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Overview

Test the conversation flow with predefined interactions where you send specific user utterances to your agent and validate exact responses.

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Reference

A traditional test is a YAML file with the following structure: 
# test.yaml

# Name of the test.
name: Example test
# Brief description of the test.
description: These are some tests

# A interactions is the test itself: given an input, you will validate the agent response returned by Voiceflow
# You can have multiple interactions defined
interactions:
  # The ID of the interactions
  - id: test_1
    user:
      # the input type
      # it could be text, audio or prompt
      type: text
      # The input itself in text format. For type: audio, you have to specify the audio file.
      text: I want 3 pizzas
    agent:
      validate:
        # String validation to check if the response returned by Voiceflow is correct
        - type: contains
          value: pizza

  - id: test_2
    user: 
      type: text
      text: hi
    agent:
      # example with a traceType validation
      validate:
        - type: traceType
          value: speak

  - id: test_3
    user: 
      type: text
      audio: hello
    agent:
      # example with a regexp validation
      validate:
        - type: regexp
          value: '/my-regex/'

  - id: test_4
    user: 
      type: text
      audio: hello
    agent:
      # example with a similarity validation
      validate:
        - type: similarity
          similarityConfig:
            provider: 'openai'
            model: 'gpt-4o'
            temperature: 0.8
            top_k: 5
            top_p: 0.9
            similarityThreshold: 0.5
          values:
            - 'hi'
            - 'Hello'

  - id: test_5
    user: 
      type: text
      text: 'myVariableValue1'
    agent:
      # example with a variable validation
      validate:
        - type: variable
          value: 'myVariableValue1'
          variableConfig:
            name: 'variableName1'

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Input types


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Text input

The input text is the simplest one. You just have to specify the text you want to send to Voiceflow. Make sure that the text is in the language you specified in the localeId field. to use this type you have to set the type field to text and the text field to the text you want to send. 
user:
  type: text
  text: I want 3 pizzas

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Launch input

The launch input is used to start a new conversation session. This is typically the first interaction in a test. To use this type you have to set the type field to launch. 
user:
  type: launch

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Event input

The event input allows you to send custom events to your Voiceflow agent. Events can be used to trigger specific flows or actions in your agent. To use this type you have to set the type field to event and the event field to the event name you want to send. 
user:
  type: event
  event: user_logged_in
Example with validation: 
- id: event_example
  user:
    type: event
    event: user_logged_in
  agent:
    validate:
      - type: contains
        value: "Welcome back!"

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Intent input

The intent input allows you to directly send an intent to your Voiceflow agent, bypassing NLU processing. This is useful when you have your own NLU matching or want to test specific intent handling. To use this type you have to set the type field to intent and provide an intent object with the intent name and optional entities. 
user:
  type: intent
  intent:
    name: order_pizza
    entities:
      - name: pizza_type
        value: pepperoni
      - name: size
        value: large
The intent object accepts the following properties:
  • name: (Required) The name of the intent to trigger
  • entities: (Optional) An array of entity objects with name and value fields
Examples: 
# Intent with entities
- id: intent_with_entities
  user:
    type: intent
    intent:
      name: order_pizza
      entities:
        - name: pizza_type
          value: pepperoni
        - name: size
          value: large
  agent:
    validate:
      - type: contains
        value: "one large pepperoni pizza"

# Intent without entities
- id: intent_no_entities
  user:
    type: intent
    intent:
      name: get_help
  agent:
    validate:
      - type: contains
        value: "How can I help you?"

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Button input

The button input allows you to simulate clicking a button that was presented in a previous choice/button response from your Voiceflow agent. This is useful for testing conversational flows that include button interactions. To use this type you have to set the type field to button and the value field to the button label you want to click. 
user:
  type: button
  value: Yes, continue
The button interaction automatically:
  • Finds the matching button from the previous choice trace by its label
  • Sends the complete button request (including path type and payload) back to Voiceflow
  • Handles the button click as if a user clicked it in a real conversation
Important: A button interaction must follow an interaction that returned a choice trace type with buttons. The value must match the label field in one of the button’s payload. Example workflow: 
# First interaction receives a choice with buttons
- id: show_options
  user:
    type: text
    text: "Show me options"
  agent:
    validate:
      - type: traceType
        value: choice

