Inference

model_id: String, required, https://sinkin.notion.site/SinkIn-API-7fa0dc746d624629bb3c680d913cbbf4

prompt: String, required

lcm: String, optional use lcm or not (half the cost with some tradeoff on quality) pass in “true” or “false”, default = “false”

version: String, optional Model version, default to the latest version

width: Int, optional default = 512, must be increment of 8 valid range is 128 to 896 commonly used values: 512, 640, 768

height: Int, optional default = 768, must be increment of 8 valid range is 128 to 896 commonly used values: 512, 640, 768

negative_prompt: String, optional use_default_neg: String, optional Append the default negative prompt or not pass in “true” or “false”, default = “true”

steps: Int, optional Number of inference steps default = 30 valid range is 1 to 50

scale: Float, optional Guidance scale default = 7.5 or model's default scale if one is set valid range is 1 to 20

num_images: Int, optional, default = 4 seed: Int, optional, default = -1 scheduler: String, optional, default = ”DPMSolverMultistep” or model’s default scheduler if one is set, https://sinkin.notion.site/SinkIn-API-7fa0dc746d624629bb3c680d913cbbf4

lora: String, optional id of the LoRA model. You can query https://sinkin.notion.site/SinkIn-API-7fa0dc746d624629bb3c680d913cbbf4 to get the full list of LoRA lora_scale: Float, optional, default = 0.75 | | Extra input for img2img | init_image_file: a file object, the base image, required for img2img

image_strength: Float, optional How much to transform the base image, default = 0.75

controlnet: String, optional ControlNet to use, legit values are canny, depth and openpose Note when controlnet is set, image_strength will have no effect

see https://sinkin.notion.site/SinkIn-API-7fa0dc746d624629bb3c680d913cbbf4 | | Output | Success: { error_code: 0, images=[ ‘image url’, ‘image url’, …] , credit_cost: 2.2, inf_id: 'xxxxxxxxxxxxxx' }

Failure: { error_code: 1, message: “This is an error message” } |

Model ID

You can call /models to get the complete model list, including LoRAs. The id of each model can be found in the returned json.

You can also go to sinkin.ai, enter a model page and the last part of the url is the model id. E.g. for the model at https://sinkin.ai/m/vlDnKP6, the model id is vlDnKP6.

The ids of some commonly used models:

Scheduler Options

An example of how to make an img2img request in python

    params = {
        'access_token': 'xxxxxxxxxxxxxxxxxxxxxxxxxx',
        'model_id': 'xxxxx',
        'prompt': 'an angry orc looking at camera smiling',
        'num_images': 1,
        'scale': 7,
        'steps': 30,
        'width': 512,
        'height': 768,
        # 'image_strength': 0.75,
        # 'controlnet': 'openpose'
    }

    files = {'init_image_file': open('path-to-image-file', 'rb')}
    
    r = requests.post('<https://sinkin.ai/api/inference>', files=files, data=params)

    print(r.text)

Models

Get all available models and LoRAs

error_code: 0, 
models: [ {'id': 'XXXX', 'title': 'XXXX', 'cover_img': 'xxxxxxxx', 'link': 'xxxxxxx'}, ... ] ,
loras: [ {'id': 'XXXX', 'title': 'XXXX', 'cover_img': 'xxxxxxxx', 'link': 'xxxxxxx'}, ... ] 

}

Failure: { error_code: 1, message: “This is an error message” } |

Upscale