OpenDialog Docs
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  • GETTING STARTED
    • Introduction
    • Getting ready
    • Billing and plans
    • Quick Start AI Agents
      • Quick Start AI Agent
      • The "Start from Scratch" AI Agent
        • Chat Management Conversation
        • Welcome Conversation
        • Topic Conversation
        • Global No Match Conversation
        • Supporting LLM Actions
        • Semantic Classifier: Query Classifier
      • A Process Handling AI Agent
  • STEP BY STEP GUIDES
    • AI Agent Creation Overview
    • Add a new topic of discussion
    • Use knowledge sources via RAG
    • Adding a structured conversation
    • Add a 3rd party integration
    • Test and tweak your AI Agent
    • Publish your AI Agent
  • CORE CONCEPTS
    • OpenDialog Approach
      • Designing Conversational AI Agents
    • OpenDialog Platform
      • Scenarios
        • Conversations
        • Scenes
        • Turns and intents
      • Language Services
      • OpenDialog Account Management
        • Creating and managing users
        • Deleting OpenDialog account
        • Account Security
    • OpenDialog Conversation Engine
    • Contexts and attributes
      • Contexts
      • Attributes
      • Attribute Management
      • Conditions and operators
      • Composite Attributes
  • CREATE AI APPLICATIONS
    • Designing your application
      • Conversation Design
        • Conversational Patterns
          • Introduction to conversational patterns
          • Building robust assistants
            • Contextual help
            • Restart
            • End chat
            • Contextual and Global No Match
            • Contextual FAQ
          • Openings
            • Anatomy of an opening
            • Transactional openings
            • Additional information
          • Authentication
            • Components
            • Example dialog
            • Using in OpenDialog
          • Information collection
            • Components
            • Example dialog
            • Using in OpenDialog
            • Additional information
          • Recommendations
            • Components
            • Example dialog
            • Additional information
          • Extended telling
            • Components
            • Example dialog
            • Additional information
          • Repair
            • Types of repair
            • User request not understood
            • Example dialog
            • Additional information
          • Transfer
            • Components
            • Example dialog
            • Additional information
          • Closing
            • Components
            • Example dialog
            • Using in OpenDialog
            • Additional information
        • Best practices
          • Use Case
          • Subject Matter Expertise
          • Business Goals
          • User needs
            • Primary research
            • Secondary research
            • Outcome: user profile
          • Assistant personality
          • Sample dialogs
          • Conversation structure
          • API Integration Capabilities
          • NLU modeling
          • Testing strategy
          • The team
            • What does a conversation designer do
          • Select resources
      • Message Design
        • Message editor
        • Constructing Messages
        • Message Conditions
        • Messages best practices
        • Subsequent Messages - Virtual Intents
        • Using Attributes in Messages
        • Using Markdown in messages
        • Message Types
          • Text Message
          • Image Message
          • Button Message
          • Date Picker Message
          • Audio Message
          • Form Message
          • Full Page Message
          • Conversation Handover message
          • Autocomplete Message
          • Address Autocomplete Message
          • List Message
          • Rich Message
          • Location Message
          • E-Sign Message
          • File Upload Message
          • Meta Messages
            • Progress Bar Message
          • Attribute Message
      • Webchat Interface design
        • Webchat Interface Settings
        • Webchat Controls
      • Accessibility
      • Inclusive design
    • Leveraging Generative AI
      • Language Services
        • Semantic Intent Classifier
          • OpenAI
          • Azure
          • Google Gemini
          • Output attributes
        • Retrieval Augmented Generation
        • Example-based intent classification [Deprecated]
      • Interpreters
        • Available interpreters
          • OpenDialog interpreter
          • Amazon Lex interpreter
          • Google Dialogflow
            • Google Dialogflow interpreter
            • Google Dialogflow Knowledge Base
          • OpenAI interpreter
        • Using a language service interpreter
        • Interpreter Orchestration
        • Troubleshooting interpreters
      • LLM Actions
        • OpenAI
        • Azure OpenAI
        • Output attributes
        • Using conversation history (memory) in LLM actions
        • LLM Action Analytics
    • 3rd party Integrations in your application
      • Webhook actions
      • Actions from library
        • Freshdesk Action
        • Send to Email Action
        • Set Attributes Action
      • Conversation Hand-off
        • Chatwoot
    • Previewing your application
    • Launching your application
    • Monitoring your application
    • Debugging your application
    • Translating your application
    • FAQ
    • Troubleshooting and Common Problems
  • Developing With OpenDialog
    • Integrating with OpenDialog
    • Actions
      • Webhook actions
      • LLM actions
    • WebChat
      • Chat API
      • WebChat authentication
      • User Tracking
      • Load Webchat within page Element
      • How to enable JavaScript in your browser
      • SDK
        • Methods
        • Events
        • Custom Components
    • External APIs
  • Release Notes
    • Version 3 Upgrade Guide
    • Release Notes
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On this page
  • What is a Language Service?
  • When to use a language service
  • Types of language services
  • Semantic Intent Classifier
  • RAG Service
  • Intent classification
  • Where to find
  • How to use
  1. CORE CONCEPTS
  2. OpenDialog Platform

Language Services

What is a Language Service?

To interpret an end user's input, your conversational application needs to be equipped with Natural Language Processing (NLP) capabilities. OpenDialog's language services allow you to set up this capability directly in the OpenDialog interface.

When to use a language service

By creating a Language Service in OpenDialog, you gain the convenience of managing your language model within a single interface. This model can then be used across various scenarios in OpenDialog, making your development process more efficient.

Types of language services

OpenDialog is tailored to three types of Language Services: Semantic Intent Classifier, RAG Service (for retrieval augmented generation), and Intent Classification, all of which are powered by an LLM (Large Language Model).

Semantic Intent Classifier

A Semantic Intent Classifier allows you to create intents and sub-intents with instructions that optimise how an LLM is prompted. This will allow the application to make more informed choices when selecting intents within a conversation, and provide more accurate responses to customers.

A Semantic Intent Classifier also allows you to define additional prompt informationhould act and behave in response to user queries. You can use the prompt to provide the LLM with background information such as the role it needs to play, essential business information that could be key to answering a query, or specific criteria that must be met within an Intent/sub intent to ensure the handoff to another conversation meets the requirements of a customers query.

RAG Service

You can also add a knowledge service to your OpenDialog scenarios. This feature enables you to define topics you want to make available for your users to converse with and add related text sources to each topic. This type of knowledge service (underpinned by an LLM) will allow your application to generate relevant responses to your users based on the provided text sources.

Intent classification

Using our intent classification service, you will define intents and entities to then utilize them in your scenarios through an Interpreter. This will allow your application to categorize incoming user input into separate intents and extract any mentioned entities.

For example : "When are you open until", "When do you close" = OpeningHoursIntent

Where to find

  • Log into your OpenDialog account

  • You will access your workspace and immediately see the workspace dashboard

  • From there, click on `Create/Manage language services' in the central panel to access the language services section of the platform

  • You can also access Language Services from the main menu on the left when you are viewing your workspace dashboard

  • You are now in the Language Services section of OpenDialog 🙌

How to use

Read more about our different language services and how to use them:

PreviousTurns and intentsNextOpenDialog Account Management

Last updated 8 months ago

You can access the language services section of the platform directly from the .

Workspace Dashboard
Access the language services section from the Workspace Dashboard
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Add a language service to your scenario to interpret what end-users input into your conversational application.

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Learn how to use OpenDialog's language services to create custom ready-to-use language capabilities

Using language services
Leveraging Generative AI