Last week I presented at DevFest Caribbean. It was a Google Developer Group event, where the GDG of multiple regions came together, it involved the groups from Trinidad and Tobago, Guyana, Jamaica and others. There were some really good presentations, and you can check them out here.
My presentation focused on virtual agents I created in Microsoft Teams. I demonstrated a messaging extension from Microsoft, that I extended to work with BambooHR’s platform.
Exercise is a big deal at Teleios. So, when Geon demonstrated his Power App, it inspired me to make a virtual agent to help with updating. In my presentation, I showed a bot that uploads data for access to the Power App … plus, it pushes updates to Strava!
The Ministry of Planning has a website for checking air quality in T&T. I wrote an API to talk to that site and then a bot that works in Teams directly. The bigger challenge in this agent was getting something, anything really, up and running on my google home mini. And I did! So, I was very glad.
Finally, I’ve started experimenting with virtual agents that can interact with in-progress meetings on Microsoft Teams. I heavily relied on the Microsoft Graph samples library related to accessing meetings. I got a zany bot to work. It can inject audio into live meetings, without anyone having to share media from their devices. It’s great for sound effects, like a play off sound for people who are taking up too much time in a meeting.
All told, presenting at DevFest was fun, yet again. It was my third time presenting, and third year in a row talking about conversational user interfaces. You can catch the whole talk here:
Today is GDG DevFest 2019 in Trinidad. The organizers put out a call for sessions, and I was happy to share one of the ideas that had been rolling around in my head for a while.
I Facebook in pirate, don’t @ me.
So, here’s the TL;DR: my idea was to take my likes on @Twitter and funnel them into Google Keep. Along the way, I’ll automatically categorize the tweets and then confirm that categorization via a chatbot. Simple stuff.
So simple, I didn’t even use Visio to diagram it.
What I actually did:
Twitter Likes
I made an Azure Function that would periodically poll my twitter account and get the last tweets that I liked. To do this, I had to create a developer account in twitter to get the appropriate creds. The function was pretty simple:
In the DotNetConf keynote a few weeks ago, I saw an ML.NET demo and I got the idea to use it here, too.
ML.Net to build models (easy peasy)
All my notes
I pulled all my notes in keep to train an ML model. It was very easy, particularly because I used gkeepapi, an unsupported library for interacting with keep.
Doing this made me glad that I could think in terms of a bunch of cooperating functions, because the function to extract the notes from keep was written in python, while most everything else is in C#.
importlogging
importgkeepapi
importjsonpickle
importos
importazure.functionsasfunc
classKeepNote(object):
label=""
text=""
category=""
# The class "constructor" – It's actually an initializer
KeepIt: A function to get my notes from Google Keep
The funny thing is, I didn’t really need the model. Most of the things I stored in keep, were in one or two categories – not very good for modelling. I guess I hadn’t really realized that. To be honest, I was probably storing things in keep that I had a very high priority on, which turned out to be mostly cloud things. Go figure.
How the bot will help change things
So, I’m grabbing my tweets, categorizing them based on history and preference and I’m ready to store them, except, as I’ve shown above, my categorization is whack. Thus, I also made a chatbot, that will take my liked tweets and ask me to adjust the category I’ve labelled it as.
TweetWhisperer: Helping me categorize my tweets better.
So, with these three components, a likes-harvester, a categorizer and a chatbot, maybe, I’ll get better at returning to these topics that I have an interest in.