시작
Kore.ai 대화형 플랫폼
챗봇 개요
자연어 처리(NLP)
봇 개념 및 용어들
빠른 시작 가이드
봇 빌더 접근 방법
사용 고지 사항 (영어)
Kore.ai 봇 빌더로 작업하기
봇 구축 시작하기
릴리스 정보
현재 버전 (영어)
이전 버전 (영어)

개념
디자인
스토리보드
대화 작업
개요
Using the Dialog Builder Tool
노드 유형
사용자 의도 노드
대화 노드
엔티티 노드
양식 노드
확인 노드
서비스 노드
봇 조치 노드
Service Node
WebHook 노드
스크립트 노드
노드 그룹화하기
Agent Transfer Node
사용자 프롬프트
음성 통화 속성
대화 관리
노드 및 전환
구성 요소 전환
컨텍스트 개체
이벤트 기반 봇 조치
지식 그래프
소개
지식 추출
지식 그래프 생성
봇에 지식 그래프 추가
그래프 생성
지식 그래프 작성
FAQ 추가
작업 실행
기존 소스에서 FAQ 구축
특성, 동의어 및 불용어
변수 네임스페이스 관리
수정
용어 편집 및 삭제
용어 편집 및 삭제
질문과 응답 편집
Knowledge Graph Training
지식 그래프 분석
봇 온톨로지 가져오기 및 내보내기
지식 그래프 가져오기
지식 그래프 내보내기
지식 그래프 생성
CSV 파일에서
JSON 파일
지식 그래프 생성
경고 작업
스몰 토크
Digital Skills
디지털 양식
Views
Digital Views
Panels
Widgets
기차
봇 성능 향상 – NLP 최적화
기계 학습
소개
모델 검증
기초 의미
지식 그래프 학습
특성
순위 및 해결
고급 NLP 설정
NLP 설정 및 지침
봇 인텔리전스
소개
컨텍스트 관리
컨텍스트 관리
대화 관리
다중 – 의도 탐지
엔티티 수정
기본 대화
정서 관리
어조 분석
Test & Debug
봇과 대화
발화 테스트
배치 테스트하기
대화 테스트
배포
채널 활성화
봇 게시
분석
봇 분석하기
Conversations Dashboard
Performance Dashboard
사용자 정의 대시보드
소개
맞춤형 메타 태그
사용자 정의 대시보드 생성 방법
Conversation Flows
NLP 지표
Containment Metrics
사용량 지표
스마트 봇
소개
범용 봇
소개
범용 봇 정의
범용 봇 생성
범용 봇 학습
범용 봇 커스터마이징
범용 봇용 추가 언어 활성화
스토어
Manage Assistant
플랜 및 사용량
Overview
Usage Plans
Support Plans
플랜 관리
봇 인증
다국어 봇
개인 식별 정보 삭제하기
봇 변수 사용
IVR 통합
일반 설정
봇 관리

방법
간단한 봇 생성하기
Design Conversation Skills
뱅킹 봇 생성
뱅킹 봇 – 자금 이체
뱅킹 봇 – 잔액 업데이트
Knowledge Graph (KG) 구축
스마트 경고를 예약하는 방법
Design Digital Skills
디지털 양식 설정 방법
디지털 보기 설정 방법
데이터 테이블에 데이터를 추가하는 방법
데이터 테이블 내 데이터 업데이트 방법
UI 양식에서 데이터 테이블에 데이터를 추가하는 방법
Train the Assistant
특성 사용 방법
의도와 엔티티에 대한 패턴 사용 방법
컨텍스트 전환 관리 방법
Deploy the Assistant
상담사 전환을 설정하는 방법
봇 기능 사용 방법
콘텐츠 변수 사용 방법
전역 변수 사용 방법
Kore.ai 웹 SDK 튜토리얼
Kore.ai 위젯 SDK 튜토리얼
Analyze the Assistant
사용자 정의 대시보드 생성 방법
사용자 지정 태그를 사용하여 봇 메트릭을 필터링하는 방법

API 및 SDK
API 참조
Kore.ai API 사용
API 목록
API 컬렉션
koreUtil Libraries
SDK 참조
상담사 전환을 설정하는 방법
봇 기능 사용 방법
콘텐츠 변수 사용 방법
전역 변수 사용 방법
소개
Kore.ai 웹 SDK 튜토리얼
Kore.ai 위젯 SDK 튜토리얼

관리
소개
봇 관리자 콘솔
대시보드
사용자 관리
사용자 관리
그룹 관리
역할 관리
봇 관리 모듈
등록
사용자 초대
사용자 등록을 위한 대량 초대 보내기
사용자 및 사용자 데이터 가져오기
Active Directory에서 사용자 동기화
보안 및 준수
싱글 사인 온 사용
보안 설정
Kore.ai 커넥터
봇 관리자용 분석
Billing (지원하지 않음)
  1. Docs
  2. Virtual Assistants
  3. Natural Language
  4. LLM and Generative AI
  5. Introduction to LLM and Generative AI

Introduction to LLM and Generative AI

The Kore.ai XO Platform helps enhance your bot development process and enrich end-user conversational experiences by integrating pre-built (OpenAI, Azure OpenAI, Anthropic) or custom models in the backend.

