Gen AI API's

The GETTING STARTED section provides essential information for developers to quickly familiarize themselves with the FastAPI API. Users can learn how to authenticate, make basic API requests, and navigate through the documentation to get started with integrating FastAPI into their projects efficiently.

Header Parameters

Authorizationstring

Body Parameters

app_idstring Required

-> Each model is uniquely characterized by its own app_id.

heightnumber

-> The height parameter represents the vertical dimension of an image. -> The valid range for the parameter is between 256 and 1536 pixels.

Minimum

512

Maximum

1536

Multiple of

64

Default value

512

widthnumber (int32)

-> The width parameter represents the horizontal dimension of an image. -> The valid range for the parameter is between 256 and 1536 pixels.

Minimum

512

Maximum

1536

Multiple of

64

Default value

512

num_inference_stepsnumber

-> The num_inference_steps parameter represents the number of denoising iterations to perform during the image generation process. Generally, more iterations can result in higher-quality images, but they also increase the time required for generation. -> The valid range for the num_inference_steps parameter is between 1 and 50.

Minimum

10

Maximum

100

Default value

50

guidance_scalenumber

-> The guidance_scale parameter determines how closely the generated image adheres to the provided prompt. Higher values result in the model following the prompt more closely, while lower values allow for more creative deviation. -> The valid range for the guidance_scale parameter is between 1 and 30.

Minimum

2

Maximum

25

Default value

7.5

batchnumber

-> The batch parameter allows you to specify the number of images to generate at once. -> The valid range for this parameter is between 1 and 8.

Minimum

1

Maximum

4

Default value

1

promptstring

-> The prompt parameter is the textual input that guides the image generation process. This prompt serves as an artistic compass, shaping the visual output.

Default value

a beautiful painting

negative_promptstring

-> The negative_prompt parameter allows you to specify content that you want the image generation model to avoid or minimize in the output. This can be useful for excluding certain visual elements or styles that you do not want to be present in the generated image.

celeryboolean

-> The celery parameter is used for queuing tasks that require extended processing time. When you enqueue a task, you receive a unique task_id. This task_id allows you to check the task's status later using the task status API, which is useful for managing and tracking long-running tasks.

Default value

false

inference_typestring

-> The inference_type parameter allows you to specify the GPU to be used for the image generation task. The supported values are: a10g a100 h100 This parameter is only applicable for Qolaba-deployed models, including Turbo Vision, Qolaba Style, Cartoon, Realistic, and Anime Style. The different GPU options provide varying levels of performance and capabilities, allowing you to choose the most suitable GPU based on your requirements and the demand for the task.

Response

200

Object

Successful Response

Response Attributes

time_requiredstring

This parameter specifies both the container startup time and the duration needed to complete the assigned task.

Default value

[object Object]

errorstring

None

error_datastring

None

inputstring

Here, you'll find the user-provided input parameters – a glimpse into the data supplied by users.

Default value

[object Object]

outputstring

This parameter provides the outcome of task execution, offering the results achieved during the process.

Default value

[object Object]

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

Default value

[object Object]

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

422

Object

Validation Error

Response Attributes

detailarray

Show child attributes

500

Object

Response Attributes

time_requiredstring

None

errorstring

This parameter specifies the error type, giving valuable information about the issue encountered.

error_datastring

This parameter contains comprehensive information about the error, offering valuable insights that can aid in resolving similar issues in the future.

inputstring

None

outputstring

None

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

curl --location 'https://qolaba-server-b2b.up.railway.app/api/v1/studio/getTextToImage' \
--header 'Authorization: Bearer {token}' \
--data '{
  "app_id": "ap-oDVXRQ7bCaWW05O52P1mlA",
  "height": 1024,
  "width": 1024,
  "num_inference_steps": 50,
  "guidance_scale": 7.5,
  "batch": 1,
  "prompt": "a beautiful girl pilot wearing aviator googles, unreal engine render, 8k",
  "negative_prompt": " ",
  "celery": false,
  "inference_type": "a10g"
}'

{
  "time_required": "",
  "error": "",
  "error_data": "",
  "input": "",
  "output": "",
  "app_id": "",
  "task_id": "",
  "status": ""
}

Header Parameters

Authorizationstring

Body Parameters

app_idstring Required

-> Each model is uniquely characterized by its own app_id.

imagestring Required

-> The file_url parameter specifies the URL of an existing image that will be used as a reference for the generation process. -> If the original image dimensions exceed 1536x1536 pixels, the image will be adjusted to fit within this size while preserving the original aspect ratio.

promptstring

-> The prompt parameter is the textual input that guides the image generation process. This prompt serves as an artistic compass, shaping the visual output.

Default value

a beautiful painting

guidance_scalenumber

-> The guidance_scale parameter determines how closely the generated image adheres to the provided prompt. Higher values result in the model following the prompt more closely, while lower values allow for more creative deviation. -> The valid range for the guidance_scale parameter is between 1 and 30.

Minimum

2

Maximum

25

Default value

7.5

batchnumber

-> The batch parameter allows you to specify the number of images to generate at once. -> The valid range for this parameter is between 1 and 8.

Minimum

1

Maximum

4

Default value

1

strengthnumber

-> The strength parameter specifies the degree of transformation applied to the reference image. -> A higher strength value (up to 1) results in the generated image deviating more from the initial reference image, as more noise is introduced. A strength of 1 completely disregards the initial image.

Maximum

1

Default value

0.7

heightnumber

-> The height parameter represents the vertical dimension of an image. -> The valid range for the parameter is between 256 and 1536 pixels. -> This parameter is only applicable for the SDXL API, as it requires specific height and width values.

Minimum

512

Maximum

1536

Multiple of

64

Default value

1024

widthnumber

-> The width parameter represents the horizontal dimension of an image. -> The valid range for the parameter is between 256 and 1536 pixels. -> This parameter is only applicable for the SDXL API, as it requires specific height and width values.

Minimum

512

Maximum

1536

Multiple of

64

Default value

1024

negative_promptstring

-> The negative_prompt parameter allows you to specify content that you want the image generation model to avoid or minimize in the output. This can be useful for excluding certain visual elements or styles that you do not want to be present in the generated image.

celeryboolean

-> The celery parameter is used for queuing tasks that require extended processing time. When you enqueue a task, you receive a unique task_id. This task_id allows you to check the task's status later using the task status API, which is useful for managing and tracking long-running tasks.

