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class ModelCopyResponse: …
model: Model
capabilities: List[Literal["3d23d", "audio2audio", "audio2txt", 30 more]]List of model capabilities (example: [“txt2img”, “img2img”, “txt2img_ip_adapter”, …])
List of model capabilities (example: [“txt2img”, “img2img”, “txt2img_ip_adapter”, …])
Whether the model is a custom model and can be used only with POST /generate/custom/{modelId} endpoint
type: Literal["custom", "elevenlabs-voice", "flux.1", 28 more]The model type (example: “flux.1-lora”)
The model type (example: “flux.1-lora”)
access_restrictions: Optional[Literal[0, 100, 25, 2 more]]The access restrictions of the model
0: Free plan
25: Creator plan
50: Pro plan
75: Team plan
100: Enterprise plan
The access restrictions of the model 0: Free plan 25: Creator plan 50: Pro plan 75: Team plan 100: Enterprise plan
class_: Optional[ModelClass]The class of the model
The class of the model
List of base model IDs compliant with the model (example: [“flux.1-dev”, “flux.1-schnell”]) This attribute is mainly used for Flux LoRA models
concepts: Optional[List[ModelConcept]]The concepts is required for the type model: composition
The concepts is required for the type model: composition
When true, credits spent on a generation with this model are not automatically refunded if the generation fails. Absent or false means failed generations are refunded as usual.
The epoch of the model. Only available for Flux Lora Trained models. If not set, uses the final model epoch (latest)
epochs: Optional[List[ModelEpoch]]The epochs of the model. Only available for Flux Lora Trained models.
The epochs of the model. Only available for Flux Lora Trained models.
inputs: Optional[List[ModelInput]]The inputs of the model. Only used for custom models. To retrieve this list, get it by modelId with GET /models/{modelId}
The inputs of the model. Only used for custom models. To retrieve this list, get it by modelId with GET /models/{modelId}
The allowed values for the input. For `string` or `number` types, creates a single-select dropdown. For `string_array` type, creates a multi-select dropdown.
background_behavior: Optional[Literal["opaque", "transparent"]]Specifies the background behavior for the input. Only available for `file` and `file_array`
input types with kind `image`.
Specifies the background behavior for the input. Only available for `file` and `file_array` input types with kind `image`.
Help text displayed in the UI to provide additional information about the input
Used to visually group inputs together in the UI. Inputs with the same group value appear consecutively in the UI.
The list of inputs which form an object within a container array. All inputs are the same as the current object. This is only available for type inputs_array inputs.
kind: Optional[Literal["3d", "audio", "document", 5 more]]The asset kind of the input. Only taken into account for `file` and `file_array` input types.
If model provides multiple kinds,
the input will be not able to create the asset on the flight on API side with dataurl without data:kind, prefix
`file` and `file_array` inputs always expose a kind: when a model does not declare one,
`image` is returned, which is the kind used at generation time.
The asset kind of the input. Only taken into account for `file` and `file_array` input types. If model provides multiple kinds, the input will be not able to create the asset on the flight on API side with dataurl without data:kind, prefix `file` and `file_array` inputs always expose a kind: when a model does not declare one, `image` is returned, which is the kind used at generation time.
The maximum allowed media duration in seconds. Only applies to `file` and `file_array` input types for video and audio assets. Validated against `asset.properties.duration` at job creation time.
The maximum allowed length for `string` and `model` inputs, in characters. For the array types (`string_array`, `model_array`) it bounds the NUMBER OF ITEMS instead — the length of each item is not constrained.
The maximum allowed file size in bytes. Only applies to `file` and `file_array` input types. Validated against `asset.properties.size` at job creation time.
The minimum allowed length for `string` and `model` inputs, in characters. For the array types (`string_array`, `model_array`) it bounds the NUMBER OF ITEMS instead — the length of each item is not constrained.
model_types: Optional[List[Literal["custom", "elevenlabs-voice", "flux.1", 28 more]]]The allowed model types for this input. Example: `[“flux.1-lora”]`.
Only available for `model_array` input type.
The allowed model types for this input. Example: `[“flux.1-lora”]`. Only available for `model_array` input type.
Whether this input represents a parent asset to assign to the produced assets. Only available for `file` and `file_array` input types.
For `file_array`, the parent asset is the first item in the array.
Whether the input is a prompt. When true, displays as a text area with prompt spark feature. Only available for `string` input type.
Whether the input is used with prompt spark. Only available for `string` input type.
required: Optional[ModelInputRequired]Set of rules that describes when this input is required:
- `always`: Input is always required
- `ifNotDefined`: Input is required when another specified input is not defined
- `ifDefined`: Input is required when another specified input is defined
- `conditionalValues`: Input is required when another input has a specific value
By default, the input is not required.
Set of rules that describes when this input is required:
- `always`: Input is always required
- `ifNotDefined`: Input is required when another specified input is not defined
- `ifDefined`: Input is required when another specified input is defined
- `conditionalValues`: Input is required when another input has a specific value
By default, the input is not required.
Makes this input required when another input has a specific value:
- Key: name of the input to check
- Value: operation and allowed values that trigger the requirement
The model keyword, this is a legacy parameter, please use conceptPrompt in parameters
Fine-tune the model’s inferences with negative prompt embedding
parameters: Optional[ModelParameters]The parameters of the model
The parameters of the model
Age group of the voice (for professional cloning)
Only available for ElevenLabs voice training
The batch size Less steps, and will increase the learning rate
Only available for Flux LoRA training
The prompt to specify images in the same class as provided instance images
Deprecated legacy training parameter.
Type of voice cloning: “instant” (fast) or “professional” (higher quality, requires captcha)
Only available for ElevenLabs voice training
The prompt with identifier specifying the instance (or subject) of the class (example: “a daiton dog”)
Default value varies depending on the model type. For Flux LoRA, the default is an empty string.
Gender of the voice (for professional cloning)
Only available for ElevenLabs voice training
Language of the audio samples (ISO 639-1 code)
Only available for ElevenLabs voice training
Initial learning rate (after the potential warmup period)
Default value varies depending on the model type. For Flux LoRA, the default is 0.0001.
Initial learning rate (after the potential warmup period) for the text encoder
Maximum [Flux LoRA: 0.001] Default [Flux LoRA: 0.00001] Minimum [Flux LoRA: 0.000001]
Initial learning rate (after the potential warmup period) for the UNet
Deprecated legacy training parameter.
lr_scheduler: Optional[Literal["constant", "constant-with-warmup", "cosine", 3 more]]The scheduler type to use (default: “constant”)
Deprecated legacy training parameter.
The scheduler type to use (default: “constant”)
Deprecated legacy training parameter.
Maximum number of training steps to execute (default: varies depending on the model type)
Default value varies depending on the model type:
- For Flux: number of training images * 100
Maximum value varies depending on the model type:
- For Flux: [0, 10000]
The number of epochs to train for
Only available for Flux LoRA training
The number of times to repeat the training
Only available for Flux LoRA training
The number of training steps for the text encoder
Deprecated legacy training parameter.
The number of training steps for the UNet
Deprecated legacy training parameter.
Optimize the model training task for a specific type of input images. The available values are:
- “likeness”: optimize training for likeness or portrait (targets specific transformer blocks)
- “all”: train all transformer blocks
- “none”: train no specific transformer blocks
This parameter controls which double and single transformer blocks are trained during the LoRA training process.
Only available for Flux LoRA training
The weight of prior preservation loss
Deprecated legacy training parameter.
Whether to random crop or center crop images before resizing to the working resolution
Deprecated legacy training parameter.
Ratio of random crops
Deprecated legacy training parameter.
Scale of random crops
Deprecated legacy training parameter.
The dimension of the LoRA update matrices
Only available for Flux LoRA and Musubi training
Default value varies depending on the model type:
- For Flux: 16
- For Musubi: 64
Each trainer enforces its own tighter limit (Flux LoRA: [2; 64], Musubi: [2; 128])
Whether to remove background noise from audio samples before cloning. When enabled, each sample must be at least 5 seconds long.
Only available for ElevenLabs voice training
The prompts to use for each epoch Only available for Flux LoRA training
The sample prompt images (AssetIds) paired with samplePrompts Only available for Flux LoRA training Must be the same length as samplePrompts
Whether to scale the learning rate
Note: Legacy parameter, will be ignored
Deprecated legacy training parameter.
Used to reproduce previous results. Default: randomly generated number.
Deprecated legacy training parameter.
Whether to train the text encoder or not
Example: For 100 steps and a value of 0.2, it means that the text encoder will be trained for 20 steps and then the UNet for 80 steps
Note: Legacy parameter, please use numTextTrainSteps and numUNetTrainSteps
Deprecated legacy training parameter.
Validation frequency. Cannot be greater than maxTrainSteps value
Deprecated legacy training parameter.
performance_stats: Optional[ModelPerformanceStats]Aggregated performance stats
Aggregated performance stats
The model short description (example: “This model generates highly detailed cinematic scenes.”)
training_images: Optional[List[ModelTrainingImage]]The URLs of the first 3 training images of the model. To retrieve the full set of images, get it by modelId
The URLs of the first 3 training images of the model. To retrieve the full set of images, get it by modelId
training_progress: Optional[ModelTrainingProgress]Additional information about the training progress of the model
Additional information about the training progress of the model
Signed URL of the captcha image to read aloud during PVC voice cloning. Only present when stage === ‘pending-captcha’. Overwritten on each retry.
