Comments (4)
How might this work with persisted context? In real world, context will be persisted somewhere in a redis database. This means that as of now, the mapping will have to be relied upon the skill name.
Also, when a followUp flag is set, should the response automatically be marked final or can multiple skills mark their own followUps? How will this scale to multiple responses?
Potentially, upon a multiple response to multiple followups, the bot could split the response into a stack and then pass the response one by one to each of the followup skills who can then decide what to take off of the stack.
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Mapping is relied upon the skill name.
Response is automatically marked as final.
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How can a skill release a follow-up? Think about the following conversation:
YOU:[1]> I'd like to make a payment
BOT:[2]> Sure! What's your payment method? <----------- Lock acquired
YOU:[3]> You know what, nevermind.
BOT:[4]> No problem <----------- Lock naturally released
Here the natural locking works quite well. However, it does not for the following:
YOU:[1]> I'd like to make a payment
BOT:[2]> Sure! What's your payment method? <----------- Lock acquired
YOU:[3]> Actually, what's my balance?
BOT:[4]> It is £350.00. <----------- Lock manually released, sentence gets re-evaluated.
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In case 2, the skill will have to set a custom message to the response.message
object and finish the execution like so:
response.message = new Message('ReevalRequested', 'Cannot process this message. Irrelavent to the skill.');
return response.final();
The code handling the bot, with the final callback to the resolve
method could interpret the message and call the bot back for re-evaluation.
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Related Issues (20)
- Add simple tutorial
- When using trainAll finished function should be optional HOT 2
- Add filters HOT 2
- Add extractors
- Raise error immediately when any of the parameters for resolve method are undefined
- Types for binding static text responses to topics
- Type for binding topics to random response from a list of response
- Wrap default classifier into an abstract implementation HOT 1
- Multi-sentence queries don't work properly when sentences are all lower case
- Enable single-sentence query mode HOT 1
- undefined topic for skills does not work when confidence resolution for skill fails
- Move to event driven architecture
- Bot not selecting right skill HOT 4
- Support for non-English locales HOT 2
- Support for multiple classifiers
- Allow classifiers to supply extra information to skills HOT 5
- Support array input for terms in TrainingDocument HOT 2
- Accept single message object with callback as optional argument for resolve method.
- when bot dont have an response for that
- Feature req: Please integrate apipie.ai
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