I started working on Chatbot series and it has been eye-opening. One thing I didn't expect in this project was the significant amount of time required for training the bot to recognize and respond to various user intents effectively. Initially, I anticipated that setting up Amazon Lex would be straightforward, but I quickly realized that users express their inquiries in many different ways, which added complexity to the intent recognition process.
In this Project:
๐I configured multiple slots with a shared slot type. I set up two different slots, sourceAccountType and targetAccountType, that both utilize the same underlying accountType slot. This streamlines data handling in my bot.
๐I implemented a confirmation prompt that repeats the transaction details back to the user for verification.
๐I used the conversation flow and visual builder features that I got familiar with and will henceforth, be used to create a Lex chatbot!
๐I used AWS CloudFormation to automate the deployment of my banking bot. This not only saved time but also made sure all resources were correctly configured and linked!
Here is a link to the Project: https://drive.google.com/file/d/1lgXe907z7CjPxCnDk821yw3Iu8UX2swJ/view?usp=sharing
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