GETTING STARTED
Kore.ai XO Platform
Virtual Assistants Overview
Natural Language Processing (NLP)
Concepts and Terminology
Quick Start Guide
Accessing the Platform
Navigating the Kore.ai XO Platform
Building a Virtual Assistant
Help & Learning Resources
Release Notes
Current Version
Recent Updates
Previous Versions
Deprecations
Request a Feature
CONCEPTS
Design
Storyboard
Overview
FAQs
Conversation Designer
Overview
Dialog Tasks
Mock Scenes
Dialog Tasks
Overview
Navigate Dialog Tasks
Build Dialog Tasks
Node Types
Overview
Intent Node
Dialog Node
Dynamic Intent Node
GenAI Node
GenAI Prompt
Entity Node
Form Node
Confirmation Node
Message Nodes
Logic Node
Bot Action Node
Service Node
Webhook Node
Script Node
Process Node
Agent Transfer
Node Connections
Node Connections Setup
Sub-Intent Scoping
Entity Types
Entity Rules
User Prompts or Messages
Voice Call Properties
Knowledge AI
Introduction
Knowledge Graph
Introduction
Terminology
Build a Knowledge Graph
Manage FAQs
Knowledge Extraction
Import or Export Knowledge Graph
Prepare Data for Import
Importing Knowledge Graph
Exporting Knowledge Graph
Auto-Generate Knowledge Graph
Knowledge Graph Analysis
Answer from Documents
Alert Tasks
Small Talk
Digital Skills
Overview
Digital Forms
Digital Views
Introduction
Widgets
Panels
Session and Context Variables
Context Object
Intent Discovery
Train
NLP Optimization
ML Engine
Overview
Model Validation
FM Engine
KG Engine
Traits Engine
Ranking and Resolver
Training Validations
NLP Configurations
NLP Guidelines
LLM and Generative AI
Introduction
LLM Integration
Kore.ai XO GPT Module
Prompts & Requests Library
Co-Pilot Features
Dynamic Conversations Features
Intelligence
Introduction
Event Handlers
Contextual Memory
Contextual Intents
Interruption Management
Multi-intent Detection
Amending Entities
Default Conversations
Conversation Driven Dialog Builder
Sentinment Management
Tone Analysis
Default Standard Responses
Ignore Words & Field Memory
Test & Debug
Overview
Talk to Bot
Utterance Testing
Batch Testing
Conversation Testing
Conversation Testing Overview
Create a Test Suite
Test Editor
Test Case Assertion
Test Case Execution Summary
Glossary
Health and Monitoring
NLP Health
Flow Health
Integrations
Actions
Actions Overview
Asana
Configure
Templates
Azure OpenAI
Configure
Templates
BambooHR
Configure
Templates
Bitly
Configure
Templates
Confluence
Configure
Templates
DHL
Configure
Templates
Freshdesk
Configure
Templates
Freshservice
Configure
Templates
Google Maps
Configure
Templates
Here
Configure
Templates
HubSpot
Configure
Templates
JIRA
Configure
Templates
Microsoft Graph
Configure
Templates
Open AI
Configure
Templates
Salesforce
Configure
Templates
ServiceNow
Configure
Templates
Stripe
Configure
Templates
Shopify
Configure
Templates
Twilio
Configure
Templates
Zendesk
Configure
Templates
Agents
Agent Transfer Overview
Custom (BotKit)
Drift
Genesys
Intercom
NiceInContact
NiceInContact(User Hub)
Salesforce
ServiceNow
Configure Tokyo and Lower versions
Configure Utah and Higher versions
Unblu
External NLU Adapters
Overview
Dialogflow Engine
Test and Debug
Deploy
Channels
Publishing
Versioning
Analyze
Introduction
Dashboard Filters
Overview Dashboard
Conversations Dashboard
Users Dashboard
Performance Dashboard
Custom Dashboards
Introduction
Custom Meta Tags
Create Custom Dashboard
Create Custom Dashboard Filters
LLM and Generative AI Logs
NLP Insights
Task Execution Logs
Conversations History
Conversation Flows
Conversation Insights
Feedback Analytics
Usage Metrics
Containment Metrics
Universal Bots
Introduction
Universal Bot Definition
Universal Bot Creation
Training a Universal Bot
Universal Bot Customizations
Enabling Languages
Store
Manage Assistant
Team Collaboration
Plan & Usage
Overview
Usage Plans
Templates
Support Plans
Invoices
Authorization
Conversation Sessions
Multilingual Virtual Assistants
Get Started
Supported Components & Features
Manage Languages
Manage Translation Services
Multiingual Virtual Assistant Behavior
Feedback Survey
Masking PII Details
Variables
Collections
IVR Settings
General Settings
Assistant Management
Manage Namespace
Data
Overview
Data Table
Table Views
App Definitions
Data as Service
HOW TOs
Build a Travel Planning Assistant
Travel Assistant Overview
Create a Travel Virtual Assistant
Design Conversation Skills
Create an ‘Update Booking’ Task
Create a Change Flight Task
Build a Knowledge Graph
Schedule a Smart Alert
Design Digital Skills
Configure Digital Forms
Configure Digital Views
Train the Assistant
Use Traits
Use Patterns
Manage Context Switching
Deploy the Assistant
Use Bot Functions
Use Content Variables
Use Global Variables
Use Web SDK
Build a Banking Assistant
Design Conversation Skills
Create a Sample Banking Assistant
Create a Transfer Funds Task
Create a Update Balance Task
Create a Knowledge Graph
Set Up a Smart Alert
Design Digital Skills
Configure Digital Forms
Configure Digital Views
Add Data to Data Tables
Update Data in Data Tables
Add Data from Digital Forms
Train the Assistant
Composite Entities
Use Traits
Use Patterns for Intents & Entities
Manage Context Switching
Deploy the Assistant
Configure an Agent Transfer
Use Assistant Functions
Use Content Variables
Use Global Variables
Intent Scoping using Group Node
Analyze the Assistant
Create a Custom Dashboard
Use Custom Meta Tags in Filters
Migrate External Bots
Google Dialogflow Bot
APIs & SDKs
API Reference
API Introduction
Rate Limits
API List
koreUtil Libraries
SDK Reference
SDK Introduction
Web SDK
How the Web SDK Works
SDK Security
SDK Registration
Web Socket Connect and RTM
Tutorials
Widget SDK Tutorial
Web SDK Tutorial
BotKit SDK
BotKit SDK Deployment Guide
Installing the BotKit SDK
Using the BotKit SDK
SDK Events
SDK Functions
Tutorials
BotKit - Blue Prism
BotKit - Flight Search Sample VA
BotKit - Agent Transfer
  1. Docs
  2. Virtual Assistants
  3. API Guide
  4. NLP 설정 업데이트