# Second interaction clicks one of the buttons
- id: select_option
  user:
    type: button
    value: "Yes, continue"  # Must match button label
  agent:
    validate:
      - type: contains
        value: "Great! Continuing..."
Complete example: 
name: Button Interaction Example
description: Test demonstrating button click simulation

interactions:
  - id: launch_conversation
    user:
      type: launch
    agent:
      validate:
        - type: contains
          value: "Welcome"
        - type: traceType
          value: choice
  
  - id: click_yes_button
    user:
      type: button
      value: "Yes"  # Clicks the button with label "Yes"
    agent:
      validate:
        - type: contains
          value: "You selected yes"

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Validation types

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Contains

The contains validation type is the simplest one. It just checks if the response returned by the Voiceflow agent contains the value specified in the value field. To use this type you have to set the type field to contains and the value field to the value you want to check: 
validate:
  # String validation to check if the response returned by Voiceflow is correct
  - type: contains
    value: pizza

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Equals

The equals validation type is a little bit more complex. It checks if the response returned by the Voiceflow agent is equal to the value specified in the value field. To use this type you have to set the type field to equals and the value field to the value you want to check: 
validate:
  # String validation to check if the response returned by Voiceflow is correct
  - type: equals
    value: Here you have 3 pizzas

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Regexp

The regexp validation type is the most complex one. It checks if the response returned by the Voiceflow agent matches the regexp specified in the value field. To use this type you have to set the type field to regexp and the value field to the regular expression you want to check: 
validate:
  # String validation to check if the response returned by Voiceflow is correct
  - type: regexp
    value: '/Here you have \d pizzas/'

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TraceType

The traceType validation type checks if the response returned by the Voiceflow agent has the trace type specified in the value field. To use this type you have to set the type field to traceType and the value field to the trace type you want to check: 
validate:
  # String validation to check if the response returned by Voiceflow is correct
  - type: traceType
    value: speak

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Similarity

The similarity validation type checks if the response returned by the Voiceflow agent is similar to the values specified in the values field. To use this type you have to set the type field to similarity and the values field to the values you want to check: 
validate:
  # String validation to check if the response returned by Voiceflow is correct
  - type: similarity
    similarityConfig:
      provider: 'openai'
      model: 'gpt-4o'
      temperature: 0.8
      top_k: 5
      top_p: 0.9
      similarityThreshold: 0.5
    values:
      - 'hi'
      - 'Hello'
You can also use the similarityConfig field to specify the similarity configuration. The provider field specifies the similarity provider you want to use. The model field specifies the model you want to use. The temperature field specifies the temperature you want to use. The top_k field specifies the top k you want to use. The top_p field specifies the top p you want to use. The similarityThreshold field specifies the similarity threshold you want to use. The only provider available for now is openai. For LLM Providers authentication please check the Authentication page.

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Variable

The variable validation type checks if a variable in the Voiceflow agent has the expected value. To use this type you have to set the type field to variable, the value field to the expected value, and provide a variableConfig object with the variable details: 
validate:
  # Variable validation to check if a variable has the expected value
  - type: variable
    value: 'myVariableValue1'
    variableConfig:
      name: 'variableName1'
The variableConfig object accepts the following properties:
  • name: (Required) The name of the variable to validate
  • jsonPath: (Optional) A JSONPath expression to extract nested values from JSON/object variables
Examples: 
validate:
  # Simple variable validation
  - type: variable
    value: 'myVariableValue1'
    variableConfig:
      name: 'variableName1'
  
  # Multiple variable validations
  - type: variable
    value: 'myVariableValue2'
    variableConfig:
      name: 'variableName2'
  
  # Variable validation with JSONPath if the variable is a JSON/object
  - type: variable
    value: 'myVariableValue3'
    variableConfig:
      name: 'variableName3'
      jsonPath: '$.hello'

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JSON Schema

voiceflow-cli also has a jsonschema file, which you can use to have better
editor support: 
https://voiceflow.xavidop.me/static/conversationtest.json
You can also specify it in your yml config files by adding a
comment like the following: 
# yaml-language-server: $schema=https://voiceflow.xavidop.me/static/conversationtest.json


# yaml-language-server: $schema=https://voiceflow.xavidop.me/static/conversationtest.json