WEBVTT

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Okay, now I press the plus button here by tool, and I'm going to search for sheets and open the Google

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Sheets tool like so.

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Here it is.

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This is how we give our LLM the ability to access a Google Sheet.

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So it starts by saying credential to connect with.

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We're going to say create new credential.

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And this is where we're going to hook up our n810 running the cloud with our Google Sheets.

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And this is something which could be really really challenging.

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Sometimes some of the integrations we do this step is going to be challenging.

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In the case of Google Sheets in particular, it's actually really simple.

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There's just a sign in with Google button right here and ignore any of this stuff.

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Just press the sign in with Google button.

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If you're doing this on the self-hosted version, it's a bit more involved.

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But for now, we're just going to press this sign in with Google button, and up comes like a Google

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auth screen like this.

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And I'm just going to press my Google auth like so I'm going to say continue and connection successful

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appears.

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I'm going to close this down.

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And there's a green box that says Account connected.

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Come on.

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It could be much simpler than that.

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We are connected and cloud is connected to our Google Sheet.

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Well, it's connected to our Google Sheets for our account.

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We haven't connected it to a specific sheet yet.

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All right.

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So now press the X button here to come back to this screen.

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So this is now saying it's connected.

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The tool description will leave it set automatically.

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The resource we're going to say sheet within a document.

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Operations for this one is going to be like get rows.

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And now we choose the document and the sheet from this drop down uh, of of all of the Google Docs,

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uh, that it has access to all of the sheets.

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So I've just selected portfolio from, from this list right here, which is the one that we just created.

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And now the sheet there only is one sheet in here I'm selecting sheet one.

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And here it is.

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And there's there's ability to add filters and things.

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But we're going to leave all of that as it is.

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Um and so this is our tool that is is available now.

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So we now go back to this screen we've got.

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We've got this.

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We'll clear this chat and we're going to have a quick chat with our sheet.

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Okay.

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So I'm going to clear the chat.

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Let's let's say uh hi there.

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All right.

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It's thinking about that.

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Hello.

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How can I assist you today.

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All right I'm going to say please describe the sheet that you have access to read.

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We'll see what it tells us.

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It's going to connect hopefully to Google Sheets.

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And it's doing some stuff.

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And it's saying the sheet contains stock information with the following columns and data ticker quantity

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price.

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And then it says Google quantity three.

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Apple quantity two Tesla quantity three.

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There we have it.

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We have successfully connected our Naa10 agent to a Google sheet.

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And it took minutes, maybe even seconds if you were following along fast if you sped me up.

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All right.

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Now let's make it do something.

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I'm sure you can guess what we're gonna do.

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I'm going to move this over here.

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I'm going to add in another tool.

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The tool I'm going to add is called Market Stack.

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Remember that we did that yesterday.

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Select that.

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Now we're getting faster at this point.

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You know what we're doing.

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We've got the credential right here.

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We're going to say uh the tool description is automatic resources.

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End of day data.

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The operations get many.

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The ticker is to be set by the model.

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You click that purple button.

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Uh, we will say um, that we want to add a filter, the latest turn that on.

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And that I believe is all we need for getting stock data.

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Now we're going to add another tool.

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Let's just rearrange this a little bit.

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Let's put that there.

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Let's move the market data there.

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Let's press the plus button.

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That's just to tidy up.

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It doesn't matter.

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And now we're going to go and have another sheet a Google Sheets tool.

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This time it's going to be a resource.

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It's going to be sheets.

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The operation is not going to be get row.

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It's going to be update row.

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Uh okay.

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Uh let's select the document.

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And so I just gone to this from list and I chose the portfolio document, which is the sheet that we

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want to update.

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The sheet itself we're going to choose will of course be sheet one.

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Okay.

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This is important.

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This is when we tell what is it that we want to update in this sheet.

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And it knows about the the columns in our table.

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Let's read the sheet.

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And it sees it's got a ticker a quantity and a price.

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And the first thing we say is what column do we want to match on.

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So when it's picking what row to update, which column should it use to decide which is the row that

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I care about.

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And we want it to do it based on the ticker.

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We want to be able to our our LLM to say, I want to update Google's stock price based on the Google

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ticker.

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So that's the column to match on.

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And now in terms of the values to get updated, the actual fields that the LLM can specify, we don't

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care about quantity.

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I'm removing that.

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We want it to be able to to specify a ticker and a price.

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The ticker is the one that gets matched.

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The price is what it changes the price to.

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So I press this button here to say the model gets to define what ticker, and the model gets to define

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what price to set.

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And this has now defined what we want this tool to do.

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We want this tool to match on a ticker, to specify the ticker and to specify the price.

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And that price will be updated.

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So hopefully this makes this makes sense to you.

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This is how you go about telling Nan that the purpose of this tool is to be able to match on a ticker,

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set a price.