Position of the job in the queue (ie. the number of job in the queue before this one)
Last recoverable failure message during PVC. Present when the model has bounced back to stage === ‘ready-for-captcha’ after a step 2 or step 3 failure (e.g. captcha rejected, time limit exceeded). Surface above the retry button so the user understands why they’re back here.
ui_config: Optional[ModelUiConfig]The UI configuration for the model
The UI configuration for the model
input_properties: Optional[Dict[str, ModelUiConfigInputProperties]]Configuration for the input properties
Configuration for the input properties
output_properties: Optional[Dict[str, ModelUiConfigOutputProperties]]Configuration for the provider outputs exposed by exposeOutput
Configuration for the provider outputs exposed by exposeOutput
resolution_component: Optional[ModelUiConfigResolutionComponent]Configuration for the resolution component
Configuration for the resolution component
class ModelCreateResponse: …
model: Model
capabilities: List[Literal["3d23d", "audio2audio", "audio2txt", 30 more]]List of model capabilities (example: [“txt2img”, “img2img”, “txt2img_ip_adapter”, …])
List of model capabilities (example: [“txt2img”, “img2img”, “txt2img_ip_adapter”, …])
Whether the model is a custom model and can be used only with POST /generate/custom/{modelId} endpoint
type: Literal["custom", "elevenlabs-voice", "flux.1", 28 more]The model type (example: “flux.1-lora”)
The model type (example: “flux.1-lora”)
access_restrictions: Optional[Literal[0, 100, 25, 2 more]]The access restrictions of the model
0: Free plan
25: Creator plan
50: Pro plan
75: Team plan
100: Enterprise plan
The access restrictions of the model 0: Free plan 25: Creator plan 50: Pro plan 75: Team plan 100: Enterprise plan
class_: Optional[ModelClass]The class of the model
The class of the model
List of base model IDs compliant with the model (example: [“flux.1-dev”, “flux.1-schnell”]) This attribute is mainly used for Flux LoRA models
concepts: Optional[List[ModelConcept]]The concepts is required for the type model: composition
The concepts is required for the type model: composition
When true, credits spent on a generation with this model are not automatically refunded if the generation fails. Absent or false means failed generations are refunded as usual.
The epoch of the model. Only available for Flux Lora Trained models. If not set, uses the final model epoch (latest)
epochs: Optional[List[ModelEpoch]]The epochs of the model. Only available for Flux Lora Trained models.
The epochs of the model. Only available for Flux Lora Trained models.
inputs: Optional[List[ModelInput]]The inputs of the model. Only used for custom models. To retrieve this list, get it by modelId with GET /models/{modelId}
The inputs of the model. Only used for custom models. To retrieve this list, get it by modelId with GET /models/{modelId}
The allowed values for the input. For `string` or `number` types, creates a single-select dropdown. For `string_array` type, creates a multi-select dropdown.
background_behavior: Optional[Literal["opaque", "transparent"]]Specifies the background behavior for the input. Only available for `file` and `file_array`
input types with kind `image`.
Specifies the background behavior for the input. Only available for `file` and `file_array` input types with kind `image`.
Help text displayed in the UI to provide additional information about the input
Used to visually group inputs together in the UI. Inputs with the same group value appear consecutively in the UI.
The list of inputs which form an object within a container array. All inputs are the same as the current object. This is only available for type inputs_array inputs.
kind: Optional[Literal["3d", "audio", "document", 5 more]]The asset kind of the input. Only taken into account for `file` and `file_array` input types.
If model provides multiple kinds,
the input will be not able to create the asset on the flight on API side with dataurl without data:kind, prefix
`file` and `file_array` inputs always expose a kind: when a model does not declare one,
`image` is returned, which is the kind used at generation time.
The asset kind of the input. Only taken into account for `file` and `file_array` input types. If model provides multiple kinds, the input will be not able to create the asset on the flight on API side with dataurl without data:kind, prefix `file` and `file_array` inputs always expose a kind: when a model does not declare one, `image` is returned, which is the kind used at generation time.
The maximum allowed media duration in seconds. Only applies to `file` and `file_array` input types for video and audio assets. Validated against `asset.properties.duration` at job creation time.
The maximum allowed length for `string` and `model` inputs, in characters. For the array types (`string_array`, `model_array`) it bounds the NUMBER OF ITEMS instead — the length of each item is not constrained.
The maximum allowed file size in bytes. Only applies to `file` and `file_array` input types. Validated against `asset.properties.size` at job creation time.
The minimum allowed length for `string` and `model` inputs, in characters. For the array types (`string_array`, `model_array`) it bounds the NUMBER OF ITEMS instead — the length of each item is not constrained.
model_types: Optional[List[Literal["custom", "elevenlabs-voice", "flux.1", 28 more]]]The allowed model types for this input. Example: `[“flux.1-lora”]`.
Only available for `model_array` input type.
The allowed model types for this input. Example: `[“flux.1-lora”]`. Only available for `model_array` input type.
Whether this input represents a parent asset to assign to the produced assets. Only available for `file` and `file_array` input types.
For `file_array`, the parent asset is the first item in the array.
Whether the input is a prompt. When true, displays as a text area with prompt spark feature. Only available for `string` input type.
Whether the input is used with prompt spark. Only available for `string` input type.
required: Optional[ModelInputRequired]Set of rules that describes when this input is required:
- `always`: Input is always required
- `ifNotDefined`: Input is required when another specified input is not defined
- `ifDefined`: Input is required when another specified input is defined
- `conditionalValues`: Input is required when another input has a specific value
By default, the input is not required.
Set of rules that describes when this input is required:
- `always`: Input is always required
- `ifNotDefined`: Input is required when another specified input is not defined
- `ifDefined`: Input is required when another specified input is defined
- `conditionalValues`: Input is required when another input has a specific value
By default, the input is not required.
Makes this input required when another input has a specific value:
- Key: name of the input to check
- Value: operation and allowed values that trigger the requirement
The model keyword, this is a legacy parameter, please use conceptPrompt in parameters
Fine-tune the model’s inferences with negative prompt embedding
parameters: Optional[ModelParameters]The parameters of the model
The parameters of the model
Age group of the voice (for professional cloning)
Only available for ElevenLabs voice training
The batch size Less steps, and will increase the learning rate
Only available for Flux LoRA training
The prompt to specify images in the same class as provided instance images
Deprecated legacy training parameter.
Type of voice cloning: “instant” (fast) or “professional” (higher quality, requires captcha)
Only available for ElevenLabs voice training
The prompt with identifier specifying the instance (or subject) of the class (example: “a daiton dog”)
Default value varies depending on the model type. For Flux LoRA, the default is an empty string.
Gender of the voice (for professional cloning)
Only available for ElevenLabs voice training
Language of the audio samples (ISO 639-1 code)
Only available for ElevenLabs voice training
Initial learning rate (after the potential warmup period)
Default value varies depending on the model type. For Flux LoRA, the default is 0.0001.
Initial learning rate (after the potential warmup period) for the text encoder
Maximum [Flux LoRA: 0.001] Default [Flux LoRA: 0.00001] Minimum [Flux LoRA: 0.000001]
Initial learning rate (after the potential warmup period) for the UNet
Deprecated legacy training parameter.
lr_scheduler: Optional[Literal["constant", "constant-with-warmup", "cosine", 3 more]]The scheduler type to use (default: “constant”)
Deprecated legacy training parameter.
The scheduler type to use (default: “constant”)
Deprecated legacy training parameter.
Maximum number of training steps to execute (default: varies depending on the model type)
Default value varies depending on the model type:
- For Flux: number of training images * 100
Maximum value varies depending on the model type:
- For Flux: [0, 10000]
The number of epochs to train for
Only available for Flux LoRA training
The number of times to repeat the training
Only available for Flux LoRA training
The number of training steps for the text encoder
Deprecated legacy training parameter.
The number of training steps for the UNet
Deprecated legacy training parameter.
Optimize the model training task for a specific type of input images. The available values are:
- “likeness”: optimize training for likeness or portrait (targets specific transformer blocks)
- “all”: train all transformer blocks
- “none”: train no specific transformer blocks
This parameter controls which double and single transformer blocks are trained during the LoRA training process.
Only available for Flux LoRA training
The weight of prior preservation loss
Deprecated legacy training parameter.
Whether to random crop or center crop images before resizing to the working resolution
Deprecated legacy training parameter.
Ratio of random crops
Deprecated legacy training parameter.
Scale of random crops
Deprecated legacy training parameter.
The dimension of the LoRA update matrices
Only available for Flux LoRA and Musubi training
Default value varies depending on the model type:
- For Flux: 16
- For Musubi: 64
Each trainer enforces its own tighter limit (Flux LoRA: [2; 64], Musubi: [2; 128])
Whether to remove background noise from audio samples before cloning. When enabled, each sample must be at least 5 seconds long.
Only available for ElevenLabs voice training
The prompts to use for each epoch Only available for Flux LoRA training
The sample prompt images (AssetIds) paired with samplePrompts Only available for Flux LoRA training Must be the same length as samplePrompts
Whether to scale the learning rate
Note: Legacy parameter, will be ignored
Deprecated legacy training parameter.
Used to reproduce previous results. Default: randomly generated number.
Deprecated legacy training parameter.
Whether to train the text encoder or not
Example: For 100 steps and a value of 0.2, it means that the text encoder will be trained for 20 steps and then the UNet for 80 steps
Note: Legacy parameter, please use numTextTrainSteps and numUNetTrainSteps
Deprecated legacy training parameter.
Validation frequency. Cannot be greater than maxTrainSteps value
Deprecated legacy training parameter.
performance_stats: Optional[ModelPerformanceStats]Aggregated performance stats
Aggregated performance stats
The model short description (example: “This model generates highly detailed cinematic scenes.”)
training_images: Optional[List[ModelTrainingImage]]The URLs of the first 3 training images of the model. To retrieve the full set of images, get it by modelId
The URLs of the first 3 training images of the model. To retrieve the full set of images, get it by modelId
training_progress: Optional[ModelTrainingProgress]Additional information about the training progress of the model
Additional information about the training progress of the model
Signed URL of the captcha image to read aloud during PVC voice cloning. Only present when stage === ‘pending-captcha’. Overwritten on each retry.
