chore: import upstream snapshot with attribution
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import ModelClient from "@azure-rest/ai-inference";
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import { AzureKeyCredential } from "@azure/core-auth";
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// Get these from your Microsoft Foundry project's "Overview" page
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// (GitHub Models is retiring end of July 2026 - see https://ai.azure.com/catalog/models)
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const token = process.env["AZURE_INFERENCE_CREDENTIAL"];
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if (!token) {
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throw new Error("AZURE_INFERENCE_CREDENTIAL environment variable is required. Please set it before running this application.");
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}
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const endpoint = process.env["AZURE_INFERENCE_ENDPOINT"];
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if (!endpoint) {
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throw new Error("AZURE_INFERENCE_ENDPOINT environment variable is required. Please set it before running this application.");
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}
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/* By using the Azure AI Inference SDK, you can easily experiment with different models
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by modifying the value of `modelName` in the code below. For this code sample
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you need a model supporting tools. The following compatible models are
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available in the Microsoft Foundry Models catalog:
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Cohere: Cohere-command-r-08-2024, Cohere-command-r-plus-08-2024
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Mistral AI: Mistral-large-2411, Mistral-small-2503
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OpenAI: gpt-4o-mini, gpt-4o, gpt-4.1, gpt-4.1-mini */
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const modelName = "gpt-4o-mini";
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function getFlightInfo({ originCity, destinationCity }) {
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if (originCity === "Seattle" && destinationCity === "Miami") {
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return JSON.stringify({
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airline: "Delta",
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flight_number: "DL123",
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flight_date: "May 7th, 2024",
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flight_time: "10:00AM"
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});
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}
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return JSON.stringify({ error: "No flights found between the cities" });
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}
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function getHotelInfo({ destination }) {
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if ( destination === "Miami") {
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return JSON.stringify({
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hotelName: "Contoso Suites"
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});
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}
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return JSON.stringify({ error: "No available hotels found in this city" });
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}
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const namesToFunctions = {
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getFlightInfo: (data) =>
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getFlightInfo(data),
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getHotelInfo: (data) =>
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getHotelInfo(data)
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};
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export async function main() {
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const tool = {
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"type": "function",
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"function": {
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name: "getFlightInfo",
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description: "Returns information about the next flight between two cities." +
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"This includes the name of the airline, flight number and the date and time" +
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"of the next flight",
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parameters: {
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"type": "object",
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"properties": {
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"originCity": {
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"type": "string",
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"description": "The name of the city where the flight originates",
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},
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"destinationCity": {
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"type": "string",
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"description": "The flight destination city",
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},
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},
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"required": [
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"originCity",
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"destinationCity"
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],
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},
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}
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};
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const hotels ={
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"type": "function",
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"function": {
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name: "getHotelInfo",
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description: "Returns information about the hotel of the destination city.",
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parameters: {
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"type": "object",
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"properties": {
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"destination": {
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"type": "string",
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"description": "The city that the traveller would like to stay",
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},
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},
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"required": [
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"destination"
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],
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},
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}
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}
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const client = new ModelClient(endpoint, new AzureKeyCredential(token));
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let messages = [
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{ role: "system", content: "You an assistant that helps users find flight and hotel information." },
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{ role: "user", content: "I'm interested in going to Miami and staying in a hotel." },
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// { role: "user", content: "I'm interested in going to Seattle. Are there flights to Denver?" },
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];
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let response = await client.path("/chat/completions").post({
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body: {
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messages: messages,
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tools: [tool, hotels],
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model: modelName
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}
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});
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if (response.status !== "200") {
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throw response.body.error;
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}
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// We expect the model to ask for a tool call
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if (response.body.choices[0].finish_reason === "tool_calls") {
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// Append the model response to the chat history
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messages.push(response.body.choices[0].message);
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// We expect a single tool call
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if (response.body.choices[0].message && response.body.choices[0].message.tool_calls.length === 1) {
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const toolCall = response.body.choices[0].message.tool_calls[0];
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// We expect the tool to be a function call
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if (toolCall.type === "function") {
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const toolCall = response.body.choices[0].message.tool_calls[0];
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// SECURITY: Validate function name exists in allowed functions map
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const functionName = toolCall.function.name;
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if (!Object.prototype.hasOwnProperty.call(namesToFunctions, functionName)) {
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throw new Error(`Unknown function requested: ${functionName}. Only allowed functions are: ${Object.keys(namesToFunctions).join(', ')}`);
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}
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// SECURITY: Safely parse JSON with error handling
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let functionArgs;
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try {
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functionArgs = JSON.parse(toolCall.function.arguments);
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} catch (parseError) {
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throw new Error(`Failed to parse function arguments: ${parseError.message}`);
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}
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// Log function call (avoid logging sensitive data in production)
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console.log(`Calling function \`${functionName}\` with arguments ${toolCall.function.arguments}`);
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const callableFunc = namesToFunctions[functionName];
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const functionReturn = callableFunc(functionArgs);
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console.log(`Function returned = ${functionReturn}`);
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// Append the function call result fo the chat history
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messages.push(
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{
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"tool_call_id": toolCall.id,
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"role": "tool",
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"name": toolCall.function.name,
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"content": functionReturn,
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}
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)
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response = await client.path("/chat/completions").post({
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body: {
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messages: messages,
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tools: [tool, hotels],
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model: modelName
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}
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});
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if (response.status !== "200") {
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throw response.body.error;
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}
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console.log(`Model response = ${response.body.choices[0].message.content}`);
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}
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}
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}
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}
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main().catch((err) => {
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console.error("The sample encountered an error:", err);
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});
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