stable-diffusion-aws-extension/docs/zh/developer-guide/api.md

title	language_tabs	language_clients	toc_footers	includes	headingLevel
Stable Diffusion AWS extension API v2023-07-05	python Python javascript Javascript	python javascript			2

Stable Diffusion AWS extension API

Overview

This document describe all the api for Stable Diffusion AWS extension solution. This Solution contains two parts, one part is stable diffusion WebUI extension which is gradio based client to provide a user-friendly interface, another part is called middle-ware which is resources deploy on AWS cloud, the middleware provide several API interfaces to let stable diffusion aws extension client to interact services on AWS cloud like Sagemaker and S3 to do the model update/training and inference operations.

In order to support users who do not use stable diffusion aws extension. We provide this document to list all the API interfaces to help user understand how to call API methods to do the training or inference.

After user deployed solution middleware cloudformation, user can get the API URL and Token in the output part of the main stack. Please refer to this document

Base URLs:

• https://API_Gateway_ID.execute-api.AWS_Account_Region.amazonaws.com/prod

Authentication

• API Key (api_key)
  • Parameter Name: x-api-key, in: header.

User Scenarios

1. Deploy a new Endpoint

Call /inference/deploy-sagemaker-endpoint to create a new sagemaker endpoint, you need to specify two parameters for creating, one is instance_type, candidate values are "ml.g4dn.2xlarge","ml.g4dn.4xlarge","ml.g4dn.8xlarge","ml.g4dn.12xlarge", another is initial_instance_count, candidate values are 1|2|3|4.

After calling /inference/deploy-sagemaker-endpoint, you need to call /inference/list-endpoint-deployment-jobs to list all the endpoint status. Normally it took about more than 10 minutes to make a new Sagemaker endpoint change to inService status. The Sagemaker endpoint can only be used for inference when it is inService status.

If the endpoint is in failed status, you can call /inference/get-endpoint-deployment-job with parameter jobID, the response will show the reason why endpoint deployment is failed, normally it is caused by AWS account quota limitation.

sequence digram raw

title Create a Sagemaker Endpoint

Client->Middleware:Call /inference/deploy-sagemaker-endpoint Middleware->Middleware: Start a workflow to configure sagemaker endpoint \n based on uer request configuration Client->Middleware:Call /inference/list-endpoint-deployment-jobs \n to list all the endpoint creation job list Client->Middleware:Call /inference/get-endpoint-deployment-job \n to check whether Sagemaker endpoint is in \n 'inService' state.

2. Upload a model

3. Train a model

4. Do Inference

After Sagemaker endpoint is in inService status, you can call /inference-api/inference to do the txt2image or image2image inference. You specify the endpoint name in "sagemaker_endpoint" parameter in the post body of the request. Other required parameters are located in /inference-api/inference.

/inference-api/inference will return following json structure to client:

{
  "inference_id": "XXXXXXX",
  "status": "inprogress | failed",
  "endpoint_name": "NAME_OF_ENDPOINT",
  "output_path": "path_of_prediction_output"
}

Client then can call /inference/get-inference-job using the inference_id as parameter to query the inference job status. If the inference job has finished successfully(status is "succeed"), Client can use /inference/get-inference-job-image-output to get all inference result images, the images will be returned as S3 presigned url list so client can download. following is am example of get-inference-job-image-output result:

[
  "https://stable-diffusion-aws-extension-aigcbucketa457cb49-1tlr2pqwkosg3.s3.amazonaws.com/out/1f9679f3-25b8-4c44-8345-0a845da30094/result/image_0.jpg"
]

Also Client can call /inference/get-inference-job-param-output to get all the inference parameters, the response of /inference/get-inference-job-param-output is an S3 presigned url contains the json format of the parameters, following is an response example:

[
  "https://stable-diffusion-aws-extension-aigcbucketa457cb49-1tlr2pqwkosg3.s3.amazonaws.com/out/1f9679f3-25b8-4c44-8345-0a845da30094/result/1f9679f3-25b8-4c44-8345-0a845da30094_param.json"
]

sequence digram raw

title Do Inference

Client->Middleware:Call /inference-api/inference Middleware->Middleware: Start a async inference job \n on configure sagemaker endpoint \n based on uer request configuration Middleware->Client: return inference_id Client->Middleware:Call /inference/get-inference-job \n to query the inference job status Middleware->Client: return inference_id and the job status(inprocess | succeed | failure)

abox over Client: If the inference job is succeed, \n call /inference/get-inference-job-image-output and \n /inference/get-inference-job-param-output to get the \n inference result Client->Middleware:Call /inference/get-inference-job-image-output \n to get all inference result images.

Middleware->Client: return the inference result images in presigned url format

Client->Middleware:Call /inference/get-inference-job-param-output \n to get inference parameters.

Middleware->Client: return the inference parameter in presigned url format

# API List

Index	Http Method	API Name	Description
1	GET	/inference/test-connection	Test whether client can connect to api and check the API_TOKEN is correct
3	GET	/inference/get-inference-job	Retrieves details of a specific inference job.
4	GET	/inference/get-inference-job-image-output	Gets image output of a specific inference job.
5	GET	/inference/get-inference-job-param-output	Gets parameter output of a specific inference job.
6	POST	/inference-api/inference	Run sagemaker inference using default parameters
7	POST	/inference/deploy-sagemaker-endpoint	Deploys a SageMaker endpoint.
8	POST	/inference/delete-sagemaker-endpoint	Deletes a SageMaker endpoint.
9	GET	/inference/list-endpoint-deployment-jobs	Lists all endpoint deployment jobs.
10	GET	/inference/get-endpoint-deployment-job	Gets a specific endpoint deployment job.
11	GET	/inference/generate-s3-presigned-url-for-uploading	Generates an S3 presigned URL for uploading.
12	GET	/inference/get-texual-inversion-list	Gets the list of textual inversions.
13	GET	/inference/get-lora-list	Gets the list of LoRa.
14	GET	/inference/get-hypernetwork-list	Gets the list of hypernetworks.
15	GET	/inference/get-controlnet-model-list	Gets the list of ControlNet models.
16	POST	/inference/run-model-merge	Runs a model merge.
17	POST	/model	Creates a new model.
18	PUT	/model	Upload the model file
19	GET	/models	Lists all models.
20	GET	/checkpoint	Gets a checkpoint.
21	PUT	/checkpoint	Updates a checkpoint.
22	GET	/checkpoints	Lists all checkpoints.
23	POST	/train	Starts a training job.
24	PUT	/train	Updates a training job.
25	GET	/trains	Lists all training jobs.
26	POST	/dataset	Creates a new dataset.
27	PUT	/dataset	Updates a dataset.
28	GET	/datasets	Lists all datasets.
29	GET	/{dataset_name}/data	Gets data of a specific dataset.