Position of the job in the queue (ie. the number of job in the queue before this one)
Last recoverable failure message during PVC. Present when the model has bounced back to stage === ‘ready-for-captcha’ after a step 2 or step 3 failure (e.g. captcha rejected, time limit exceeded). Surface above the retry button so the user understands why they’re back here.
ui_config: Optional[ModelUiConfig]The UI configuration for the model
The UI configuration for the model
input_properties: Optional[Dict[str, ModelUiConfigInputProperties]]Configuration for the input properties
Configuration for the input properties
output_properties: Optional[Dict[str, ModelUiConfigOutputProperties]]Configuration for the provider outputs exposed by exposeOutput
Configuration for the provider outputs exposed by exposeOutput
resolution_component: Optional[ModelUiConfigResolutionComponent]Configuration for the resolution component
Configuration for the resolution component
class ModelGetBulkResponse: …
models: List[Model]
type: Literal["custom", "elevenlabs-voice", "flux.1", 28 more]The model type (example: “flux.1-lora”)
The model type (example: “flux.1-lora”)
access_restrictions: Optional[Literal[0, 100, 25, 2 more]]The access restrictions of the model
0: Free plan
25: Creator plan
50: Pro plan
75: Team plan
100: Enterprise plan
The access restrictions of the model 0: Free plan 25: Creator plan 50: Pro plan 75: Team plan 100: Enterprise plan
capabilities: Optional[List[Literal["3d23d", "audio2audio", "audio2txt", 30 more]]]List of model capabilities (example: [“txt2img”, “img2img”, “txt2img_ip_adapter”, …])
List of model capabilities (example: [“txt2img”, “img2img”, “txt2img_ip_adapter”, …])
class_: Optional[ModelClass]The class of the model
The class of the model
List of base model IDs compliant with the model (example: [“flux.1-dev”, “flux.1-schnell”]) This attribute is mainly used for Flux LoRA models
concepts: Optional[List[ModelConcept]]The concepts is required for the type model: composition
The concepts is required for the type model: composition
The model creation date as an ISO string (example: “2023-02-03T11:19:41.579Z”)
Whether the model is a custom model and can be used only with POST /generate/custom/{modelId} endpoint
When true, credits spent on a generation with this model are not automatically refunded if the generation fails. Absent or false means failed generations are refunded as usual.
The epoch of the model. Only available for Flux Lora Trained models. If not set, uses the final model epoch (latest)
epochs: Optional[List[ModelEpoch]]The epochs of the model. Only available for Flux Lora Trained models.
The epochs of the model. Only available for Flux Lora Trained models.
inputs: Optional[List[ModelInput]]The inputs of the model. Only used for custom models. To retrieve this list, get it by modelId with GET /models/{modelId}
The inputs of the model. Only used for custom models. To retrieve this list, get it by modelId with GET /models/{modelId}
The allowed values for the input. For `string` or `number` types, creates a single-select dropdown. For `string_array` type, creates a multi-select dropdown.
background_behavior: Optional[Literal["opaque", "transparent"]]Specifies the background behavior for the input. Only available for `file` and `file_array`
input types with kind `image`.
Specifies the background behavior for the input. Only available for `file` and `file_array` input types with kind `image`.
Help text displayed in the UI to provide additional information about the input
Used to visually group inputs together in the UI. Inputs with the same group value appear consecutively in the UI.
The list of inputs which form an object within a container array. All inputs are the same as the current object. This is only available for type inputs_array inputs.
kind: Optional[Literal["3d", "audio", "document", 5 more]]The asset kind of the input. Only taken into account for `file` and `file_array` input types.
If model provides multiple kinds,
the input will be not able to create the asset on the flight on API side with dataurl without data:kind, prefix
`file` and `file_array` inputs always expose a kind: when a model does not declare one,
`image` is returned, which is the kind used at generation time.
The asset kind of the input. Only taken into account for `file` and `file_array` input types. If model provides multiple kinds, the input will be not able to create the asset on the flight on API side with dataurl without data:kind, prefix `file` and `file_array` inputs always expose a kind: when a model does not declare one, `image` is returned, which is the kind used at generation time.
The maximum allowed media duration in seconds. Only applies to `file` and `file_array` input types for video and audio assets. Validated against `asset.properties.duration` at job creation time.
The maximum allowed length for `string` and `model` inputs, in characters. For the array types (`string_array`, `model_array`) it bounds the NUMBER OF ITEMS instead — the length of each item is not constrained.
The maximum allowed file size in bytes. Only applies to `file` and `file_array` input types. Validated against `asset.properties.size` at job creation time.
The minimum allowed length for `string` and `model` inputs, in characters. For the array types (`string_array`, `model_array`) it bounds the NUMBER OF ITEMS instead — the length of each item is not constrained.
model_types: Optional[List[Literal["custom", "elevenlabs-voice", "flux.1", 28 more]]]The allowed model types for this input. Example: `[“flux.1-lora”]`.
Only available for `model_array` input type.
The allowed model types for this input. Example: `[“flux.1-lora”]`. Only available for `model_array` input type.
Whether this input represents a parent asset to assign to the produced assets. Only available for `file` and `file_array` input types.
For `file_array`, the parent asset is the first item in the array.
Whether the input is a prompt. When true, displays as a text area with prompt spark feature. Only available for `string` input type.
Whether the input is used with prompt spark. Only available for `string` input type.
required: Optional[ModelInputRequired]Set of rules that describes when this input is required:
- `always`: Input is always required
- `ifNotDefined`: Input is required when another specified input is not defined
- `ifDefined`: Input is required when another specified input is defined
- `conditionalValues`: Input is required when another input has a specific value
By default, the input is not required.
Set of rules that describes when this input is required:
- `always`: Input is always required
- `ifNotDefined`: Input is required when another specified input is not defined
- `ifDefined`: Input is required when another specified input is defined
- `conditionalValues`: Input is required when another input has a specific value
By default, the input is not required.
Makes this input required when another input has a specific value:
- Key: name of the input to check
- Value: operation and allowed values that trigger the requirement
The model keyword, this is a legacy parameter, please use conceptPrompt in parameters
Fine-tune the model’s inferences with negative prompt embedding
parameters: Optional[ModelParameters]The parameters of the model
The parameters of the model
Age group of the voice (for professional cloning)
Only available for ElevenLabs voice training
The batch size Less steps, and will increase the learning rate
Only available for Flux LoRA training
The prompt to specify images in the same class as provided instance images
Deprecated legacy training parameter.
Type of voice cloning: “instant” (fast) or “professional” (higher quality, requires captcha)
Only available for ElevenLabs voice training
The prompt with identifier specifying the instance (or subject) of the class (example: “a daiton dog”)
Default value varies depending on the model type. For Flux LoRA, the default is an empty string.
Gender of the voice (for professional cloning)
Only available for ElevenLabs voice training
Language of the audio samples (ISO 639-1 code)
Only available for ElevenLabs voice training
Initial learning rate (after the potential warmup period)
Default value varies depending on the model type. For Flux LoRA, the default is 0.0001.
Initial learning rate (after the potential warmup period) for the text encoder
Maximum [Flux LoRA: 0.001] Default [Flux LoRA: 0.00001] Minimum [Flux LoRA: 0.000001]
Initial learning rate (after the potential warmup period) for the UNet
Deprecated legacy training parameter.
lr_scheduler: Optional[Literal["constant", "constant-with-warmup", "cosine", 3 more]]The scheduler type to use (default: “constant”)
Deprecated legacy training parameter.
The scheduler type to use (default: “constant”)
Deprecated legacy training parameter.
Maximum number of training steps to execute (default: varies depending on the model type)
Default value varies depending on the model type:
- For Flux: number of training images * 100
Maximum value varies depending on the model type:
- For Flux: [0, 10000]
The number of epochs to train for
Only available for Flux LoRA training
The number of times to repeat the training
Only available for Flux LoRA training
The number of training steps for the text encoder
Deprecated legacy training parameter.
The number of training steps for the UNet
Deprecated legacy training parameter.
Optimize the model training task for a specific type of input images. The available values are:
- “likeness”: optimize training for likeness or portrait (targets specific transformer blocks)
- “all”: train all transformer blocks
- “none”: train no specific transformer blocks
This parameter controls which double and single transformer blocks are trained during the LoRA training process.
Only available for Flux LoRA training
The weight of prior preservation loss
Deprecated legacy training parameter.
Whether to random crop or center crop images before resizing to the working resolution
Deprecated legacy training parameter.
Ratio of random crops
Deprecated legacy training parameter.
Scale of random crops
Deprecated legacy training parameter.
The dimension of the LoRA update matrices
Only available for Flux LoRA and Musubi training
Default value varies depending on the model type:
- For Flux: 16
- For Musubi: 64
Each trainer enforces its own tighter limit (Flux LoRA: [2; 64], Musubi: [2; 128])
Whether to remove background noise from audio samples before cloning. When enabled, each sample must be at least 5 seconds long.
Only available for ElevenLabs voice training
The prompts to use for each epoch Only available for Flux LoRA training
The sample prompt images (AssetIds) paired with samplePrompts Only available for Flux LoRA training Must be the same length as samplePrompts
Whether to scale the learning rate
Note: Legacy parameter, will be ignored
Deprecated legacy training parameter.
Used to reproduce previous results. Default: randomly generated number.
Deprecated legacy training parameter.
Whether to train the text encoder or not
Example: For 100 steps and a value of 0.2, it means that the text encoder will be trained for 20 steps and then the UNet for 80 steps
Note: Legacy parameter, please use numTextTrainSteps and numUNetTrainSteps
Deprecated legacy training parameter.
Validation frequency. Cannot be greater than maxTrainSteps value
Deprecated legacy training parameter.
performance_stats: Optional[ModelPerformanceStats]Aggregated performance stats
Aggregated performance stats
The model short description (example: “This model generates highly detailed cinematic scenes.”)
training_images: Optional[List[ModelTrainingImage]]The URLs of the first 3 training images of the model. To retrieve the full set of images, get it by modelId
The URLs of the first 3 training images of the model. To retrieve the full set of images, get it by modelId
training_progress: Optional[ModelTrainingProgress]Additional information about the training progress of the model
Additional information about the training progress of the model
Signed URL of the captcha image to read aloud during PVC voice cloning. Only present when stage === ‘pending-captcha’. Overwritten on each retry.