Default value

false

inference_typestring

-> The inference_type parameter allows you to specify the GPU to be used for the image generation task. The supported values are: a10g a100 h100 This parameter is only applicable for Qolaba-deployed models, including Turbo Vision, Qolaba Style, Cartoon, Realistic, and Anime Style. The different GPU options provide varying levels of performance and capabilities, allowing you to choose the most suitable GPU based on your requirements and the demand for the task.

Response

200

Object

Successful Response

Response Attributes

time_requiredstring

This parameter specifies both the container startup time and the duration needed to complete the assigned task.

Default value

[object Object]

errorstring

None

error_datastring

None

inputstring

Here, you'll find the user-provided input parameters – a glimpse into the data supplied by users.

Default value

[object Object]

outputstring

This parameter provides the outcome of task execution, offering the results achieved during the process.

Default value

[object Object]

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

Default value

[object Object]

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

422

Object

Validation Error

Response Attributes

detailarray

Show child attributes

500

Object

Internal Error

Response Attributes

time_requiredstring

None

errorstring

This parameter specifies the error type, giving valuable information about the issue encountered.

error_datastring

This parameter contains comprehensive information about the error, offering valuable insights that can aid in resolving similar issues in the future.

inputstring

None

outputstring

None

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

curl --location 'https://qolaba-server-b2b.up.railway.app/api/v1/studio/getImageToImage' \
--header 'Authorization: Bearer {token}' \
--data '{
  "app_id": "ap-eRSyl0imzrUrbvgdAYwDTl",
  "image": "https://res.cloudinary.com/qolaba/image/upload/v1695690455/kxug1tmiolt1dtsvv5br.jpg",
  "prompt": "a beautiful girl pilot wearing aviator googles, unreal engine render, 8k",
  "guidance_scale": 7.5,
  "batch": 1,
  "strength": 0.7,
  "height": 1024,
  "width": 1024,
  "negative_prompt": " ",
  "celery": false,
  "inference_type": "a10g"
}'

{
  "time_required": "",
  "error": "",
  "error_data": "",
  "input": "",
  "output": "",
  "app_id": "",
  "task_id": "",
  "status": ""
}

App ID	Model Name
ap-1us0FK21Ach6eiWxo22is8	Canny ControlNet
ap-WrXnJBXy23XpPh6IlH5tRX	Depth ControlNet
ap-a1b2c3d4e5f6g7h8i9j0kq	OpenPose ControlNet

Header Parameters

Authorizationstring

Body Parameters

app_idstring Required

-> Each model is uniquely characterized by its own app_id.

imagestring Required

-> The file_url parameter specifies the URL of an existing image that will be used as a reference for the generation process. -> If the original image dimensions exceed 1536x1536 pixels, the image will be adjusted to fit within this size while preserving the original aspect ratio.

promptstring

-> The prompt parameter is the textual input that guides the image generation process. This prompt serves as an artistic compass, shaping the visual output.

Default value

a beautiful painting

guidance_scalenumber

-> The guidance_scale parameter determines how closely the generated image adheres to the provided prompt. Higher values result in the model following the prompt more closely, while lower values allow for more creative deviation. -> The valid range for the guidance_scale parameter is between 1 and 30.

Minimum

2

Maximum

25

Default value

7.5

batchnumber

-> The batch parameter allows you to specify the number of images to generate at once. -> The valid range for this parameter is between 1 and 8.

Minimum

1

Maximum

4

Default value

1

strengthnumber

-> The strength parameter specifies the degree of transformation applied to the reference image.

negative_promptstring

-> The negative_prompt parameter allows you to specify content that you want the image generation model to avoid or minimize in the output. This can be useful for excluding certain visual elements or styles that you do not want to be present in the generated image.

num_inference_stepsnumber

-> The num_inference_steps parameter represents the number of denoising iterations to perform during the image generation process. Generally, more iterations can result in higher-quality images, but they also increase the time required for generation. -> The valid range for the num_inference_steps parameter is between 1 and 50.

celeryboolean

-> The celery parameter is used for queuing tasks that require extended processing time. When you enqueue a task, you receive a unique task_id. This task_id allows you to check the task's status later using the task status API, which is useful for managing and tracking long-running tasks.

Default value

false

inference_typestring

-> The inference_type parameter allows you to specify the GPU to be used for the image generation task. The supported values are: a10g a100 h100 The different GPU options provide varying levels of performance and capabilities, allowing you to choose the most suitable GPU based on your requirements and the demand for the task.

Response

200

Object

Successful Response

Response Attributes

time_requiredstring

This parameter specifies both the container startup time and the duration needed to complete the assigned task.

Default value

[object Object]

errorstring

None

error_datastring

None

inputstring

Here, you'll find the user-provided input parameters – a glimpse into the data supplied by users.

Default value

[object Object]

outputstring

This parameter provides the outcome of task execution, offering the results achieved during the process.

Default value

[object Object]

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

Default value

[object Object]

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

422

Object

Validation Error

Response Attributes

detailarray

Show child attributes

500

Object

Response Attributes

time_requiredstring

None

errorstring

This parameter specifies the error type, giving valuable information about the issue encountered.

error_datastring

This parameter contains comprehensive information about the error, offering valuable insights that can aid in resolving similar issues in the future.

inputstring

None

outputstring

None

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

curl --location 'https://qolaba-server-b2b.up.railway.app/api/v1/studio/getImageToImage' \
--header 'Authorization: Bearer {token}' \
--data '{
  "app_id": "ap-1us0FK21Ach6eiWxo22is8",
  "image": "https://res.cloudinary.com/qolaba/image/upload/v1695690455/kxug1tmiolt1dtsvv5br.jpg",
  "prompt": "a beautiful girl pilot wearing aviator googles, unreal engine render, 8k",
  "guidance_scale": 7.5,
  "batch": 1,
  "strength": 0.7,
  "negative_prompt": " ",
  "num_inference_steps": 30,
  "celery": false,
  "inference_type": "a10g"
}'

