added function calling gh models lesson

11-integrating-with-function-calling/js-githubmodels/app.js

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+import ModelClient from "@azure-rest/ai-inference";
+import { AzureKeyCredential } from "@azure/core-auth";
+
+const token = process.env["GITHUB_TOKEN"];
+const endpoint = "https://models.inference.ai.azure.com";
+
+/* By using the Azure AI Inference SDK, you can easily experiment with different models
+   by modifying the value of `modelName` in the code below. For this code sample
+   you need a model supporting tools. The following compatible models are
+   available in the GitHub Models service:
+
+   Cohere: Cohere-command-r, Cohere-command-r-plus
+   Mistral AI: Mistral-large, Mistral-large-2407, Mistral-Nemo, Mistral-small
+   Azure OpenAI: gpt-4o-mini, gpt-4o */
+const modelName = "gpt-4o";
+
+function getFlightInfo({ originCity, destinationCity }) {
+    if (originCity === "Seattle" && destinationCity === "Miami") {
+        return JSON.stringify({
+            airline: "Delta",
+            flight_number: "DL123",
+            flight_date: "May 7th, 2024",
+            flight_time: "10:00AM"
+        });
+    }
+    return JSON.stringify({ error: "No flights found between the cities" });
+}
+
+function getHotelInfo({ destination }) {
+    if ( destination === "Miami") {
+        return JSON.stringify({
+            hotelName: "Contoso Suites"
+        });
+    }
+    return JSON.stringify({ error: "No available hotels found in this city" });
+}
+
+const namesToFunctions = {
+    getFlightInfo: (data) =>
+        getFlightInfo(data),
+    getHotelInfo: (data) =>
+        getHotelInfo(data)
+};
+
+export async function main() {
+
+    const tool = {
+        "type": "function",
+        "function": {
+            name: "getFlightInfo",
+            description: "Returns information about the next flight between two cities." +
+                "This includes the name of the airline, flight number and the date and time" +
+                "of the next flight",
+            parameters: {
+                "type": "object",
+                "properties": {
+                    "originCity": {
+                        "type": "string",
+                        "description": "The name of the city where the flight originates",
+                    },
+                    "destinationCity": {
+                        "type": "string",
+                        "description": "The flight destination city",
+                    },
+                },
+                "required": [
+                    "originCity",
+                    "destinationCity"
+                ],
+            },
+
+        }
+    };
+
+    const hotels ={
+    "type": "function",
+        "function": {
+        name: "getHotelInfo",
+            description: "Returns information about the hotel of the destination city.",
+                parameters: {
+            "type": "object",
+                "properties": {
+                "destination": {
+                    "type": "string",
+                        "description": "The city that the traveller would like to stay",
+                    },
+            },
+            "required": [
+                "destination"
+            ],
+            },
+        }
+
+    }
+
+    const client = new ModelClient(endpoint, new AzureKeyCredential(token));
+
+    let messages = [
+        { role: "system", content: "You an assistant that helps users find flight and hotel information." },
+        { role: "user", content: "I'm interested in going to Miami and staying in a hotel." },
+        // { role: "user", content: "I'm interested in going to Seattle. Are there flights to Denver?" },
+
+
+
+
+    ];
+
+    let response = await client.path("/chat/completions").post({
+        body: {
+            messages: messages,
+            tools: [tool, hotels],
+            model: modelName
+        }
+    });
+    if (response.status !== "200") {
+        throw response.body.error;
+    }
+
+    // We expect the model to ask for a tool call
+    if (response.body.choices[0].finish_reason === "tool_calls") {
+
+        // Append the model response to the chat history
+        messages.push(response.body.choices[0].message);
+
+        // We expect a single tool call
+        if (response.body.choices[0].message && response.body.choices[0].message.tool_calls.length === 1) {
+
+            const toolCall = response.body.choices[0].message.tool_calls[0];
+            // We expect the tool to be a function call
+            if (toolCall.type === "function") {
+                const toolCall = response.body.choices[0].message.tool_calls[0];
+                // Parse the function call arguments and call the function
+                const functionArgs = JSON.parse(toolCall.function.arguments);
+                console.log(`Calling function \`${toolCall.function.name}\` with arguments ${toolCall.function.arguments}`);
+                const callableFunc = namesToFunctions[toolCall.function.name];
+                const functionReturn = callableFunc(functionArgs);
+                console.log(`Function returned = ${functionReturn}`);
+
+                // Append the function call result fo the chat history
+                messages.push(
+                    {
+                        "tool_call_id": toolCall.id,
+                        "role": "tool",
+                        "name": toolCall.function.name,
+                        "content": functionReturn,
+                    }
+                )
+
+                response = await client.path("/chat/completions").post({
+                    body: {
+                        messages: messages,
+                        tools: [tool, hotels],
+                        model: modelName
+                    }
+                });
+                if (response.status !== "200") {
+                    throw response.body.error;
+                }
+                console.log(`Model response = ${response.body.choices[0].message.content}`);
+            }
+        }
+    }
+}
+
+main().catch((err) => {
+    console.error("The sample encountered an error:", err);
+});