WEBVTT

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Ah, not so fast, you say.

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You notice that I'm missing the setting?

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The module name and the class name, which we also have to do.

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There we go.

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Module name is accounts.py and the class name is account.

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And actually that wasn't the only mistake also in task's YAML.

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I had some some missing.

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I had some stray tabs going on that some of these things weren't formatted properly.

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And I'll tell you, the reason I found that out is because I tried to run this and it failed.

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The error message I got was was quite obscure.

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It was like some long stack trace and it was not immediately obvious what was wrong.

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And I think, you know, I had to go through quite carefully and look for problems.

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And I sort of had a clue about the kind of thing I was looking for.

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But I can imagine if you're new to to using crew, then that could be quite a painful experience because

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there's not many clues given to where to go.

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And I really think that that is the kind of that's the deal that you make signing up for a framework

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like this, you get a lot out of the box, you get a lot of head start.

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Think of the memory stuff that we did last time and the whole way that this this fits together and the

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code execution stuff.

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I mean, it's amazing, but what you you get are that you are trading off is the fact that some stuff

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is is hidden from you.

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And when things go wrong, it can be harder to debug and figure out what's actually happening behind

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the scenes.

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But anyway, with all of that, it should be time now for us to actually give this a try.

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So we go into our directory, we go into engineering team and we get ready to run.

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Crew I run.

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Okay, here we go.

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And it's off.

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Thinking okay, the engineering lead is starting off the engineering lead.

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Of course that is GPT four zero.

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The way I have it set up, you may have picked a different model.

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You may even be trying with a llama.

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Now, I will say that if you are trying it with a llama, if you're looking for the free service, I

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do imagine that this will stretch llama to the max.

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This is going to be very, very hard challenge and depending on which model you pick underneath a llama,

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you may have limited success with this.

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This may be a case of where you have to watch what I'm doing here, and I'm saving the results in example

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output folder so that you can have that to hand.

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And you know, this might give you something to watch and learn from rather than running it yourself.

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But if you want to try it with GPT four and mini, that should work just fine.

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Anyway, we can see that it's done the design.

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It's now in the hands of the Python engineer, and I know that this can now take a couple of minutes.

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In fact, I think last time it took about five minutes to run all the way through.

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And that wasn't with deep seek.

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And deep seek can be a bit slower.

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So we'll see what happens.

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I will be right back in a minute.

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Okay.

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It just finished.

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It's exciting.

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I guess it did take about five minutes I think.

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Let's have a look at what was produced in the output folder.

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So I guess well there's a lot of files there.

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That's a good start.

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Let's start with the design document.

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It is indeed in markdown.

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It's uh, let's get rid of this terminal.

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It's got certainly like a design written out there and it's got like method signatures and things.

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That seems great.

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And now the big guy accounts dot pi.

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Okay, so it's got the get share price dummy at the top, which is what we wanted to to return a share

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price for Apple, Tesla and Google as example to to seed it.

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Okay.

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Class account.

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That's good.

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And it's got the right kinds of, uh, setups deposit accounts, withdraw accounts with comments with

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docstrings.

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Okay.

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That's that looks good from eyeballing.

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I'm seeing good looking stuff.

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Obviously we'd expect to see, uh, price times quantity.

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And then, uh, I see they, they're going to, uh, return false or return true depending on whether

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it was successful or not.

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That's interesting.

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Okay.

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And yeah, this all looks pretty comprehensive, doesn't it.

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Calculate profit or loss.

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Get the holdings takes a copy.

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That's that's an that's a pro thing to have done.

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I wouldn't have even thought of that if I was doing it myself.

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That of course is the right thing to do.

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Okay.

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Very nice.

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This looks very comprehensive.

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This looks like the Kobe we're looking for.

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Let's look at the test accounts.

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Sure.

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I mean, these are the kinds of tests you'd expect plenty of of assertions in here.

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That's great.

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And then that's the right kind of scaffolding around a unit test.

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And there is an API.

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But we're not going to look at that App.py, because we're going to look at it in a whole different

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way when I'm back.

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Let's, uh, let's try this.

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Okay.

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So I've gone into a terminal now as we try out the code written by our engineering team, by our front

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end developer, we're going to go into the folder called output.

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Here we are.

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Now I imagine that we're going to need to install gradio.

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I imagine if we just do app.py it's going to have an import failure.

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Let's try this.

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You've run App.py which you remember.

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You've run is the equivalent of Python when you're using UV environment.

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Let me see.

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No module named Gradio.

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Okay, so I have to do UV add gradio.

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And it's now added.

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And now we try this again.

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You've run App.py.

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Okay.

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It's thinking it's doing its stuff.

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Thinking thinking hasn't crashed.

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It's loading the various gradio dependencies right now, I believe.

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Okay.

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So it's it started a radio app.

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This is kind of crazy.

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Follow the link.

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Okay.

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Here we go.

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Here is a user interface.

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Okay.

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So first of all the first thing I'll notice this is you're getting like a raw reaction video here.

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I'm like astonished.

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You can see that it's done an audio out with with these tabs.

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Account management trading and reports.

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That's cool.

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So create an account.

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I get to give it a user ID, so I guess I'll call it ad initial deposit.

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We'll put that in I'll press create account.

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Account created for ad with initial deposit of 10,000.

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And there we go.

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Holdings.

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No holdings.

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All right.

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Fine.

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Now we go over to.

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I guess I can withdraw and, uh, and add.

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That's cool.

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I'll go to trading.

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We'll do symbol apple quantity one, buy shares.

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And here we go.

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Successfully bought one share of Apple at.

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Let's zoom out a bit.

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Let's see if we can.

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There we go.

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Zoom out again at that much.

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So the user is editor.

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That's now my cash balance that's come down.

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The portfolio value is of course the full amount because I've I've spent some money but I've bought

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equivalent Apple shares.

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That's calculating that.

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Right.

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And there's the holdings one share at 150 each.

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That's great.

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Let's go over to reports.

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Portfolio value is uh 10,000.

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Profit loss zero.

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Current holdings.

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Is there transaction history uh deposit and buy shares.

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This is great.

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This is so cool.

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I can't believe this.

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This is this isn't a simple user interface.

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This is a really good user interface.

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Look at the way things are organized into groups and are, like, nicely laid out.

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I'm kind of surprised about this because actually, in the past I've used GPT four or mini, and it's

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not looked as good as this.

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It's worked for sure, but this is a sharp user interface with with tabs, with sections organized quite

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nicely.

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And, uh, I guess we better let's try selling a share of Tesla that we don't have.

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Quantity one sell shares.

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Error.

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Insufficient shares to sell.

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Okay, we get an error message.

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Now let's try selling an Apple share Sell.

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Share.

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Successfully sold one share of Apple.

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And now we have no holdings.

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And if we go and look at our transactions, hopefully we'll see that we both bought and sold.

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Transaction history.

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Buy one share of Apple.

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Sell one share of Apple.

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Well, I got to tell you, this is astonishing.

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I'm, uh.

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There's there's this.

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This isn't a fake.

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I haven't run this in advance to to see this before.

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You're getting my raw reaction.

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And it's definitely surpassing my expectations in terms of this being a nice user interface.

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Like, if I had built this, I would be quite pleased with it.

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I'm, uh, frankly, I'm astonished.

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So that's a great conclusion.

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I will be sure to make sure I'll put some examples in example outputs.

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I'll try and put one with with mini so you can see a more raw user interface and then something like

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this.

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And uh yeah it's really amazing to see.

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So a collaboration between GPT four and Claude 37 and deep seek to build this platform with, frankly,

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a really impressive user interface.

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Wow.