MachineLearning API

All URIs are relative to http://localhost:1000

Method	HTTP request	Description
personificationTechnicalLanguageGeneration	POST /machine_learning/text/technical_language/generators/personification	/machine_learning/text/technical_language/generators/personification [GET]
segmentTechnicalLanguage	POST /machine_learning/text/technical_language/parsers/segmentation	/machine_learning/text/technical_language/parsers/segmentation [POST]

personificationTechnicalLanguageGeneration

OnboardedPersonaDetails personificationTechnicalLanguageGeneration()

This is going to take in some personification details ie languages & personas. and will return generated Seeds that can be used as snippets post/pre onboarding.

Example

import * as Pieces from '@pieces.app/pieces-os-client'

const configuration = Pieces.Configuration()
const apiInstance = new Pieces.MachineLearningApi(configuration)

const body: Pieces.PersonificationTechnicalLanguageGenerationRequest = {
// PreonboardedPersonaDetails (optional)
preonboardedPersonaDetails: ,
};

apiInstance.personificationTechnicalLanguageGeneration(body).then((data: OnboardedPersonaDetails) => {
console.log('API called successfully. Returned data: ' + data)
}).catch((error: unknown) => console.error(error))

Parameters

Name	Type	Description	Notes
preonboardedPersonaDetails	PreonboardedPersonaDetails

Return type

OnboardedPersonaDetails

HTTP request headers

• Content-Type: application/json
• Accept: application/json, text/plain

HTTP response details

Status code	Description	Response headers
200	OK	-
500	Internal Server Error	-

segmentTechnicalLanguage

SegmentedTechnicalLanguage segmentTechnicalLanguage()

This is a functional endpoint that will parse a message or text in to text or code. if the optional query param is passed along 'classify' then we will optionally classify the just the code that is segmented.

Example

import * as Pieces from '@pieces.app/pieces-os-client'

const configuration = Pieces.Configuration()
const apiInstance = new Pieces.MachineLearningApi(configuration)

const body: Pieces.SegmentTechnicalLanguageRequest = {
// boolean | This will let us know if you want us to classifiy your code, this is default to false. (optional)
classify: true,
// UnsegmentedTechnicalLanguage (optional)
unsegmentedTechnicalLanguage: ,
};

apiInstance.segmentTechnicalLanguage(body).then((data: SegmentedTechnicalLanguage) => {
console.log('API called successfully. Returned data: ' + data)
}).catch((error: unknown) => console.error(error))

Parameters

Name	Type	Description	Notes
unsegmentedTechnicalLanguage	UnsegmentedTechnicalLanguage
classify	[boolean]	This will let us know if you want us to classifiy your code, this is default to false.	(optional) defaults to undefined

Return type

SegmentedTechnicalLanguage

HTTP request headers

• Content-Type: application/json
• Accept: application/json, text/plain

HTTP response details

Status code	Description	Response headers
200	OK	-
500	Internal Server Error	-