/inference/test-connection

test middleware connection

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/test-connection', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/test-connection',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /inference/test-connection

Example responses

200 Response

null

Responses

Status	Meaning	Description	Schema
200	OK	Successful Response	Inline

Response Schema

This operation does not require authentication

/inference-api/inference

Generate a new image from a text prompt.

Code samples :

Python example code:

import requests
headers = {
  "Content-Type": "application/json",
  "Accept": "application/json",
  'x-api-key': 'API_TOKEN_VALUE'
}
body = {
  "task_type": "txt2img",
  "models": {
    "Stable-diffusion": [
      "v1-5-pruned-emaonly.safetensors"
    ]
  },
  "sagemaker_endpoint_name": "infer-endpoint-cb821ea",
  "prompt": "a cute panda",
  "denoising_strength": 0.75
}

r = requests.post("https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference-api/inference", headers = headers, json = body)

print(r.json())

Javascript example code:

const inputBody = '{
  "task_type": "txt2img",
  "models": {
    "Stable-diffusion": [
      "v1-5-pruned-emaonly.safetensors"
    ]
  },
  "sagemaker_endpoint_name": "infer-endpoint-cb821ea",
  "prompt": "a cute panda",
  "denoising_strength": 0.75
}';
const headers = {
  "Content-Type":"application/json",
  "Accept":"application/json",
  'x-api-key': 'API_TOKEN_VALUE'
};

fetch("https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference-api/inference",
{
  method: "POST",
  body: inputBody,
  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

POST /inference-api/inference

Body parameter

{
  "task_type": "txt2img",
  "models": {
    "Stable-diffusion": [
      "v1-5-pruned-emaonly.safetensors"
    ]
  },
  "sagemaker_endpoint_name": "infer-endpoint-cb821ea",
  "prompt": "a cute panda",
  "denoising_strength": 0.75
}

Parameters

Parameter example

Below JSON shows the parameters with default value. sagemaker_endpoint_name, task_type, prompt and Stable-diffusion are mandatory, other parameters are optional.

{
  "sagemaker_endpoint_name": "infer-endpoint-ef3abcd", 
  "task_type": "txt2img",
  "prompt": "",
  "models": {
    "Stable-diffusion": [
      "v1-5-pruned-emaonly.safetensors"
    ],
    "Lora": [
      "raidenshogun1-000009.safetensors"
    ]
  },
  "enable_hr": false,
  "denoising_strength": null,
  "firstphase_width": 0,
  "firstphase_height": 0,
  "hr_scale": 2.0,
  "hr_upscaler": "Latent",
  "hr_second_pass_steps": 0,
  "hr_resize_x": 0,
  "hr_resize_y": 0,
  "hr_sampler_name": null,
  "hr_prompt": "",
  "hr_negative_prompt": "",
  "prompt": "",
  "styles": [],
  "seed": -1,
  "subseed": -1,
  "subseed_strength": 0.0,
  "seed_resize_from_h": 0,
  "seed_resize_from_w": 0,
  "sampler_name": "Euler a",
  "batch_size": 1,
  "n_iter": 1,
  "steps": 28,
  "cfg_scale": 7.0,
  "width": 512,
  "height": 512,
  "restore_faces": false,
  "tiling": false,
  "do_not_save_samples": false,
  "do_not_save_grid": false,
  "negative_prompt": "",
  "eta": null,
  "s_min_uncond": 0.0,
  "s_churn": 0.0,
  "s_tmax": 1.0,
  "s_tmin": 0.0,
  "s_noise": 1.0,
  "override_settings": {},
  "override_settings_restore_afterwards": true,
  "script_args": [],
  "sampler_index": "Euler a",
  "script_name": null,
  "send_images": true,
  "save_images": false,
  "alwayson_scripts": {
    "controlnet": {
      "args": [
        {
          "enabled": false,
          "module": "none",
          "model": "None",
          "weight": 1,
          "image": null,
          "resize_mode": "Crop and Resize",
          "low_vram": false,
          "processor_res": -1,
          "threshold_a": -1,
          "threshold_b": -1,
          "guidance_start": 0,
          "guidance_end": 1,
          "pixel_perfect": false,
          "control_mode": "Balanced",
          "is_ui": true,
          "input_mode": "simple",
          "batch_images": "",
          "output_dir": "",
          "loopback": false
        }
      ]
    },
    "extra options": {
      "args": []
    }
  }
}

Example responses

200 Response

{
  "inference_id": "XXXXXXX",
  "status": "inprogress | failed",
  "endpoint_name": "NAME_OF_ENDPOINT",
  "output_path": "path_of_prediction_output"
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful Response	Inline

/inference/deploy-sagemaker-endpoint

Code samples :