{
  "time_required": "",
  "error": "",
  "error_data": "",
  "input": "",
  "output": "",
  "app_id": "",
  "task_id": "",
  "status": ""
}

Header Parameters

Authorizationstring

Body Parameters

app_idstring Required

-> The celery parameter is used for queuing tasks that require extended processing time. When you enqueue a task, you receive a unique task_id. This task_id allows you to check the task's status later using the task status API, which is useful for managing and tracking long-running tasks.

imagestring Required

-> The file_url parameter specifies the URL of an existing image that will be used as a reference for the generation process. -> If the original image dimensions exceed 1536x1536 pixels, the image will be adjusted to fit within this size while preserving the original aspect ratio.

mask_urlstring

-> The mask_url parameter is used for providing image mask. It specifies a binary mask image that defines the regions of the input image that should be inpainted.

promptstring

-> The prompt parameter is the textual input that guides the image generation process. This prompt serves as an artistic compass, shaping the visual output.

Default value

a beautiful painting

batchnumber

-> The batch parameter allows you to specify the number of images to generate at once. -> The valid range for this parameter is between 1 and 8.

Minimum

1

Maximum

4

Default value

1

negative_promptstring

-> The negative_prompt parameter allows you to specify content that you want the image generation model to avoid or minimize in the output. This can be useful for excluding certain visual elements or styles that you do not want to be present in the generated image.

celeryboolean

-> The celery parameter is used for queuing tasks that require extended processing time. When you enqueue a task, you receive a unique task_id. This task_id allows you to check the task's status later using the task status API, which is useful for managing and tracking long-running tasks.

Default value

false

Response

200

Object

Successful Response

Response Attributes

time_requiredstring

This parameter specifies both the container startup time and the duration needed to complete the assigned task.

Default value

[object Object]

errorstring

None

error_datastring

None

inputstring

Here, you'll find the user-provided input parameters – a glimpse into the data supplied by users.

Default value

[object Object]

outputstring

This parameter provides the outcome of task execution, offering the results achieved during the process.

Default value

[object Object]

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

Default value

[object Object]

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

422

Object

Validation Error

Response Attributes

detailarray

Show child attributes

500

Object

Internal Error

Response Attributes

time_requiredstring

None

errorstring

This parameter specifies the error type, giving valuable information about the issue encountered.

error_datastring

This parameter contains comprehensive information about the error, offering valuable insights that can aid in resolving similar issues in the future.

inputstring

None

outputstring

None

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

curl --location 'https://qolaba-server-b2b.up.railway.app/api/v1/studio/getImageToImage' \
--header 'Authorization: Bearer {token}' \
--data '{
  "app_id": "ap-7XmHk4LtVgFJq2cQoE3yB8",
  "image": "https://storage.googleapis.com/qolaba-staging/20240418174355_89987b26-8ccb-4be9-9012-820003441c05.jpg",
  "mask_url": "https://storage.googleapis.com/qolaba-staging/1714616201732_image.png",
  "prompt": " ",
  "batch": 1,
  "negative_prompt": " ",
  "celery": false
}'

{
  "time_required": "",
  "error": "",
  "error_data": "",
  "input": "",
  "output": "",
  "app_id": "",
  "task_id": "",
  "status": ""
}

Header Parameters

Authorizationstring

Body Parameters

app_idstring Required

-> Each model is uniquely characterized by its own app_id.

imagestring Required

-> The file_url parameter specifies the URL of an existing image that will be used as a reference for the generation process. -> If the original image dimensions exceed 1536x1536 pixels, the image will be adjusted to fit within this size while preserving the original aspect ratio.

promptstring

-> The prompt parameter is the textual input that guides the image generation process. This prompt serves as an artistic compass, shaping the visual output.

Default value

a beautiful painting

batchnumber

-> The batch parameter allows you to specify the number of images to generate at once. -> The valid range for this parameter is between 1 and 8.

Minimum

1

Maximum

4

Default value

1

negative_promptstring

-> The negative_prompt parameter allows you to specify content that you want the image generation model to avoid or minimize in the output. This can be useful for excluding certain visual elements or styles that you do not want to be present in the generated image.

celerystring

-> The celery parameter is used for queuing tasks that require extended processing time. When you enqueue a task, you receive a unique task_id. This task_id allows you to check the task's status later using the task status API, which is useful for managing and tracking long-running tasks.

Default value

false

Response

200

Object

Successful Response

Response Attributes

time_requiredstring

This parameter specifies both the container startup time and the duration needed to complete the assigned task.

Default value

[object Object]

errorstring

None

error_datastring

None

inputstring

Here, you'll find the user-provided input parameters – a glimpse into the data supplied by users.

Default value

[object Object]

outputstring

This parameter provides the outcome of task execution, offering the results achieved during the process.

Default value

[object Object]

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

Default value

[object Object]

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

422

Object

Validation Error

Response Attributes

detailarray

Show child attributes

500

Object

Internal Error

Response Attributes

time_requiredstring

None

errorstring

This parameter specifies the error type, giving valuable information about the issue encountered.

error_datastring

This parameter contains comprehensive information about the error, offering valuable insights that can aid in resolving similar issues in the future.

inputstring

None

outputstring

None

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

curl --location 'https://qolaba-server-b2b.up.railway.app/api/v1/studio/getImageToImage' \
--header 'Authorization: Bearer {token}' \
--data '{
  "app_id": "ap-L4vHj7YbXeT2qKoU1fW3G7",
  "image": "https://res.cloudinary.com/qolaba/image/upload/v1695690455/kxug1tmiolt1dtsvv5br.jpg",
  "prompt": "a beautiful girl pilot wearing aviator googles, unreal engine render, 8k",
  "batch": 1,
  "negative_prompt": " ",
  "celery": "false"
}'

{
  "time_required": "",
  "error": "",
  "error_data": "",
  "input": "",
  "output": "",
  "app_id": "",
  "task_id": "",
  "status": ""
}

The concept of a "Consistent Face Model" involves the creation of images where the face maintains a consistent appearance across multiple generated Images. To achieve this, you start with an initial facial image and provide it as a reference. Using this reference, a sophisticated model goes to work, crafting new images while keeping the facial features in line with the original picture. In essence, the model uses your input to generate images where the face remains faithful to the structure and characteristics you've specified in your prompt. This way, you can effortlessly create a series of images with a consistent and recognizable face

For more insights and a deeper dive into how it all works, you can find a treasure trove of details right over here.

