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drum_server_api.yaml
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openapi: 3.0.1
info:
title: DRUM prediction server.
description: DRUM prediction server.
version: "1.12.0"
paths:
/URL_PREFIX/:
$ref: "#/paths/~1URL_PREFIX~1ping~1"
/URL_PREFIX/ping/:
get:
description: Check whether server is alive.
responses:
200:
description: OK
content:
application/json:
schema:
type: object
properties:
message:
type: string
description: Status message.
example:
message: OK
513:
description: 'Error loading/initializing model. Requires DRUM server has to be started with --with-error-server option'
content:
application/json:
schema:
type: object
properties:
message:
type: string
description: Status message
example:
message: "ERROR: \n\nRunning environment language: Python.\n Failed loading hooks from [/tmp/model/python3_sklearn/custom.py] : No module named 'andas'"
/URL_PREFIX/health/:
get:
description: Get functional health status, e.g. whether model is loaded and functioning properly.
responses:
200:
description: OK
content:
application/json:
schema:
type: object
properties:
message:
type: string
description: Status message.
example:
message: OK
513:
description: 'Error loading/initializing model. Requires DRUM server has to be started with --with-error-server option'
content:
application/json:
schema:
type: object
properties:
message:
type: string
description: Status message
example:
message: "ERROR: \n\nRunning environment language: Python.\n Failed loading hooks from [/tmp/model/python3_sklearn/custom.py] : No module named 'andas'"
/URL_PREFIX/info/:
get:
description: Get information about running model (metadata, paths, predictor type, etc.).
responses:
200:
description: OK
content:
application/json:
schema:
type: object
properties:
codeDir:
type: string
description: Custom code (model) location.
drumServer:
type: string
description: DRUM server backend.
drumVersion:
type: string
description: DRUM version.
language:
type: string
description: Custom code (model) language.
modelMetadata:
type: object
description: Model metadata taken from model-metadata.yaml, if exists in the code dir. May have arbitrary structure.
predictor:
type: string
description: Internal predictor used to load a model.
targetType:
type: string
description: Model target type
example:
codeDir: /tmp/model/python3_sklearn
drumServer: flask
drumVersion: 1.5.3
language: python
modelMetadata:
environmentID: 5e8c889607389fe0f466c72d
inferenceModel:
targetName: Grade 2014
modelId: 5f1f15a4d6111f01cb7f91fd
name: regression model
targetType: regression
type: inference
validation:
input: ../../../tests/testdata/juniors_3_year_stats_regression.csv
predictor: scikit-learn
targetType: regression
/URL_PREFIX/stats/:
get:
description: Shows running model statistics (memory).
responses:
200:
description: OK
content:
application/json:
schema:
type: object
properties:
drum_info:
type: array
items:
type: object
properties:
cmdline:
type: array
items:
type: string
cpu_percent:
type: number
description: CPU percentage used by DRUM.
mem:
type: number
description: Memory used by DRUM.
pid:
type: number
description: DRUM server process PID.
mem_info:
type: object
properties:
avail:
type: number
description: Total available memory on the system.
container_limit:
type: number
description: Value is not null when starting DRUM server in container, using --docker argument.
container_max_used:
type: number
description: Value is not null when starting DRUM server in container, using --docker argument.
container_used:
type: number
drum_rss:
type: number
description: Resident memory occupied by DRUM.
free:
type: number
description: Free memory in system.
total:
type: number
description: DRUM server process PID.
time_info:
type: object
properties:
run_predictor_total:
type: object
properties:
avg:
type: number
description: Average requeest time (s)
max:
type: number
description: Maximum request time (s)
min:
type: number
description: Minimum request time (s)
example:
drum_info: [ cmdline: [ "/tmp/drum_tests_virtual_environment/bin/python3",
"/tmp/drum_tests_virtual_environment/bin/drum",
"server",
"--code-dir",
"/tmp/model/python3_sklearn",
"--target-type",
"regression",
"--address",
"localhost:6789",
"--with-error-server",
"--show-perf" ], mem: 256.71484375, pid: 342391 ]
mem_info:
avail: 17670.828125
container_limit: null
container_max_used: null
container_used: null
drum_rss: 256.71484375
free: 312.33203125
total: 31442.73046875
time_info:
run_predictor_total:
avg: 0.0165
max: 0.023
min: 0.013
/URL_PREFIX/capabilities/:
get:
description: Get payload formats supported by the internal predictor in use. Predictor selection depends on the model.