Python example code:

import requests
headers = {
  'Content-Type': 'application/json',
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}
inputBody = {
	"instance_type": "ml.g4dn.xlarge | ml.g4dn.2xlarge | ml.g4dn.4xlarge",
	"initial_instance_count": "1|2|3|4"
}

r = requests.post('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/deploy-sagemaker-endpoint', headers = headers, json = inputBody)

print(r.json())

Javascript example code:

const inputBody = '{
  "instance_type": "ml.g4dn.xlarge | ml.g4dn.2xlarge | ml.g4dn.4xlarge",
  "initial_instance_count": "1|2|3|4"
}';
const headers = {
  'Content-Type':'application/json',
  'Accept':'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/deploy-sagemaker-endpoint',
{
  method: 'POST',
  body: inputBody,
  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

POST /inference/deploy-sagemaker-endpoint

Body parameter

{
  "instance_type": "ml.g4dn.xlarge | ml.g4dn.2xlarge | ml.g4dn.4xlarge",
  "initial_instance_count": "1|2|3|4"
}

Parameters

Name	In	Type	Required	Description
body	body	object	false	none

Example responses

200 Response

null

Responses

Status	Meaning	Description	Schema
200	OK	Successful Response	Inline

Response Schema

This operation does not require authentication

/inference/delete-sagemaker-endpoint

Code samples :

Python example code:

import requests
headers = {
  'Content-Type': 'application/json',
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

inputBody = {
"delete_endpoint_list": [
  "infer-endpoint-XXXXXX",
  "infer-endpoint-YYYYYY"
]
}

r = requests.post('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/delete-sagemaker-endpoint', headers = headers, json = inputBody)

print(r.json())

Javascript example code:

const inputBody = '{
  "delete_endpoint_list": [
    "infer-endpoint-XXXXXX",
    "infer-endpoint-YYYYYY"
  ]
}';
const headers = {
  'Content-Type':'application/json',
  'Accept':'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/delete-sagemaker-endpoint',
{
  method: 'POST',
  body: inputBody,
  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

POST /inference/delete-sagemaker-endpoint

Body parameter

{
  "delete_endpoint_list": [
    "infer-endpoint-XXXXXX",
    "infer-endpoint-YYYYYY"
  ]
}

Parameters

Name	In	Type	Required	Description
body	body	object	false	none

Example responses

200 Response

null

Responses

Status	Meaning	Description	Schema
200	OK	Successful Response	Inline

Response Schema

This operation does not require authentication

/inference/list-endpoint-deployment-jobs

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/list-endpoint-deployment-jobs', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/list-endpoint-deployment-jobs',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /inference/list-endpoint-deployment-jobs

Example responses

200 Response

[
  {
    "EndpointDeploymentJobId": "e0f9ccfd-8d14-4e77-9e75-b340e1ef23c8",
    "startTime": "2023-07-04 08:00:35.171309",
    "endTime": "2023-07-04 08:00:37.158519",
    "error": "",
    "status": "failed"
  },
  {
    "EndpointDeploymentJobId": "1bd447d2-e561-4cb3-965d-2707b30aea81",
    "startTime": "2023-07-04 08:00:22.435828",
    "endTime": "2023-07-04 08:00:25.421777",
    "error": "",
    "status": "failed"
  },
  {
    "EndpointDeploymentJobId": "cb821ea9-e9d1-4bae-98f8-c20ecadf11e0",
    "startTime": "2023-07-04 08:00:47.736033",
    "endTime": "2023-07-04 08:12:55.148070",
    "endpoint_name": "infer-endpoint-cb821ea",
    "endpoint_status": "InService",
    "status": "success"
  }
]

Responses

Status	Meaning	Description	Schema
200	OK	Successful Response	Inline

Response Schema

This operation does not require authentication

/inference/list-inference-jobs

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/list-inference-jobs', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/list-inference-jobs',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /inference/list-inference-jobs

Example responses

200 Response

[
  {
    "inference_info_name": "/tmp/417d8bc5-f6d0-49c6-9669-c981beeb602a_param.json",
    "startTime": "2023-07-04 09:14:21.170303",
    "taskType": "txt2img",
    "completeTime": "2023-07-04-09-14-26",
    "InferenceJobId": "417d8bc5-f6d0-49c6-9669-c981beeb602a",
    "status": "succeed",
    "sagemakerRaw": "",
    "image_names": [
      "image_0.jpg"
    ]
  },
  {
    "inference_info_name": "/tmp/1f9679f3-25b8-4c44-8345-0a845da30094_param.json",
    "startTime": "2023-07-05 06:38:45.752740",
    "taskType": "txt2img",
    "completeTime": "2023-07-05-06-38-49",
    "InferenceJobId": "1f9679f3-25b8-4c44-8345-0a845da30094",
    "status": "succeed",
    "sagemakerRaw": "{'awsRegion': 'us-west-2', 'eventTime': '2023-07-05T06:38:47.73Z', 'receivedTime': '2023-07-05T06:38:45.725Z', 'invocationStatus': 'Completed', 'requestParameters': {'accept': '*/*', 'endpointName': 'infer-endpoint-cb821ea', 'inputLocation': 's3://sagemaker-us-west-2-489670441870/async-endpoint-inputs/infer-endpoint-cb821ea-230705-0638/2023-07-05-06-38-45-445-81a1ec03-f000-4a20-9a60-032ab1558a9d'}, 'responseParameters': {'contentType': 'application/json', 'outputLocation': 's3://stable-diffusion-aws-extension-aigcbucketa457cb49-1tlr2pqwkosg3/sagemaker_output/211d2095-68bc-4404-a9e1-8a18a41f4dc7.out'}, 'inferenceId': '1f9679f3-25b8-4c44-8345-0a845da30094', 'eventVersion': '1.0', 'eventSource': 'aws:sagemaker', 'eventName': 'InferenceResult'}",
    "image_names": [
      "image_0.jpg"
    ]
  }
]

