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OpenAPI Specification
openapi: 3.2.0
info:
title: Ask Sage Server Training API
description: Ask Sage is an AI-powered platform providing intelligent completions, knowledge management, and workflow automation.
version: '2.0'
contact:
name: Ask Sage Support
email: support@asksage.ai
url: https://asksage.ai
servers:
- url: '{baseUrl}/server'
description: Ask Sage Server API
variables:
baseUrl:
default: https://api.asksage.ai
description: API base URL. Use https://api.asksage.ai for production, or your self-hosted instance URL.
security:
- ApiKeyAuth: []
tags:
- name: Training
description: Model training and content ingestion
paths:
/train:
post:
summary: Train the model
description: Add new content to the knowledge base
tags:
- Training
requestBody:
required: true
content:
application/json:
schema:
type: object
required:
- content
properties:
content:
type: string
description: Content to train/ingest
context:
type: string
description: Additional context for the content
skip_vectordb:
type: boolean
default: false
description: Skip adding to vector database
force_dataset:
type: string
description: Force specific dataset for training
responses:
'200':
description: Training successful
content:
application/json:
schema:
type: object
properties:
response:
type: string
embedding:
type: string
status:
type: integer
operationId: postTrain
x-operation-id-source: derived
get:
summary: Train the model (GET)
description: Add new content to the knowledge base
tags:
- Training
responses:
'200':
description: Training successful
content:
application/json:
schema:
type: object
properties:
response:
type: string
embedding:
type: string
status:
type: integer
operationId: getTrain
x-operation-id-source: derived
/train-with-file:
post:
summary: Train with file
description: Train the model using file content
tags:
- Training
requestBody:
required: true
content:
multipart/form-data:
schema:
type: object
required:
- file
properties:
file:
type: string
format: binary
description: File to train from
dataset:
type: string
description: Dataset to add content to
responses:
'200':
description: File training successful
content:
application/json:
schema:
type: object
properties:
response:
type: string
embedding:
type: array
items:
type: string
status:
type: integer
operationId: postTrainWithFile
x-operation-id-source: derived
get:
summary: Train with file (GET)
description: Train the model using file content
tags:
- Training
responses:
'200':
description: File training successful
content:
application/json:
schema:
type: object
properties:
response:
type: string
embedding:
type: array
items:
type: string
status:
type: integer
operationId: getTrainWithFile
x-operation-id-source: derived
/train-with-array:
post:
summary: Train with array of data
description: Train the model using an array of content
tags:
- Training
requestBody:
required: true
content:
multipart/form-data:
schema:
type: object
required:
- data
- dataset
properties:
data:
type: string
description: JSON array of data to train
dataset:
type: string
description: Dataset name
context:
type: string
description: Additional context
filename:
type: string
description: Source filename
responses:
'200':
description: Array training successful
content:
application/json:
schema:
type: object
properties:
response:
type: string
embedding:
type: array
items:
type: array
items:
type: string
status:
type: integer
operationId: postTrainWithArray
x-operation-id-source: derived
get:
summary: Train with array of data (GET)
description: Train the model using an array of content
tags:
- Training
responses:
'200':
description: Array training successful
content:
application/json:
schema:
type: object
properties:
response:
type: string
embedding:
type: array
items:
type: array
items:
type: string
status:
type: integer
operationId: getTrainWithArray
x-operation-id-source: derived
components:
securitySchemes:
ApiKeyAuth:
type: apiKey
in: header
name: x-access-tokens
description: JWT authentication token. Obtain a token by calling the User API endpoint `/user/get-token-with-api-key` with your email and API key.