Merge pull request #4981 from aahill/agents-js

updating javascript code

Author: rmca14

articles/ai-services/agents/how-to/tools/azure-ai-search-samples.md

@@ -291,53 +291,37 @@ agentClient.Administration.DeleteAgent(agent.Id);
 First, create an Azure AI Client using the connection string of your project.
 
 ```javascript
-const connectionString =
-  process.env["AZURE_AI_PROJECTS_CONNECTION_STRING"] || "<project connection string>";
+const projectEndpoint = process.env["PROJECT_ENDPOINT"] || "<project connection string>";
 
-if (!connectionString) {
+if (!projectString) {
   throw new Error("AZURE_AI_PROJECTS_CONNECTION_STRING must be set in the environment variables");
 }
 
-const client = AIProjectsClient.fromConnectionString(
-    connectionString || "",
-    new DefaultAzureCredential(),
-);
-```
-
-## Get the connection ID for the Azure AI Search resource
-Get the connection ID of the Azure AI Search connection in the project.
-
-```javascript
-const cognitiveServicesConnectionName = "<cognitiveServicesConnectionName>";
-const cognitiveServicesConnection = await client.connections.getConnection(
-  cognitiveServicesConnectionName,
-);
+const client = new AgentsClient(projectEndpoint, new DefaultAzureCredential());
 ```
 
 ## Configure the Azure AI Search tool
-Using the connection ID you got in the previous step, you can now configure the Azure AI Search tool to use your Azure AI Search index.
+Using the connection ID of the Azure AI Search resource, configure the Azure AI Search tool to use your Azure AI Search index.
 
 ```javascript
-const azureAISearchTool = ToolUtility.createAzureAISearchTool(
-  cognitiveServicesConnection.id,
-  cognitiveServicesConnection.name,
-);
+const connectionId = process.env["AZURE_AI_CONNECTION_ID"] || "<connection-name>";
+
+const azureAISearchTool = ToolUtility.createAzureAISearchTool(connectionId, "ai-search-sample", {
+    queryType: "simple",
+    topK: 3,
+    filter: "",
+    indexConnectionId: "",
+    indexName: "",
+  });
 
-// Create agent with the Azure AI search tool
-const agent = await client.agents.createAgent("gpt-4o-mini", {
-  name: "my-agent",
-  instructions: "You are a helpful agent",
-  tools: [azureAISearchTool.definition],
-  toolResources: azureAISearchTool.resources,
-});
-console.log(`Created agent, agent ID : ${agent.id}`);
 ```
 
 ## Create an agent with the Azure AI Search tool enabled
 
 Change the model to the one deployed in your project. You can find the model name in the Azure AI Foundry under the **Models** tab. You can also change the name and instructions of the agent to suit your needs.
 
 ```javascript
+
 const agent = await client.agents.createAgent("gpt-4o-mini", {
   name: "my-agent",
   instructions: "You are a helpful agent",
@@ -352,60 +336,69 @@ console.log(`Created agent, agent ID : ${agent.id}`);
 Now that the agent is created, ask it questions about the data in your Azure AI Search index.
 
 ```javascript
-// create a thread
-const thread = await client.agents.createThread();
-
-// add a message to thread
-await client.agents.createMessage(
-  thread.id, {
-  role: "user",
-  content: "what are my health insurance plan coverage types?",
-});
+// Create thread for communication
+  const thread = await client.threads.create();
+  console.log(`Created thread, thread ID: ${thread.id}`);
+
+// Create message to thread
+const message = await client.messages.create(
+  thread.id,
+  "user",
+  "What is the temperature rating of the cozynights sleeping bag?",
+);
+console.log(`Created message, message ID : ${message.id}`);
 