Responses

Status	Meaning	Description	Schema
200	OK	Successful Response	Inline

Response Schema

This operation does not require authentication

/inference/get-endpoint-deployment-job

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/get-endpoint-deployment-job', params={
  'jobID': 'string'
}, headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/get-endpoint-deployment-job?jobID=string',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /inference/get-endpoint-deployment-job

Parameters

Name	In	Type	Required	Description
jobID	query	string	true	none

Example responses

200 Response

{
  "EndpointDeploymentJobId": "cb821ea9-e9d1-4bae-98f8-c20ecadf11e0",
  "startTime": "2023-07-04 08:00:47.736033",
  "endTime": "2023-07-04 08:12:55.148070",
  "endpoint_name": "infer-endpoint-cb821ea",
  "endpoint_status": "InService",
  "status": "success"
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful Response	Inline
422	Unprocessable Entity	Validation Error	HTTPValidationError

Response Schema

This operation does not require authentication

/inference/get-inference-job

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/get-inference-job', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/get-inference-job',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /inference/get-inference-job

Parameters

Name	In	Type	Required	Description
jobID	query	string	false	none

Example responses

200 Response

{
  "inference_info_name": "/tmp/1f9679f3-25b8-4c44-8345-0a845da30094_param.json",
  "startTime": "2023-07-05 06:38:45.752740",
  "taskType": "txt2img",
  "completeTime": "2023-07-05-06-38-49",
  "InferenceJobId": "1f9679f3-25b8-4c44-8345-0a845da30094",
  "status": "succeed",
  "sagemakerRaw": "{'awsRegion': 'us-west-2', 'eventTime': '2023-07-05T06:38:47.73Z', 'receivedTime': '2023-07-05T06:38:45.725Z', 'invocationStatus': 'Completed', 'requestParameters': {'accept': '*/*', 'endpointName': 'infer-endpoint-cb821ea', 'inputLocation': 's3://sagemaker-us-west-2-489670441870/async-endpoint-inputs/infer-endpoint-cb821ea-230705-0638/2023-07-05-06-38-45-445-81a1ec03-f000-4a20-9a60-032ab1558a9d'}, 'responseParameters': {'contentType': 'application/json', 'outputLocation': 's3://stable-diffusion-aws-extension-aigcbucketa457cb49-1tlr2pqwkosg3/sagemaker_output/211d2095-68bc-4404-a9e1-8a18a41f4dc7.out'}, 'inferenceId': '1f9679f3-25b8-4c44-8345-0a845da30094', 'eventVersion': '1.0', 'eventSource': 'aws:sagemaker', 'eventName': 'InferenceResult'}",
  "image_names": [
    "image_0.jpg"
  ]
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful Response	Inline
422	Unprocessable Entity	Validation Error	HTTPValidationError

Response Schema

This operation does not require authentication

/inference/get-inference-job-image-output

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/get-inference-job-image-output', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/get-inference-job-image-output',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /inference/get-inference-job-image-output

Parameters

Name	In	Type	Required	Description
jobID	query	string	false	none

Example responses

200 Response

[
  "https://stable-diffusion-aws-extension-aigcbucketa457cb49-1tlr2pqwkosg3.s3.amazonaws.com/out/1f9679f3-25b8-4c44-8345-0a845da30094/result/image_0.jpg"
]

Responses

Status	Meaning	Description	Schema
200	OK	Successful Response	Inline
422	Unprocessable Entity	Validation Error	HTTPValidationError

Response Schema

Status Code 200

Response Get Inference Job Image Output Inference Get Inference Job Image Output Get

Name	Type	Required	Restrictions	Description
Response Get Inference Job Image Output Inference Get Inference Job Image Output Get	[string]	false	none	none

This operation does not require authentication

/inference/get-inference-job-param-output

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/get-inference-job-param-output', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/get-inference-job-param-output',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /inference/get-inference-job-param-output

Parameters

Name	In	Type	Required	Description
jobID	query	string	false	none

Example responses

200 Response

[
  "https://stable-diffusion-aws-extension-aigcbucketa457cb49-1tlr2pqwkosg3.s3.amazonaws.com/out/1f9679f3-25b8-4c44-8345-0a845da30094/result/1f9679f3-25b8-4c44-8345-0a845da30094_param.json"
]

Responses

Status	Meaning	Description	Schema
200	OK	Successful Response	Inline
422	Unprocessable Entity	Validation Error	HTTPValidationError

Response Schema

Status Code 200

Response Get Inference Job Param Output Inference Get Inference Job Param Output Get

Name	Type	Required	Restrictions	Description
Response Get Inference Job Param Output Inference Get Inference Job Param Output Get	[string]	false	none	none

This operation does not require authentication

/inference/generate-s3-presigned-url-for-uploading

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/generate-s3-presigned-url-for-uploading', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/generate-s3-presigned-url-for-uploading',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /inference/generate-s3-presigned-url-for-uploading

Parameters

Name	In	Type	Required	Description
s3_bucket_name	query	string	false	none
key	query	string	false	none

Example responses

200 Response

"https://stable-diffusion-aws-extension-aigcbucketa457cb49-1tlr2pqwkosg3.s3.amazonaws.com/config/aigc.json?XXX"

Responses

Status	Meaning	Description	Schema
200	OK	Successful Response	string
422	Unprocessable Entity	Validation Error	HTTPValidationError

This operation does not require authentication

/inference/get-texual-inversion-list

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/get-texual-inversion-list', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/get-texual-inversion-list',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /inference/get-texual-inversion-list

Example responses

200 Response

null

Responses

Status	Meaning	Description	Schema
200	OK	Successful Response	Inline

Response Schema

This operation does not require authentication

/inference/get-lora-list

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/get-lora-list', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/get-lora-list',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /inference/get-lora-list

Example responses

200 Response

null

Responses

Status	Meaning	Description	Schema
200	OK	Successful Response	Inline

Response Schema

This operation does not require authentication

/inference/get-hypernetwork-list

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/get-hypernetwork-list', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/get-hypernetwork-list',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /inference/get-hypernetwork-list

