snips-skill 0.1.11

Boilerplate for Snips skills in Python3

snips-skill

Helpers to keep Snips skills in Python3 free of boilerplate code.

Contents

• MqttClient: A thin wrapper around paho-mqtt
• CommandLineClient skeleton MQTT command line client with connection settings.
• SnipsClient: Reads connection parameters from /etc/snips/toml
• Snips-specific decorators for callbacks, see below.
• MultiRoomConfig: Utilities for multi-room setups.
• Skill: Base class for Snips actions.
• @intent decorator, see below.

Plain MQTT clients

Plain MQTT is supported via the MqttClient and CommandLineClient classes and the @topic decorator.

A CommandLineClient provides argument parsing for connection parameters and includes standard logging. For message handling, define a function or method as above, and decorate it with @topic. This registers the method (or function) as a callback for the given MQTT topic.

Usage example

from snips_skill import CommandLineClient, topic

class Logger(CommandLineClient):
    'Log all incoming MQTT messages'
    
    @topic('#')
    def print_msg(self, userdata, msg):
        self.log.info("%s: %s", msg.topic, msg.payload[:64])

if __name__ == '__main__':
    Logger().run()

Snips session event decorators

The Skill class provides automatic connection configuration via /etc/snips/toml. Also, the following Snips-specific decorators for session events are provided:

• on_intent: Handle intents,
• on_intent_not_recognized: Handle unknown intents,
• on_start_session: Called before session start,
• on_continue_session: Called for subsequent session prompts,
• on_session_started: Called at session start,
• on_end_session: Called before session end,
• on_session_ended: Called at session end.

All decorators can be used either on standalone callback functions, or on methods of the various client classes (including Skill).

Methods should expect the parameters self, userdata, msg, and standalone functions should expect client, userdata, msg.

Multiple decorators on the same method are possible, but if they have inconsistent qos values, the results will be unpredictable. Also note that multiple decorators will produce repetitive log lines with DEBUG level. Set log_level=None on all but one decorator to fix it.

The @intent decorator

@intent-decorated callbacks receive msg.paylod as an IntentPayload object, a parsed version of the JSON intent data. Slot values are converted to appropriate Python types.

The next step in the Snips session depends on the outcome of the decorated function or method:

• If the function returns a string or raises a SnipsError, the session ends with a message,
• If it returns en empty string, the session is ended silently.
• If it raises a SnipsClarificationError, the session is continued with a question. This can be used to narrow down parameters or to implement question-and-answer sequences.

To require a minimum level of confidence for an intent, put @min_confidence below @intent.

To ensure that certain slots are present in the intent, put @require_slot with a slot name below @intent.

The @intent decorator should not be used in combination with any on_* decorators.

Usage example

from snips_skill import intent, Skill

class HelloSkill(Skill):
    'Snips skill to say hello'
    
    @intent('example:hello')
    def say_hello(self, userdata, msg):
        return 'Hello, there'
        
if __name__ == '__main__':
    HelloSkill().run()