Position of the job in the queue (ie. the number of job in the queue before this one)
Last recoverable failure message during PVC. Present when the model has bounced back to stage === ‘ready-for-captcha’ after a step 2 or step 3 failure (e.g. captcha rejected, time limit exceeded). Surface above the retry button so the user understands why they’re back here.
ui_config: Optional[ModelUiConfig]The UI configuration for the model
The UI configuration for the model
input_properties: Optional[Dict[str, ModelUiConfigInputProperties]]Configuration for the input properties
Configuration for the input properties
output_properties: Optional[Dict[str, ModelUiConfigOutputProperties]]Configuration for the provider outputs exposed by exposeOutput
Configuration for the provider outputs exposed by exposeOutput
resolution_component: Optional[ModelUiConfigResolutionComponent]Configuration for the resolution component
Configuration for the resolution component
class ModelListResponse: …
capabilities: List[Literal["3d23d", "audio2audio", "audio2txt", 30 more]]List of model capabilities (example: [“txt2img”, “img2img”, “txt2img_ip_adapter”, …])
List of model capabilities (example: [“txt2img”, “img2img”, “txt2img_ip_adapter”, …])
Whether the model is a custom model and can be used only with POST /generate/custom/{modelId} endpoint
type: Literal["custom", "elevenlabs-voice", "flux.1", 28 more]The model type (example: “flux.1-lora”)
The model type (example: “flux.1-lora”)
access_restrictions: Optional[Literal[0, 100, 25, 2 more]]The access restrictions of the model
0: Free plan
25: Creator plan
50: Pro plan
75: Team plan
100: Enterprise plan
The access restrictions of the model 0: Free plan 25: Creator plan 50: Pro plan 75: Team plan 100: Enterprise plan
class_: Optional[Class]The class of the model
The class of the model
List of base model IDs compliant with the model (example: [“flux.1-dev”, “flux.1-schnell”]) This attribute is mainly used for Flux LoRA models
concepts: Optional[List[Concept]]The concepts is required for the type model: composition
The concepts is required for the type model: composition
When true, credits spent on a generation with this model are not automatically refunded if the generation fails. Absent or false means failed generations are refunded as usual.
The epoch of the model. Only available for Flux Lora Trained models. If not set, uses the final model epoch (latest)
inputs: Optional[List[Input]]The inputs of the model. Only used for custom models. To retrieve this list, get it by modelId with GET /models/{modelId}
The inputs of the model. Only used for custom models. To retrieve this list, get it by modelId with GET /models/{modelId}
The allowed values for the input. For `string` or `number` types, creates a single-select dropdown. For `string_array` type, creates a multi-select dropdown.
background_behavior: Optional[Literal["opaque", "transparent"]]Specifies the background behavior for the input. Only available for `file` and `file_array`
input types with kind `image`.
Specifies the background behavior for the input. Only available for `file` and `file_array` input types with kind `image`.
Help text displayed in the UI to provide additional information about the input
Used to visually group inputs together in the UI. Inputs with the same group value appear consecutively in the UI.
The list of inputs which form an object within a container array. All inputs are the same as the current object. This is only available for type inputs_array inputs.
kind: Optional[Literal["3d", "audio", "document", 5 more]]The asset kind of the input. Only taken into account for `file` and `file_array` input types.
If model provides multiple kinds,
the input will be not able to create the asset on the flight on API side with dataurl without data:kind, prefix
`file` and `file_array` inputs always expose a kind: when a model does not declare one,
`image` is returned, which is the kind used at generation time.
The asset kind of the input. Only taken into account for `file` and `file_array` input types. If model provides multiple kinds, the input will be not able to create the asset on the flight on API side with dataurl without data:kind, prefix `file` and `file_array` inputs always expose a kind: when a model does not declare one, `image` is returned, which is the kind used at generation time.
The maximum allowed media duration in seconds. Only applies to `file` and `file_array` input types for video and audio assets. Validated against `asset.properties.duration` at job creation time.
The maximum allowed length for `string` and `model` inputs, in characters. For the array types (`string_array`, `model_array`) it bounds the NUMBER OF ITEMS instead — the length of each item is not constrained.
The maximum allowed file size in bytes. Only applies to `file` and `file_array` input types. Validated against `asset.properties.size` at job creation time.
The minimum allowed length for `string` and `model` inputs, in characters. For the array types (`string_array`, `model_array`) it bounds the NUMBER OF ITEMS instead — the length of each item is not constrained.
model_types: Optional[List[Literal["custom", "elevenlabs-voice", "flux.1", 28 more]]]The allowed model types for this input. Example: `[“flux.1-lora”]`.
Only available for `model_array` input type.
The allowed model types for this input. Example: `[“flux.1-lora”]`. Only available for `model_array` input type.
Whether this input represents a parent asset to assign to the produced assets. Only available for `file` and `file_array` input types.
For `file_array`, the parent asset is the first item in the array.
Whether the input is a prompt. When true, displays as a text area with prompt spark feature. Only available for `string` input type.
Whether the input is used with prompt spark. Only available for `string` input type.
required: Optional[InputRequired]Set of rules that describes when this input is required:
- `always`: Input is always required
- `ifNotDefined`: Input is required when another specified input is not defined
- `ifDefined`: Input is required when another specified input is defined
- `conditionalValues`: Input is required when another input has a specific value
By default, the input is not required.
Set of rules that describes when this input is required:
- `always`: Input is always required
- `ifNotDefined`: Input is required when another specified input is not defined
- `ifDefined`: Input is required when another specified input is defined
- `conditionalValues`: Input is required when another input has a specific value
By default, the input is not required.
Makes this input required when another input has a specific value:
- Key: name of the input to check
- Value: operation and allowed values that trigger the requirement
The model keyword, this is a legacy parameter, please use conceptPrompt in parameters
Fine-tune the model’s inferences with negative prompt embedding
parameters: Optional[Parameters]The parameters of the model
The parameters of the model
Age group of the voice (for professional cloning)
Only available for ElevenLabs voice training
The batch size Less steps, and will increase the learning rate
Only available for Flux LoRA training
The prompt to specify images in the same class as provided instance images
Deprecated legacy training parameter.
Type of voice cloning: “instant” (fast) or “professional” (higher quality, requires captcha)
Only available for ElevenLabs voice training
The prompt with identifier specifying the instance (or subject) of the class (example: “a daiton dog”)
Default value varies depending on the model type. For Flux LoRA, the default is an empty string.
Gender of the voice (for professional cloning)
Only available for ElevenLabs voice training
Language of the audio samples (ISO 639-1 code)
Only available for ElevenLabs voice training
Initial learning rate (after the potential warmup period)
Default value varies depending on the model type. For Flux LoRA, the default is 0.0001.
Initial learning rate (after the potential warmup period) for the text encoder
Maximum [Flux LoRA: 0.001] Default [Flux LoRA: 0.00001] Minimum [Flux LoRA: 0.000001]
Initial learning rate (after the potential warmup period) for the UNet
Deprecated legacy training parameter.
lr_scheduler: Optional[Literal["constant", "constant-with-warmup", "cosine", 3 more]]The scheduler type to use (default: “constant”)
Deprecated legacy training parameter.
The scheduler type to use (default: “constant”)
Deprecated legacy training parameter.
Maximum number of training steps to execute (default: varies depending on the model type)
Default value varies depending on the model type:
- For Flux: number of training images * 100
Maximum value varies depending on the model type:
- For Flux: [0, 10000]
The number of epochs to train for
Only available for Flux LoRA training
The number of times to repeat the training
Only available for Flux LoRA training
The number of training steps for the text encoder
Deprecated legacy training parameter.
The number of training steps for the UNet
Deprecated legacy training parameter.
Optimize the model training task for a specific type of input images. The available values are:
- “likeness”: optimize training for likeness or portrait (targets specific transformer blocks)
- “all”: train all transformer blocks
- “none”: train no specific transformer blocks
This parameter controls which double and single transformer blocks are trained during the LoRA training process.
Only available for Flux LoRA training
The weight of prior preservation loss
Deprecated legacy training parameter.
Whether to random crop or center crop images before resizing to the working resolution
Deprecated legacy training parameter.
Ratio of random crops
Deprecated legacy training parameter.
Scale of random crops
Deprecated legacy training parameter.
The dimension of the LoRA update matrices
Only available for Flux LoRA and Musubi training
Default value varies depending on the model type:
- For Flux: 16
- For Musubi: 64
Each trainer enforces its own tighter limit (Flux LoRA: [2; 64], Musubi: [2; 128])
Whether to remove background noise from audio samples before cloning. When enabled, each sample must be at least 5 seconds long.
Only available for ElevenLabs voice training
The prompts to use for each epoch Only available for Flux LoRA training
The sample prompt images (AssetIds) paired with samplePrompts Only available for Flux LoRA training Must be the same length as samplePrompts
Whether to scale the learning rate
Note: Legacy parameter, will be ignored
Deprecated legacy training parameter.
Used to reproduce previous results. Default: randomly generated number.
Deprecated legacy training parameter.
Whether to train the text encoder or not
Example: For 100 steps and a value of 0.2, it means that the text encoder will be trained for 20 steps and then the UNet for 80 steps
Note: Legacy parameter, please use numTextTrainSteps and numUNetTrainSteps
Deprecated legacy training parameter.
Validation frequency. Cannot be greater than maxTrainSteps value
Deprecated legacy training parameter.
performance_stats: Optional[PerformanceStats]Aggregated performance stats
Aggregated performance stats
The model short description (example: “This model generates highly detailed cinematic scenes.”)
training_images: Optional[List[TrainingImage]]The URLs of the first 3 training images of the model. To retrieve the full set of images, get it by modelId
The URLs of the first 3 training images of the model. To retrieve the full set of images, get it by modelId
training_progress: Optional[TrainingProgress]Additional information about the training progress of the model
Additional information about the training progress of the model
Signed URL of the captcha image to read aloud during PVC voice cloning. Only present when stage === ‘pending-captcha’. Overwritten on each retry.
Position of the job in the queue (ie. the number of job in the queue before this one)
Last recoverable failure message during PVC. Present when the model has bounced back to stage === ‘ready-for-captcha’ after a step 2 or step 3 failure (e.g. captcha rejected, time limit exceeded). Surface above the retry button so the user understands why they’re back here.
ui_config: Optional[UiConfig]The UI configuration for the model
The UI configuration for the model
input_properties: Optional[Dict[str, UiConfigInputProperties]]Configuration for the input properties
Configuration for the input properties
output_properties: Optional[Dict[str, UiConfigOutputProperties]]Configuration for the provider outputs exposed by exposeOutput
Configuration for the provider outputs exposed by exposeOutput
resolution_component: Optional[UiConfigResolutionComponent]Configuration for the resolution component
Configuration for the resolution component
class ModelRetrieveResponse: …
model: Model
capabilities: List[Literal["3d23d", "audio2audio", "audio2txt", 30 more]]List of model capabilities (example: [“txt2img”, “img2img”, “txt2img_ip_adapter”, …])
List of model capabilities (example: [“txt2img”, “img2img”, “txt2img_ip_adapter”, …])
Whether the model is a custom model and can be used only with POST /generate/custom/{modelId} endpoint
type: Literal["custom", "elevenlabs-voice", "flux.1", 28 more]The model type (example: “flux.1-lora”)
The model type (example: “flux.1-lora”)
access_restrictions: Optional[Literal[0, 100, 25, 2 more]]The access restrictions of the model
0: Free plan
25: Creator plan
50: Pro plan
75: Team plan
100: Enterprise plan
The access restrictions of the model 0: Free plan 25: Creator plan 50: Pro plan 75: Team plan 100: Enterprise plan
class_: Optional[ModelClass]The class of the model
The class of the model
List of base model IDs compliant with the model (example: [“flux.1-dev”, “flux.1-schnell”]) This attribute is mainly used for Flux LoRA models
concepts: Optional[List[ModelConcept]]The concepts is required for the type model: composition
The concepts is required for the type model: composition
When true, credits spent on a generation with this model are not automatically refunded if the generation fails. Absent or false means failed generations are refunded as usual.