Example responses

200 Response

null

Responses

Status	Meaning	Description	Schema
200	OK	Successful Response	Inline

Response Schema

This operation does not require authentication

/inference/get-controlnet-model-list

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/get-controlnet-model-list', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/get-controlnet-model-list',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /inference/get-controlnet-model-list

Example responses

200 Response

null

Responses

Status	Meaning	Description	Schema
200	OK	Successful Response	Inline

Response Schema

This operation does not require authentication

/inference/run-model-merge

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.post('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/run-model-merge', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/inference/run-model-merge',
{
  method: 'POST',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

POST /inference/run-model-merge

Example responses

200 Response

{
  "primary_model_name": "primary_model_name,",
  "secondary_model_name": "secondary_model_name,",
  "tertiary_model_name": "teritary_model_name"
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful Response	Inline

Response Schema

This operation does not require authentication

default

/model(POST)

Code samples :

Python example code:

import requests
headers = {
  'Content-Type': 'application/json',
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.post('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/model', headers = headers)

print(r.json())

Javascript example code:

const inputBody = '{
  "model_type": "Stable-diffusion",
  "name": "testmodelcreation01",
  "filenames": [
    {
      "filename": "v1-5-pruned-emaonly.safetensors.tar",
      "parts_number": 5
    }
  ],
  "params": {
    "create_model_params": {
      "new_model_name": "testmodelcreation01",
      "ckpt_path": "v1-5-pruned-emaonly.safetensors",
      "from_hub": false,
      "new_model_url": "",
      "new_model_token": "",
      "extract_ema": false,
      "train_unfrozen": false,
      "is_512": true
    }
  }
}';
const headers = {
  'Content-Type':'application/json',
  'Accept':'application/json',
  'x-api-key':'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/model',
{
  method: 'POST',
  body: inputBody,
  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

POST /model

Body parameter

{
  "model_type": "Stable-diffusion",
  "name": "testmodelcreation01",
  "filenames": [
    {
      "filename": "v1-5-pruned-emaonly.safetensors.tar",
      "parts_number": 5
    }
  ],
  "params": {
    "create_model_params": {
      "new_model_name": "testmodelcreation01",
      "ckpt_path": "v1-5-pruned-emaonly.safetensors",
      "from_hub": false,
      "new_model_url": "",
      "new_model_token": "",
      "extract_ema": false,
      "train_unfrozen": false,
      "is_512": true
    }
  }
}

Parameters

Name	In	Type	Required	Description
body	body	object	false	none

Example responses

200 Response

{
  "statusCode": 200,
  "job": {
    "id": "id",
    "status": "Initialed",
    "s3_base": "s3://S3_Location",
    "model_type": "Stable-diffusion",
    "params": {},
    "s3PresignUrl": [
      {
        "upload_id": "id",
        "bucket": "bucket name",
        "key": "object key"
      }
    ]
  }
}

500 Response

{
  "statusCode": 500,
  "error": "error_message"
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful response	Inline
500	Internal Server Error	Error response	Inline

Response Schema

To perform this operation, you must be authenticated by means of one of the following methods: api_key

/model(PUT)

Code samples :

Python example code:

import requests
headers = {
  'Content-Type': 'application/json',
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

inputBody = {
"model_id": "c9f59ee7-0672-4fd1-8a45-8a494de8a48d",
"status": "Creating",
"multi_parts_tags": {
  "v1-5-pruned-emaonly.safetensors.tar": [
    {
      "ETag": "cc95c41fa28463c8e9b88d67805f24e0",
      "PartNumber": 1
    },
    {
      "ETag": "e4378bd84b0497559c55be8373cb79d0",
      "PartNumber": 2
    },
    {
      "ETag": "815b68042f6ac5e60b9cff5c697ffea6",
      "PartNumber": 3
    },
    {
      "ETag": "2c6cfbd9bfbafd5664cdc8b3ba07df6d",
      "PartNumber": 4
    },
    {
      "ETag": "e613d37e5065b0cd63f1cad216423141",
      "PartNumber": 5
    }
  ]
}
}

r = requests.put('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/model', headers = headers, json = inputBody)

print(r.json())

Javascript example code:

const inputBody = '{
  "model_id": "c9f59ee7-0672-4fd1-8a45-8a494de8a48d",
  "status": "Creating",
  "multi_parts_tags": {
    "v1-5-pruned-emaonly.safetensors.tar": [
      {
        "ETag": "cc95c41fa28463c8e9b88d67805f24e0",
        "PartNumber": 1
      },
      {
        "ETag": "e4378bd84b0497559c55be8373cb79d0",
        "PartNumber": 2
      },
      {
        "ETag": "815b68042f6ac5e60b9cff5c697ffea6",
        "PartNumber": 3
      },
      {
        "ETag": "2c6cfbd9bfbafd5664cdc8b3ba07df6d",
        "PartNumber": 4
      },
      {
        "ETag": "e613d37e5065b0cd63f1cad216423141",
        "PartNumber": 5
      }
    ]
  }
}';
const headers = {
  'Content-Type':'application/json',
  'Accept':'application/json',
  'x-api-key':'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/model',
{
  method: 'PUT',
  body: inputBody,
  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

PUT /model

Body parameter

{
  "model_id": "c9f59ee7-0672-4fd1-8a45-8a494de8a48d",
  "status": "Creating",
  "multi_parts_tags": {
    "v1-5-pruned-emaonly.safetensors.tar": [
      {
        "ETag": "cc95c41fa28463c8e9b88d67805f24e0",
        "PartNumber": 1
      },
      {
        "ETag": "e4378bd84b0497559c55be8373cb79d0",
        "PartNumber": 2
      },
      {
        "ETag": "815b68042f6ac5e60b9cff5c697ffea6",
        "PartNumber": 3
      },
      {
        "ETag": "2c6cfbd9bfbafd5664cdc8b3ba07df6d",
        "PartNumber": 4
      },
      {
        "ETag": "e613d37e5065b0cd63f1cad216423141",
        "PartNumber": 5
      }
    ]
  }
}

