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In this video, we're going to be writing the

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endpoint that will be called by our front-end

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to request the weather information.

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This endpoint will use function calling with

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the Gemini API to return weather information

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from our custom function.

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To begin, just after the request model we

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defined for our first endpoint, let's define

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another one for our weather request.

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Scroll down or scroll up and that will be

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right here.

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I'm just going to say class, weatherRequest,

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make it inherit from baseModel.

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And here we simply just need our destination

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as a string.

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That's good.

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Now let us create our endpoint.

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We'll be doing that just below our last endpoint.

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Let's scroll down to where that is.

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I'll be right here and now let us create our

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endpoint and declare the handler.

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So here I'm just going to say art app dot

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post and that will be for slash API for slash

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weather and the corresponding handler function

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is going to be an asynchronous function just

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like others and we'll call it getWeatherInfo.

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For the request, we'll pass in our weather

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request, which is the model we just defined.

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Now that we have our function defined, let

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us start our Gemini API request by first writing

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the try except block that we need to wrap

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our request in.

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So just going to say try, accept, exception

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as e, just as we've been doing before.

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And we'll also raise an HTTP exception, set

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the status code to 500.

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And for the description, we're going to return,

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set our details parameter, and we say, error,

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fetching weather, and give it a stringified

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version of that error.

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Good.

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Now to use our weather function in a tool

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call with the Gemini API, we need to add it

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to our request generation configuration.

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So let us write our generation configuration

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and add the weather tool to it.

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Come up here and say generation, config, and

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that will be types.generateContentConfig

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and

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we simply set its tools parameter and set

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it equal to a list because we can pass more

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our own tool but here we only have the getWeather

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function to pass.

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That's good.

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Now we can feed this to our Geminary API request.

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Next we need a prompt that properly instructs

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our model to use our tool and return a JSON

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response.

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And just as I've been doing with the other

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prompts, I'm going to be bringing it in from

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the completed version of the exercise files.

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So copy, paste.

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Now let us describe.

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This says, get the current weather for the

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destination, that is request.destination,

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as we have in our request model, and return

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the information in the following JSON structure.

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Use the getWeatherWrapper function to fake

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the data then format your response as valid

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JSON.

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I think we should make this getWeather not

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getWeatherWrapper.

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Yeah, getWeather function to fetch the data

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then format your response as valid JSON.

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Your response must be only in JSON with this

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exact structure.

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So inside the structure, we have a key for

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our weather data which is returned the same

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way we are returning data from our function

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and also we have a description that is just

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a summary that the model helps us to construct

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from all this weather information.

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So with that in place, we can now make our

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request.

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And for that, we'll simply just come down.

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And we can say response equals genai underscore

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client dot models dot generate content.

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And here we can feed this our model, set to

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our Gemini model constant.

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For our content, we have the prompt.

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And one more thing, we need our content generation

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configuration.

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We have defined that as generation config,

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so I'm just going to copy that and paste it

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down here good now just as we've been doing

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with the other responses would

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also need to clean up this response so I'm

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going to just grab all that code

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from here from the previous endpoint but just

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with some little changes so just

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grab it from here to here.

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That's good enough.

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Let's collapse this once again,

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expand this, come down here and continue writing

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our handler.

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So we clean up the

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response text, we strip it and finally what

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we need to do is to get our weather

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response and that will be json.loads

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and then we pass it that cleaned up response

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text.

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It's passed and because of the structure that

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this has been instructed

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to come with, which is a dictionary with another

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dictionary inside specifying

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weather data and also a key for the description,

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we can simply just return it as

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as is, and our frontend will be able to process

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that.

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Beautiful.

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We now have our weather endpoint that will

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help us retrieve weather information for destinations

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using Gemini and our custom tool.

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In the next video, we'll be integrating this

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endpoint with our frontend.