The epoch of the model. Only available for Flux Lora Trained models. If not set, uses the final model epoch (latest)
epochs: Optional[List[ModelEpoch]]The epochs of the model. Only available for Flux Lora Trained models.
The epochs of the model. Only available for Flux Lora Trained models.
inputs: Optional[List[ModelInput]]The inputs of the model. Only used for custom models. To retrieve this list, get it by modelId with GET /models/{modelId}
The inputs of the model. Only used for custom models. To retrieve this list, get it by modelId with GET /models/{modelId}
The allowed values for the input. For `string` or `number` types, creates a single-select dropdown. For `string_array` type, creates a multi-select dropdown.
background_behavior: Optional[Literal["opaque", "transparent"]]Specifies the background behavior for the input. Only available for `file` and `file_array`
input types with kind `image`.
Specifies the background behavior for the input. Only available for `file` and `file_array` input types with kind `image`.
Help text displayed in the UI to provide additional information about the input
Used to visually group inputs together in the UI. Inputs with the same group value appear consecutively in the UI.
The list of inputs which form an object within a container array. All inputs are the same as the current object. This is only available for type inputs_array inputs.
kind: Optional[Literal["3d", "audio", "document", 5 more]]The asset kind of the input. Only taken into account for `file` and `file_array` input types.
If model provides multiple kinds,
the input will be not able to create the asset on the flight on API side with dataurl without data:kind, prefix
`file` and `file_array` inputs always expose a kind: when a model does not declare one,
`image` is returned, which is the kind used at generation time.
The asset kind of the input. Only taken into account for `file` and `file_array` input types. If model provides multiple kinds, the input will be not able to create the asset on the flight on API side with dataurl without data:kind, prefix `file` and `file_array` inputs always expose a kind: when a model does not declare one, `image` is returned, which is the kind used at generation time.
The maximum allowed media duration in seconds. Only applies to `file` and `file_array` input types for video and audio assets. Validated against `asset.properties.duration` at job creation time.
The maximum allowed length for `string` and `model` inputs, in characters. For the array types (`string_array`, `model_array`) it bounds the NUMBER OF ITEMS instead — the length of each item is not constrained.
The maximum allowed file size in bytes. Only applies to `file` and `file_array` input types. Validated against `asset.properties.size` at job creation time.
The minimum allowed length for `string` and `model` inputs, in characters. For the array types (`string_array`, `model_array`) it bounds the NUMBER OF ITEMS instead — the length of each item is not constrained.
model_types: Optional[List[Literal["custom", "elevenlabs-voice", "flux.1", 28 more]]]The allowed model types for this input. Example: `[“flux.1-lora”]`.
Only available for `model_array` input type.
The allowed model types for this input. Example: `[“flux.1-lora”]`. Only available for `model_array` input type.
Whether this input represents a parent asset to assign to the produced assets. Only available for `file` and `file_array` input types.
For `file_array`, the parent asset is the first item in the array.
Whether the input is a prompt. When true, displays as a text area with prompt spark feature. Only available for `string` input type.
Whether the input is used with prompt spark. Only available for `string` input type.
required: Optional[ModelInputRequired]Set of rules that describes when this input is required:
- `always`: Input is always required
- `ifNotDefined`: Input is required when another specified input is not defined
- `ifDefined`: Input is required when another specified input is defined
- `conditionalValues`: Input is required when another input has a specific value
By default, the input is not required.
Set of rules that describes when this input is required:
- `always`: Input is always required
- `ifNotDefined`: Input is required when another specified input is not defined
- `ifDefined`: Input is required when another specified input is defined
- `conditionalValues`: Input is required when another input has a specific value
By default, the input is not required.
Makes this input required when another input has a specific value:
- Key: name of the input to check
- Value: operation and allowed values that trigger the requirement
The model keyword, this is a legacy parameter, please use conceptPrompt in parameters
Fine-tune the model’s inferences with negative prompt embedding
parameters: Optional[ModelParameters]The parameters of the model
The parameters of the model
Age group of the voice (for professional cloning)
Only available for ElevenLabs voice training
The batch size Less steps, and will increase the learning rate
Only available for Flux LoRA training
The prompt to specify images in the same class as provided instance images
Deprecated legacy training parameter.
Type of voice cloning: “instant” (fast) or “professional” (higher quality, requires captcha)
Only available for ElevenLabs voice training
The prompt with identifier specifying the instance (or subject) of the class (example: “a daiton dog”)
Default value varies depending on the model type. For Flux LoRA, the default is an empty string.
Gender of the voice (for professional cloning)
Only available for ElevenLabs voice training
Language of the audio samples (ISO 639-1 code)
Only available for ElevenLabs voice training
Initial learning rate (after the potential warmup period)
Default value varies depending on the model type. For Flux LoRA, the default is 0.0001.
Initial learning rate (after the potential warmup period) for the text encoder
Maximum [Flux LoRA: 0.001] Default [Flux LoRA: 0.00001] Minimum [Flux LoRA: 0.000001]
Initial learning rate (after the potential warmup period) for the UNet
Deprecated legacy training parameter.
lr_scheduler: Optional[Literal["constant", "constant-with-warmup", "cosine", 3 more]]The scheduler type to use (default: “constant”)
Deprecated legacy training parameter.
The scheduler type to use (default: “constant”)
Deprecated legacy training parameter.
Maximum number of training steps to execute (default: varies depending on the model type)
Default value varies depending on the model type:
- For Flux: number of training images * 100
Maximum value varies depending on the model type:
- For Flux: [0, 10000]
The number of epochs to train for
Only available for Flux LoRA training
The number of times to repeat the training
Only available for Flux LoRA training
The number of training steps for the text encoder
Deprecated legacy training parameter.
The number of training steps for the UNet
Deprecated legacy training parameter.
Optimize the model training task for a specific type of input images. The available values are:
- “likeness”: optimize training for likeness or portrait (targets specific transformer blocks)
- “all”: train all transformer blocks
- “none”: train no specific transformer blocks
This parameter controls which double and single transformer blocks are trained during the LoRA training process.
Only available for Flux LoRA training
The weight of prior preservation loss
Deprecated legacy training parameter.
Whether to random crop or center crop images before resizing to the working resolution
Deprecated legacy training parameter.
Ratio of random crops
Deprecated legacy training parameter.
Scale of random crops
Deprecated legacy training parameter.
The dimension of the LoRA update matrices
Only available for Flux LoRA and Musubi training
Default value varies depending on the model type:
- For Flux: 16
- For Musubi: 64
Each trainer enforces its own tighter limit (Flux LoRA: [2; 64], Musubi: [2; 128])
Whether to remove background noise from audio samples before cloning. When enabled, each sample must be at least 5 seconds long.
Only available for ElevenLabs voice training
The prompts to use for each epoch Only available for Flux LoRA training
The sample prompt images (AssetIds) paired with samplePrompts Only available for Flux LoRA training Must be the same length as samplePrompts
Whether to scale the learning rate
Note: Legacy parameter, will be ignored
Deprecated legacy training parameter.
Used to reproduce previous results. Default: randomly generated number.
Deprecated legacy training parameter.
Whether to train the text encoder or not
Example: For 100 steps and a value of 0.2, it means that the text encoder will be trained for 20 steps and then the UNet for 80 steps
Note: Legacy parameter, please use numTextTrainSteps and numUNetTrainSteps
Deprecated legacy training parameter.
Validation frequency. Cannot be greater than maxTrainSteps value
Deprecated legacy training parameter.
performance_stats: Optional[ModelPerformanceStats]Aggregated performance stats
Aggregated performance stats
The model short description (example: “This model generates highly detailed cinematic scenes.”)
training_images: Optional[List[ModelTrainingImage]]The URLs of the first 3 training images of the model. To retrieve the full set of images, get it by modelId
The URLs of the first 3 training images of the model. To retrieve the full set of images, get it by modelId
training_progress: Optional[ModelTrainingProgress]Additional information about the training progress of the model
Additional information about the training progress of the model
Signed URL of the captcha image to read aloud during PVC voice cloning. Only present when stage === ‘pending-captcha’. Overwritten on each retry.
Position of the job in the queue (ie. the number of job in the queue before this one)
Last recoverable failure message during PVC. Present when the model has bounced back to stage === ‘ready-for-captcha’ after a step 2 or step 3 failure (e.g. captcha rejected, time limit exceeded). Surface above the retry button so the user understands why they’re back here.
ui_config: Optional[ModelUiConfig]The UI configuration for the model
The UI configuration for the model
input_properties: Optional[Dict[str, ModelUiConfigInputProperties]]Configuration for the input properties
Configuration for the input properties
output_properties: Optional[Dict[str, ModelUiConfigOutputProperties]]Configuration for the provider outputs exposed by exposeOutput
Configuration for the provider outputs exposed by exposeOutput
resolution_component: Optional[ModelUiConfigResolutionComponent]Configuration for the resolution component
Configuration for the resolution component
class ModelTransferResponse: …
model: Model
capabilities: List[Literal["3d23d", "audio2audio", "audio2txt", 30 more]]List of model capabilities (example: [“txt2img”, “img2img”, “txt2img_ip_adapter”, …])
List of model capabilities (example: [“txt2img”, “img2img”, “txt2img_ip_adapter”, …])
Whether the model is a custom model and can be used only with POST /generate/custom/{modelId} endpoint
type: Literal["custom", "elevenlabs-voice", "flux.1", 28 more]The model type (example: “flux.1-lora”)
The model type (example: “flux.1-lora”)
access_restrictions: Optional[Literal[0, 100, 25, 2 more]]The access restrictions of the model
0: Free plan
25: Creator plan
50: Pro plan
75: Team plan
100: Enterprise plan
The access restrictions of the model 0: Free plan 25: Creator plan 50: Pro plan 75: Team plan 100: Enterprise plan
class_: Optional[ModelClass]The class of the model
The class of the model
List of base model IDs compliant with the model (example: [“flux.1-dev”, “flux.1-schnell”]) This attribute is mainly used for Flux LoRA models
concepts: Optional[List[ModelConcept]]The concepts is required for the type model: composition
The concepts is required for the type model: composition
When true, credits spent on a generation with this model are not automatically refunded if the generation fails. Absent or false means failed generations are refunded as usual.