In addition to the out-of-box integration with pre-built models, the Platform supports the bring-your-own (BYO) model framework to integrate with externally hosted models by third parties as well as models hosted by the enterprises themselves. The framework allows the creation of custom prompts that are optimized for specific purposes and models. This generic framework works seamlessly with the Auth Profiles module of the Platform, enabling enterprises to use the authentication mechanism of their choice.

The new Kore.ai XO GPT Models module provides fine-tuned large language models optimized for enterprise conversational AI applications. These models have been evaluated and fine-tuned to be accurate, safe, and efficient for production deployment. For more information, see Kore.ai XO GPT.

By leveraging LLM and Generative AI capabilities, you can create intelligent, human-like conversational experiences for your end-users.

You can find Generative AI and LLM features by going to Build > Natural Language > Generative AI & LLM.

Key Features

The Integration of Generative AI and LLM enables the following features:

  • Prompts & Requests Library: Complete flexibility to create fully customized prompts optimized for particular use cases using custom models.
  • Co-Pilot features:
    • Automatic Dialog Generation: This feature helps build production-ready dialog tasks automatically by briefly describing the task. A preview of the generated dialog is available and lets you modify the intent description and create multiple iterations of the dialog.
    • Conversation Test Cases Suggestion: The Platform suggests simulated user inputs covering various scenarios from an end-user perspective at every test step. You can use these suggestions to create test suites.
    • Conversation Summary: Implements the Conversation Summary public API to fetch the details of the entire conversation between the customer and the VA or agent. This API leverages the Flan-T5 foundational model to summarize conversations.
    • NLP Batch Test Cases Suggestion: The Platform generates NLP test cases for every intent, including entity checks. You only need to create test suites in the Builder using the generated testing utterances.
    • Training Utterance Suggestions: Generate high-quality training data quickly and easily with our platform’s suggested utterances for each intent. Review and add the suggestions as needed to create a powerful training set for your bot.
    • Use Case Suggestions: Uses the Open AI LLM model to generate use cases during the VA (Bot) creation journey.
  • Dynamic Conversations features:
    • GenAI Node: Collect Entities from end-users in a free-flowing conversation using LLM and Generative AI in the background. You can define entities to be collected as well as rules & scenarios.
    • Answer from Documents: Helps answer end-user queries from unstructured PDF documents without the need to extract individual FAQs and train them.
    • GenAI Prompt: Leverage this node to unlock the power of Generative AI with your prompts, enabling you to build creative and custom use cases.
    • Rephrase Dialog Responses: Enhance end-user experience with empathetic and contextual bot responses.
    • Zero-shot ML Model: Uses the Open AI LLM model for intent identification during run time based on semantic similarity.
    • Repeat Responses: Use LLM to reiterate the last bot responses when the Repeat Bot Response event is triggered.
    • Rephrase User Query: Improve intent detection and entity extraction by enriching the user query with relevant details from the ongoing conversation context.
    • Few-shot ML Model: Uses the Kore Ai’s hosted embeddings for intent identification during run time based on semantic similarity.

Benefits

All these features benefit VA developers, NLP developers, and testers as follows:

  • Being able to select among Kore.ai XO GPT or custom or pre-built LLM integrations.
  • Developers can create dialog tasks on the fly through the prebuilt Dialog Tasks Flow.
  • Developers can unlock the power of Generative AI with their prompts, enabling them to build creative and custom use cases.
  • Mundane tasks like generating dialog tasks or training utterances are automated to help developers be more productive and focus on other important tasks like enhancing conversation design, creating complex test cases, and more.
  • Testers can ensure that their intent descriptions are meaningful in the right context to generate the right content.
  • The Platform provides suggestions and nudges developers in the right direction for the better design and development of Virtual Assistants. For example, it offers curated use case suggestions while creating the VA, including probable user inputs (simulating end-user behavior) in Conversation Testing. This way, the VA can simulate the end user’s behavior at every conversation step and respond more realistically by considering error scenarios, digressions, and contextual changes.
  • Allows enterprises and advanced users to bypass the platform’s pre-built integrations. They can establish customized connections to large language models and optimize prompts and requests for their specific use cases.

Important Considerations

Generative AI features are available for English and non-English NLU and VA languages on the Kore.ai XO Platform. However, custom LLM-specific features are currently limited to English. To learn more about managing languages for VAs, click here.

LLM and Generative AI also require sharing data with third parties: OpenAI (when using the OpenAI integration) or OpenAI and Microsoft (when using the Azure integration).

Next Steps

  1. Integrate a pre-built or custom or Kore.ai XO GPT LLM
  2. (Optional – only for custom LLM model) Add Prompts.
  3. Enable Co-Pilot and Dynamic Conversations features.