NLP 설정 업데이트

NLP 임곗값 및 설정을 업데이트합니다

이 API를 사용하려면 앱은 NLP 설정의 봇 빌더 API 범위가 필요합니다. 또는 테스트 및 학습에서 NLP 설정의 관리자 API 범위가 필요합니다.

POST https://{{host}}/api/public/bot/{{BotID}}/configurations?language={{languageCode}}&groupName={{groupName}}

쿼리 매개 변수

매개 변수 필수/선택 사항 설명
host 필수 환경 URL(예: https://bots.kore.ai)
BotID 필수 봇 ID 또는 스트림 ID. 봇의 일반 설정 페이지에서 이를 액세스할 수 있습니다.
languageCode 필수 이러한 설정을 업데이트해야 하는 봇 언어입니다.
groupName 다중 ML 모델에 필요 GroupName을 사용하여 특정 그룹의 ML 매개 변수를 업데이트할 수 있습니다. 봇 수준 의도 모델 설정 groupName을 업데이트하려면 그룹 이름을 "봇 수준 의도 모델"로 설정해야 합니다.

본문 매개 변수

매개 변수는 업데이트해야 하는 임곗값 설정에 따라 달라집니다. 다음은 다양한 임곗값 설정에 대한 전체 매개 변수 목록입니다.

설정 업데이트

머신 러닝 엔진

이 섹션에서는 머신 러닝 엔진과 관련된 설정을 다룹니다. 설정에 대한 자세한 내용은 여기를 참조하세요.

{
    "configurations": [
        {
            "mode": "ml",               // Machine Learning Engine
            "exactMatchThreshold": 90,  // ML Definitive Score - value in range [80-100]
            "minThreshold": 0.4,        // ML threshold - value in range [0-1]
        }
    ],
    "mlParams": {
        "intentParams": {
            "useSynonyms": true,       // Bot Synonyms 
            "useStopwords": true,      // Stopwords 
            "usePlaceholders": true,   // Entity Placeholders 
            "features": "n_gram"       // Feature Extraction - value in range [skip_gram, n_gram]
            "skip_gram": {             // features should be 'skip_gram'
                "seqLength": 2,        // Sequence Length - value in range [2-4]
                "maxSkipDistance": 1   // Maximum Skip Distance - value in range [1-3]
              },
            "ngram": 3,                // ngram Sequence Length - value in range [1-4]
                                       // features should be ‘n_gram’
        },
        "nerParams": {
            "type": "corenlp"          // NER Model
                                       // could be "corenlp" for  Conditional Random Field 
                                       //       or "spacy" -  Deep Neural Network
         }
    }
}

Fundamental Meaning Engine

이 섹션에서는 엔진의 기본 의미와 관련된 설정을 다룹니다. 설정에 대한 자세한 내용은 여기를 참조하세요.

{
    "configurations": [
        {
            "mode": "cs",            // Fundamental Meaning Engine
            "labelMatch": true       // Intent Detection using Task Name Words
            "isFMThreshold": true,   //FM Threshold
            "fmThreshold": 15        //FM Threshold value
        }
  ]
}

지식 그래프 엔진

이 섹션에서는 지식 그래프 엔진과 관련된 설정을 다룹니다. 설정에 대한 자세한 내용은 여기를 참조하세요.