The epoch of the model. Only available for Flux Lora Trained models. If not set, uses the final model epoch (latest)
epochs: Optional[List[ModelEpoch]]The epochs of the model. Only available for Flux Lora Trained models.
The epochs of the model. Only available for Flux Lora Trained models.
inputs: Optional[List[ModelInput]]The inputs of the model. Only used for custom models. To retrieve this list, get it by modelId with GET /models/{modelId}
The inputs of the model. Only used for custom models. To retrieve this list, get it by modelId with GET /models/{modelId}
The allowed values for the input. For `string` or `number` types, creates a single-select dropdown. For `string_array` type, creates a multi-select dropdown.
background_behavior: Optional[Literal["opaque", "transparent"]]Specifies the background behavior for the input. Only available for `file` and `file_array`
input types with kind `image`.
Specifies the background behavior for the input. Only available for `file` and `file_array` input types with kind `image`.
Help text displayed in the UI to provide additional information about the input
Used to visually group inputs together in the UI. Inputs with the same group value appear consecutively in the UI.
The list of inputs which form an object within a container array. All inputs are the same as the current object. This is only available for type inputs_array inputs.
kind: Optional[Literal["3d", "audio", "document", 5 more]]The asset kind of the input. Only taken into account for `file` and `file_array` input types.
If model provides multiple kinds,
the input will be not able to create the asset on the flight on API side with dataurl without data:kind, prefix
`file` and `file_array` inputs always expose a kind: when a model does not declare one,
`image` is returned, which is the kind used at generation time.
The asset kind of the input. Only taken into account for `file` and `file_array` input types. If model provides multiple kinds, the input will be not able to create the asset on the flight on API side with dataurl without data:kind, prefix `file` and `file_array` inputs always expose a kind: when a model does not declare one, `image` is returned, which is the kind used at generation time.
The maximum allowed media duration in seconds. Only applies to `file` and `file_array` input types for video and audio assets. Validated against `asset.properties.duration` at job creation time.
The maximum allowed length for `string` and `model` inputs, in characters. For the array types (`string_array`, `model_array`) it bounds the NUMBER OF ITEMS instead — the length of each item is not constrained.
The maximum allowed file size in bytes. Only applies to `file` and `file_array` input types. Validated against `asset.properties.size` at job creation time.
The minimum allowed length for `string` and `model` inputs, in characters. For the array types (`string_array`, `model_array`) it bounds the NUMBER OF ITEMS instead — the length of each item is not constrained.
model_types: Optional[List[Literal["custom", "elevenlabs-voice", "flux.1", 28 more]]]The allowed model types for this input. Example: `[“flux.1-lora”]`.
Only available for `model_array` input type.
The allowed model types for this input. Example: `[“flux.1-lora”]`. Only available for `model_array` input type.
Whether this input represents a parent asset to assign to the produced assets. Only available for `file` and `file_array` input types.
For `file_array`, the parent asset is the first item in the array.
Whether the input is a prompt. When true, displays as a text area with prompt spark feature. Only available for `string` input type.
Whether the input is used with prompt spark. Only available for `string` input type.
required: Optional[ModelInputRequired]Set of rules that describes when this input is required:
- `always`: Input is always required
- `ifNotDefined`: Input is required when another specified input is not defined
- `ifDefined`: Input is required when another specified input is defined
- `conditionalValues`: Input is required when another input has a specific value
By default, the input is not required.
Set of rules that describes when this input is required:
- `always`: Input is always required
- `ifNotDefined`: Input is required when another specified input is not defined
- `ifDefined`: Input is required when another specified input is defined
- `conditionalValues`: Input is required when another input has a specific value
By default, the input is not required.
Makes this input required when another input has a specific value:
- Key: name of the input to check
- Value: operation and allowed values that trigger the requirement
The model keyword, this is a legacy parameter, please use conceptPrompt in parameters
Fine-tune the model’s inferences with negative prompt embedding
parameters: Optional[ModelParameters]The parameters of the model
The parameters of the model
Age group of the voice (for professional cloning)
Only available for ElevenLabs voice training
The batch size Less steps, and will increase the learning rate
Only available for Flux LoRA training
The prompt to specify images in the same class as provided instance images
Deprecated legacy training parameter.
Type of voice cloning: “instant” (fast) or “professional” (higher quality, requires captcha)
Only available for ElevenLabs voice training
The prompt with identifier specifying the instance (or subject) of the class (example: “a daiton dog”)
Default value varies depending on the model type. For Flux LoRA, the default is an empty string.
Gender of the voice (for professional cloning)
Only available for ElevenLabs voice training
Language of the audio samples (ISO 639-1 code)
Only available for ElevenLabs voice training
Initial learning rate (after the potential warmup period)
Default value varies depending on the model type. For Flux LoRA, the default is 0.0001.
Initial learning rate (after the potential warmup period) for the text encoder
Maximum [Flux LoRA: 0.001] Default [Flux LoRA: 0.00001] Minimum [Flux LoRA: 0.000001]
Initial learning rate (after the potential warmup period) for the UNet
Deprecated legacy training parameter.
lr_scheduler: Optional[Literal["constant", "constant-with-warmup", "cosine", 3 more]]The scheduler type to use (default: “constant”)
Deprecated legacy training parameter.
The scheduler type to use (default: “constant”)
Deprecated legacy training parameter.
Maximum number of training steps to execute (default: varies depending on the model type)
Default value varies depending on the model type:
- For Flux: number of training images * 100
Maximum value varies depending on the model type:
- For Flux: [0, 10000]
The number of epochs to train for
Only available for Flux LoRA training
The number of times to repeat the training
Only available for Flux LoRA training
The number of training steps for the text encoder
Deprecated legacy training parameter.
The number of training steps for the UNet
Deprecated legacy training parameter.
Optimize the model training task for a specific type of input images. The available values are:
- “likeness”: optimize training for likeness or portrait (targets specific transformer blocks)
- “all”: train all transformer blocks
- “none”: train no specific transformer blocks
This parameter controls which double and single transformer blocks are trained during the LoRA training process.
Only available for Flux LoRA training
The weight of prior preservation loss
Deprecated legacy training parameter.
Whether to random crop or center crop images before resizing to the working resolution
Deprecated legacy training parameter.
Ratio of random crops
Deprecated legacy training parameter.
Scale of random crops
Deprecated legacy training parameter.
The dimension of the LoRA update matrices
Only available for Flux LoRA and Musubi training
Default value varies depending on the model type:
- For Flux: 16
- For Musubi: 64
Each trainer enforces its own tighter limit (Flux LoRA: [2; 64], Musubi: [2; 128])
Whether to remove background noise from audio samples before cloning. When enabled, each sample must be at least 5 seconds long.
Only available for ElevenLabs voice training
The prompts to use for each epoch Only available for Flux LoRA training
The sample prompt images (AssetIds) paired with samplePrompts Only available for Flux LoRA training Must be the same length as samplePrompts
Whether to scale the learning rate
Note: Legacy parameter, will be ignored
Deprecated legacy training parameter.
Used to reproduce previous results. Default: randomly generated number.
Deprecated legacy training parameter.
Whether to train the text encoder or not
Example: For 100 steps and a value of 0.2, it means that the text encoder will be trained for 20 steps and then the UNet for 80 steps
Note: Legacy parameter, please use numTextTrainSteps and numUNetTrainSteps
Deprecated legacy training parameter.
Validation frequency. Cannot be greater than maxTrainSteps value
Deprecated legacy training parameter.
performance_stats: Optional[ModelPerformanceStats]Aggregated performance stats
Aggregated performance stats
The model short description (example: “This model generates highly detailed cinematic scenes.”)
training_images: Optional[List[ModelTrainingImage]]The URLs of the first 3 training images of the model. To retrieve the full set of images, get it by modelId
The URLs of the first 3 training images of the model. To retrieve the full set of images, get it by modelId
training_progress: Optional[ModelTrainingProgress]Additional information about the training progress of the model
Additional information about the training progress of the model
Signed URL of the captcha image to read aloud during PVC voice cloning. Only present when stage === ‘pending-captcha’. Overwritten on each retry.
Position of the job in the queue (ie. the number of job in the queue before this one)
Last recoverable failure message during PVC. Present when the model has bounced back to stage === ‘ready-for-captcha’ after a step 2 or step 3 failure (e.g. captcha rejected, time limit exceeded). Surface above the retry button so the user understands why they’re back here.
ui_config: Optional[ModelUiConfig]The UI configuration for the model
The UI configuration for the model
input_properties: Optional[Dict[str, ModelUiConfigInputProperties]]Configuration for the input properties
Configuration for the input properties
output_properties: Optional[Dict[str, ModelUiConfigOutputProperties]]Configuration for the provider outputs exposed by exposeOutput
Configuration for the provider outputs exposed by exposeOutput
resolution_component: Optional[ModelUiConfigResolutionComponent]Configuration for the resolution component
Configuration for the resolution component
class ModelUpdateResponse: …
model: Model
capabilities: List[Literal["3d23d", "audio2audio", "audio2txt", 30 more]]List of model capabilities (example: [“txt2img”, “img2img”, “txt2img_ip_adapter”, …])
List of model capabilities (example: [“txt2img”, “img2img”, “txt2img_ip_adapter”, …])
Whether the model is a custom model and can be used only with POST /generate/custom/{modelId} endpoint
type: Literal["custom", "elevenlabs-voice", "flux.1", 28 more]The model type (example: “flux.1-lora”)
The model type (example: “flux.1-lora”)
access_restrictions: Optional[Literal[0, 100, 25, 2 more]]The access restrictions of the model
0: Free plan
25: Creator plan
50: Pro plan
75: Team plan
100: Enterprise plan
The access restrictions of the model 0: Free plan 25: Creator plan 50: Pro plan 75: Team plan 100: Enterprise plan
class_: Optional[ModelClass]The class of the model
The class of the model
List of base model IDs compliant with the model (example: [“flux.1-dev”, “flux.1-schnell”]) This attribute is mainly used for Flux LoRA models
concepts: Optional[List[ModelConcept]]The concepts is required for the type model: composition
The concepts is required for the type model: composition
When true, credits spent on a generation with this model are not automatically refunded if the generation fails. Absent or false means failed generations are refunded as usual.
