Dashboard

We're currently seeing developers build the following use cases using AI: 

1. Text Generation (eg: support ticket response, marketing content, emails)
2. Text Classification (eg: labelling support tickets, analysing sentiment of customer reviews)
3. Assistance in decision-making (eg: AI recommendation for loan approval, order refund)
4. Data extraction from images  (eg: extract data from receipts, KYC documents)
    

Let us know in the comments what use cases you’re building using AI and what building blocks you would like Appsmith to support. 

Comment "AI" if you'd like to fork a copy of the sample app showcased in the post 

Very nice

Wow - that is so cool! It is much easier than I originally thought it would be.

We looked at making this scenario even easier with the new sqlcmd (https://aka.ms/sqlcmd)

1. brew install sqlcmd
2. sqlcmd create mssql --accept-eula
3. sqlcmd open ads

Let me know if "sqlcmd create mssql" is useful for you, and/or how we can improve it!

Some months ago wanted to load libraries to support using Arangodb arongosh in appsmith objects but never succeeded.  Would this now be possible?  Think Joseph P suggested Iframes but was unable to follow-up on that.

Great video. Thanks Confidence ❤️

I whole heartedly agree with #13.
#36 @ron why did you have to torture him?😅

Thanks Oscar and Ed! I had fun building this one. 

Charts are looking cool!

I'm still working on one dashboard with the chart, and I use a completely custom Fusion Charts definition there.

Here's a sneak peek:

JSON

Chart

Thanks for this template Joseph, People at my workplace will love this work!

Great article! The power of contextual AI is just an amazing feature! 

Thank you! I had a great time building this app :)

Loved it!

Congrats to all the winners, and thank you to everyone who contributed! 

Can this be replicated on a mobile phone?

I tried to play with Tesseract one or two years ago and literally fell into a rabbit hole. The image quality is very-very condition sensitive and requires tons of pre-processing and maybe a PhD in Computer Vision.

From what I learned the main goal is to get as contrast and sharp text as possible (black readable letters on white background) so that tesseract's neural network can confidently recognize them. So, in many applications OpenCV library does some heavy lifting even before the text gets into tesseract.