Header Parameters

Authorizationstring

Body Parameters

app_idstring Required

-> Each model is uniquely characterized by its own app_id.

imagestring Required

-> The file_url parameter specifies the URL of an existing image that will be used as a reference for the generation process. -> If the original image dimensions exceed 1536x1536 pixels, the image will be adjusted to fit within this size while preserving the original aspect ratio.

promptstring

-> The prompt parameter is the textual input that guides the image generation process. This prompt serves as an artistic compass, shaping the visual output.

Default value

a beautiful painting

batchnumber

-> The batch parameter allows you to specify the number of images to generate at once. -> The valid range for this parameter is between 1 and 8.

Minimum

1

Maximum

4

Default value

1

heightnumber

-> The height parameter represents the vertical dimension of an image. -> The valid range for the parameter is between 256 and 1536 pixels.

Minimum

256

Maximum

1536

Default value

1024

widthnumber

-> The width parameter represents the horizontal dimension of an image.

Minimum

256

Maximum

1536

Default value

1024

num_inference_stepsnumber

-> The num_inference_steps parameter represents the number of denoising iterations to perform during the image generation process. Generally, more iterations can result in higher-quality images, but they also increase the time required for generation. -> The valid range for the num_inference_steps parameter is between 1 and 50.

guidance_scalenumber

-> The guidance_scale parameter determines how closely the generated image adheres to the provided prompt. Higher values result in the model following the prompt more closely, while lower values allow for more creative deviation. -> The valid range for the guidance_scale parameter is between 1 and 30.

negative_promptstring

-> The negative_prompt parameter allows you to specify content that you want the image generation model to avoid or minimize in the output. This can be useful for excluding certain visual elements or styles that you do not want to be present in the generated image.

strengthnumber

-> The strength parameter specifies the degree of transformation applied to the reference image. -> A higher strength value (up to 1) results in the generated image closely following the reference image.

celerystring

-> The celery parameter is used for queuing tasks that require extended processing time. When you enqueue a task, you receive a unique task_id. This task_id allows you to check the task's status later using the task status API, which is useful for managing and tracking long-running tasks.

Default value

false

inference_typestring

-> The inference_type parameter allows you to specify the GPU to be used for the image generation task. The supported values are: a10g a100 h100 The different GPU options provide varying levels of performance and capabilities, allowing you to choose the most suitable GPU based on your requirements and the demand for the task.

Response

200

Object

Successful Response

Response Attributes

time_requiredstring

This parameter specifies both the container startup time and the duration needed to complete the assigned task.

Default value

[object Object]

errorstring

None

error_datastring

None

inputstring

Here, you'll find the user-provided input parameters – a glimpse into the data supplied by users.

Default value

[object Object]

outputstring

This parameter provides the outcome of task execution, offering the results achieved during the process.

Default value

[object Object]

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

Default value

[object Object]

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

422

Object

Validation Error

Response Attributes

detailarray

Show child attributes

500

Object

Response Attributes

time_requiredstring

None

errorstring

This parameter specifies the error type, giving valuable information about the issue encountered.

error_datastring

This parameter contains comprehensive information about the error, offering valuable insights that can aid in resolving similar issues in the future.

inputstring

None

outputstring

None

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

curl --location 'https://qolaba-server-b2b.up.railway.app/api/v1/studio/getImageToImage' \
--header 'Authorization: Bearer {token}' \
--data '{
  "app_id": "ap-SwsTOsD7STxJ0obCkskUHw",
  "image": "https://res.cloudinary.com/qolaba/image/upload/v1695690455/kxug1tmiolt1dtsvv5br.jpg",
  "prompt": "a beautiful girl pilot wearing aviator googles, unreal engine render, 8k",
  "batch": 1,
  "height": 768,
  "width": 768,
  "num_inference_steps": 30,
  "guidance_scale": 7.5,
  "negative_prompt": " ",
  "strength": 0.7,
  "celery": "false",
  "inference_type": "a10g"
}'

{
  "time_required": "",
  "error": "",
  "error_data": "",
  "input": "",
  "output": "",
  "app_id": "",
  "task_id": "",
  "status": ""
}

The concept of a "Face Avatar" involves the creation of images where the face maintains a consistent appearance across multiple generated Images. To achieve this, you start with an initial facial image and provide it as a reference. Using this reference, a sophisticated model goes to work, crafting new images while keeping the facial features in line with the original picture. In essence, the model uses your input to generate images where the face remains faithful to the structure and characteristics you've specified in your prompt. This way, you can effortlessly create a series of images with a consistent and recognizable face.

Working insights :

In this model, the default prompt settings includes a prompt, “black plain background, VECTOR CARTOON ILLUSTRATION, half-body shot portrait {gender_word}, 5 o clock shadow, 3d bitmoji avatar render, pixar, high def textures 8k, highly detailed, 3d render, award winning, no background elements”.

If you provide a custom prompt, it will override these default settings. To include a specific gender in your custom prompt, you must explicitly mention it in custom prompt. If you prefer to use the default settings without specifying any custom prompt, simply pass None in the prompt parameter. Subsequently, you can define the gender by using the gender parameter, which will apply the specified gender to the default image configuration.

Header Parameters

Authorizationstring

Body Parameters

app_idstring Required

-> Each model is uniquely characterized by its own app_id.

imagestring Required

-> The file_url parameter specifies the URL of an existing image that will be used as a reference for the generation process.

promptstring

-> The prompt parameter is the textual input that guides the image generation process. This prompt serves as an artistic compass, shaping the visual output.

batchnumber (int32)

-> The batch parameter allows you to specify the number of images to generate at once. -> The valid range for this parameter is between 1 and 8.

Exclusive minimum

True

Exclusive maximum

True

Multiple of

1

Default value

1

heightnumber (int32)

-> The height parameter represents the vertical dimension of an image. -> The valid range for the parameter is between 256 and 1536 pixels.

