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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
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      • 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
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          • Authentication
            • Components
            • Example dialog
            • Using in OpenDialog
          • Information collection
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            • Example dialog
            • Using in OpenDialog
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            • Example dialog
            • Additional information
          • Extended telling
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            • Example dialog
            • Additional information
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          • Transfer
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            • Example dialog
            • Additional information
          • Closing
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            • Example dialog
            • Using in OpenDialog
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        • Best practices
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          • Assistant personality
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          • Conversation structure
          • API Integration Capabilities
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          • 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
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          • Text Message
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          • Meta Messages
            • Progress Bar Message
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      • Webchat Interface design
        • Webchat Interface Settings
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      • Accessibility
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    • 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
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        • Freshdesk Action
        • Send to Email Action
        • Set Attributes Action
      • Conversation Hand-off
        • Chatwoot
    • Previewing your application
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    • FAQ
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  • 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
  • No Match Response Generation
  • Agent Capability Response
  • Topic Generation Response
  • Statement Responses
  • Feedback Responses
  • Customise welcome message
  • Casual Conversation Response
  1. GETTING STARTED
  2. Quick Start AI Agents
  3. The "Start from Scratch" AI Agent

Supporting LLM Actions

The LLM Actions used by the "Start from Scratch" scenario

PreviousGlobal No Match ConversationNextSemantic Classifier: Query Classifier

Last updated 6 months ago

To support fluid conversation exchange the "Start from Scratch" scenario uses a number of LLM Actions that can form a solid basis / template for your own LLM Actions.

No Match Response Generation

This action is attached to the NoMatchResponse APP intent in the Global No Match conversation and provides an appropriate response to explain to the user that we were not able to classify and hence respond to their phrase.

Crucially, since we were not able to classify the user phrase we do not send it to the underlying LLM to provide a further level of safety.

Agent Capability Response

The Agent Capability response action is attached to the AboutTheBotResposne APP intent and generates an answer to questions around what the bot can do.

Topic Generation Response

The Topic Generation Response action is the most often used on and it is attached to all the intents that are broad topics (which would be using a specific knowledge source).

Please make sure to update this action with any specific topic sources you want to use.

Statement Responses

This LLM Action generates a context response to statements based on whether the statements are relevant or not to the topic of the conversation.

Feedback Responses

Similarly to Statement Responses this LLM action generates Feedback responses based on the type of feedback and whether it was positive or negative.

Customise welcome message

By default the welcome message is static - but you can use this LLM action as your starting point to create dynamic welcome messages that take into account topic and user attributes.

Casual Conversation Response

Finally the Casual Conversation Response action generates an appropriate response to casual conversation statements such as greetings, simpler jokes and other small talk.

LLM Actions of the "Start from Scratch" scenario