Parameters

Name	In	Type	Required	Description
body	body	object	false	none

Example responses

200 Response

{
  "statusCode": 200,
  "job": {
    "output_path": "s3://S3_Location",
    "id": "job.id",
    "endpointName": "endpoint_name",
    "jobStatus": "Created",
    "jobType": "Stable-diffusion"
  }
}

500 Response

{
  "statusCode": 500,
  "error": "error_message"
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful response	Inline
500	Internal Server Error	Error response	Inline

Response Schema

To perform this operation, you must be authenticated by means of one of the following methods: api_key

/models(GET)

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/models', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key':'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/models',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /models

Parameters

Name	In	Type	Required	Description
types	query	array[string]	false	none

Example responses

200 Response

{
  "statusCode": 200,
  "models": {
    "id": "id",
    "model_name": "name",
    "created": 12341234,
    "params": {},
    "status": "Initialed",
    "output_s3_location": "s3://S3_LOCATION/"
  }
}

500 Response

{
  "statusCode": 500,
  "error": "error_message"
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful response	Inline
500	Internal Server Error	Error response	Inline

Response Schema

To perform this operation, you must be authenticated by means of one of the following methods: api_key

/checkpoint

Code samples :

Python example code:

import requests
headers = {
  'Content-Type': 'application/json',
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

inputBody = {
"checkpoint_type": "Stable-diffusion",
"filenames": [
  {
    "filename": "v1-5-pruned-emaonly.safetensors",
    "parts_number": 5
  }
],
"params": {
  "new_model_name": "test_api",
  "number": 1,
  "string": "abc"
}
}

r = requests.post('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/checkpoint', headers = headers, json = inputBody)

print(r.json())

Javascript example code:

const inputBody = '{
  "checkpoint_type": "Stable-diffusion",
  "filenames": [
    {
      "filename": "v1-5-pruned-emaonly.safetensors",
      "parts_number": 5
    }
  ],
  "params": {
    "new_model_name": "test_api",
    "number": 1,
    "string": "abc"
  }
}';
const headers = {
  'Content-Type':'application/json',
  'Accept':'application/json',
  'x-api-key':'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/checkpoint',
{
  method: 'POST',
  body: inputBody,
  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

POST /checkpoint

Body parameter

{
  "checkpoint_type": "Stable-diffusion",
  "filenames": [
    {
      "filename": "v1-5-pruned-emaonly.safetensors",
      "parts_number": 5
    }
  ],
  "params": {
    "new_model_name": "test_api",
    "number": 1,
    "string": "abc"
  }
}

Parameters

Name	In	Type	Required	Description
body	body	object	false	none

Example responses

200 Response

{
  "statusCode": 200,
  "checkpoint": {
    "id": "id",
    "type": "Stable-diffusion",
    "s3_location": "s3://S3_Location",
    "status": "Initialed",
    "params": {}
  },
  "s3PresignUrl": [
    {
      "upload_id": "id,",
      "bucket": "bucket name,",
      "key": "key,"
    }
  ]
}

500 Response

{
  "statusCode": 500,
  "error": "error_message"
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful response	Inline
500	Internal Server Error	Error response	Inline

Response Schema

To perform this operation, you must be authenticated by means of one of the following methods: api_key

/checkpoint(put)

Code samples :

Python example code:

import requests
headers = {
  'Content-Type': 'application/json',
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

inputBody = {
"checkpoint_id": "906a5a1f-6833-45aa-8a10-fb0e983e0eae",
"status": "Active",
"multi_parts_tags": {
  "v1-5-pruned-emaonly.safetensors.tar": [
    {
      "ETag": "cc95c41fa28463c8e9b88d67805f24e0",
      "PartNumber": 1
    },
    {
      "ETag": "e4378bd84b0497559c55be8373cb79d0",
      "PartNumber": 2
    },
    {
      "ETag": "815b68042f6ac5e60b9cff5c697ffea6",
      "PartNumber": 3
    },
    {
      "ETag": "2c6cfbd9bfbafd5664cdc8b3ba07df6d",
      "PartNumber": 4
    },
    {
      "ETag": "e613d37e5065b0cd63f1cad216423141",
      "PartNumber": 5
    }
  ]
}
}

r = requests.put('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/checkpoint', headers = headers, json = inputBody)

print(r.json())

Javascript example code:

const inputBody = '{
  "checkpoint_id": "906a5a1f-6833-45aa-8a10-fb0e983e0eae",
  "status": "Active",
  "multi_parts_tags": {
    "v1-5-pruned-emaonly.safetensors.tar": [
      {
        "ETag": "cc95c41fa28463c8e9b88d67805f24e0",
        "PartNumber": 1
      },
      {
        "ETag": "e4378bd84b0497559c55be8373cb79d0",
        "PartNumber": 2
      },
      {
        "ETag": "815b68042f6ac5e60b9cff5c697ffea6",
        "PartNumber": 3
      },
      {
        "ETag": "2c6cfbd9bfbafd5664cdc8b3ba07df6d",
        "PartNumber": 4
      },
      {
        "ETag": "e613d37e5065b0cd63f1cad216423141",
        "PartNumber": 5
      }
    ]
  }
}';
const headers = {
  'Content-Type':'application/json',
  'Accept':'application/json',
  'x-api-key':'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/checkpoint',
{
  method: 'PUT',
  body: inputBody,
  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

