Amazon Q Developer-Your Inline Code Suggestion- Comparing With Github Copilot

Key Takeaways

hello all my name is Kush naak and welcome to my YouTube channel so guys uh as we know that we are learning generative AI uh specifically in the AWS Cloud so uh today one amazing productivity tool that we can specifically use which is uh I think available for everyone and the name is Amazon code Whisperer so this is the page we'll talk more about it but uh if you just want to know what exactly Amazon code Whisperer does uh it's very much simple um I hope everybody has seen GitHub co-pilot where it provides General suggestion with respect to different kind of codes and all so similarly you can also use Amazon code Whisperer which is also now called as Amazon Q developers okay and this you can probably use to again get all the suggestion with respect to various codes and all I will show you in this particular video how you can enable it in your vs code and trust me this is amazing productivity tool altogether to do your work very much faster and quicker uh at the end of this particular video since I have used both GitHub co-pilot and Amazon code Whisperer that is nothing but Amazon C developer so I will be making a brief comparison about it um you know most of the functionalities overlap but uh if I talk about Amazon Q developer it is specifically for some purpose so when you are actually developing and let's say you are probably using AWS account a lot uh you are doing all your work specifically to AWS then Amazon Q developer will be the better code suest register for you okay so let me just go ahead and show you how you can probably enable it uh for enabling it it is very much simple what you really need to do is that just go to the extension right and just search for Amazon Q okay so Amazon Q over here if you probably suggesting if you're searching you'll be able to see this right now I have already installed it and you can also install it uh let's see whether there is something called as Amazon Cube developer also I hope so we find it out if it is not not there then we can specifically use Amazon Q so this is the extension that you really need to install and understand once you probably install you know in the left hand side there will be a box that will probably be opened wherein it will be asking you for the information uh regarding your AWS account where you really need to log in just and trust me uh no credit card will be also required you just go ahead and log in into this particular account with respect to your own personal email ID uh it is also called as AWS Builder which will specifically provide you the access to Amazon Q okay so there will be a page that will be probably coming up over here uh it will ask you for the user name password and it'll tell you to authenticate from the AWS account itself so once uh that step is specifically done then what you can do you can just go ahead and exit this particular notebook and uh exit the vs studio and restart it okay once you probably restart it now you see the power of this and I as I told you right I've been using both GitHub C pilot and uh this one that is Amazon Q developers trust me both of them works amazingly well whenever you're specifically writing the code so just to give you a demo right now my extension is enabled uh and definitely use this for your coding purpose it will be very much helpful also so first of all I will go ahead and write down the comment let's say write me uh write me uh python code or write me a function to perform write me a python write a python function to perform to perform binary search okay so I'm just asking one simple binary search okay okay now this is the comment that I've have written now you can see Amazon Q is generating right now it does not show you something right over here and also it depends on internet speed both Respec to kind of suggestion and how quickly it also gives you so if I go ahead and just write definition over here and you know that function is going to get created automatically just press Tab and all the entire suggestion will be in front of you right so say just understand like how good the productivity basically becomes right uh if let's say for the first time I I'm planning to write this particular function right obviously I'll do some amount of Google search um yeah I'm lazy I'll not remember each and everything and definitely unless and there is not an interview I think you you will also not remember it right so over here you can see just just by writing a comment and probably doing it automatically all the suggestion is probably coming up right so this is really really amazing right um let me just go ahead and do one more thing okay some more complex thing related to generative AI okay provide me a streamlet app to call open a apis okay so let's say I am going and writing like this so the first thing is that I will uh specifically go ahead and import streamlet as St okay now let's see import open AI I'm not doing it anything all the suggestion is probably coming from you know the Amazon G developer over here right so same thing has got imported but I think that part you can probably fix it if it is not providing any suggestion that basically means it is telling you to give one line of code one line as an empty space and again now see not if it is not suggesting you something just press enter go to the next line and again it'll start suggesting you right so there it has probably created this message variable and now I think if generated oh session State also it is basically using which is quite amazing okay um okay past sessions everything over here it looks good again uh same thing I think no uh this is also making sure that I think it is also saving