The epoch of the model. Only available for Flux Lora Trained models. If not set, uses the final model epoch (latest)
epochs: Optional[List[ModelEpoch]]The epochs of the model. Only available for Flux Lora Trained models.
The epochs of the model. Only available for Flux Lora Trained models.
inputs: Optional[List[ModelInput]]The inputs of the model. Only used for custom models. To retrieve this list, get it by modelId with GET /models/{modelId}
The inputs of the model. Only used for custom models. To retrieve this list, get it by modelId with GET /models/{modelId}
The allowed values for the input. For `string` or `number` types, creates a single-select dropdown. For `string_array` type, creates a multi-select dropdown.
background_behavior: Optional[Literal["opaque", "transparent"]]Specifies the background behavior for the input. Only available for `file` and `file_array`
input types with kind `image`.
Specifies the background behavior for the input. Only available for `file` and `file_array` input types with kind `image`.
Help text displayed in the UI to provide additional information about the input
Used to visually group inputs together in the UI. Inputs with the same group value appear consecutively in the UI.
The list of inputs which form an object within a container array. All inputs are the same as the current object. This is only available for type inputs_array inputs.
kind: Optional[Literal["3d", "audio", "document", 5 more]]The asset kind of the input. Only taken into account for `file` and `file_array` input types.
If model provides multiple kinds,
the input will be not able to create the asset on the flight on API side with dataurl without data:kind, prefix
`file` and `file_array` inputs always expose a kind: when a model does not declare one,
`image` is returned, which is the kind used at generation time.
The asset kind of the input. Only taken into account for `file` and `file_array` input types. If model provides multiple kinds, the input will be not able to create the asset on the flight on API side with dataurl without data:kind, prefix `file` and `file_array` inputs always expose a kind: when a model does not declare one, `image` is returned, which is the kind used at generation time.
The maximum allowed media duration in seconds. Only applies to `file` and `file_array` input types for video and audio assets. Validated against `asset.properties.duration` at job creation time.
The maximum allowed length for `string` and `model` inputs, in characters. For the array types (`string_array`, `model_array`) it bounds the NUMBER OF ITEMS instead — the length of each item is not constrained.
The maximum allowed file size in bytes. Only applies to `file` and `file_array` input types. Validated against `asset.properties.size` at job creation time.
The minimum allowed length for `string` and `model` inputs, in characters. For the array types (`string_array`, `model_array`) it bounds the NUMBER OF ITEMS instead — the length of each item is not constrained.
model_types: Optional[List[Literal["custom", "elevenlabs-voice", "flux.1", 28 more]]]The allowed model types for this input. Example: `[“flux.1-lora”]`.
Only available for `model_array` input type.
The allowed model types for this input. Example: `[“flux.1-lora”]`. Only available for `model_array` input type.
Whether this input represents a parent asset to assign to the produced assets. Only available for `file` and `file_array` input types.
For `file_array`, the parent asset is the first item in the array.
Whether the input is a prompt. When true, displays as a text area with prompt spark feature. Only available for `string` input type.
Whether the input is used with prompt spark. Only available for `string` input type.
required: Optional[ModelInputRequired]Set of rules that describes when this input is required:
- `always`: Input is always required
- `ifNotDefined`: Input is required when another specified input is not defined
- `ifDefined`: Input is required when another specified input is defined
- `conditionalValues`: Input is required when another input has a specific value
By default, the input is not required.
Set of rules that describes when this input is required:
- `always`: Input is always required
- `ifNotDefined`: Input is required when another specified input is not defined
- `ifDefined`: Input is required when another specified input is defined
- `conditionalValues`: Input is required when another input has a specific value
By default, the input is not required.
Makes this input required when another input has a specific value:
- Key: name of the input to check
- Value: operation and allowed values that trigger the requirement
The model keyword, this is a legacy parameter, please use conceptPrompt in parameters
Fine-tune the model’s inferences with negative prompt embedding
parameters: Optional[ModelParameters]The parameters of the model
The parameters of the model
Age group of the voice (for professional cloning)
Only available for ElevenLabs voice training
The batch size Less steps, and will increase the learning rate
Only available for Flux LoRA training
The prompt to specify images in the same class as provided instance images
Deprecated legacy training parameter.
Type of voice cloning: “instant” (fast) or “professional” (higher quality, requires captcha)
Only available for ElevenLabs voice training
The prompt with identifier specifying the instance (or subject) of the class (example: “a daiton dog”)
Default value varies depending on the model type. For Flux LoRA, the default is an empty string.
Gender of the voice (for professional cloning)
Only available for ElevenLabs voice training
Language of the audio samples (ISO 639-1 code)
Only available for ElevenLabs voice training
Initial learning rate (after the potential warmup period)
Default value varies depending on the model type. For Flux LoRA, the default is 0.0001.
Initial learning rate (after the potential warmup period) for the text encoder
Maximum [Flux LoRA: 0.001] Default [Flux LoRA: 0.00001] Minimum [Flux LoRA: 0.000001]
Initial learning rate (after the potential warmup period) for the UNet
Deprecated legacy training parameter.
lr_scheduler: Optional[Literal["constant", "constant-with-warmup", "cosine", 3 more]]The scheduler type to use (default: “constant”)
Deprecated legacy training parameter.
The scheduler type to use (default: “constant”)
Deprecated legacy training parameter.
Maximum number of training steps to execute (default: varies depending on the model type)
Default value varies depending on the model type:
- For Flux: number of training images * 100
Maximum value varies depending on the model type:
- For Flux: [0, 10000]
The number of epochs to train for
Only available for Flux LoRA training
The number of times to repeat the training
Only available for Flux LoRA training
The number of training steps for the text encoder
Deprecated legacy training parameter.
The number of training steps for the UNet
Deprecated legacy training parameter.
Optimize the model training task for a specific type of input images. The available values are:
- “likeness”: optimize training for likeness or portrait (targets specific transformer blocks)
- “all”: train all transformer blocks
- “none”: train no specific transformer blocks
This parameter controls which double and single transformer blocks are trained during the LoRA training process.
Only available for Flux LoRA training
The weight of prior preservation loss
Deprecated legacy training parameter.
Whether to random crop or center crop images before resizing to the working resolution
Deprecated legacy training parameter.
Ratio of random crops
Deprecated legacy training parameter.
Scale of random crops
Deprecated legacy training parameter.
The dimension of the LoRA update matrices
Only available for Flux LoRA and Musubi training
Default value varies depending on the model type:
- For Flux: 16
- For Musubi: 64
Each trainer enforces its own tighter limit (Flux LoRA: [2; 64], Musubi: [2; 128])
Whether to remove background noise from audio samples before cloning. When enabled, each sample must be at least 5 seconds long.
Only available for ElevenLabs voice training
The prompts to use for each epoch Only available for Flux LoRA training
The sample prompt images (AssetIds) paired with samplePrompts Only available for Flux LoRA training Must be the same length as samplePrompts
Whether to scale the learning rate
Note: Legacy parameter, will be ignored
Deprecated legacy training parameter.
Used to reproduce previous results. Default: randomly generated number.
Deprecated legacy training parameter.
Whether to train the text encoder or not
Example: For 100 steps and a value of 0.2, it means that the text encoder will be trained for 20 steps and then the UNet for 80 steps
Note: Legacy parameter, please use numTextTrainSteps and numUNetTrainSteps
Deprecated legacy training parameter.
Validation frequency. Cannot be greater than maxTrainSteps value
Deprecated legacy training parameter.
performance_stats: Optional[ModelPerformanceStats]Aggregated performance stats
Aggregated performance stats
The model short description (example: “This model generates highly detailed cinematic scenes.”)
training_images: Optional[List[ModelTrainingImage]]The URLs of the first 3 training images of the model. To retrieve the full set of images, get it by modelId
The URLs of the first 3 training images of the model. To retrieve the full set of images, get it by modelId
training_progress: Optional[ModelTrainingProgress]Additional information about the training progress of the model
Additional information about the training progress of the model
Signed URL of the captcha image to read aloud during PVC voice cloning. Only present when stage === ‘pending-captcha’. Overwritten on each retry.
Position of the job in the queue (ie. the number of job in the queue before this one)
Last recoverable failure message during PVC. Present when the model has bounced back to stage === ‘ready-for-captcha’ after a step 2 or step 3 failure (e.g. captcha rejected, time limit exceeded). Surface above the retry button so the user understands why they’re back here.
ui_config: Optional[ModelUiConfig]The UI configuration for the model
The UI configuration for the model
input_properties: Optional[Dict[str, ModelUiConfigInputProperties]]Configuration for the input properties
Configuration for the input properties
output_properties: Optional[Dict[str, ModelUiConfigOutputProperties]]Configuration for the provider outputs exposed by exposeOutput
Configuration for the provider outputs exposed by exposeOutput
resolution_component: Optional[ModelUiConfigResolutionComponent]Configuration for the resolution component
Configuration for the resolution component
ModelsDescription
Retrieve
Update
ModelsExpand Collapse
class DescriptionRetrieveResponse: …
description: Description
assets: List[DescriptionAsset]The list of assets referenced by the Markdown {asset} tag in the description.
The list of assets referenced by the Markdown {asset} tag in the description.
The owner (project) ID (example: “proj_23tlk332lkht3kl2” or “team_dlkhgs23tlk3hlkth32lkht3kl2” for old teams)
properties: DescriptionAssetPropertiesThe properties of the asset, content may depend on the kind of asset returned
The properties of the asset, content may depend on the kind of asset returned
camera_mode: Optional[Literal["aerial", "interior", "turntable"]]Recommended preview camera mode emitted by the generator (gsplat route);
passed through to mesh-rendering verbatim.