PUT /checkpoint

Body parameter

{
  "checkpoint_id": "906a5a1f-6833-45aa-8a10-fb0e983e0eae",
  "status": "Active",
  "multi_parts_tags": {
    "v1-5-pruned-emaonly.safetensors.tar": [
      {
        "ETag": "cc95c41fa28463c8e9b88d67805f24e0",
        "PartNumber": 1
      },
      {
        "ETag": "e4378bd84b0497559c55be8373cb79d0",
        "PartNumber": 2
      },
      {
        "ETag": "815b68042f6ac5e60b9cff5c697ffea6",
        "PartNumber": 3
      },
      {
        "ETag": "2c6cfbd9bfbafd5664cdc8b3ba07df6d",
        "PartNumber": 4
      },
      {
        "ETag": "e613d37e5065b0cd63f1cad216423141",
        "PartNumber": 5
      }
    ]
  }
}

Parameters

Name	In	Type	Required	Description
body	body	object	false	none

Example responses

200 Response

{
  "statusCode": 200,
  "checkpoint": {
    "id": "id",
    "type": "Stable-diffusion",
    "s3_location": "s3://S3_Location",
    "status": "Active",
    "params": {}
  }
}

500 Response

{
  "statusCode": 500,
  "error": "error_message"
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful response	Inline
500	Internal Server Error	Error response	Inline

Response Schema

To perform this operation, you must be authenticated by means of one of the following methods: api_key

/checkpoints

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/checkpoints', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key':'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/checkpoints',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /checkpoints

Parameters

Name	In	Type	Required	Description
status	query	array[string]	false	none
types	query	array[string]	false	none

Example responses

200 Response

{
  "statusCode": 200,
  "checkpoints": [
    {
      "id": "id",
      "s3Location": "s3://S3_Location",
      "type": "Stable-diffusion",
      "status": "Active",
      "name": [
        "object_1",
        "object_2"
      ],
      "created": 12341234
    }
  ]
}

500 Response

{
  "statusCode": 500,
  "error": "error_message"
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful response	Inline
500	Internal Server Error	Error response	Inline

Response Schema

To perform this operation, you must be authenticated by means of one of the following methods: api_key

/train(POST)

Code samples :

Python example code:

import requests
headers = {
  'Content-Type': 'application/json',
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

const inputBody = {
"train_type": "dreambooth",
"model_id": "36c9d05e-3445-42a6-8be1-d7d054df7b9d",
"params": {
  "train_params": {
    "training_instance_type": "ml.g4dn.2xlarge"
  },
  "test1": 2
},
"filenames": [
  "training_config.json",
  "images.tar"
]
}

r = requests.post('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/train', headers = headers, json = inputBody)

print(r.json())

Javascript example code:

const inputBody = '{
  "train_type": "dreambooth",
  "model_id": "36c9d05e-3445-42a6-8be1-d7d054df7b9d",
  "params": {
    "train_params": {
      "training_instance_type": "ml.g4dn.2xlarge"
    },
    "test1": 2
  },
  "filenames": [
    "training_config.json",
    "images.tar"
  ]
}';
const headers = {
  'Content-Type':'application/json',
  'Accept':'application/json',
  'x-api-key':'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/train',
{
  method: 'POST',
  body: inputBody,
  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

POST /train

Body parameter

{
  "train_type": "dreambooth",
  "model_id": "36c9d05e-3445-42a6-8be1-d7d054df7b9d",
  "params": {
    "train_params": {
      "training_instance_type": "ml.g4dn.2xlarge"
    },
    "test1": 2
  },
  "filenames": [
    "training_config.json",
    "images.tar"
  ]
}

Parameters

Name	In	Type	Required	Description
body	body	object	false	none

Example responses

200 Response

{
  "statusCode": 200,
  "job": {
    "id": "id",
    "status": "Initialed",
    "trainType": "Stable-diffusion",
    "params": {},
    "input_location": "s3://S3_Location"
  },
  "s3PresignUrl": [
    {
      "filename": "s3://S3_Location"
    }
  ]
}

500 Response

{
  "statusCode": 500,
  "error": "error_message"
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful response	Inline
500	Internal Server Error	Error response	Inline

Response Schema

To perform this operation, you must be authenticated by means of one of the following methods: api_key

/train(PUT)

Code samples :

Python example code:

import requests
headers = {
  'Content-Type': 'application/json',
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

inputBody = {
"train_job_id": "b5183dd3-0279-46ff-b64e-6cd687c0fe71",
"status": "Training"
}

r = requests.put('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/train', headers = headers, json = inputBody)

print(r.json())

Javascript example code:

const inputBody = '{
  "train_job_id": "b5183dd3-0279-46ff-b64e-6cd687c0fe71",
  "status": "Training"
}';
const headers = {
  'Content-Type':'application/json',
  'Accept':'application/json',
  'x-api-key':'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/train',
{
  method: 'PUT',
  body: inputBody,
  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

PUT /train

Body parameter

{
  "train_job_id": "b5183dd3-0279-46ff-b64e-6cd687c0fe71",
  "status": "Training"
}

Parameters

Name	In	Type	Required	Description
body	body	object	false	none

Example responses

200 Response

{
  "statusCode": 200,
  "job": {
    "id": "id",
    "status": "Training",
    "created": 12341234,
    "trainType": "Stable-diffusion",
    "params": {},
    "input_location": "s3://S3_Location"
  }
}

500 Response

{
  "statusCode": 500,
  "error": "error_message"
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful response	Inline
500	Internal Server Error	Error response	Inline

Response Schema

To perform this operation, you must be authenticated by means of one of the following methods: api_key

/trains(GET)

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/trains', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key':'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/trains',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /trains

Parameters

Name	In	Type	Required	Description
types	query	array[string]	false	none

Example responses

200 Response

{
  "statusCode": "200,",
  "trainJobs": [
    {
      "id": "id",
      "modelName": "model_name",
      "status": "Complete",
      "trainType": "Stable-diffusion",
      "created": 1234124,
      "sagemakerTrainName": "sagemaker_train_name"
    }
  ]
}