-// Intermission is now correlated with thread
-// Intermission messages will retrieve the message just added
-
-// create a run
-const streamEventMessages = await client.agents.createRun(thread.id, agent.id).stream();
-
-for await (const eventMessage of streamEventMessages) {
-  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";
+// Create and process agent run in thread with tools
+let run = await client.runs.create(thread.id, agent.id);
+while (run.status === "queued" || run.status === "in_progress") {
+  await delay(1000);
+  run = await client.runs.get(thread.id, run.id);
+}
+if (run.status === "failed") {
+  console.log(`Run failed:`, JSON.stringify(run, null, 2));
+}
+console.log(`Run finished with status: ${run.status}`);
+
+// Fetch run steps to get the details of agent run
+const runSteps = await client.runSteps.list(thread.id, run.id);
+
+for await (const step of runSteps) {
+  console.log(`Step ID: ${step.id}, Status: ${step.status}`);
+  const stepDetails = step.stepDetails;
+  if (isOutputOfType(stepDetails, "tool_calls")) {
+    const toolCalls = stepDetails.toolCalls;
+    for (const toolCall of toolCalls) {
+      console.log(`Tool Call ID: ${toolCall.id}, Tool type: ${toolCall.type}`);
+      if (isOutputOfType(toolCall, "azure_ai_search")) {
+        {
+          const azureAISearch = toolCall.azureAISearch;
+          if (azureAISearch) {
+            console.log(`Azure AI Search Tool Call input: ${azureAISearch.input}`);
+            console.log(`Azure AI Search Tool Call output: ${azureAISearch.output}`);
           }
-        });
+        }
       }
-      break;
-
-    case RunStreamEvent.ThreadRunCompleted:
-      break;
-    case ErrorEvent.Error:
-      console.log(`An error occurred. Data ${eventMessage.data}`);
-      break;
-    case DoneEvent.Done:
-      break;
+    }
   }
 }
-
-// Print the messages from the agent
-const messages = await client.agents.listMessages(thread.id);
-
-// Messages iterate from oldest to newest
-// messages[0] is the most recent
-for (let i = messages.data.length - 1; i >= 0; i--) {
-  const m = messages.data[i];
-  if (isOutputOfType<MessageTextContentOutput>(m.content[0], "text")) {
-    const textContent = m.content[0];
-    console.log(`${textContent.text.value}`);
-    console.log(`---------------------------------`);
+// Delete the assistant when done
+await client.deleteAgent(agent.id);
+console.log(`Deleted agent, agent ID: ${agent.id}`);
+
+// Fetch and log all messages
+const messagesIterator = client.messages.list(thread.id);
+console.log(`Messages:`);
+
+// Get the first message
+for await (const m of messagesIterator) {
+  if (m.content.length > 0) {
+    const agentMessage = m.content[0];
+    if (isOutputOfType(agentMessage, "text")) {
+      const textContent = agentMessage;
+      console.log(`Text Message Content - ${textContent.text.value}`);
+    }
   }
+  break; // Just process the first message
 }
 ```
 

articles/ai-services/agents/how-to/tools/azure-functions-samples.md

@@ -10,7 +10,7 @@ ms.date: 01/30/2025
 author: aahill
 ms.author: aahi
 ms.custom: azure-ai-agents
-zone_pivot_groups: selection-function-calling-samples
+zone_pivot_groups: selection-azure-functions-samples
 ---
 
 # How to use Azure Functions with Azure AI Agents 
@@ -275,7 +275,7 @@ curl --request GET \
 
 ::: zone-end
 
-
+<!--
 ::: zone pivot="typescript"
 
 ## Define a function for your agent to call
@@ -309,7 +309,7 @@ For any issues with the TypeScript code, create an issue on the [sample code rep
 
 
 ::: zone-end
-
+-->
 ::: zone pivot="csharp"
 
 ## Prerequisites for .NET Azure Function Sample

articles/ai-services/agents/how-to/tools/bing-code-samples.md

@@ -285,16 +285,16 @@ agentClient.Administration.DeleteAgent(agentId: agent.Id);
 Create a client object, which will contain the connection string for connecting to your AI project and other resources.
 
 ```javascript
-const connectionString =
-  process.env["AZURE_AI_PROJECTS_CONNECTION_STRING"] || "<project connection string>";
+const { AgentsClient, ToolUtility, isOutputOfType } = require("@azure/ai-agents");
+const { delay } = require("@azure/core-util");
+const { DefaultAzureCredential } = require("@azure/identity");
 
-if (!connectionString) {
-  throw new Error("AZURE_AI_PROJECTS_CONNECTION_STRING must be set.");
-}
-const client = AIProjectsClient.fromConnectionString(
-    connectionString || "",
-    new DefaultAzureCredential(),
-);
+require("dotenv/config");
+
+const projectEndpoint = process.env["PROJECT_ENDPOINT"] || "<project connection string>";
+
+// Create an Azure AI Client
+const client = new AgentsClient(projectEndpoint, new DefaultAzureCredential());
 ```
 
 
@@ -303,12 +303,13 @@ const client = AIProjectsClient.fromConnectionString(
 To make the Grounding with Bing search tool available to your agent, use a connection to initialize the tool and attach it to the agent. You can find your connection in the **connected resources** section of your project in the [Azure AI Foundry portal](https://ai.azure.com/).
 
