Update JS agents code + enhance output formatting

samples/microsoft/javascript/mslearn-resources/quickstart/src/quickstart.js

@@ -1,17 +1,21 @@
+import fs from 'fs';
+import path from 'path';
+import { fileURLToPath } from 'url';
 import { DefaultAzureCredential } from '@azure/identity';
 import { AIProjectClient } from '@azure/ai-projects';
-import { AgentsClient } from '@azure/ai-agents';
+import { AgentsClient, ToolUtility, DoneEvent, ErrorEvent, RunStreamEvent, MessageStreamEvent } from '@azure/ai-agents';
 import { config } from 'dotenv';
 config();
 
+const __dirname = path.dirname(fileURLToPath(import.meta.url));
+
 async function chatCompletion() {
     // <chat_completion>
     const endpoint = process.env.INFERENCE_ENDPOINT;
     const deployment = process.env.MODEL_DEPLOYMENT_NAME || 'gpt-4o';
     const project = new AIProjectClient(endpoint, new DefaultAzureCredential());
 
     const client = project.inference.azureOpenAI();
-
     const chatCompletion = await client.chat.completions.create({
         deployment,
         messages: [
@@ -24,9 +28,9 @@ async function chatCompletion() {
     // </chat_completion>
 }
 
-chatCompletion().catch(console.error);
+// chatCompletion().catch(console.error);
 
-async function runAgent() {
+async function runAgents() {
     // <create_and_run_agent>
 
     // Create an Azure AI Client
@@ -39,36 +43,140 @@ async function runAgent() {
         name: 'my-agent',
         instructions: 'You are a helpful agent',
     });
+    console.log(`\n==================== 🕵️  POEM AGENT ====================`);
 
-    // Create a thread and mesage
+    // Create a thread and message
     const thread = await client.createThread();
-    const message = await client.createMessage(thread.id, 'user', 'hello, world!');
-
-    console.log(`Created message, message ID: ${message.id}`);
+    const prompt = 'Write me a poem about flowers';
+    console.log(`\n---------------- 📝 User Prompt ---------------- \n${prompt}`);
+    await client.createMessage(thread.id, 'user', prompt);
 
     // Create run
     let run = await client.createRun(thread.id, agent.id);
-    console.log(`Usage for run ${run.id}:`, JSON.stringify(run.usage, null, 2));
 
     // Wait for run to complete
+    console.log(`\n---------------- 🚦 Run Status ----------------`);
     while (['queued', 'in_progress', 'requires_action'].includes(run.status)) {
+        // Avoid adding a lot of messages to the console
         await new Promise((resolve) => setTimeout(resolve, 1000));
         run = await client.getRun(thread.id, run.id);
         console.log(`Run status: ${run.status}`);
     }
 
-    console.log(`Usage for run ${run.id}:`, JSON.stringify(run.usage, null, 2));
+    console.log('\n---------------- 📊 Token Usage ----------------');
+    console.table([run.usage]);
+
+    const messages = await client.listMessages(thread.id);
+    const assistantMessage = messages.data.find(m => m.role === 'assistant');
+    console.log('\n---------------- 💬 Response ----------------');
+    printAssistantMessage(assistantMessage);
 
     // Delete the Agent
     await client.deleteAgent(agent.id);
     console.log(`Deleted Agent, Agent ID: ${agent.id}`);
+
     // </create_and_run_agent>
 
     // <create_filesearch_agent> 
 
-    // Create the file search agent
-
+    // Upload a file named product_info_1.md
+    console.log(`\n==================== 🕵️  FILE AGENT ====================`);
+    const filePath = path.join(__dirname, '../../../../data/product_info_1.md');
+    const fileStream = fs.createReadStream(filePath);
+    const file = await client.uploadFile(fileStream, 'assistants', {
+        fileName: 'product_info_1.md'
+    });
+    console.log(`Uploaded file, ID: ${file.id}`);
+    const vectorStore = await client.createVectorStore({
+        fileIds: [file.id],
+        name: 'my_vectorstore'
+    });
+    console.log('\n---------------- 🗃️ Vector Store Info ----------------');
+    console.table([
+        {
+            'Vector Store ID': vectorStore.id,
+            'Usage (bytes)': vectorStore.usageBytes,
+            'File Count': vectorStore.fileCounts?.total ?? 'N/A'
+        }
+    ]);
+
+    // Create an Agent and a FileSearch tool
+    const fileSearchTool = ToolUtility.createFileSearchTool([vectorStore.id]);
+    const fileAgent = await client.createAgent(deployment, {
+        name: 'my-file-agent',
+        instructions: 'You are a helpful assistant and can search information from uploaded files',
+        tools: [fileSearchTool.definition],
+        toolResources: fileSearchTool.resources,
+    });
+
+    // Create a thread and message
+    const fileSearchThread = await client.createThread({ toolResources: fileSearchTool.resources });
+    const filePrompt = 'What are the steps to setup the TrailMaster X4 Tent?';
+    console.log(`\n---------------- 📝 User Prompt ---------------- \n${filePrompt}`);
+    await client.createMessage(fileSearchThread.id, 'user', filePrompt);
+
+    // Create run
+    let fileSearchRun = await client.createRun(fileSearchThread.id, fileAgent.id).stream();
+
+    for await (const eventMessage of fileSearchRun) {
+        switch (eventMessage.event) {
+            case RunStreamEvent.ThreadRunCreated:
+                break;
+            case MessageStreamEvent.ThreadMessageDelta:
+                {
+                    const messageDelta = eventMessage.data;
+                    messageDelta.delta.content.forEach((contentPart) => {
+                        if (contentPart.type === "text") {
+                            const textContent = contentPart;
+                            const textValue = textContent.text?.value || "No text";
+                        }
+                    });
+                }
+                break;
+
+            case RunStreamEvent.ThreadRunCompleted:
+                break;
+            case ErrorEvent.Error:
+                console.log(`An error occurred. Data ${eventMessage.data}`);
+                break;
+            case DoneEvent.Done:
+                break;
+        }
+    }
+
+    const fileSearchMessages = await client.listMessages(fileSearchThread.id);
+    const fileAssistantMessage = fileSearchMessages.data.find(m => m.role === 'assistant');
+    console.log(`\n---------------- 💬 Response ---------------- \n`);
+    printAssistantMessage(fileAssistantMessage);
+
+    client.deleteVectorStore(vectorStore.id);
+    client.deleteFile(file.id);
+    client.deleteAgent(fileAgent.id);
+    console.log(`\n🧹 Deleted VectorStore, File, and FileAgent. FileAgent ID: ${fileAgent.id}`);
+
     // </create_filesearch_agent>
 }
 
-runAgent().catch(console.error);
+runAgents().catch(console.error);
+
+// Helper function to print assistant message content nicely (handles nested text.value)
+function printAssistantMessage(message) {
+    if (!message || !Array.isArray(message.content)) {
+        console.log('No assistant message found or content is not in expected format.');
+        return;
+    }
+    let output = message.content.map(c => {
+        if (typeof c.text === 'object' && c.text.value) {
+            return c.text.value;
+        } else if (typeof c.text === 'string') {
+            return c.text;
+        } else {
+            return JSON.stringify(c);
+        }
+    }).join('');
+    if (typeof output !== 'string') {
+        console.log('Value is not a string:', output);
+        return;
+    }
+    output.split('\n').forEach(line => console.log(line));
+}