`width` / `height`	integer	`896` / `512`	Max 1536, must be divisible by 32.
`duration_seconds`	number	`2.0`	Video duration in seconds (0.1 to 10.0).
`seed`	integer	`42`	Seed for reproducibility.
`callback_url`	string	,	Webhook URL on completion.
`server_id`	string	,	Enterprise: pin to a dedicated pod.

Response — poll GET …/status/{job_id} until status is completed:

{
  "job_id": "job_4d9e07a2",
  "status": "completed",
  "result_url": "https://cdn.imagepipeline.io/o/4d9e07a2.mp4",
  "processing_time_seconds": 118.2,
  "balance_remaining_usd": 187.52
}

POST /generate/speech/v1, synthesize speech from text.

cURL
JavaScript
Python
Java

curl -X POST https://api.imagepipeline.io/generate/speech/v1 \
  -H "X-API-Key: $IMAGEPIPELINE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "text": "Welcome to ImagePipeline.",
  "language_id": "en",
  "exaggeration": 0.5
}'

const res = await fetch("https://api.imagepipeline.io/generate/speech/v1", {
  method: "POST",
  headers: {
    "X-API-Key": process.env.IMAGEPIPELINE_API_KEY,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
  "text": "Welcome to ImagePipeline.",
  "language_id": "en",
  "exaggeration": 0.5
}),
});
const { job_id } = await res.json();

import requests

res = requests.post(
    "https://api.imagepipeline.io/generate/speech/v1",
    headers={"X-API-Key": API_KEY},
    json={
  "text": "Welcome to ImagePipeline.",
  "language_id": "en",
  "exaggeration": 0.5
},
)
job_id = res.json()["job_id"]

HttpRequest req = HttpRequest.newBuilder()
    .uri(URI.create("https://api.imagepipeline.io/generate/speech/v1"))
    .header("X-API-Key", System.getenv("IMAGEPIPELINE_API_KEY"))
    .header("Content-Type", "application/json")
    .POST(HttpRequest.BodyPublishers.ofString("""
{
  "text": "Welcome to ImagePipeline.",
  "language_id": "en",
  "exaggeration": 0.5
}
"""))
    .build();
HttpResponse<String> res = client.send(req, BodyHandlers.ofString());

Field	Type	Default	Notes
`text`	string	,	Required. Text to convert to speech.
`language_id`	string	`en`	Language code, e.g. `en`, `zh`, `ja`, `ko`, `he`.
`target_voice_path`	string	,	Public URL of a reference voice audio file for cloning.
`max_new_tokens`	integer	`256`	Maximum tokens to generate.
`exaggeration`	number	`0.5`	Expressiveness (0.0 neutral to 1.0 maximum).
`apply_watermark`	boolean	`true`	Embed an inaudible audio watermark (recommended).
`callback_url`	string	,	Webhook URL on completion.
`server_id`	string	,	Enterprise: pin to a dedicated pod.

Response — poll GET …/status/{job_id} until status is completed:

{
  "job_id": "job_b1c6f3d0",
  "status": "completed",
  "result_url": "https://cdn.imagepipeline.io/o/b1c6f3d0.wav",
  "processing_time_seconds": 5.9,
  "balance_remaining_usd": 187.52
}

POST /generate/3d/v1, turn an image into a 3D mesh (image_path required).

cURL
JavaScript
Python
Java

curl -X POST https://api.imagepipeline.io/generate/3d/v1 \
  -H "X-API-Key: $IMAGEPIPELINE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "image_path": "https://.../object.webp",
  "mode": "generate"
}'

const res = await fetch("https://api.imagepipeline.io/generate/3d/v1", {
  method: "POST",
  headers: {
    "X-API-Key": process.env.IMAGEPIPELINE_API_KEY,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
  "image_path": "https://.../object.webp",
  "mode": "generate"
}),
});
const { job_id } = await res.json();

import requests

res = requests.post(
    "https://api.imagepipeline.io/generate/3d/v1",
    headers={"X-API-Key": API_KEY},
    json={
  "image_path": "https://.../object.webp",
  "mode": "generate"
},
)
job_id = res.json()["job_id"]

HttpRequest req = HttpRequest.newBuilder()
    .uri(URI.create("https://api.imagepipeline.io/generate/3d/v1"))
    .header("X-API-Key", System.getenv("IMAGEPIPELINE_API_KEY"))
    .header("Content-Type", "application/json")
    .POST(HttpRequest.BodyPublishers.ofString("""
{
  "image_path": "https://.../object.webp",
  "mode": "generate"
}
"""))
    .build();
HttpResponse<String> res = client.send(req, BodyHandlers.ofString());

Field	Type	Default	Notes
`image_path`	string	,	Required. Public URL of the input image.
`mode`	string	`generate`	`generate` (mesh only) or `paint` (texture and mesh).
`mesh_save_name`	string	,	Optional filename for the output mesh, e.g. `model.obj`.
`painted_save_name`	string	,	Optional filename for the textured mesh.
`auto_unload`	boolean	`true`	Unload the pipeline from GPU after completion.
`callback_url`	string	,	Webhook URL on completion.
`server_id`	string	,	Enterprise: pin to a dedicated pod.

Response — poll GET …/status/{job_id} until status is completed:

{
  "job_id": "job_c7e21a94",
  "status": "completed",
  "result_url": "https://cdn.imagepipeline.io/o/c7e21a94.glb",
  "processing_time_seconds": 112.0,
  "balance_remaining_usd": 187.52
}