Exclusive minimum

True

Exclusive maximum

True

Default value

1024

widthnumber

-> The height parameter represents the vertical dimension of an image. -> The valid range for the parameter is between 256 and 1536 pixels.

celeryboolean

-> The celery parameter is used for queuing tasks that require extended processing time. When you enqueue a task, you receive a unique task_id. This task_id allows you to check the task's status later using the task status API, which is useful for managing and tracking long-running tasks.

num_inference_stepsnumber

-> The num_inference_steps parameter represents the number of denoising iterations to perform during the image generation process. Generally, more iterations can result in higher-quality images, but they also increase the time required for generation. -> The valid range for the num_inference_steps parameter is between 1 and 50.

guidance_scalenumber

-> The guidance_scale parameter determines how closely the generated image adheres to the provided prompt. Higher values result in the model following the prompt more closely, while lower values allow for more creative deviation. -> The valid range for the guidance_scale parameter is between 1 and 30.

negative_promptstring

-> The negative_prompt parameter allows you to specify content that you want the image generation model to avoid or minimize in the output. This can be useful for excluding certain visual elements or styles that you do not want to be present in the generated image.

genderstring Required

-> The gender parameter is used to guide the image generation model towards producing outputs with a specific gender representation. This can help avoid gender-related confusion or bias in the AI model's outputs.

remove_backgroundboolean Required

-> When the remove_background parameter is enabled, the background of the generated image will be removed and replaced with a transparent background.

bg_colorstring

-> The bg_color parameter allows you to set the background color of the generated image. The color value should be provided in hexadecimal format (e.g., #FFFFFF for white).

Response

200

Object

Response Attributes

time_requiredstring

errorstring

error_datastring

inputstring

outputstring

app_idstring

task_idstring

statusstring

500

Object

Response Attributes

time_requiredstring

errorstring

error_datastring

inputstring

outputstring

app_idstring

task_idstring

statusstring

Production:

https://qolaba-server-b2b.up.railway.app/api/v1/studio/

curl --location 'https://qolaba-server-b2b.up.railway.app/api/v1/studio/getImageToImage' \
--header 'Authorization: Bearer {token}' \
--data '{
  "app_id": "ap-jL9u1wFpY5sRv2XmN3aQ44",
  "image": "https://res.cloudinary.com/qolaba/image/upload/v1695690455/kxug1tmiolt1dtsvv5br.jpg",
  "prompt": "a beautiful girl pilot wearing aviator googles, unreal engine render, 8k",
  "batch": 1,
  "height": 1024,
  "width": 1024,
  "celery": true,
  "num_inference_steps": 30,
  "guidance_scale": 7.5,
  "negative_prompt": " ",
  "gender": "male",
  "remove_background": false,
  "bg_color": "#F1B8FF"
}'

{
  "time_required": "",
  "error": "",
  "error_data": "",
  "input": "",
  "output": "",
  "app_id": "",
  "task_id": "",
  "status": ""
}

This model based on IP-Adapter possesses the remarkable ability to create diverse visual image variation by drawing inspiration from an input image it receives.

Header Parameters

Authorizationstring

Body Parameters

app_idstring Required

-> Each model is uniquely characterized by its own app_id.

imagestring

-> The file_url parameter specifies the URL of an existing image that will be used as a reference for the generation process. -> If the original image dimensions exceed 1536x1536 pixels, the image will be adjusted to fit within this size while preserving the original aspect ratio.

promptstring

-> The prompt parameter is the textual input that guides the image generation process. This prompt serves as an artistic compass, shaping the visual output.

guidance_scalenumber

-> The guidance_scale parameter determines how closely the generated image adheres to the provided prompt. Higher values result in the model following the prompt more closely, while lower values allow for more creative deviation.

batchnumber

-> The batch parameter allows you to specify the number of images to generate at once. -> The valid range for this parameter is between 1 and 8.

Minimum

1

Maximum

4

Default value

1

strengthnumber

-> The strength parameter specifies the degree of transformation applied to the reference image. -> A higher strength value (up to 1) results in the generated image closely following the initial reference image.

negative_promptstring

-> The negative_prompt parameter allows you to specify content that you want the image generation model to avoid or minimize in the output. This can be useful for excluding certain visual elements or styles that you do not want to be present in the generated image.

num_inference_stepsnumber

-> The num_inference_steps parameter represents the number of denoising iterations to perform during the image generation process. Generally, more iterations can result in higher-quality images, but they also increase the time required for generation.

celeryboolean

-> The celery parameter is used for queuing tasks that require extended processing time. When you enqueue a task, you receive a unique task_id. This task_id allows you to check the task's status later using the task status API, which is useful for managing and tracking long-running tasks.

Default value

false

inference_typestring

-> The inference_type parameter allows you to specify the GPU to be used for the image generation task. The supported values are: a10g a100 h100 The different GPU options provide varying levels of performance and capabilities, allowing you to choose the most suitable GPU based on your requirements and the demand for the task.

Response

200

Object

Successful Response

Response Attributes

time_requiredstring

This parameter specifies both the container startup time and the duration needed to complete the assigned task.

Default value

[object Object]

errorstring

None

error_datastring

None

inputstring

Here, you'll find the user-provided input parameters – a glimpse into the data supplied by users.

Default value

[object Object]

outputstring

This parameter provides the outcome of task execution, offering the results achieved during the process.