500 Response

{
  "statusCode": 500,
  "error": "error_message"
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful response	Inline
500	Internal Server Error	Error response	Inline

Response Schema

To perform this operation, you must be authenticated by means of one of the following methods: api_key

/dataset(POST)

Code samples :

Python example code:

import requests
headers = {
  'Content-Type': 'application/json',
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

const inputBody = {
"dataset_name": "test_dataset",
"content": [
  {
    "filename": "/path/to/a/file.png",
    "name": "another_name",
    "type": "png"
  }
],
"params": {}
}

r = requests.post('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/dataset', headers = headers, json = inputBody)

print(r.json())

Javascript example code:

const inputBody = '{
  "dataset_name": "test_dataset",
  "content": [
    {
      "filename": "/path/to/a/file.png",
      "name": "another_name",
      "type": "png"
    }
  ],
  "params": {}
}';
const headers = {
  'Content-Type':'application/json',
  'Accept':'application/json',
  'x-api-key':'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/dataset',
{
  method: 'POST',
  body: inputBody,
  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

POST /dataset

Body parameter

{
  "dataset_name": "test_dataset",
  "content": [
    {
      "filename": "/path/to/a/file.png",
      "name": "another_name",
      "type": "png"
    }
  ],
  "params": {}
}

Parameters

Name	In	Type	Required	Description
body	body	object	false	none

Example responses

200 Response

{
  "statusCode": 200,
  "datasetName": "dataset_name",
  "s3PresignUrl": [
    {
      "filename": "s3://S3_Location"
    }
  ]
}

500 Response

{
  "statusCode": 500,
  "error": "error_message"
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful response	Inline
500	Internal Server Error	Error response	Inline

Response Schema

To perform this operation, you must be authenticated by means of one of the following methods: api_key

/dataset(PUT)

Code samples :

Python example code:

import requests
headers = {
  'Content-Type': 'application/json',
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

inputBody = {
"dataset_name": "test_dataset",
"status": "Enabled"
}

r = requests.put('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/dataset', headers = headers, json = inputBody)

print(r.json())

Javascript example code:

const inputBody = '{
  "dataset_name": "test_dataset",
  "status": "Enabled"
}';
const headers = {
  'Content-Type':'application/json',
  'Accept':'application/json',
  'x-api-key':'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/dataset',
{
  method: 'PUT',
  body: inputBody,
  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

PUT /dataset

Body parameter

{
  "dataset_name": "test_dataset",
  "status": "Enabled"
}

Parameters

Name	In	Type	Required	Description
body	body	object	false	none

Example responses

200 Response

{
  "statusCode": 200,
  "datasetName": "dataset_name",
  "status": "Enabled"
}

500 Response

{
  "statusCode": 500,
  "error": "error_message"
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful response	Inline
500	Internal Server Error	Error response	Inline

Response Schema

To perform this operation, you must be authenticated by means of one of the following methods: api_key

/datasets(GET)

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/datasets', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key':'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/prod/datasets',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /prod/datasets

Parameters

Name	In	Type	Required	Description
dataset_status	query	array[string]	false	none

Example responses

200 Response

{
  "statusCode": 200,
  "datasets": [
    {
      "datasetName": "dataset_name",
      "s3": "s3://S3_Location",
      "status": "Enabled",
      "timestamp": 1234124
    }
  ]
}

500 Response

{
  "statusCode": 500,
  "error": "error_message"
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful response	Inline
500	Internal Server Error	Error response	Inline

Response Schema

To perform this operation, you must be authenticated by means of one of the following methods: api_key

/{dataset_name}/data

Code samples :

Python example code:

import requests
headers = {
  'Accept': 'application/json',
  'x-api-key': 'API_TOKEN_VALUE'
}

r = requests.get('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/{dataset_name}/data', headers = headers)

print(r.json())

Javascript example code:

const headers = {
  'Accept':'application/json',
  'x-api-key':'API_TOKEN_VALUE'
};

fetch('https://<Your API Gateway ID>.execute-api.<Your AWS Account Region>.amazonaws.com/{basePath}/{dataset_name}/data',
{
  method: 'GET',

  headers: headers
})
.then(function(res) {
    return res.json();
}).then(function(body) {
    console.log(body);
});

GET /{dataset_name}/data

Parameters

Name	In	Type	Required	Description
dataset_name	path	string	true	none

Example responses

200 Response

{
  "statusCode": 200,
  "dataset_name": "dataset_name",
  "data": [
    {
      "key": "key",
      "name": "file name",
      "type": "image",
      "preview_url": "https://presigned_s3_url",
      "dataStatus": "Enabled"
    }
  ]
}

500 Response

{
  "statusCode": 500,
  "error": "error_message"
}

Responses

Status	Meaning	Description	Schema
200	OK	Successful response	Inline
500	Internal Server Error	Error response	Inline

Response Schema

To perform this operation, you must be authenticated by means of one of the following methods: api_key

Schemas

Empty

{}

Empty Schema

Properties

None

HTTPValidationError

{
  "detail": [
    {
      "loc": [
        "string"
      ],
      "msg": "string",
      "type": "string"
    }
  ]
}

HTTPValidationError

Properties

Name	Type	Required	Restrictions	Description
detail	[ValidationError]	false	none	none

ValidationError

{
  "loc": [
    "string"
  ],
  "msg": "string",
  "type": "string"
}

ValidationError

Properties

Name	Type	Required	Restrictions	Description
loc	[anyOf]	true	none	none

anyOf

Name	Type	Required	Restrictions	Description
» anonymous	string	false	none	none

or

Name	Type	Required	Restrictions	Description
» anonymous	integer	false	none	none

continued

Name	Type	Required	Restrictions	Description
msg	string	true	none	none
type	string	true	none	none