Fabric and Sharepoint samples (#32033)

Co-authored-by: Grace Brigham <[email protected]>

sdk/ai/ai-projects/review/ai-projects.api.md

@@ -275,7 +275,7 @@ export interface ConnectionsOperations {
 export enum connectionToolType {
     BingGrounding = "bing_grounding",
     MicrosoftFabric = "microsoft_fabric",
-    SharePointGrounding = "sharepoint_grounding"
+    SharepointGrounding = "sharepoint_grounding"
 }
 
 // @public

sdk/ai/ai-projects/samples-dev/agents/agents_fabric.ts

@@ -0,0 +1,91 @@
+// Copyright (c) Microsoft Corporation.
+// Licensed under the MIT License.
+
+/**
+ * 
+ * FILE: agents_fabric.ts
+ *
+ * DESCRIPTION:
+ *  This sample demonstrates how to use agent operations with the Microsoft Fabric tool from
+ *  the Azure Agents service using a asynchronous client.
+ *
+ * USAGE:
+ *  npx ts-node agents_fabric.ts
+ *
+ *  Before running the sample:
+ *
+ *  npm install @azure/ai-projects @azure/identity @azure/core-util dotenv
+ *
+ *  Set this environment variables with your own values:
+ *  AZURE_AI_PROJECTS_CONNECTION_STRING - the Azure AI Project connection string, as found in your AI Studio Project
+ *  FABRIC_CONNECTION_NAME
+ */
+
+import { AIProjectsClient, fromConnectionId, connectionToolType, MessageContentOutput, isOutputOfType, MessageTextContentOutput } from "@azure/ai-projects";
+import { delay } from "@azure/core-util";
+import { DefaultAzureCredential } from "@azure/identity";
+
+import * as dotenv from "dotenv";
+dotenv.config();
+
+const connectionString = process.env["AZURE_AI_PROJECTS_CONNECTION_STRING"] || "<endpoint>>;<subscription>;<resource group>;<project>";
+
+export async function main(): Promise<void> {
+  // Create an Azure AI Client from a connection string, copied from your AI Studio project.
+  // At the moment, it should be in the format "<HostName>;<AzureSubscriptionId>;<ResourceGroup>;<HubName>"
+  // Customer needs to login to Azure subscription via Azure CLI and set the environment variables
+  const client = AIProjectsClient.fromConnectionString(connectionString || "", new DefaultAzureCredential());
+  const fabricConnection = await client.connections.getConnection(process.env["FABRIC_CONNECTION_NAME"] || "<connection-name>");
+  const connectionId = fabricConnection.id;
+
+  // Initialize agent Microsoft Fabric tool with the connection id
+  const fabricTool = fromConnectionId(connectionToolType.MicrosoftFabric, [connectionId]);
+
+  // Create agent with the Microsoft Fabric tool and process assistant run
+  const agent  = await client.agents.createAgent(
+    "gpt-4-0125-preview", {
+      name: "my-agent", 
+      instructions: "You are a helpful agent",
+      tools: [fabricTool]
+    }, {
+      headers: {"x-ms-enable-preview": "true"}
+    });
+  console.log(connectionId)
+  console.log(`Created agent, agent ID : ${agent.id}`);
+
+  // Create thread for communication
+  const thread = await client.agents.createThread()
+  console.log(`Created thread, thread ID: ${thread.id}`);
+
+  // Create message to thread
+  const message = await client.agents.createMessage(thread.id, {role: "user", content: "What inventory is currently available?"});
+  console.log(`Created message, message ID: ${message.id}`);
+
+  // Create and process agent run in thread with tools
+  let run = await client.agents.createRun(thread.id, agent.id);
+  while (run.status === "queued" || run.status === "in_progress") {
+    await delay(1000);
+    run = await client.agents.getRun(thread.id, run.id);
+  }
+  if (run.status === "failed") {
+      console.log(`Run failed: ${run.last_error}`);
+  }
+  console.log(`Run finished with status: ${run.status}`);
+
+  // Delete the assistant when done
+  client.agents.deleteAgent(agent.id)
+  console.log(`Deleted agent, agent ID: ${agent.id}`);
+
+  // Fetch and log all messages
+  const messages = await client.agents.listMessages(thread.id)
+  console.log(`Messages:`);
+  const agentMessage: MessageContentOutput = messages.data[0].content[0];
+  if (isOutputOfType<MessageTextContentOutput>(agentMessage, "text")) {
+    const textContent = agentMessage as MessageTextContentOutput;
+    console.log(`Text Message Content - ${textContent.text.value}`);
+  }
+}
+
+main().catch((err) => {
+  console.error("The sample encountered an error:", err);
+});