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We're done.

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We've created our update row.

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It looks a little bit messy.

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Let's move that over there.

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So now we have three tools.

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We've got one that gets a row.

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We've got one that gets market data, and we've got one that updates the row in the sheet.

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Okay.

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What I'm now going to do is I'm going to switch over to my portfolio as we have it right here.

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And I'm just going to detach this window like that and then just shrink it over and put it over here

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so we can, we can just keep an eye on the spreadsheet over here, the Google sheet.

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And I'm going to come back here, uh, to this screen, go back to our integrations, and I'm gonna

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move this cunningly over like this so we can be looking at our chats here, but also keeping a healthy

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eye over on the right at our Google Sheets.

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All right.

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And now I'm going to say hi there.

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Okay.

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It says hello.

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How may I assist you today I'm going to say please update the prices in my, uh, equity portfolio sheet

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to reflect the latest market prices.

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There's my instruction.

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Off it goes.

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Things happen.

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Keep your eye on the right.

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Keep an eye on the right hand side of the screen, please.

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Things are happening.

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Stuff is going on.

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Messages are spinning.

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Bam!

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You see that?

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The Tesla price just appeared.

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Apple price just appeared.

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Google price just appeared.

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It all happened.

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Workflow executed successfully.

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We just saw an agent in action, reading a sheet, collecting market data, writing the prices to our

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Google Sheet.

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Wasn't that fabulous?

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So what I love about this example is it feels so tangible to be able to see the stock prices change

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like that as we as we run it and see the spreadsheet changing.

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So it's really, really cool.

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What I want you to do now, though, is just dig in a bit more into these tools themselves to get a

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better sense for what was going on.

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And what do I mean by that?

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Well, you can double click on a tool like this update tool.

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You double click on it and it comes up with the details.

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And we already set this part here so we know it well.

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But let me show you what's on the left and the right.

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This is showing you the inputs and outputs.

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When this tool was actually called a moment ago and it was called three times.

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And you can tell because there's this drop down here run where there's one, two and three out of three.

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And if you pick something like two, then it updates on the left and the right to show you the inputs

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and outputs.

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The second time this tool was called and the inputs are shown in this this stuff on the left, which

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is in fact you're seeing JSON here.

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And some of you probably know JSON very well, but for those that don't, you will get comfortable with

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this.

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This is just a way of showing structured data like this.

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Um, and as it happens, anytime you see JSON like this, you can choose to either see it as JSON or

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say, hey, I don't want to see it as JSON, I just want to see it in a normal table.

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I'm more comfortable with tables, or you can see it in something called schema when you see the sort

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of structure of the data.

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But we're going to stick with JSON for now.

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You can see that this tool was called to update a row.

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It was saying please use this ticker to match Apple.

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And this is the thing to update the row with.

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And that's why on the right you can see we got back an output showing that that ticker was updated with

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that price.

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And you can flip between the three tool calls to see that it was updating each of the stock prices in

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that table.

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It all did just what we were expecting.

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And now I'm going to press escape click and press escape.

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And I'm going to show you the the Market Stack tool.

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Here it is.

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It was also called three times, shockingly, and it was called three times because it was called for

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the ticker Google.

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It was called for the ticker Apple, and it was called for the ticker Tesla.

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And over here on the right you can see what came back.

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And again you can see it in the form of JSON like this, this long bit of structured data or in a table

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format.

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And we'll see that there is an open high and low that came back for Tesla's price.

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And we can also flip that to to Apple and flip it to Google.

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And you're seeing over on the right what came back when the tool was called.

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And then press escape or click and press escape.

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And then let's go and look at this tool.

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Was this one called three times?

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No, it was not.

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This was only called once.

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This was called once.

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And it was just just just called with no inputs particularly.

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And what came back was the the table itself.

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I've got it selected on the table version.

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This is it in JSON style.

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You can see the JSON structure.

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It has this very recognizable look to it.

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We can look at it in a table form.

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And what came back is basically the table itself.

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The Excel spreadsheet had come back, but it came back in the form of JSON.

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It came back showing that we had three rows Google, Apple, Tesla and that these were the quantities,

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but the price was empty, which was before our our LLM decided to set the price.

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So this shows you the three tool calls.

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And I want you now to go in, dig in, have a look at this.

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Get a sense of what was called.

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Look at the JSON.

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Look at the table.

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Start to get more familiar with this build up a little bit of experience with this and you should also

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take this project in a new direction.

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Add another column, add some more information.

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Try try maybe adding the highs and the lows or whatever.

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Uh, figure out what more information you could get the LLM to set in that table and enjoy it.

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Watch it updating while you watch.

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It's such a spooky experience.

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Uh, and get a good sense of what it's like to use an AI agent that's hooked up to Google Sheets.