{
    "configurations": [ THRESHOLDS & CONFIGURATIONS 
         {
            "mode": "faq",  
            "autoSpellCorrectEnabled": true,             // Auto Correction
            "useBotSynonyms": true,                      // Bot Synonyms
            "enPatternLemma": false,                     // Lemmatization using Parts of Speech
            "pathCoverage": 50,                          // Path Coverage - value in range [0-100]
            "exactMatchThreshold": 95,                   // Minimum and Definitive Level for Knowledge Tasks 
                                                         // value in range [0-100] 
                                                         // should be more than minThreshold & maxThreshold
            "maxThreshold": 80,                          // Probable range for Knowledge Task 
                                                         // value in range [0-100] 
                                                         // should be between minThreshold & exactMatchThreshold 
            "minThreshold": 60,                          // Low confidence range for Knowledge Task 
                                                         // value in range [0-100] 
                                                         // should be less than maxThreshold & exactMatchThreshold  
            "suggestionsCount": 3,                       // KG suggestionsCount | [0-5]
            "taskMatchTolerance": 35,                    // Proximity of Suggested Matches | [0-50]
            "longResponses": {
                "readMore": true,                        // Manage Long Responses
                "useCustomReadMoreURL": true,            // readMore should be true
                "customReadMoreURL": "www.siteurl.com"   // readMore link; readMore should be true
              },
            "searchInAnswer": {
                "enabled": true,                         //  Search in Answer
                "notifyUser": true,                      // Inform end user that it is a probable answer
                "responseType": "relevantWithReadMore",  // can be "complete" - Show complete response, 
                                                         //      or "relevant" - Show only the relevant paragraph,
                                                         //      or "relevantWithReadMore" - Show only the relevant paragraph with “read more” link ]
                "customReadMoreURL": "www.siteurl.com",  // “read more” link 
                "useCustomReadMoreURL": true             // enabled should be true
            }
            "qualifyContextualPaths": false,             // Qualify Contextual Paths
        }
 ]
}

순위 및 해결 엔진

이 섹션에서는 순위 및 해결 엔진과 관련된 설정을 다룹니다. 설정에 대한 자세한 내용은 여기를 참조하세요.

{
    "configurations": 
        {
            "mode": "rr",                 // Ranking and Resolver Engine
            "taskMatchTolerance": 2,      // Proximity of Probable Matches - value in range [0-20]
            "useDependencyParser": true,  // Dependency Parsing Model 
            "minMatchVal": 0.4,           // Minimum Match Score - value in range [0-1] 
                                          // useDependencyParser should be true
            "rankingParameters": ""       //  Advanced Configurations                                           
                                          // useDependencyParser should be true
            "intentRescoring": false,     // Rescoring of Intents
            "isPreferDefinitiveMatch": true // Prefer Definitive Matches
        }
 ]
}

고급 NLP 설정

이 섹션에서는 자연어 -> 학습의 고급 NLP 설정 섹션에 나와 있는 설정을 참조합니다. 설정에 대한 자세한 내용은 여기를 참조하세요. 다음은 위에서 언급한 고급 NLP 구성을 설정하기 위한 샘플 요청입니다.

{
    "advancedNLPSettings":[
        {
            "configurationKeyName": "NoneIntent",
            "configurationValue":true,
            "nlpEngine":"ML"
        }
    ]
}

다음은 허용 가능한 고급 NLP 설정 및 가능한 값의 전체 목록입니다. 복합어 분할

{
        "configurationName": "Split Compound Words",
        "configurationKeyName": "splitCompoundWords",
        "desc": "The settings enables splitting of the compound words into multiple stems and then process the individual stem",
        "nlpEngine": "ML",
        "dataType": "Boolean",
        "range": [true, false],
        "defaultValue": false,
        "requiresTraining": true,
        "language": ["de", "nl"],
        "isChild": false
    }

의도 없음

{
        "configurationName": "None Intent",
        "configurationKeyName": "NoneIntent",
        "desc": "Once enabled, a None intent is created which reduces the chances of getting a false positive for an intent match using ML engine",
        "nlpEngine": "ML",
        "dataType": "Boolean",
        "range": [true, false],
        "defaultValue": true,
        "requiresTraining": true,
        "language": "ALL",
        "isChild": false
    }

코사인 유사도 감소

{
        "configurationName": "Cosine similarity dampening",
        "configurationKeyName": "cosineSimilarityDampening",
        "desc": "Avoid penalty on short length questions using Cosine Similarity Dampening",
        "nlpEngine": "KG",
        "dataType": "Boolean",
        "range": [true, false],
        "defaultValue": true,
        "requiresTraining": false,
        "language": "ALL",
        "isChild": false
    }

네트워크 유형

{
        "configurationName" : "Network Type",
        "configurationKeyName" : "network",
        "desc" : "Networks available for intent training",
        "nlpEngine" : "ML",
        "dataType" : "enum",
        "range" : ["Standard","MLP-BOW","MLP-WordEmbeddings","LSTM","CNN", "KoreBERT"],
        "defaultValue": "Standard",
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : false
    }

에포크(Epoch)

{
        "configurationName": "Epochs",
        "configurationKeyName": "epochs",
        "desc": "Number of iterations in training the model",
        "nlpEngine": "ML",
        "dataType": "Number",
        "range": [20, 300],
        "defaultValue": 20,
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : true,
        "parentConfiguration" : "network",
        "requiredParentInput" : ["MLP-BOW","MLP-WordEmbeddings","LSTM","CNN","KoreBERT"]
    }

배치 크기

{
        "configurationName" : "Batch Size",
        "configurationKeyName" : "batch_size",
        "desc" : "Number of training samples used for each batch while training",
        "nlpEngine" : "ML",
        "dataType" : "Number",
        "range" : [10,30],
        "defaultValue":10,
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : true,
        "parentConfiguration" : "network",
        "requiredParentInput" : ["MLP-BOW","MLP-WordEmbeddings","LSTM","CNN","KoreBERT"]
    }