sdk/ai/ai-projects/samples-dev/agents/agents_sharepoint.ts

@@ -0,0 +1,91 @@
+// Copyright (c) Microsoft Corporation.
+// Licensed under the MIT License.
+
+/**
+ * 
+ * FILE: agents_sharepoint.ts
+ *
+ * DESCRIPTION:
+ *  This sample demonstrates how to use agent operations with the Sharepoint tool from
+ *  the Azure Agents service using a asynchronous client.
+ *
+ * USAGE:
+ *  npx ts-node agents_sharepoint.ts
+ *
+ *  Before running the sample:
+ *
+ *  npm install @azure/ai-projects @azure/identity @azure/core-util dotenv
+ *
+ *  Set this environment variables with your own values:
+ *  AZURE_AI_PROJECTS_CONNECTION_STRING - the Azure AI Project connection string, as found in your AI Studio Project
+ *  SHAREPOINT_CONNECTION_NAME
+ */
+
+import { AIProjectsClient, fromConnectionId, connectionToolType, MessageContentOutput, isOutputOfType, MessageTextContentOutput } from "@azure/ai-projects";
+import { delay } from "@azure/core-util";
+import { DefaultAzureCredential } from "@azure/identity";
+
+import * as dotenv from "dotenv";
+dotenv.config();
+
+const connectionString = process.env["AZURE_AI_PROJECTS_CONNECTION_STRING"] || "<endpoint>>;<subscription>;<resource group>;<project>";
+
+export async function main(): Promise<void> {
+  // Create an Azure AI Client from a connection string, copied from your AI Studio project.
+  // At the moment, it should be in the format "<HostName>;<AzureSubscriptionId>;<ResourceGroup>;<HubName>"
+  // Customer needs to login to Azure subscription via Azure CLI and set the environment variables
+  const client = AIProjectsClient.fromConnectionString(connectionString || "", new DefaultAzureCredential());
+  const sharepointConnection = await client.connections.getConnection(process.env["SHAREPOINT_CONNECTION_NAME"] || "<connection-name>");
+  const connectionId = sharepointConnection.id;
+
+  // Initialize agent Sharepoint tool with the connection id
+  const sharepointTool = fromConnectionId(connectionToolType.SharepointGrounding, [connectionId]);
+
+  // Create agent with the Sharepoint tool and process assistant run
+  const agent  = await client.agents.createAgent(
+    "gpt-4-0125-preview", {
+      name: "my-agent", 
+      instructions: "You are a helpful agent",
+      tools: [sharepointTool]
+    }, {
+      headers: {"x-ms-enable-preview": "true"}
+    });
+  console.log(connectionId)
+  console.log(`Created agent, agent ID : ${agent.id}`);
+
+  // Create thread for communication
+  const thread = await client.agents.createThread()
+  console.log(`Created thread, thread ID: ${thread.id}`);
+
+  // Create message to thread
+  const message = await client.agents.createMessage(thread.id, {role: "user", content: "Hello, tell me about my health insurance options"});
+  console.log(`Created message, message ID: ${message.id}`);
+
+  // Create and process agent run in thread with tools
+  let run = await client.agents.createRun(thread.id, agent.id);
+  while (run.status === "queued" || run.status === "in_progress") {
+    await delay(1000);
+    run = await client.agents.getRun(thread.id, run.id);
+  }
+  if (run.status === "failed") {
+      console.log(`Run failed: ${run.last_error}`);
+  }
+  console.log(`Run finished with status: ${run.status}`);
+
+  // Delete the assistant when done
+  client.agents.deleteAgent(agent.id)
+  console.log(`Deleted agent, agent ID: ${agent.id}`);
+
+  // Fetch and log all messages
+  const messages = await client.agents.listMessages(thread.id)
+  console.log(`Messages:`);
+  const agentMessage: MessageContentOutput = messages.data[0].content[0];
+  if (isOutputOfType<MessageTextContentOutput>(agentMessage, "text")) {
+    const textContent = agentMessage as MessageTextContentOutput;
+    console.log(`Text Message Content - ${textContent.text.value}`);
+  }
+}
+
+main().catch((err) => {
+  console.error("The sample encountered an error:", err);
+});

sdk/ai/ai-projects/src/agents/utils.ts

@@ -36,7 +36,7 @@ export enum connectionToolType {
   /** Microsoft Fabric tool */
   MicrosoftFabric = "microsoft_fabric",
   /** Sharepoint tool */
-  SharePointGrounding = "sharepoint_grounding",
+  SharepointGrounding = "sharepoint_grounding",
 }
 
 /**