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chatbot.yaml configuration file

chatbot.yaml is the main chatbot configuration file. It contains all configurable properties for the project, such as:

  • The name of the main script file.
  • Information on imported dependencies.
  • NLU configuration.
  • The list of included test files.

This article describes the properties which can be set in chatbot.yaml and their purpose.

tip
Learn more about YAML syntax

Script entry point​

entryPoint: main.sc

This property sets the script entry point — the file which is the first to load when the chatbot is deployed. The file must be located in the src folder and is conventionally named main.sc or entryPoint.sc.

tip
When the script code consists of several files, all required files must be imported into the entry point itself or into files imported by the entry point. Use the require tag for importing files.
caution
entryPoint is a required property.

Bot name​

name: echo-bot

This property sets the bot name, by which it will be referenced in deploy logs and other system messages. If the property is missing, the internal project name will be used instead.

NLU settings​

Bot engine​

botEngine: v2

This property sets the chatbot engine version.

tip
The second bot engine (v2) enables the NLU core for natural language understanding. This is the recommended setting for all new projects.
caution
If the property is missing or has a value other than v2, the legacy bot engine (v1) will be used instead. This engine allows only patterns for NLU.

Bot language​

language: en

This property sets the language the bot will understand. The value should be a language ISO code.

caution
When using the second bot engine, setting this property is required.

Thresholds​

You can set thresholds:

Intent thresholds​

nlp:
  intentNoMatchThresholds:
    phrases: 0.2
    patterns: 0.2

The phrases and patterns fields in the nlp.intentNoMatchThresholds section set the thresholds for intents.

This is how the classifier works:

  1. The user sends a request to the bot.

  2. When generating hypotheses, the classifier compares the request with patterns and training phrases individually. It calculates the probability for each of the hypotheses.

    tip
    A hypothesis is the result of the classifier. When the classifier generates a hypothesis, it determines the extent to which the user’s request corresponds to a particular intent. Thus, the classifier expresses the degree of its confidence that this intent really contains a phrase or a pattern from the user’s request.

  3. If the hypothesis probability is less than the threshold of phrases or patterns, it is discarded and ignored during subsequent request processing and defining the state in the script.

In other words, intentNoMatchThresholds sets the minimum required similarity of the request to the intent phrases or intent patterns. The closer its value is to 1, the stricter are the matches that it requires.

The default value of phrases and patterns is 0.2. This value is used if you do not specify another one for any of the fields.

caution
In earlier projects, the caila section was used instead of nlp. It contains the noMatchThreshold property, which sets a common threshold for both phrases and patterns. For new projects, it is recommended to use the nlp section instead for correct determination of patterns, because the classifier and the algorithm that calculates pattern weights may have different scales.

Pattern threshold​

Patterns can be specified in the q and q! tags. By default, these patterns are taken into account with any weight.

The patternNoMatchThreshold parameter in the nlp section allows you to set a threshold value for the patterns:

nlp:
  patternNoMatchThreshold: 0.5

If the match weight of a pattern is less than this value, the pattern is ignored during request processing. The closer the threshold value is to 1, the more accurate matches are required.

$context.nBest length​

nlp:
  nbest: 3
  nbestPatterns: 1
  nbestIntents: 2
  nbestExamples: 3

Properties beginning with nlp.nbest determine the number of activation rules available from the script via the $context object.

  • The nbest property sets the length of $context.nBest — an array of activation rules of all possible types (patterns, intents, and examples) triggered for the request. The default value is 1.
  • nbestPatterns sets the length of $context.nBestPatterns — an array of activation rules only triggered by patterns. The array is unavailable if this property is omitted.

nbestIntents and nbestExamples work the same with respect to intents and examples.

tip
Learn more about $context.nBest

Request processing limits​

Request length limit​

nlp:
  lengthLimit:
    enabled: true
    symbols: 100
    words: -1

nlp.lengthLimit sets a length limit on requests processed by the bot:

  • enabled enables or disables the limit.
  • symbols is the maximum number of characters contained in the request.
  • words is the maximum number of words in the request. This limit is disabled if set to -1.

By default, the limit is enabled and set to 400 characters. The word limit is disabled.

caution
If the request exceeds one of the limits, the lengthLimit event will be triggered.

Request processing timeout​

nlp:
  timeLimit:
    enabled: true
    timeout: 500

nlp.timeLimit sets a limit on the time allotted for processing the request:

  • enabled enables or disables the limit.
  • timeout is the maximum time allowed for request processing, in milliseconds.