학습률

{
        "configurationName": "Learning rate",
        "configurationKeyName": "lr",
        "desc": "Learning rate is a hyper-parameter that controls how much we are adjusting the weights of our network with respect to the loss gradient",
        "nlpEngine": "ML",
        "dataType": "enum",
        "range": [1e-4, 1e-3, 1e-2],
        "defaultValue": 1e-3,
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : true,
        "parentConfiguration" : "network",
        "requiredParentInput" : ["MLP-BOW","MLP-WordEmbeddings","LSTM","CNN","KoreBERT"]
    }

Dropout

{
        "configurationName": "Dropout",
        "configurationKeyName": "dropout",
        "desc": "Regularization parameter to avoid overfitting of the model",
        "nlpEngine": "ML",
        "dataType": "Number",
        "range": [0, 0.8],
        "defaultValue": 0,
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : true,
        "parentConfiguration" : "network",
        "requiredParentInput" : ["MLP-BOW","MLP-WordEmbeddings","LSTM","CNN", "KoreBERT"]
    }

벡터화

{
        "configurationName": "Vectorizer",
        "configurationKeyName": "vector_type",
        "desc": "Feature extraction technique on training data",
        "nlpEngine": "ML",
        "dataType": "enum",
        "range": ["count", "tfidf"],
        "defaultValue": "count",
        "requiresTraining": true,
        "language": "ALL",
        "isChild": true,
        "parentConfiguration": "network",
        "requiredParentInput": ["MLP-BOW"]
    }

최대 시퀀스 길이

{
        "configurationName": "Maximum sequence length",
        "configurationKeyName": "max_seq_length",
        "desc": "Length of the training sample or user input",
        "nlpEngine": "ML",
        "dataType": "Number",
        "range": [10, 30],
        "defaultValue": 20,
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : true,
        "parentConfiguration" : "network",
        "requiredParentInput" : ["MLP-WordEmbeddings","LSTM","CNN","KoreBERT"]
    }

임베딩 유형

{
        "configurationName": "Embeddings Type",
        "configurationKeyName": "word_embedding_type",
        "desc": "Feature extraction technique on training data",
        "nlpEngine": "ML",
        "dataType": "enum",
        "range": ["generated", "pretrained", "random"],
        "defaultValue": "random",
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : true,
        "parentConfiguration" : "network",
        "requiredParentInput" : ["MLP-WordEmbeddings","LSTM","CNN", "KoreBERT"]
    }

임베딩 차원

{
        "configurationName": "Embeddings Dimensions",
        "configurationKeyName": "embedding_dim",
        "desc": "Embeddings Dimensions to be used in featurization",
        "nlpEngine": "ML",
        "dataType": "Number",
        "range": [100, 400],
        "defaultValue": 300,
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : true,
        "parentConfiguration" : "network",
        "requiredParentInput" : ["MLP-WordEmbeddings","LSTM","CNN", "KoreBERT"]
    }

K Fold 교차 검증

{
        "configurationName" : "kfold",
        "configurationKeyName" : "kfold",
        "desc" : "kfold parameter for Crossvalidation",
        "nlpEngine" : "ML",
        "dataType" : "Number",
        "range" : [2,10],
        "defaultValue": 5,
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : false
    }

의도 이름으로서의 FAQ 이름

{
        "configurationName": "FAQ Name as Intent Name",
        "configurationKeyName": "FAQ_Name_Intent_Name",
        "desc": "Enable to use FAQ Name as Intent Name. ",
        "nlpEngine": "KG",
        "dataType": "Boolean",
        "range": [true, false],
        "defaultValue": false,
        "requiresTraining" : false,
        "language" : "ALL",
        "isChild" : false
    }

퍼지 매치

{
        "configurationName" : "Fuzzy Match",
        "configurationKeyName" : "fuzzyMatch",
        "desc" : "This setting enables the use of the fuzzy matching algorithm for intent identification",
        "nlpEngine" : "ML",
        "dataType" : "Boolean",
        "range" : [true,false],
        "defaultValue": true,
        "requiresTraining" : false,
        "language" : "ALL",
        "isChild" : false
    }

부정어 처리

{
        "configurationName" : "Handle Negation",
        "configurationKeyName" : "f_negation",
        "desc" : "This setting enables the handling of negated words in intent identification",
        "nlpEngine" : "ML",
        "dataType" : "Boolean",
        "range" : [true,false],
        "defaultValue": true,
        "requiresTraining" : true,
        "language" : ["en", "es"],
        "isChild" : false
    }

다중 발생 무시

{
        "configurationName" : "Ignore Multiple occurences",
        "configurationKeyName" : "binary",
        "desc" : "This setting enables to just use presence or absence of a term instead of the raw counts",
        "nlpEngine" : "ML",
        "dataType" : "Boolean",
        "range" : [true,false],
        "defaultValue": false,
        "requiresTraining" : true,
        "language" : ["en"],
        "isChild" : true,
        "parentConfiguration" : "network",
        "requiredParentInput" : ["MLP-BOW"]
    }

사용자 발화의 엔티티 플레이스홀더

{
        "configurationName": "Test PlaceHolders",
        "configurationKeyName": "TestPlaceHolders",
        "desc": "Enable to replace entity values present in the user input with the corresponding entity placeholders during prediction",
        "nlpEngine": "ML",
        "dataType": "Boolean",
        "range": [true, false],
        "defaultValue": true,
        "requiresTraining": false,
        "language": "ALL",
        "isChild": false
    }