this prompt in the session State let's see if user not in session State how can I help you okay perfect I think this should be working fine but again unless and until I don't execute it there will be some amount of errors that will specifically be there now see U now what this has basically done is that it is mostly hardcoding things over here um you know mostly hardcoding things right with respect to my name is chat GPT and all so I think it is not doing that amazing job but with with respect to GitHub co-pilot that I found right uh it was able to give me a good response and that is where I'm going to make a of comparison okay so let's do one thing let's remove this again I think it is it is in that hallucination mode okay let's go to the new line or let's come after this particular function let's see what what suggestion it will probably give us okay now finally it is probably given this entire generator response function uh what you can basically do is that I think I'll not use even this session because I just wanted a simple uh this one right uh so this is the function that I've actually created and you can also guide it just not based on the suggestion you should probably go and just press tab right so generate responses over here here it is specifically communicating with text TC 02 um let me do one thing let me also go ahead and uh make sure that create this open API key okay let's see open Dot API uncore key and I will probably go ahead and set my API key over here uh after setting this particular API key let's see what kind of suggestion more it gives right so this is my messages return message okay so perfect I'm getting from this particular function my entire message this is my main session State again session State then again this messages append okay perfectly it is appending right it is appending with respect to the different roles and all so with some amount but see at the end of the day I'm not writing much code and uh again what we see and why it is not that better when compared to the GitHub copilot because I'll tell you a specific reason why it is not okay okay let's try one more thing okay so here I'm going to write a comment now see how the performance of this particular code will become better by using Code whisper or Amazon Q developer write uh streamlet python code to invoke AWS Bedrock AWS Bedrock Foundation models okay I'm just going to go ahead write this right let's see import stream L as St boto 3 okay perfect it is coming up okay perfect st. title again a stream late get the model name from the user perfect so enter the model name okay I will enter the model name what model name I specifically want uh enter the input data okay I'm splitting the data then input data will be this let's see what it is trying to do let's see input data finally I get over here print input data invoke the model okay perfect see boto 3. client is basically used to invoke Sage maker runtime or you can also use it for AWS Bedrock okay so model name body input but I feel it is good enough get the predicted output see with respect to the boto 3 we can basically just change this instead of writing Sage maker runtime I can write by Dr run time okay so predicted response body good enough and this is basically my predicted output I guess so it is right enter the model name enter the input data so some amount so here you can probably see the code is well structured and what I feel is that see when I probably write a code and if you have seen my AWS playlist where I'm specifically using Bedrock right U you can probably see it follows most of the similar structure so if I probably create a function if I try to write it much more in a better way and I cannot just depend on the entire application on this right so here uh it has done a pretty good work right and that is where see why with respect to only AWS work it is doing well because this entire product is from Amazon Q developer is belonging to AWS right so uh just to make a brief comparison right or let's see I I'll just try it like this okay uh Define a function to invoke uh ews now see see this Bedrock models okay and that is where you'll be able to understand so I'll write definition okay and uh I will try to create a definition where I'll say call Bedrock model done see this automatically all the things are done only the thing that I really need to change Bedrock model endpoint Define the endpoint Sage maker runtime instead of writing Sage maker runtime I need to also give the model name so model input is over here I have to probably create this payload from my side which is nothing but the same model input which I will be providing to this particular function now just to make a brief comparison between GitHub co-pilot you should understand that GitHub co-pilot is specifically used for general purpose and I also have that specific access if I probably consider Amazon Q developers um assistant that we have code assistant that we specifically have it is used to do or it provides you good suggestion with respect to any kind of AWS task that you are probably doing in AWS itself so just to make this brief comparison so always try to make sure that uh it is good that you should know this but again at the end of the day which is the most generic model uh GitHub co-pilot that is a kind of suggestion that I would like to give you to both are trained in huge amount of data but definitely if I talk about Amazon Q developer it is your generative AI power assistant across specifically to most of the aw services and that is what I have found out by exploring all these things so I hope you like this particular video this was it for my side I'll see you in the next video have a great day thank you wonder all take care bye-bye