By default, the limit is enabled and set to 10000 (10 seconds).

caution
If the request exceeds the limit, the timeLimit event will be triggered.

XML tests​

tests:
  include:
    - "authorization.xml"
    - "integration-tests/*.xml"
  exclude:
    - "broken.xml"
  caseSensitive: false

You can use XML tests to verify the chatbot script by emulating client requests and asserting that bot responses behave as expected.

By default, all tests contained in the test folder are executed. You can override this behavior by setting the values for include and/or exclude in the tests section:

  • include — only the tests from the files matching the patterns listed in this subsection will be executed.
  • exclude — all the files matching the patterns listed in this subsection will be excluded from execution.
tip
Apache Ant syntax is used for patterns.

The caseSensitive property determines whether patterns should be case-sensitive. It is true by default.

Dependencies​

dependencies:
  - name: common
    type: git
    url: https://<repository>
    version: heads/master

The dependencies section contains a list of project dependencies.

tip
Learn more about dependencies

Action tags​

customTags:
  - src/blocks/SumTwoNumbers/block.json

The customTags section defines the list of custom action tags used in the project.

Custom reactions​

customBlocks:
  - src/blocks/video.json

The customBlocks section defines the list of custom reactions used in text campaigns.

Error messages​

messages:
  onError:
    locales:
      en: Failed on request processing.
      de: Es ist etwas schiefgelaufen.
    defaultMessage: Something went wrong.
    # defaultMessages:
    #   - Sorry, the bot just crashed.
    #   - An error occurred when processing your request.

The messages.onError allows setting the text of the message the chatbot will send if any errors occur in the script.

The locales subsection should contain messages localized based on user locale data. In this subsection, the keys are language ISO codes, and the values are the message texts themselves.

In the defaultMessage property, you can configure the text which will be sent by default if the necessary language or the locales section itself is missing. You can also set a list of such messages in defaultMessages, in which case a random error message will be chosen every time.

caution
If the whole messages.onErrorsection is missing, the bot will not respond at all if an error occurs.
tip
Use error handlers to set up a more flexible error processing behavior.

Injector​

injector:
  catchAllLimit: 10
  api:
    protocol: https
    host: example.com
    port: 443

Use the injector section to set up the chatbot configuration. All properties will be accessible from the chatbot script via the $injector variable.

tip
Learn more about $injector

SMTP server configuration​

Use the injector.smtp section to configure the settings for the SMTP server that will be used for sending email messages via the $mail.sendMessage method.

injector:
  smtp:
    host: smtp.just-ai.com  # SMTP server host
    port: 2525  # SMTP server port
    user: user@just-ai.com  # SMTP server user
    password: qwerty  # SMTP server password
    from: bot@just-ai.com  # Email sender

    # Optional properties
    hiddenCopy: admin@just-ai.com  # Email hidden copy recipient
    # You can specify a list of recipients:
    # hiddenCopy:
    #   - admin@just-ai.com
    #   - support@just-ai.com
    debugMode: true  # Whether debug mode is on or off

Other settings​

Request modification​

nlp:
  modifyRequestInPreMatch: true

When enabled, the nlp.modifyRequestInPreMatch property allows modifying the request content in the preMatch handler, e.g. changing the request text.

Word tokenization in patterns​

tokenizeWordsInPatterns: true

The tokenizeWordsInPatterns property enables word tokenization in patterns for languages without word separators.

caution
This property is required for projects in Chinese so that patterns work correctly.

File import strategy​

scenarioLoadStrategy: v2

The scenarioLoadStrategy property sets the strategy for loading files into the script consisting of multiple files. The property has two possible values: v1 (set by default) and v2. When using the v1 strategy, required files are loaded in the top-to-bottom order in the dependency tree, while v2 makes them load from bottom to top.

The following example illustrates the difference. The main.sc file imports r1.sc, r2.sc, and r3.scusing the require tag, and both r1.sc and r2.sc also have two imported files. When the script is deployed, the files will be loaded in the order illustrated in the image below.

The v1 strategy makes the root load first and the leaves to follow. The v2 strategy does the opposite

Influence of context distance on intent score​

nlp:
  considerContextDepthInStateSelectionV2: false

The nlp.considerContextDepthInStateSelectionV2 property determines whether the context distance to states triggered by the intent/intent! tag or the intentGroup/intentGroup! tag should be taken into account when calculating intent scores.

  • true (default value) — context distance is used for calculating intent scores and selecting the target state.
  • false — intent scores do not depend on context distance and are calculated the same way in all states.