설정 삭제

설정을 삭제하려면 위 섹션에서 언급한 설정 이름을 다음과 같이 사용합니다.

curl --location -g --request POST \
  'https://{{host}}/api/public/bot/{{bot-id}}/configurations?language={{languageCode}}' \
  --header 'auth: YOUR_JWT_ACCESS_TOKEN' \
  --header 'content-type: application/json' \
  --data-raw '{
    "delete": {
        "advancedNLPSettings": [
            "kfold"
        ]
    }
}'

설정 재설정

설정을 재설정하려면 위 섹션에서 언급한 설정 이름을 다음과 같이 사용합니다.

curl --location -g --request POST \
  'https://{{host}}/api/public/bot/{{bot-id}}/configurations?language={{languageCode}}' \
  --header 'auth: YOUR_JWT_ACCESS_TOKEN' \
  --header 'content-type: application/json' \
  --data-raw '{
      "reset": {
         "faq": [
             "pathCoverage",                // Path Coverage
             "suggestionsCount",            // KG suggestionsCount
             "minimumAndDefinitiveLevels",  // Minimum and Definitive Level for Knowledge Tasks (will reset all three values)
             "taskMatchTolerance"           // Proximity of Suggested Matches
        ],
        "ml": [
            "exactMatchThreshold",          // ML Definitive Score 
            "minThreshold"                  // ML threshold 
        ],
        "rr": [
            "taskMatchTolerance",           // Proximity of Probable Matches
            "minMatchVal"                   // Minimum Match Score
        ],
        "mlParams": [
            "ngram",                        // ngram Sequence Length
            "seqLength",                    // Sequence Length
            "maxSkipDistance"               // Maximum Skip Distance
        ]
    }
}'

권한 부여

다음과 같이 헤더에 JWT와 API를 호출합니다. auth: {{JWT}}

콘텐츠 유형 응답

application/json

샘플 요청

curl --location -g --request POST \
  'https://{{host}}/api/public/bot/{{bot-id}}/configurations?language={{languageCode}}' \
  --header 'auth: YOUR_JWT_ACCESS_TOKEN' \
  --header 'content-type: application/json' \
  --data-raw '{
    "advancedNLPSettings": [
        {
            "configurationKeyName": "NoneIntent",
            "configurationValue": true,
            "nlpEngine": "ML"
        }
    ],
    "configurations": [
        {
            "mode": "ml",
            "exactMatchThreshold": 85,
            "useDependencyParser": true,
            "minThreshold": 0.2
        },
        {
            "mode": "faq",
            "useBotSynonyms": true,
            "searchInAnswer": {
                "enabled": true,
                "notifyUser": false,
                "responseType": "relevantWithReadMore",
                "customReadMoreURL": "aa",
                "useCustomReadMoreURL": true
            }
        }
    ],
    "mlParams": {
        "intentParams": {
            "features": "skip_gram",
            "skip_gram": {
                "seqLength": 3,
                "maxSkipDistance": 2
            }
        }
    },
    "nlSettings": {
        "enableAutoUtteranceAddition": false,
        "enableNegativePatterns": true
    }
}'

샘플 응답

[
    {
        "message": "Training Queued.",
        "Training_ID": "5d14b03edba48abcb44375a1"
    }
]

NLP 설정 업데이트

NLP 임곗값 및 설정을 업데이트합니다

이 API를 사용하려면 앱은 NLP 설정의 봇 빌더 API 범위가 필요합니다. 또는 테스트 및 학습에서 NLP 설정의 관리자 API 범위가 필요합니다.

POST https://{{host}}/api/public/bot/{{BotID}}/configurations?language={{languageCode}}&groupName={{groupName}}

쿼리 매개 변수

매개 변수 필수/선택 사항 설명
host 필수 환경 URL(예: https://bots.kore.ai)
BotID 필수 봇 ID 또는 스트림 ID. 봇의 일반 설정 페이지에서 이를 액세스할 수 있습니다.
languageCode 필수 이러한 설정을 업데이트해야 하는 봇 언어입니다.
groupName 다중 ML 모델에 필요 GroupName을 사용하여 특정 그룹의 ML 매개 변수를 업데이트할 수 있습니다. 봇 수준 의도 모델 설정 groupName을 업데이트하려면 그룹 이름을 "봇 수준 의도 모델"로 설정해야 합니다.

본문 매개 변수

매개 변수는 업데이트해야 하는 임곗값 설정에 따라 달라집니다. 다음은 다양한 임곗값 설정에 대한 전체 매개 변수 목록입니다.

설정 업데이트

머신 러닝 엔진

이 섹션에서는 머신 러닝 엔진과 관련된 설정을 다룹니다. 설정에 대한 자세한 내용은 여기를 참조하세요.

