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Switching states

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A chat bot script is defined in a text file with a tree structure. This means some elements are nested in other ones. These elements are states of the system it can switch to in the course of a conversation. They are called system states. Generic states include more specific states.

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Switching to a state

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A state is switched in the following cases:

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Activation rules for patterns, intents and groups of examples in a script are processed for the following objects in descending priority: q!, eg!, intent!.

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The conversation can switch to a global tag state from any other state. A local tag is only active in the context of the conversation; you can switch to this state from one of the nearest parent or child states.

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Processing activation rules

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When the system is in a state, rules associated with that state and all its parents are activated. Activation rules associated with that state have the highest priority.

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Therefore, identical activation rules can be declared in different states, but they are processed depending on the current state of the system.

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Consider the following script:

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patterns:\n    $Yes = (yes|of course)\n    $No = (no|not|no way)\n\ntheme: /\n    state: Start\n        q!: $regexp</start>\n        go!: ../morning exercise\n\n    state: morning exercise\n        a: Do you do morning exercise?\n\n        state: every day\n            q: * $Yes *\n            a: Do you do morning exercise every day?\n\n            state:\n                q: * $Yes *\n                a: Good!\n\n            state:\n                q: * $No *\n                a: Morning exercise has to become your habit!\n\n        state:\n            q: * $No *\n            a: Morning exercise helps your body and brain wake up, work on yourself!
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This script shows how a client’s yes/no answers are processed depending on the active state.

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Let us have a look at how this script is processed:

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  1. The script is started, go! redirect the client to the morning exercise state.
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  2. The bot asks Do you do morning exercise? from the morning exercise state.
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  3. The system will then remain the current state where the patterns are active: q: * $Yes *, q: * $No *.
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  4. The client answers yes and the system switches to the morning exercise/every day state. The bot then asks Do you do morning exercise every day?, and the system activates the next set of patterns.
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  5. The system will interpret the next answer of the client in the morning exercise/every day context. Responses activate nested state patterns as they have a higher priority.
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