Qolaba

GETTING STARTED

Introduction

Authentication

Pricing

Errors

API REFERENCE

Text To Image

Image To Image

Inpainting

Replace Background

Text To Speech

Get Status

Chat Completions

File Upload

Stream-Chat

Store File in Vector Database

Chat

FastAPI

ML APIs

Gen AI API's

Production

Production v1

Sandbox

<p class="slate-p " >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.</p><p class="slate-p " ></p><p class="slate-p " ></p>

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.

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

app_id

-> The height parameter represents the vertical dimension of an image.  -> The valid range for the parameter is between 256 and 1600 pixels. 

height

-> The width parameter represents the horizontal dimension of an image.  -> The valid range for the parameter is between 256 and 1600 pixels. 

width

-> 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.

num_inference_steps

-> 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.

guidance_scale

-> 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.

batch

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

prompt

-> 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.

negative_prompt

-> 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.

celery

-> The inference_type parameter allows you to specify the GPU to be used for the image generation task. The supported value is: a10g. This parameter is only applicable for Qolaba-deployed models, including Image Gen 4, SD 3.5 medium, SD 3.5, SD 3.5 Turbo, Recraft V3, Flux Dev, Flux Pro, Dalle 3, Leonardo, Ideogram, and GPT Image.
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.

inference_type

Authorization

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

time_required

error

error_data

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

input

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

output

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

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.

task_id

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

status

detail

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

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

image

-> 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.

strength

-> The height parameter represents the vertical dimension of an image.  -> The valid range for the parameter is between 256 and 1600 pixels.  -> This parameter is only applicable for the SDXL API, as it requires specific height and width values.

-> The width parameter represents the horizontal dimension of an image.  -> The valid range for the parameter is between 256 and 1600 pixels.  

-> The inference_type parameter allows you to specify the GPU to be used for the image generation task. The supported value is: a10g. This parameter is only applicable for Qolaba-deployed models, including Flux Dev, Ideogram Remix, Flux Redux, Flux Canny, Flux Depth, Flux PulID, GPT Image, Flux Kontext Max. 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.

-> 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.

-> 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.

mask_url

The name of the voice to use for speech synthesis. Must be one of the supported voices (e.g., Zephyr, Puck, Charon, Kore, Fenrir, Aoede, etc.). Use GET /api/v1/studio/speech/voices to retrieve the full list of available voices.

voice

The input text to be converted into speech. Must be a non-empty string. This is the content that will be spoken in the generated audio output.

text

BCP-47 language code that hints the language and locale of the spoken output (e.g., en-US, fr-FR, es-ES). Use GET /api/v1/studio/speech/languages to retrieve the full list of supported language codes. If omitted, the language is inferred from the text.

language_code

A natural language instruction that controls the speaking style, tone, or emotion of the generated voice (e.g., "Speak warmly", "Read slowly and clearly", "Sound excited"). If omitted, the voice uses its default neutral style.

style_prompt

MIME type of the audio file (e.g., audio/wav)

mime_type

Unique reference ID for this generation request

referenceID

Triggered when the organization has no available credits remaining.

message

Triggered by unexpected failures in the service or middleware.

Triggered when required fields are missing or invalid.

Header required: Authorization: Bearer <your_api_key>

Triggered when the Authorization header is missing or the API key is invalid.

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

-> 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.

refID

Model ID (e.g. openai/gpt-4o-mini, google/gemini-2.5-flash)

model

messages

stream

The Authorization header parameter contains the authentication credentials required for accessing the ChatBot API.

object

created

choices

usage

Chat API

store_name

success

file_name

token_count

estimated_cost_usd

creditUtilisation

The llm parameter specifies the type of Large Language Model (LLM) to be used for processing text data.

The llm_model parameter specifies the name of the Large Language Model (LLM) to be used for processing text data.

llm_model

The history parameter contains the historical data or records to be processed by the API.

history

The temperature parameter controls the randomness and creativity of the text generation process.

temperature

The image_analyze parameter is used to provide an image for analysis by the API.

image_analyze

No description provided for this parameter.

enable_tool

The system_msg parameter contains the system message or notification to be processed by the API.

system_msg

The tools parameter specifies the tools or functionalities to be used by the API.

tools

Authentication token needed for the request.

token

Identifies the organization associated with the request.

orgID

Lists the functions called during the process.

function_call_list

Specifies the system identifier linked to the request.

systemId

Provides the last user query made in the chat.

last_user_query

Offers additional detailed information regarding the response.

Stream chat API

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

This parameter refers to the number of tokens used in the prompt sent to the AI model. 

promptTokens

This parameter represent the number of tokens generated by the AI model in response to a given prompt.

Sections