{
    "configurations": [
        {
            "mode": "ml",               // Machine Learning Engine
            "exactMatchThreshold": 90,  // ML Definitive Score - value in range [80-100]
            "minThreshold": 0.4,        // ML threshold - value in range [0-1]
        }
    ],
    "mlParams": {
        "intentParams": {
            "useSynonyms": true,       // Bot Synonyms 
            "useStopwords": true,      // Stopwords 
            "usePlaceholders": true,   // Entity Placeholders 
            "features": "n_gram"       // Feature Extraction - value in range [skip_gram, n_gram]
            "skip_gram": {             // features should be 'skip_gram'
                "seqLength": 2,        // Sequence Length - value in range [2-4]
                "maxSkipDistance": 1   // Maximum Skip Distance - value in range [1-3]
              },
            "ngram": 3,                // ngram Sequence Length - value in range [1-4]
                                       // features should be ‘n_gram’
        },
        "nerParams": {
            "type": "corenlp"          // NER Model
                                       // could be "corenlp" for  Conditional Random Field 
                                       //       or "spacy" -  Deep Neural Network
         }
    }
}

Fundamental Meaning Engine

이 섹션에서는 엔진의 기본 의미와 관련된 설정을 다룹니다. 설정에 대한 자세한 내용은 여기를 참조하세요.

{
    "configurations": [
        {
            "mode": "cs",            // Fundamental Meaning Engine
            "labelMatch": true       // Intent Detection using Task Name Words
            "isFMThreshold": true,   //FM Threshold
            "fmThreshold": 15        //FM Threshold value
        }
  ]
}

지식 그래프 엔진

이 섹션에서는 지식 그래프 엔진과 관련된 설정을 다룹니다. 설정에 대한 자세한 내용은 여기를 참조하세요.

{
    "configurations": [ THRESHOLDS & CONFIGURATIONS 
         {
            "mode": "faq",  
            "autoSpellCorrectEnabled": true,             // Auto Correction
            "useBotSynonyms": true,                      // Bot Synonyms
            "enPatternLemma": false,                     // Lemmatization using Parts of Speech
            "pathCoverage": 50,                          // Path Coverage - value in range [0-100]
            "exactMatchThreshold": 95,                   // Minimum and Definitive Level for Knowledge Tasks 
                                                         // value in range [0-100] 
                                                         // should be more than minThreshold & maxThreshold
            "maxThreshold": 80,                          // Probable range for Knowledge Task 
                                                         // value in range [0-100] 
                                                         // should be between minThreshold & exactMatchThreshold 
            "minThreshold": 60,                          // Low confidence range for Knowledge Task 
                                                         // value in range [0-100] 
                                                         // should be less than maxThreshold & exactMatchThreshold  
            "suggestionsCount": 3,                       // KG suggestionsCount | [0-5]
            "taskMatchTolerance": 35,                    // Proximity of Suggested Matches | [0-50]
            "longResponses": {
                "readMore": true,                        // Manage Long Responses
                "useCustomReadMoreURL": true,            // readMore should be true
                "customReadMoreURL": "www.siteurl.com"   // readMore link; readMore should be true
              },
            "searchInAnswer": {
                "enabled": true,                         //  Search in Answer
                "notifyUser": true,                      // Inform end user that it is a probable answer
                "responseType": "relevantWithReadMore",  // can be "complete" - Show complete response, 
                                                         //      or "relevant" - Show only the relevant paragraph,
                                                         //      or "relevantWithReadMore" - Show only the relevant paragraph with “read more” link ]
                "customReadMoreURL": "www.siteurl.com",  // “read more” link 
                "useCustomReadMoreURL": true             // enabled should be true
            }
            "qualifyContextualPaths": false,             // Qualify Contextual Paths
        }
 ]
}

순위 및 해결 엔진

이 섹션에서는 순위 및 해결 엔진과 관련된 설정을 다룹니다. 설정에 대한 자세한 내용은 여기를 참조하세요.

{
    "configurations": 
        {
            "mode": "rr",                 // Ranking and Resolver Engine
            "taskMatchTolerance": 2,      // Proximity of Probable Matches - value in range [0-20]
            "useDependencyParser": true,  // Dependency Parsing Model 
            "minMatchVal": 0.4,           // Minimum Match Score - value in range [0-1] 
                                          // useDependencyParser should be true
            "rankingParameters": ""       //  Advanced Configurations                                           
                                          // useDependencyParser should be true
            "intentRescoring": false,     // Rescoring of Intents
            "isPreferDefinitiveMatch": true // Prefer Definitive Matches
        }
 ]
}

고급 NLP 설정

이 섹션에서는 자연어 -> 학습의 고급 NLP 설정 섹션에 나와 있는 설정을 참조합니다. 설정에 대한 자세한 내용은 여기를 참조하세요. 다음은 위에서 언급한 고급 NLP 구성을 설정하기 위한 샘플 요청입니다.

{
    "advancedNLPSettings":[
        {
            "configurationKeyName": "NoneIntent",
            "configurationValue":true,
            "nlpEngine":"ML"
        }
    ]
}

다음은 허용 가능한 고급 NLP 설정 및 가능한 값의 전체 목록입니다. 복합어 분할

{
        "configurationName": "Split Compound Words",
        "configurationKeyName": "splitCompoundWords",
        "desc": "The settings enables splitting of the compound words into multiple stems and then process the individual stem",
        "nlpEngine": "ML",
        "dataType": "Boolean",
        "range": [true, false],
        "defaultValue": false,
        "requiresTraining": true,
        "language": ["de", "nl"],
        "isChild": false
    }

의도 없음

{
        "configurationName": "None Intent",
        "configurationKeyName": "NoneIntent",
        "desc": "Once enabled, a None intent is created which reduces the chances of getting a false positive for an intent match using ML engine",
        "nlpEngine": "ML",
        "dataType": "Boolean",
        "range": [true, false],
        "defaultValue": true,
        "requiresTraining": true,
        "language": "ALL",
        "isChild": false
    }