Default value

[object Object]

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

Default value

[object Object]

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

422

Object

Validation Error

Response Attributes

detailarray

Show child attributes

500

Object

Response Attributes

time_requiredstring

None

errorstring

This parameter specifies the error type, giving valuable information about the issue encountered.

error_datastring

This parameter contains comprehensive information about the error, offering valuable insights that can aid in resolving similar issues in the future.

inputstring

None

outputstring

None

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

curl --location 'https://qolaba-server-b2b.up.railway.app/api/v1/studio/getImageToImage' \
--header 'Authorization: Bearer {token}' \
--data '{
  "app_id": "ap-kNvCpegQY2HiDHmk5X7X6F",
  "image": "https://res.cloudinary.com/qolaba/image/upload/v1695690455/kxug1tmiolt1dtsvv5br.jpg",
  "prompt": "a beautiful girl pilot wearing aviator googles, unreal engine render, 8k",
  "guidance_scale": 7.5,
  "batch": 1,
  "strength": 0.7,
  "negative_prompt": " ",
  "num_inference_steps": 30,
  "celery": false,
  "inference_type": "a10g"
}'

{
  "time_required": "",
  "error": "",
  "error_data": "",
  "input": "",
  "output": "",
  "app_id": "",
  "task_id": "",
  "status": ""
}

Header Parameters

Authorizationstring

Body Parameters

app_idstring Required

-> Each model is uniquely characterized by its own app_id.

imagestring

-> The file_url parameter specifies the URL of an existing image that will be used as a reference for the generation process. -> If the original image dimensions exceed 1536x1536 pixels, the image will be adjusted to fit within this size while preserving the original aspect ratio.

promptstring

-> The prompt parameter is the textual input that guides the image generation process. This prompt serves as an artistic compass, shaping the visual output.

guidance_scalenumber

-> The guidance_scale parameter determines how closely the generated image adheres to the provided prompt. Higher values result in the model following the prompt more closely, while lower values allow for more creative deviation.

Minimum

2

Maximum

25

batchnumber

-> The batch parameter allows you to specify the number of images to generate at once. -> The valid range for this parameter is between 1 and 8.

Minimum

1

Maximum

4

strengthnumber

-> The strength parameter specifies the degree of transformation applied to the reference image.

Maximum

1

negative_promptstring

-> The negative_prompt parameter allows you to specify content that you want the image generation model to avoid or minimize in the output. This can be useful for excluding certain visual elements or styles that you do not want to be present in the generated image.

num_inference_stepsnumber

-> The num_inference_steps parameter represents the number of denoising iterations to perform during the image generation process. Generally, more iterations can result in higher-quality images, but they also increase the time required for generation. -> The valid range for the num_inference_steps parameter is between 1 and 50.

celeryboolean

-> The celery parameter is used for queuing tasks that require extended processing time. When you enqueue a task, you receive a unique task_id. This task_id allows you to check the task's status later using the task status API, which is useful for managing and tracking long-running tasks.

Default value

false

inference_typestring

-> The inference_type parameter allows you to specify the GPU to be used for the image generation task. The supported values are: a10g a100 h100 The different GPU options provide varying levels of performance and capabilities, allowing you to choose the most suitable GPU based on your requirements and the demand for the task.

Response

200

Object

Successful Response

Response Attributes

time_requiredstring

This parameter specifies both the container startup time and the duration needed to complete the assigned task.

Default value

[object Object]

errorstring

None

error_datastring

None

inputstring

Here, you'll find the user-provided input parameters – a glimpse into the data supplied by users.

Default value

[object Object]

outputstring

This parameter provides the outcome of task execution, offering the results achieved during the process.

Default value

[object Object]

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

Default value

[object Object]

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

422

Object

Validation Error

Response Attributes

detailarray

Show child attributes

500

Object

Response Attributes

time_requiredstring

None

errorstring

This parameter specifies the error type, giving valuable information about the issue encountered.

error_datastring

This parameter contains comprehensive information about the error, offering valuable insights that can aid in resolving similar issues in the future.

inputstring

None

outputstring

None

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

curl --location 'https://qolaba-server-b2b.up.railway.app/api/v1/studio/getImageToImage' \
--header 'Authorization: Bearer {token}' \
--data '{
  "app_id": "ap-lpocU0cB9szyuvta9lZ83B",
  "image": "https://res.cloudinary.com/qolaba/image/upload/v1695690455/kxug1tmiolt1dtsvv5br.jpg",
  "prompt": "a beautiful girl pilot wearing aviator googles, unreal engine render, 8k",
  "guidance_scale": 7.5,
  "batch": 1,
  "strength": 0.7,
  "negative_prompt": " ",
  "num_inference_steps": 30,
  "celery": false,
  "inference_type": "a10g"
}'

{
  "time_required": "",
  "error": "",
  "error_data": "",
  "input": "",
  "output": "",
  "app_id": "",
  "task_id": "",
  "status": ""
}

Header Parameters

Authorizationstring

Body Parameters

app_idstring Required

-> Each model is uniquely characterized by its own app_id.

imagestring Required

-> The file_url parameter specifies the URL of an existing image that will be used as a reference for the generation process. -> If the original image dimensions exceed 1536x1536 pixels, the image will be adjusted to fit within this size while preserving the original aspect ratio.

scalenumber

celeryboolean

-> The celery parameter is used for queuing tasks that require extended processing time. When you enqueue a task, you receive a unique task_id. This task_id allows you to check the task's status later using the task status API, which is useful for managing and tracking long-running tasks.

Default value

false

Response

200

Object

Successful Response

Response Attributes

time_requiredstring

This parameter specifies both the container startup time and the duration needed to complete the assigned task.

Default value

[object Object]

errorstring

None

error_datastring

None

inputstring

Here, you'll find the user-provided input parameters – a glimpse into the data supplied by users.

Default value

[object Object]

outputstring

This parameter provides the outcome of task execution, offering the results achieved during the process.

Default value

[object Object]

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

Default value

[object Object]

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

422

Object

Validation Error

Response Attributes

detailarray

Show child attributes

500

Object

Response Attributes

time_requiredstring

None

errorstring

This parameter specifies the error type, giving valuable information about the issue encountered.

error_datastring

This parameter contains comprehensive information about the error, offering valuable insights that can aid in resolving similar issues in the future.

inputstring

None

outputstring

None

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

curl --location 'https://qolaba-server-b2b.up.railway.app/api/v1/studio/getImageToImage' \
--header 'Authorization: Bearer {token}' \
--data '{
  "app_id": "ap-NFDMz1Rn9UlpS6zMl2FNpm",
  "image": "https://res.cloudinary.com/qolaba/image/upload/v1695690455/kxug1tmiolt1dtsvv5br.jpg",
  "scale": 2,
  "celery": false
}'

{
  "time_required": "",
  "error": "",
  "error_data": "",
  "input": "",
  "output": "",
  "app_id": "",
  "task_id": "",
  "status": ""
}

Header Parameters

Authorizationstring

Body Parameters

app_idstring Required

-> Each model is uniquely characterized by its own app_id.

imagestring Required

-> The file_url parameter specifies the URL of an existing image that will be used as a reference for the generation process. -> If the original image dimensions exceed 1536x1536 pixels, the image will be adjusted to fit within this size while preserving the original aspect ratio.

bg_imgstring

-> The bg_image parameter allows you to specify a URL for an image that will be used as the background for the generated image.

bg_colorstring

-> To use a custom background color, set the bg_color parameter to true. This will allow you to specify the desired RGB color values for the background.