 ```javascript
-const bingGroundingConnectionId = "<bingGroundingConnectionId>";
-const bingTool = ToolUtility.createConnectionTool(connectionToolType.BingGrounding, [
-  bingGroundingConnectionId,
-]);
 
-const agent = await client.agents.createAgent("gpt-4o", {
+const connectionId = process.env["AZURE_BING_CONNECTION_ID"] || "<connection-name>";
+// Initialize agent bing tool with the connection id
+const bingTool = ToolUtility.createBingGroundingTool([{ connectionId: connectionId }]);
+
+// Create agent with the bing tool and process assistant run
+const agent = await client.createAgent("gpt-4o", {
   name: "my-agent",
   instructions: "You are a helpful agent",
   tools: [bingTool.definition],
@@ -319,15 +320,17 @@ console.log(`Created agent, agent ID : ${agent.id}`);
 ## Create a thread
 
 ```javascript
-// create a thread
-const thread = await client.agents.createThread();
-
-// add a message to thread
-await client.agents.createMessage(
-    thread.id, {
-    role: "user",
-    content: "What is the weather in Seattle?",
-});
+// Create thread for communication
+const thread = await client.threads.create();
+console.log(`Created thread, thread ID: ${thread.id}`);
+
+// Create message to thread
+const message = await client.messages.create(
+  thread.id,
+  "user",
+  "How does wikipedia explain Euler's Identity?",
+);
+console.log(`Created message, message ID : ${message.id}`);
 ```
 
 ## Create a run and check the output
@@ -337,48 +340,35 @@ Create a run and observe that the model uses the Grounding with Bing Search tool
 
 ```javascript
 
-  // create a run
-  const streamEventMessages = await client.agents.createRun(thread.id, agent.id).stream();
-
-  for await (const eventMessage of streamEventMessages) {
-    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;
-    }
+// Create and process agent run in thread with tools
+let run = await client.runs.create(thread.id, agent.id);
+while (run.status === "queued" || run.status === "in_progress") {
+  await delay(1000);
+  run = await client.runs.get(thread.id, run.id);
+}
+if (run.status === "failed") {
+  console.log(`Run failed: ${run.lastError?.message}`);
+}
+console.log(`Run finished with status: ${run.status}`);
+
+// Delete the assistant when done
+await client.deleteAgent(agent.id);
+console.log(`Deleted agent, agent ID: ${agent.id}`);
+
+// Fetch and log all messages
+const messagesIterator = client.messages.list(thread.id);
+console.log(`Messages:`);
+
+// Get the first message
+const firstMessage = await messagesIterator.next();
+if (!firstMessage.done && firstMessage.value) {
+  const agentMessage = firstMessage.value.content[0];
+  if (isOutputOfType(agentMessage, "text")) {
+    const textContent = agentMessage;
+    console.log(`Text Message Content - ${textContent.text.value}`);
   }
+}
 
-  // Print the messages from the agent
-  const messages = await client.agents.listMessages(thread.id);
-
-  // Messages iterate from oldest to newest
-  // messages[0] is the most recent
-  for (let i = messages.data.length - 1; i >= 0; i--) {
-    const m = messages.data[i];
-    if (isOutputOfType<MessageTextContentOutput>(m.content[0], "text")) {
-      const textContent = m.content[0];
-      console.log(`${textContent.text.value}`);
-      console.log(`---------------------------------`);
-    }
-  }
 ```
 
 ::: zone-end

articles/ai-services/agents/how-to/tools/bing-custom-search-samples.md

@@ -252,6 +252,7 @@ agentClient.DeleteAgent(agentId: agent.Id);
 
 :::zone-end
 
+<!--
 ::: zone pivot="javascript"
 
 ## Create a project client
@@ -372,7 +373,7 @@ Create a run and observe that the model uses the Grounding with Bing Custom Sear
 ```
 
 :::zone-end
-
+-->
 
 ::: zone pivot="rest"