코사인 유사도 감소

{
        "configurationName": "Cosine similarity dampening",
        "configurationKeyName": "cosineSimilarityDampening",
        "desc": "Avoid penalty on short length questions using Cosine Similarity Dampening",
        "nlpEngine": "KG",
        "dataType": "Boolean",
        "range": [true, false],
        "defaultValue": true,
        "requiresTraining": false,
        "language": "ALL",
        "isChild": false
    }

네트워크 유형

{
        "configurationName" : "Network Type",
        "configurationKeyName" : "network",
        "desc" : "Networks available for intent training",
        "nlpEngine" : "ML",
        "dataType" : "enum",
        "range" : ["Standard","MLP-BOW","MLP-WordEmbeddings","LSTM","CNN", "KoreBERT"],
        "defaultValue": "Standard",
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : false
    }

에포크(Epoch)

{
        "configurationName": "Epochs",
        "configurationKeyName": "epochs",
        "desc": "Number of iterations in training the model",
        "nlpEngine": "ML",
        "dataType": "Number",
        "range": [20, 300],
        "defaultValue": 20,
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : true,
        "parentConfiguration" : "network",
        "requiredParentInput" : ["MLP-BOW","MLP-WordEmbeddings","LSTM","CNN","KoreBERT"]
    }

배치 크기

{
        "configurationName" : "Batch Size",
        "configurationKeyName" : "batch_size",
        "desc" : "Number of training samples used for each batch while training",
        "nlpEngine" : "ML",
        "dataType" : "Number",
        "range" : [10,30],
        "defaultValue":10,
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : true,
        "parentConfiguration" : "network",
        "requiredParentInput" : ["MLP-BOW","MLP-WordEmbeddings","LSTM","CNN","KoreBERT"]
    }

학습률

{
        "configurationName": "Learning rate",
        "configurationKeyName": "lr",
        "desc": "Learning rate is a hyper-parameter that controls how much we are adjusting the weights of our network with respect to the loss gradient",
        "nlpEngine": "ML",
        "dataType": "enum",
        "range": [1e-4, 1e-3, 1e-2],
        "defaultValue": 1e-3,
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : true,
        "parentConfiguration" : "network",
        "requiredParentInput" : ["MLP-BOW","MLP-WordEmbeddings","LSTM","CNN","KoreBERT"]
    }

Dropout

{
        "configurationName": "Dropout",
        "configurationKeyName": "dropout",
        "desc": "Regularization parameter to avoid overfitting of the model",
        "nlpEngine": "ML",
        "dataType": "Number",
        "range": [0, 0.8],
        "defaultValue": 0,
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : true,
        "parentConfiguration" : "network",
        "requiredParentInput" : ["MLP-BOW","MLP-WordEmbeddings","LSTM","CNN", "KoreBERT"]
    }

벡터화

{
        "configurationName": "Vectorizer",
        "configurationKeyName": "vector_type",
        "desc": "Feature extraction technique on training data",
        "nlpEngine": "ML",
        "dataType": "enum",
        "range": ["count", "tfidf"],
        "defaultValue": "count",
        "requiresTraining": true,
        "language": "ALL",
        "isChild": true,
        "parentConfiguration": "network",
        "requiredParentInput": ["MLP-BOW"]
    }

최대 시퀀스 길이

{
        "configurationName": "Maximum sequence length",
        "configurationKeyName": "max_seq_length",
        "desc": "Length of the training sample or user input",
        "nlpEngine": "ML",
        "dataType": "Number",
        "range": [10, 30],
        "defaultValue": 20,
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : true,
        "parentConfiguration" : "network",
        "requiredParentInput" : ["MLP-WordEmbeddings","LSTM","CNN","KoreBERT"]
    }

임베딩 유형

{
        "configurationName": "Embeddings Type",
        "configurationKeyName": "word_embedding_type",
        "desc": "Feature extraction technique on training data",
        "nlpEngine": "ML",
        "dataType": "enum",
        "range": ["generated", "pretrained", "random"],
        "defaultValue": "random",
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : true,
        "parentConfiguration" : "network",
        "requiredParentInput" : ["MLP-WordEmbeddings","LSTM","CNN", "KoreBERT"]
    }

임베딩 차원

{
        "configurationName": "Embeddings Dimensions",
        "configurationKeyName": "embedding_dim",
        "desc": "Embeddings Dimensions to be used in featurization",
        "nlpEngine": "ML",
        "dataType": "Number",
        "range": [100, 400],
        "defaultValue": 300,
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : true,
        "parentConfiguration" : "network",
        "requiredParentInput" : ["MLP-WordEmbeddings","LSTM","CNN", "KoreBERT"]
    }

K Fold 교차 검증

{
        "configurationName" : "kfold",
        "configurationKeyName" : "kfold",
        "desc" : "kfold parameter for Crossvalidation",
        "nlpEngine" : "ML",
        "dataType" : "Number",
        "range" : [2,10],
        "defaultValue": 5,
        "requiresTraining" : true,
        "language" : "ALL",
        "isChild" : false
    }