Default value

false

r_colornumber

-> The r_color parameter controls the strength of the red hue in the background color, with a range from 0 to 255. Higher values result in a more vibrant red, while lower values make the red more subdued.

Maximum

255

Default value

255

g_colorinteger

-> The g_color parameter controls the strength of the green hue in the background color, with a range from 0 to 255. Higher values result in a more vibrant green, while lower values make the green more subdued.

Maximum

255

Default value

0

b_colorinteger

-> The b_color parameter controls the strength of the blue hue in the background color, with a range from 0 to 255. Higher values result in a more vibrant blue, while lower values make the blue more subdued.

Maximum

255

Default value

0

blurstring

-> Enable the blur parameter to apply a blurring effect to the background of the generated image, creating a captivating and enchanting visual effect.

Default value

false

celerystring

-> The celery parameter is used for queuing tasks that require extended processing time. When you enqueue a task, you receive a unique task_id. This task_id allows you to check the task's status later using the task status API, which is useful for managing and tracking long-running tasks.

Default value

false

Response

200

Object

Successful Response

Response Attributes

time_requiredstring

This parameter specifies both the container startup time and the duration needed to complete the assigned task.

Default value

[object Object]

errorstring

None

error_datastring

None

inputstring

Here, you'll find the user-provided input parameters – a glimpse into the data supplied by users.

Default value

[object Object]

outputstring

This parameter provides the outcome of task execution, offering the results achieved during the process.

Default value

[object Object]

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

Default value

[object Object]

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

422

Object

Validation Error

Response Attributes

detailarray

Show child attributes

500

Object

Response Attributes

time_requiredstring

None

errorstring

This parameter specifies the error type, giving valuable information about the issue encountered.

error_datastring

This parameter contains comprehensive information about the error, offering valuable insights that can aid in resolving similar issues in the future.

inputstring

None

outputstring

None

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

curl --location 'https://qolaba-server-b2b.up.railway.app/api/v1/studio/getImageToImage' \
--header 'Authorization: Bearer {token}' \
--data '{
  "app_id": "ap-kV3kwXL9QXJxYS6jV1VtkT",
  "image": "https://res.cloudinary.com/qolaba/image/upload/v1695690455/kxug1tmiolt1dtsvv5br.jpg",
  "bg_img": "",
  "bg_color": "false",
  "r_color": 255,
  "g_color": null,
  "b_color": null,
  "blur": "false",
  "celery": "false"
}'

{
  "time_required": "",
  "error": "",
  "error_data": "",
  "input": "",
  "output": "",
  "app_id": "",
  "task_id": "",
  "status": ""
}

Header Parameters

Authorizationstring

Body Parameters

app_idstring Required

-> Each model is uniquely characterized by its own app_id.

promptstring

-> The prompt parameter is the textual input that guides the audio generation process. This prompt serves as an artistic compass, shaping the audio output. -> The minimum length of the prompt is 10 characters, and the maximum length is 2500 characters.

Min length

10

Max length

2500

Default value

Hi, we are in Qolaba

generate_audioboolean

-> Enable the generate_audio parameter to generate audio output in the form of speech.

audio_parametersobject

-> The audio_parameters parameter is a dictionary that allows you to specify various audio-related settings. Here's an example of the structure: "audio_parameters": { "voice_id": "21m00Tcm4TlvDq8ikWAM", "stability": 0.5, "similarity_boost": 0.75, "style": null, "use_speaker_boost": true } You can customize the values within this dictionary to adjust the audio generation according to your preferences.

Show child attributes

celeryboolean

-> The celery parameter is used for queuing tasks that require extended processing time. When you enqueue a task, you receive a unique task_id. This task_id allows you to check the task's status later using the task status API, which is useful for managing and tracking long-running tasks.

Default value

false

Response

200

Object

Successful Response

Response Attributes

time_requiredstring

This parameter specifies both the container startup time and the duration needed to complete the assigned task.

errorstring

None

error_datastring

None

inputstring

Here, you'll find the user-provided input parameters – a glimpse into the data supplied by users.

outputstring

This parameter provides the outcome of task execution, offering the results achieved during the process.

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

422

Object

Validation Error

Response Attributes

detailarray

Show child attributes

500

Object

Response Attributes

time_requiredstring

None

errorstring

This parameter specifies the error type, giving valuable information about the issue encountered.

error_datastring

This parameter contains comprehensive information about the error, offering valuable insights that can aid in resolving similar issues in the future.

inputstring

None

outputstring

None

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

Production:

https://qolaba-server-b2b.up.railway.app/api/v1/studio/

curl --location 'https://qolaba-server-b2b.up.railway.app/api/v1/studio/get_audio' \
--header 'Authorization: Bearer {token}' \
--data '{
  "app_id": "ap-a1Syd0inzrUrbvgdAbcser",
  "prompt": "Hey, this is an amazing day",
  "generate_audio": true,
  "audio_parameters": {
    "voice_id": "21m00Tcm4TlvDq8ikWAM",
    "stability": 0.5,
    "similarity_boost": 0.75,
    "style": 1,
    "use_speaker_boost": true
  },
  "celery": false
}'

{
  "time_required": "",
  "error": "",
  "error_data": "",
  "input": "",
  "output": "",
  "app_id": "",
  "task_id": "",
  "status": ""
}

Header Parameters

Authorizationstring

Body Parameters

idstring

-> The id parameter is used to provide the unique identifier of the scheduled task you want to check the status for.

refIDstring

-> The reference_id parameter is an optional field that allows you to provide a reference ID to identify the request, if required. If you did not specify a reference_id when passing the input parameters, there is no need to provide this parameter.