responses:
200:
description: OK
content:
application/json:
schema:
type: object
properties:
supported_payload_formats:
type: object
description: If format is supported, property present in the object. Property's value is a package version. If version is not pinned, value is null.
properties:
csv:
type: string
mtx:
type: string
supported_methods:
type: object
description: Indicates for each method if it is supported or not.
properties:
chat:
type: boolean
example:
supported_payload_formats:
csv: null
mtx: null
/URL_PREFIX/predict/:
post:
description: Make predictions on regression, binary or multiclassification models.
requestBody:
description: Scoring data to predict on.
content:
text/plain:
schema:
description: Scoring data.
type: string
format: text
text/csv:
schema:
description: Scoring data.
type: string
format: text
text/mtx:
schema:
description: Scoring data.
type: string
format: text
multipart/form-data:
schema:
description: Scoring data.
type: object
properties:
X:
type: string
format: filename
responses:
200:
description: OK
content:
application/json:
schema:
oneOf:
- $ref: "#/components/schemas/regression"
- $ref: "#/components/schemas/binary"
- $ref: "#/components/schemas/multiclass"
422:
description: "Unprocessable entity"
content:
application/json:
schema:
type: object
properties:
message:
type: string
description: Status message
example:
message: "ERROR: Samples should be provided as: - a csv or mtx under `X` form-data param key. - binary data."
/URL_PREFIX/predictions/:
$ref: "#/paths/~1URL_PREFIX~1predict~1"
/URL_PREFIX/predictUnstructured/:
post:
description: Make unstructured predictions on arbitrary data.
requestBody:
description: Scoring data to predict on.
content:
text/*:
schema:
description: Any textual scoring data.
type: string
format: text
application/json:
schema:
description: Scoring data in json format.
type: string
format: text
<other>:
schema:
description: Any other mimetype provided assumes binary data is sent.
type: string
format: binary
responses:
200:
description: OK
content:
text/plain:
schema:
type: string
format: text
application/octet-stream:
schema:
type: string
format: binary
<other>:
schema:
description: Any other mimetype returned assumes user returns data in a proper format.
type: string
422:
description: "Unprocessable entity"
content:
application/json:
schema:
type: object
properties:
message:
type: string
description: Status message
/URL_PREFIX/predictionsUnstructured/:
$ref: "#/paths/~1URL_PREFIX~1predictUnstructured~1"
/URL_PREFIX/chat/completions/:
post:
description: Get chat completions using the OpenAI-compatible chat completions API.
requestBody:
content:
application/json:
schema:
externalDocs:
url: "https://platform.openai.com/docs/api-reference/chat/create"
example: >
{
"model": "gpt-4o",
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "Hello!"
}
]
}
responses:
200:
description: Chat completion response.
content:
application/json:
example: >
{
"id": "chatcmpl-123",
"object": "chat.completion",
"created": 1677652288,
"model": "gpt-4o-mini",
"system_fingerprint": "fp_44709d6fcb",
"choices": [{
"index": 0,
"message": {
"role": "assistant",
"content": "\n\nHello there, how may I assist you today?"
},
"logprobs": null,
"finish_reason": "stop"
}],
"usage": {
"prompt_tokens": 9,
"completion_tokens": 12,
"total_tokens": 21
}
}
schema:
externalDocs:
url: "https://platform.openai.com/docs/api-reference/chat/object"
/URL_PREFIX/v1/chat/completions/:
$ref: "#/paths/~1URL_PREFIX~1chat~1completions~1"
components:
schemas:
regression:
type: object
properties:
predictions:
type: array
description: List of regression predictions.
items:
type: number
example:
predictions: [2.4, 3.2, 6.1]
binary:
type: object
properties:
predictions:
type: array
description: List of binary classification predictions.
items:
type: object
example:
predictions: [{positiveClassLabel: 0.85, negativeClassLabel: 0.15}, {positiveClassLabel: 0.25, negativeClassLabel: 0.75}]
multiclass:
type: object
properties:
predictions:
type: array
description: List of multiclass classification predictions.
items:
type: object
example:
predictions: [{classLabel1: 0.75, classLabel2: 0.15, classLabel3: 0.1}, {classLabel1: 0.2, classLabel2: 0.5, classLabel3: 0.3}]