mouthpiece
v0.3.0
Published
A conversation process flow for intelligent agents
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mouthpiece
A conversation process flow for intelligent agents.
Setup
Install via npm:
npm install mouthpiece --save
Usage
Import and initialize the conversation with a config:
var config = {
prepare: [doPrepare],
converser: converser,
actions: {
anAction: anAction,
}
};
var converse = require('mouthpiece/converse')(config);
converse('users utterance', context, function(err, result){
if(err) {
// handle it
}
});
The config is used to setup the process flow as follows:
config.prepare
- An Array of operations to run before calling the converser, optional.config.converser
- The main converser function that handles the agents dialog.config.actions
- An action map used to carry out actions in the converser output, optional.
Prepare operation signature:
function doPrepare(utterance, context, cb) {
console.log('Carring out preparatory processing');
process.nextTick(() =>
cb(null, utterance, context);
);
}
Action operation signature:
function anAction(verb, conversation_result, cb) {
console.log('Carrying out action ' + verb);
process.nextTick(() =>
cb(null, conversation_result);
);
}
Converser operation signature:
function converser(utterance, context, cb){
console.log('Carrying out conversation');
var converser_result = { context: context };
process.nextTick(() =>
cb(null, converser_result);
);
}
Converser result
The converser on sucessful completion must return a result object with the context
property set to the updated context.
This is the format of the result expected by the onward flow:
var converser_result = {
context: {
do: 'anAction, anotherAction',
replay: false,
loop: false
}
};
The returned context can also have two special properties that direct what happens next:
do
- This can be array of strings or a comma separated string. Each string is a key intoconfig.actions
. Actions corresponding to each key are then executed in order with this conversation result passed in.loop
- This boolean if set totrue
will cause the converser service to be called again running the flow a second time but with the new context taken from this conversation result.replay
- This boolean if set totrue
will cause the conversation flow to be re-entered running it a second time in its entiriety including any prepare operations, but with the new context taken from this conversation result.
If converser_result.utterance
is set it will be used as the utterance during loop and replay, otherwise the last user utterance is used. If converser_result.utterance
is not set, it is set to the last user utterance before calling any actions.
Dealing with different converser result formats
If the converser service you are using does not return a result in the expected format described above, the onward flow will break and cause errors. There are two ways to address this.
Use a wrapper function
You can wrap the non-conforming converser in a function that will take the immediate output of the converser and transform it to the form described above:
function converser_wrapper(utterance, context, cb){
console.log('Carrying out conversation');
converser(utterance, context, function(err, result){
if(err) return cb(err);
// If result is not in the expected format this is your opportunity to correct it.
var formatted_result = result;
cb(null, formatted_result);
});
}
config.converser = converser_wrapper;
This approach is suitable when the format of the result is very different from the expected one and/or an asynchronous operation is needed to transform the result into the expected format.
Provide converser.transformResult()
You can provide a transformResult()
operation on your converser, which will be called before passing its result onward into the flow. Your transformResult()
will have the opportunity to transform the result into the format expected by the onward flow.
converser.transformResult = function(result){
// If result is not in the expected format this is your opportunity to correct it.
var formatted_result = result;
return formatted_result;
}
config.converser = converser;
This approach is light-weight and works well when the result only needs minor tweaks to transform to the expected format and this can be done synchronously.
Running tests
Step 1: Get the Code
git clone https://github.com/wallali/mouthpiece.git
Step 2: Running Tests
npm test
Debugging
mouthpiece
uses the debug module to output debug messages to the console. To output all debug messages, run your node app with the DEBUG
environment variable:
DEBUG=mouthpiece:* node your-app.js
This will output debugging messages from mouthpiece
.