Response

200

Object

Production:

https://qolaba-server-b2b.up.railway.app/api/v1/studio/

curl --location 'https://qolaba-server-b2b.up.railway.app/api/v1/studio/getImage' \
--header 'Authorization: Bearer {token}' \
--data '{
  "id": "",
  "refID": ""
}'

Header Parameters

Authorizationstring

Body Parameters

llm_modelstring

-> The llm_model parameter specifies the name of the Large Language Model (LLM) to be used. The supported values for this parameter depend on the llm you have selected. For example, if the llm is OpenAI, the supported llm_model values include: "gpt-4-turbo-2024-04-09" "gpt-3.5-turbo-0125" Similarly, if the llm is MistralAI, the supported llm_model values include: "mistral-large-latest" "open-mistral-7b" Ensure that the llm_model value you p...

temperaturenumber (float)

-> The temperature parameter accepts a float value between 0 and 1. This parameter helps control the level of determinism in the output from the Large Language Model (LLM).

Exclusive minimum

True

system_msgstring

-> The system_msg parameter allows you to set a system message for the Large Language Model (LLM). This message can be used to provide context or instructions to the model, which can influence the tone and behavior of the generated responses.

llmstring

-> The llm parameter specifies the type of Large Language Model (LLM) to be used. The supported values are: ClaudeAI MistralAI OpenAI GeminiAI.

image_analyzeboolean

-> If you are passing image URLs and want the model to analyze the images, set the image_analyze parameter to true.

enable_toolboolean

-> To use the tools supported by the Chat API, enable the enable_tool parameter. The Chat API currently supports two tools: Vector Search Internet Search -> After enabling the enable_tool parameter, you can provide the details of the tool you want to use in the tools parameter.

historyarray

-> The history parameter allows you to provide the previous chat history and the last user message. The history should follow a specific pattern: The history should start with a user message. After each user message, there should be a response from the assistant. The last message in the history should be a user message or query. -> The history should be provided as a list of dictionaries, where each dictionary represents a message. The dictionary should have the following stru...

Show child attributes

toolsobject

-> The tools parameter allows you to specify the tool you want to use with the Chat API. The supported tools and their configurations are as follows: Internet Search Tool: tool_name: "Tavily" tool_type: "InternetSearch" PDF Search Tool: tool_name: "QdrantDB" tool_type: "DBSearch" pdf_references: A list of PDF IDs from which you want to retrieve details. These PDF IDs can be obtained by using the pdfVectorStore endpoint to index the PDFs. -&...

Show child attributes

take_routeboolean

routerobject

Show child attributes

Response

200

Object

Successful Response

Response Attributes

time_requiredstring

This parameter specifies both the container startup time and the duration needed to complete the assigned task.

Default value

[object Object]

errorstring

None

error_datastring

None

inputstring

Here, you'll find the user-provided input parameters – a glimpse into the data supplied by users.

Default value

[object Object]

outputstring

This parameter provides the outcome of task execution, offering the results achieved during the process.

Default value

[object Object]

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

Default value

[object Object]

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

422

Object

Validation Error

Response Attributes

detailarray

Show child attributes

500

Object

Response Attributes

time_requiredstring

None

errorstring

This parameter specifies the error type, giving valuable information about the issue encountered.

error_datastring

None

inputstring

None

outputstring

None

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

Production:

https://qolaba-server-b2b.up.railway.app/api/v1/studio/

curl --location 'https://qolaba-server-b2b.up.railway.app/api/v1/studio/streamChat' \
--header 'Authorization: Bearer {token}' \
--data '{
  "llm_model": "gpt-3.5-turbo-0125",
  "temperature": 0.5,
  "system_msg": "You are helpful assistant. ",
  "llm": "OpenAI",
  "image_analyze": false,
  "enable_tool": false,
  "history": [
    {
      "content": {
        "text": "hello",
        "image_data": [
          {
            "url": "https://res.cloudinary.com/qolaba/image/upload/v1706978255/quciudywmzscy8h4znwa.png",
            "details": "low"
          }
        ]
      },
      "role": "user"
    }
  ],
  "tools": {
    "tool_name": "QdrantDB",
    "tool_type": "DBSearch",
    "pdf_references": [
      "123"
    ]
  },
  "take_route": false,
  "router": {
    "strong_llm": "OpenAI",
    "strong_llm_model": "gpt-4o-2024-05-13",
    "weak_llm": "OpenAI",
    "weak_llm_model": "gpt-4o-mini"
  }
}'

{
  "time_required": "",
  "error": "",
  "error_data": "",
  "input": "",
  "output": "",
  "app_id": "",
  "task_id": "",
  "status": ""
}

Header Parameters

Authorizationstring

Body Parameters

Urlstring

The url parameter specifies the URL of the document to be indexed.

Response

200

Object

Successful Response

Response Attributes

outputstring

This parameter provides the outcome of task execution, offering the results achieved during the process.

Default value

[object Object]

errorstring

Error type

error_datastring

Detailed error message

422

Object

Validation Error

Response Attributes

detailarray

Show child attributes

500

Object

Response Attributes

time_requiredstring

None

errorstring

This parameter specifies the error type, giving valuable information about the issue encountered.

error_datastring

None

inputstring

None

outputstring

None

app_idstring

This parameter provides the user-selected model's app_id, allowing users to identify the chosen model.

task_idstring

This parameter relates to task_id, which is acquired when scheduling lengthy tasks with Celery, a powerful task queue system for background processing in Python.

statusstring

This parameter offers an up-to-the-minute snapshot of the task's current progress and status.

Production:

https://qolaba-server-b2b.up.railway.app/api/v1/studio/

curl --location 'https://qolaba-server-b2b.up.railway.app/api/v1/studio/pdfVectorStore' \
--header 'Authorization: Bearer {token}' \
--data '{
  "Url": "https://res.cloudinary.com/qolaba/image/upload/v1711394908/7aa8ffefd791280bb2e40151e8a81e82_ekoq8v.pdf"
}'

{
  "output": null,
  "error": null,
  "error_data": null
}

Sections

GETTING STARTED

API REFERENCE

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