의도 이름으로서의 FAQ 이름

{
        "configurationName": "FAQ Name as Intent Name",
        "configurationKeyName": "FAQ_Name_Intent_Name",
        "desc": "Enable to use FAQ Name as Intent Name. ",
        "nlpEngine": "KG",
        "dataType": "Boolean",
        "range": [true, false],
        "defaultValue": false,
        "requiresTraining" : false,
        "language" : "ALL",
        "isChild" : false
    }

퍼지 매치

{
        "configurationName" : "Fuzzy Match",
        "configurationKeyName" : "fuzzyMatch",
        "desc" : "This setting enables the use of the fuzzy matching algorithm for intent identification",
        "nlpEngine" : "ML",
        "dataType" : "Boolean",
        "range" : [true,false],
        "defaultValue": true,
        "requiresTraining" : false,
        "language" : "ALL",
        "isChild" : false
    }

부정어 처리

{
        "configurationName" : "Handle Negation",
        "configurationKeyName" : "f_negation",
        "desc" : "This setting enables the handling of negated words in intent identification",
        "nlpEngine" : "ML",
        "dataType" : "Boolean",
        "range" : [true,false],
        "defaultValue": true,
        "requiresTraining" : true,
        "language" : ["en", "es"],
        "isChild" : false
    }

다중 발생 무시

{
        "configurationName" : "Ignore Multiple occurences",
        "configurationKeyName" : "binary",
        "desc" : "This setting enables to just use presence or absence of a term instead of the raw counts",
        "nlpEngine" : "ML",
        "dataType" : "Boolean",
        "range" : [true,false],
        "defaultValue": false,
        "requiresTraining" : true,
        "language" : ["en"],
        "isChild" : true,
        "parentConfiguration" : "network",
        "requiredParentInput" : ["MLP-BOW"]
    }

사용자 발화의 엔티티 플레이스홀더

{
        "configurationName": "Test PlaceHolders",
        "configurationKeyName": "TestPlaceHolders",
        "desc": "Enable to replace entity values present in the user input with the corresponding entity placeholders during prediction",
        "nlpEngine": "ML",
        "dataType": "Boolean",
        "range": [true, false],
        "defaultValue": true,
        "requiresTraining": false,
        "language": "ALL",
        "isChild": false
    }

설정 삭제

설정을 삭제하려면 위 섹션에서 언급한 설정 이름을 다음과 같이 사용합니다.

curl --location -g --request POST \
  'https://{{host}}/api/public/bot/{{bot-id}}/configurations?language={{languageCode}}' \
  --header 'auth: YOUR_JWT_ACCESS_TOKEN' \
  --header 'content-type: application/json' \
  --data-raw '{
    "delete": {
        "advancedNLPSettings": [
            "kfold"
        ]
    }
}'

설정 재설정

설정을 재설정하려면 위 섹션에서 언급한 설정 이름을 다음과 같이 사용합니다.

curl --location -g --request POST \
  'https://{{host}}/api/public/bot/{{bot-id}}/configurations?language={{languageCode}}' \
  --header 'auth: YOUR_JWT_ACCESS_TOKEN' \
  --header 'content-type: application/json' \
  --data-raw '{
      "reset": {
         "faq": [
             "pathCoverage",                // Path Coverage
             "suggestionsCount",            // KG suggestionsCount
             "minimumAndDefinitiveLevels",  // Minimum and Definitive Level for Knowledge Tasks (will reset all three values)
             "taskMatchTolerance"           // Proximity of Suggested Matches
        ],
        "ml": [
            "exactMatchThreshold",          // ML Definitive Score 
            "minThreshold"                  // ML threshold 
        ],
        "rr": [
            "taskMatchTolerance",           // Proximity of Probable Matches
            "minMatchVal"                   // Minimum Match Score
        ],
        "mlParams": [
            "ngram",                        // ngram Sequence Length
            "seqLength",                    // Sequence Length
            "maxSkipDistance"               // Maximum Skip Distance
        ]
    }
}'

권한 부여

다음과 같이 헤더에 JWT와 API를 호출합니다. auth: {{JWT}}

콘텐츠 유형 응답

application/json

샘플 요청

curl --location -g --request POST \
  'https://{{host}}/api/public/bot/{{bot-id}}/configurations?language={{languageCode}}' \
  --header 'auth: YOUR_JWT_ACCESS_TOKEN' \
  --header 'content-type: application/json' \
  --data-raw '{
    "advancedNLPSettings": [
        {
            "configurationKeyName": "NoneIntent",
            "configurationValue": true,
            "nlpEngine": "ML"
        }
    ],
    "configurations": [
        {
            "mode": "ml",
            "exactMatchThreshold": 85,
            "useDependencyParser": true,
            "minThreshold": 0.2
        },
        {
            "mode": "faq",
            "useBotSynonyms": true,
            "searchInAnswer": {
                "enabled": true,
                "notifyUser": false,
                "responseType": "relevantWithReadMore",
                "customReadMoreURL": "aa",
                "useCustomReadMoreURL": true
            }
        }
    ],
    "mlParams": {
        "intentParams": {
            "features": "skip_gram",
            "skip_gram": {
                "seqLength": 3,
                "maxSkipDistance": 2
            }
        }
    },
    "nlSettings": {
        "enableAutoUtteranceAddition": false,
        "enableNegativePatterns": true
    }
}'

샘플 응답

[
    {
        "message": "Training Queued.",
        "Training_ID": "5d14b03edba48abcb44375a1"
    }
]
메뉴