Introduction to LLM and Generative AI

The Kore.ai XO Platform helps enhance your bot development process and enrich end-user conversational experiences by integrating pre-built (OpenAI, Azure OpenAI, Anthropic) or custom models in the backend.

In addition to the out-of-box integration with pre-built models, the Platform supports the bring-your-own (BYO) model framework to integrate with externally hosted models by third parties as well as models hosted by the enterprises themselves. The framework allows the creation of custom prompts that are optimized for specific purposes and models. This generic framework works seamlessly with the Auth Profiles module of the Platform, enabling enterprises to use the authentication mechanism of their choice.

The new Kore.ai XO GPT Models module provides fine-tuned large language models optimized for enterprise conversational AI applications. These models have been evaluated and fine-tuned to be accurate, safe, and efficient for production deployment. For more information, see Kore.ai XO GPT.

By leveraging LLM and Generative AI capabilities, you can create intelligent, human-like conversational experiences for your end-users.

You can find Generative AI and LLM features by going to Build > Natural Language > Generative AI & LLM.

Key Features

The Integration of Generative AI and LLM enables the following features:

  • Prompts & Requests Library: Complete flexibility to create fully customized prompts optimized for particular use cases using custom models.
  • Co-Pilot features:
    • Automatic Dialog Generation: This feature helps build production-ready dialog tasks automatically by briefly describing the task. A preview of the generated dialog is available and lets you modify the intent description and create multiple iterations of the dialog.
    • Conversation Test Cases Suggestion: The Platform suggests simulated user inputs covering various scenarios from an end-user perspective at every test step. You can use these suggestions to create test suites.
    • Conversation Summary: Implements the Conversation Summary public API to fetch the details of the entire conversation between the customer and the VA or agent. This API leverages the Flan-T5 foundational model to summarize conversations.
    • NLP Batch Test Cases Suggestion: The Platform generates NLP test cases for every intent, including entity checks. You only need to create test suites in the Builder using the generated testing utterances.
    • Training Utterance Suggestions: Generate high-quality training data quickly and easily with our platform’s suggested utterances for each intent. Review and add the suggestions as needed to create a powerful training set for your bot.
    • Use Case Suggestions: Uses the Open AI LLM model to generate use cases during the VA (Bot) creation journey.
  • Dynamic Conversations features:
    • GenAI Node: Collect Entities from end-users in a free-flowing conversation using LLM and Generative AI in the background. You can define entities to be collected as well as rules & scenarios.
    • Answer from Documents: Helps answer end-user queries from unstructured PDF documents without the need to extract individual FAQs and train them.
    • GenAI Prompt: Leverage this node to unlock the power of Generative AI with your prompts, enabling you to build creative and custom use cases.
    • Rephrase Dialog Responses: Enhance end-user experience with empathetic and contextual bot responses.
    • Zero-shot ML Model: Uses the Open AI LLM model for intent identification during run time based on semantic similarity.
    • Repeat Responses: Use LLM to reiterate the last bot responses when the Repeat Bot Response event is triggered.
    • Rephrase User Query: Improve intent detection and entity extraction by enriching the user query with relevant details from the ongoing conversation context.
    • Few-shot ML Model: Uses the Kore Ai’s hosted embeddings for intent identification during run time based on semantic similarity.

Benefits

All these features benefit VA developers, NLP developers, and testers as follows:

  • Being able to select among Kore.ai XO GPT or custom or pre-built LLM integrations.
  • Developers can create dialog tasks on the fly through the prebuilt Dialog Tasks Flow.
  • Developers can unlock the power of Generative AI with their prompts, enabling them to build creative and custom use cases.
  • Mundane tasks like generating dialog tasks or training utterances are automated to help developers be more productive and focus on other important tasks like enhancing conversation design, creating complex test cases, and more.
  • Testers can ensure that their intent descriptions are meaningful in the right context to generate the right content.
  • The Platform provides suggestions and nudges developers in the right direction for the better design and development of Virtual Assistants. For example, it offers curated use case suggestions while creating the VA, including probable user inputs (simulating end-user behavior) in Conversation Testing. This way, the VA can simulate the end user’s behavior at every conversation step and respond more realistically by considering error scenarios, digressions, and contextual changes.
  • Allows enterprises and advanced users to bypass the platform’s pre-built integrations. They can establish customized connections to large language models and optimize prompts and requests for their specific use cases.

Important Considerations

Generative AI features are available for English and non-English NLU and VA languages on the Kore.ai XO Platform. However, custom LLM-specific features are currently limited to English. To learn more about managing languages for VAs, click here.

LLM and Generative AI also require sharing data with third parties: OpenAI (when using the OpenAI integration) or OpenAI and Microsoft (when using the Azure integration).

Next Steps

  1. Integrate a pre-built or custom or Kore.ai XO GPT LLM
  2. (Optional – only for custom LLM model) Add Prompts.
  3. Enable Co-Pilot and Dynamic Conversations features.
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