Recommended preview camera mode emitted by the generator (gsplat route); passed through to mesh-rendering verbatim.
camera_trajectory: Optional[List[DescriptionAssetPropertiesCameraTrajectory]]Recommended preview camera path emitted by the generator (gsplat route);
passed through to mesh-rendering verbatim.
Recommended preview camera path emitted by the generator (gsplat route); passed through to mesh-rendering verbatim.
Number of Unicode code points in the text. Code-point-aware (so a non-BMP emoji counts as 1) but not full grapheme-cluster aware (a ZWJ sequence still counts as several).
classification: Optional[Literal["effect", "interview", "music", 5 more]]Classification of the audio
Classification of the audio
True when preview holds the entire content unmodified — consumers can
use it directly without fetching asset.url. False or undefined means
the content exceeds the preview budget and consumers must fetch the
full body from S3 to read past the preview.
Leading slice of the content used for inline UI display and as a search shortcut. Capped at TEXT_PREVIEW_MAX_BYTES (UTF-8) and always cut on a code-point boundary so no character is split. Number of characters in the preview varies by script (around 1024 for ASCII, ~340 for CJK, ~256 for emoji-heavy text at the default 1 KB budget).
source: Literal["3d23d", "3d23d:texture", "3d:texture", 77 more]source of the asset
source of the asset
The original file url.
Contains the url of the original file. without any conversion. Only available for some specific video, audio and threeD assets. Is only specified if the given asset data has been replaced with a new file during the creation of the asset.
original_mime_type: Optional[Literal["application/gzip", "application/json", "application/octet-stream", 46 more]]The mime type of the original file url.
The original file is stored under a key that carries no extension, so this
is the only way to know which format originalFileUrl serves (e.g. an HDRi
skybox exposes a JPEG preview as url and its .exr or .hdr file as the
original). Omitted when the stored format could not be determined.
The mime type of the original file url.
The original file is stored under a key that carries no extension, so this
is the only way to know which format originalFileUrl serves (e.g. an HDRi
skybox exposes a JPEG preview as url and its .exr or .hdr file as the
original). Omitted when the stored format could not be determined.
models: List[DescriptionModel]The list of models referenced by the Markdown {model} tag in the description.
The list of models referenced by the Markdown {model} tag in the description.
class DescriptionUpdateResponse: …
description: Description
assets: List[DescriptionAsset]The list of assets referenced by the Markdown {asset} tag in the description.
The list of assets referenced by the Markdown {asset} tag in the description.
The owner (project) ID (example: “proj_23tlk332lkht3kl2” or “team_dlkhgs23tlk3hlkth32lkht3kl2” for old teams)
properties: DescriptionAssetPropertiesThe properties of the asset, content may depend on the kind of asset returned
The properties of the asset, content may depend on the kind of asset returned
camera_mode: Optional[Literal["aerial", "interior", "turntable"]]Recommended preview camera mode emitted by the generator (gsplat route);
passed through to mesh-rendering verbatim.
Recommended preview camera mode emitted by the generator (gsplat route); passed through to mesh-rendering verbatim.
camera_trajectory: Optional[List[DescriptionAssetPropertiesCameraTrajectory]]Recommended preview camera path emitted by the generator (gsplat route);
passed through to mesh-rendering verbatim.
Recommended preview camera path emitted by the generator (gsplat route); passed through to mesh-rendering verbatim.
Number of Unicode code points in the text. Code-point-aware (so a non-BMP emoji counts as 1) but not full grapheme-cluster aware (a ZWJ sequence still counts as several).
classification: Optional[Literal["effect", "interview", "music", 5 more]]Classification of the audio
Classification of the audio
True when preview holds the entire content unmodified — consumers can
use it directly without fetching asset.url. False or undefined means
the content exceeds the preview budget and consumers must fetch the
full body from S3 to read past the preview.
Leading slice of the content used for inline UI display and as a search shortcut. Capped at TEXT_PREVIEW_MAX_BYTES (UTF-8) and always cut on a code-point boundary so no character is split. Number of characters in the preview varies by script (around 1024 for ASCII, ~340 for CJK, ~256 for emoji-heavy text at the default 1 KB budget).
source: Literal["3d23d", "3d23d:texture", "3d:texture", 77 more]source of the asset
source of the asset
The original file url.
Contains the url of the original file. without any conversion. Only available for some specific video, audio and threeD assets. Is only specified if the given asset data has been replaced with a new file during the creation of the asset.
original_mime_type: Optional[Literal["application/gzip", "application/json", "application/octet-stream", 46 more]]The mime type of the original file url.
The original file is stored under a key that carries no extension, so this
is the only way to know which format originalFileUrl serves (e.g. an HDRi
skybox exposes a JPEG preview as url and its .exr or .hdr file as the
original). Omitted when the stored format could not be determined.
The mime type of the original file url.
The original file is stored under a key that carries no extension, so this
is the only way to know which format originalFileUrl serves (e.g. an HDRi
skybox exposes a JPEG preview as url and its .exr or .hdr file as the
original). Omitted when the stored format could not be determined.
models: List[DescriptionModel]The list of models referenced by the Markdown {model} tag in the description.
The list of models referenced by the Markdown {model} tag in the description.
ModelsExamples
List
Update
ModelsExpand Collapse
class ExampleListResponse: …
examples: List[Example]
asset: ExampleAssetAsset generated by the inference
Asset generated by the inference
edit_capabilities: List[Literal["DETECTION", "GENERATIVE_FILL", "PIXELATE", 8 more]]List of edit capabilities
List of edit capabilities
metadata: ExampleAssetMetadataMetadata of the asset with some additional information
Metadata of the asset with some additional information
type: Literal["3d-texture", "3d-texture-albedo", "3d-texture-metallic", 77 more]The type of the asset. Ex: ‘inference-txt2img’ will represent an asset generated from a text to image model
The type of the asset. Ex: ‘inference-txt2img’ will represent an asset generated from a text to image model
How angular is the surface? 0 is like a sphere, 1 is like a mechanical object
The optional aspect ratio given for the generation, only applicable for some models
A bounding box around the object of interest, in the format [x1, y1, x2, y2].
The control image already processed by canny detector. Must reference an existing AssetId.
Ensure upscaled tile have the same color histogram as original tile.
concepts: Optional[List[ExampleAssetMetadataConcept]]Flux Kontext LoRA to style the image.
For Flux Kontext Prompt Editing.
Flux Kontext LoRA to style the image. For Flux Kontext Prompt Editing.
Allow the generation of “hallucinations” during the upscale process, which adds additional details and deviates from the original image. Default: optimized for your preset and style.
Amount of decay in creativity over the upscale process. The lowest the value, the less the creativity will be preserved over the upscale process.
The control image processed by depth estimator. Must reference an existing AssetId.
Determine the scale at which the upscale process works.
- With a small value, the upscale works at the largest scale, resulting in fewer added details and more coherent images. Ideal for portraits, for example.
- With a large value, the upscale works at the smallest scale, resulting in more added details and more hallucinations. Ideal for landscapes, for example.
(info): A small value is slower and more expensive to run.
Apply extra control to the Skybox 360 geometry. The higher the value, the more the 360 geometry will influence the generated skybox image.
Use with caution. Default is adapted to the other parameters.
The input image to process. Must reference an existing AssetId or be a data URL.
Strengthen the similarity to the original image during the upscale. Default: optimized for your preset and style.
image_type: Optional[Literal["seamfull", "skybox", "texture"]]Preserve the seamless properties of skybox or texture images. Input has to be of same type (seamless).
Preserve the seamless properties of skybox or texture images. Input has to be of same type (seamless).
input_fidelity: Optional[Literal["high", "low"]]When set to high, allows to better preserve details from the input images in the output.
This is especially useful when using images that contain elements like faces or logos that
require accurate preservation in the generated image.
You can provide multiple input images that will all be preserved with high fidelity, but keep
in mind that the first image will be preserved with richer textures and finer details, so if
you include elements such as faces, consider placing them in the first image.
Only available for the gpt-image-1 model.
When set to high, allows to better preserve details from the input images in the output.
This is especially useful when using images that contain elements like faces or logos that
require accurate preservation in the generated image.
You can provide multiple input images that will all be preserved with high fidelity, but keep in mind that the first image will be preserved with richer textures and finer details, so if you include elements such as faces, consider placing them in the first image.
Only available for the gpt-image-1 model.
input_location: Optional[Literal["bottom", "left", "middle", 2 more]]Location of the input image in the output.
Location of the input image in the output.
How polished is the surface? 0 is like a rough surface, 1 is like a mirror
model_type: Optional[Literal["custom", "elevenlabs-voice", "flux.1", 28 more]]The type of the generator used
The type of the generator used
Controls the influence of the negative prompt. Default 0 means the negative prompt has no effect. Higher values increase negative prompt influence. Must be > 0 if negativePrompt is provided.
The number of denoising steps for each image generation.
Override the embeddings of the model. Only your prompt and negativePrompt will be used. Use with caution.
List of points (label, x, y) in the image where label = 0 for background and 1 for object.
How polished is the surface? 0 is like a rough surface, 1 is like a mirror
Increase the fidelity to the prompt during upscale. Default: optimized for your preset and style.
How raised is the surface? 0 is flat like water, 1 is like a very rough rock
Additional refinement steps before scaling.
If scalingFactor == 1, the refinement process will be applied (1 + refinementSteps) times. If scalingFactor > 1, the refinement process will be applied refinementSteps times.
Boolean to return the source image with the mask applied as alpha channel
(RGBA PNG, transparent background) instead of the binary mask.
Mutually exclusive with resultMask — passing both as true returns a 400 error.
Note: backgroundOpacity is no longer honored — alpha is binary (0/255) only.
Boolean to return the binary masks in the response.
Mutually exclusive with resultImage — passing both as true returns a 400 error.
Save a flipbook of the texture. Deactivated when the input texture is larger than 2048x2048px
The seed used to generate this asset. <!> Can be a string or a number in some cases <!>.
How shiny is the surface? 0 is like a matte surface, 1 is like a diamond
Strength for the input image structure preservation
The control image for structure. A canny detector will be applied to this image. Must reference an existing AssetId.