Ah, not so fast, you say.
You notice that I'm missing the setting?
The module name and the class name, which we also have to do.
There we go.
Module name is accounts.py and the class name is account.
And actually that wasn't the only mistake also in task's YAML.
I had some some missing.
I had some stray tabs going on that some of these things weren't formatted properly.
And I'll tell you, the reason I found that out is because I tried to run this and it failed.
The error message I got was was quite obscure.
It was like some long stack trace and it was not immediately obvious what was wrong.
And I think, you know, I had to go through quite carefully and look for problems.
And I sort of had a clue about the kind of thing I was looking for.
But I can imagine if you're new to to using crew, then that could be quite a painful experience because
there's not many clues given to where to go.
And I really think that that is the kind of that's the deal that you make signing up for a framework
like this, you get a lot out of the box, you get a lot of head start.
Think of the memory stuff that we did last time and the whole way that this this fits together and the
code execution stuff.
I mean, it's amazing, but what you you get are that you are trading off is the fact that some stuff
is is hidden from you.
And when things go wrong, it can be harder to debug and figure out what's actually happening behind
the scenes.
But anyway, with all of that, it should be time now for us to actually give this a try.
So we go into our directory, we go into engineering team and we get ready to run.
Crew I run.
Okay, here we go.
And it's off.
Thinking okay, the engineering lead is starting off the engineering lead.
Of course that is GPT four zero.
The way I have it set up, you may have picked a different model.
You may even be trying with a llama.
Now, I will say that if you are trying it with a llama, if you're looking for the free service, I
do imagine that this will stretch llama to the max.
This is going to be very, very hard challenge and depending on which model you pick underneath a llama,
you may have limited success with this.
This may be a case of where you have to watch what I'm doing here, and I'm saving the results in example
output folder so that you can have that to hand.
And you know, this might give you something to watch and learn from rather than running it yourself.
But if you want to try it with GPT four and mini, that should work just fine.
Anyway, we can see that it's done the design.
It's now in the hands of the Python engineer, and I know that this can now take a couple of minutes.
In fact, I think last time it took about five minutes to run all the way through.
And that wasn't with deep seek.
And deep seek can be a bit slower.
So we'll see what happens.
I will be right back in a minute.
Okay.
It just finished.
It's exciting.
I guess it did take about five minutes I think.
Let's have a look at what was produced in the output folder.
So I guess well there's a lot of files there.
That's a good start.
Let's start with the design document.
It is indeed in markdown.
It's uh, let's get rid of this terminal.
It's got certainly like a design written out there and it's got like method signatures and things.
That seems great.
And now the big guy accounts dot pi.
Okay, so it's got the get share price dummy at the top, which is what we wanted to to return a share
price for Apple, Tesla and Google as example to to seed it.
Okay.
Class account.
That's good.
And it's got the right kinds of, uh, setups deposit accounts, withdraw accounts with comments with
docstrings.
Okay.
That's that looks good from eyeballing.
I'm seeing good looking stuff.
Obviously we'd expect to see, uh, price times quantity.
And then, uh, I see they, they're going to, uh, return false or return true depending on whether
it was successful or not.
That's interesting.
Okay.
And yeah, this all looks pretty comprehensive, doesn't it.
Calculate profit or loss.
Get the holdings takes a copy.
That's that's an that's a pro thing to have done.
I wouldn't have even thought of that if I was doing it myself.
That of course is the right thing to do.
Okay.
Very nice.
This looks very comprehensive.
This looks like the Kobe we're looking for.
Let's look at the test accounts.
Sure.
I mean, these are the kinds of tests you'd expect plenty of of assertions in here.
That's great.
And then that's the right kind of scaffolding around a unit test.
And there is an API.
But we're not going to look at that App.py, because we're going to look at it in a whole different
way when I'm back.
Let's, uh, let's try this.
Okay.
So I've gone into a terminal now as we try out the code written by our engineering team, by our front
end developer, we're going to go into the folder called output.
Here we are.
Now I imagine that we're going to need to install gradio.
I imagine if we just do app.py it's going to have an import failure.
Let's try this.
You've run App.py which you remember.
You've run is the equivalent of Python when you're using UV environment.
Let me see.
No module named Gradio.
Okay, so I have to do UV add gradio.
And it's now added.
And now we try this again.
You've run App.py.
Okay.
It's thinking it's doing its stuff.
Thinking thinking hasn't crashed.
It's loading the various gradio dependencies right now, I believe.
Okay.
So it's it started a radio app.
This is kind of crazy.
Follow the link.
Okay.
Here we go.
Here is a user interface.
Okay.
So first of all the first thing I'll notice this is you're getting like a raw reaction video here.
I'm like astonished.
You can see that it's done an audio out with with these tabs.
Account management trading and reports.
That's cool.
So create an account.
I get to give it a user ID, so I guess I'll call it ad initial deposit.
We'll put that in I'll press create account.
Account created for ad with initial deposit of 10,000.
And there we go.
Holdings.
No holdings.
All right.
Fine.
Now we go over to.
I guess I can withdraw and, uh, and add.
That's cool.
I'll go to trading.
We'll do symbol apple quantity one, buy shares.
And here we go.
Successfully bought one share of Apple at.
Let's zoom out a bit.
Let's see if we can.
There we go.
Zoom out again at that much.
So the user is editor.
That's now my cash balance that's come down.
The portfolio value is of course the full amount because I've I've spent some money but I've bought
equivalent Apple shares.
That's calculating that.
Right.
And there's the holdings one share at 150 each.
That's great.
Let's go over to reports.
Portfolio value is uh 10,000.
Profit loss zero.
Current holdings.
Is there transaction history uh deposit and buy shares.
This is great.
This is so cool.
I can't believe this.
This is this isn't a simple user interface.
This is a really good user interface.
Look at the way things are organized into groups and are, like, nicely laid out.
I'm kind of surprised about this because actually, in the past I've used GPT four or mini, and it's
not looked as good as this.
It's worked for sure, but this is a sharp user interface with with tabs, with sections organized quite
nicely.
And, uh, I guess we better let's try selling a share of Tesla that we don't have.
Quantity one sell shares.
Error.
Insufficient shares to sell.
Okay, we get an error message.
Now let's try selling an Apple share Sell.
Share.
Successfully sold one share of Apple.
And now we have no holdings.
And if we go and look at our transactions, hopefully we'll see that we both bought and sold.
Transaction history.
Buy one share of Apple.
Sell one share of Apple.
Well, I got to tell you, this is astonishing.
I'm, uh.
There's there's this.
This isn't a fake.
I haven't run this in advance to to see this before.
You're getting my raw reaction.
And it's definitely surpassing my expectations in terms of this being a nice user interface.
Like, if I had built this, I would be quite pleased with it.
I'm, uh, frankly, I'm astonished.
So that's a great conclusion.
I will be sure to make sure I'll put some examples in example outputs.
I'll try and put one with with mini so you can see a more raw user interface and then something like
this.
And uh yeah it's really amazing to see.
So a collaboration between GPT four and Claude 37 and deep seek to build this platform with, frankly,
a really impressive user interface.
Wow.