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adding openapi
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‎articles/ai-services/agents/how-to/tools/openapi-spec-samples.md

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@@ -42,107 +42,6 @@ Use this article to find step-by-step instructions and code samples for using Op
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:::zone-end
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:::zone-pivot="javascript"
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## Create a project client
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Create a client object that contains the connection string for connecting to your AI project and other resources.
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```javascript
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const { AgentsClient, isOutputOfType, ToolUtility } = require("@azure/ai-agents");
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const { delay } = require("@azure/core-util");
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const { DefaultAzureCredential } = require("@azure/identity");
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const fs = require("fs");
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require("dotenv/config");
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const projectEndpoint = process.env["PROJECT_ENDPOINT"] || "<project connection string>";
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// Create an Azure AI Client
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const client = new AgentsClient(projectEndpoint, new DefaultAzureCredential());
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```
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## Read in the OpenAPI spec
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```javascript
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// Read in OpenApi spec
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const filePath = "./data/weatherOpenApi.json";
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const openApiSpec = JSON.parse(fs.readFileSync(filePath, "utf-8"));
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// Define OpenApi function
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const openApiFunction = {
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name: "getWeather",
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spec: openApiSpec,
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description: "Retrieve weather information for a location",
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auth: {
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type: "anonymous",
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},
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default_params: ["format"], // optional
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};
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```
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## Create an agent and enable the OpenAPI tool
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```javascript
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// Create OpenApi tool
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const openApiTool = ToolUtility.createOpenApiTool(openApiFunction);
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// Create agent with OpenApi tool
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const agent = await client.createAgent(modelDeploymentName, {
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name: "myAgent",
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instructions: "You are a helpful agent",
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tools: [openApiTool.definition],
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});
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console.log(`Created agent, agent ID: ${agent.id}`);
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```
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## Create a thread
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```javascript
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// Create a thread
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const thread = await client.threads.create();
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console.log(`Created thread, thread ID: ${thread.id}`);
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// Create a message
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const message = await client.messages.create(thread.id, "user", "What's the weather in Seattle?");
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console.log(`Created message, message ID: ${message.id}`);
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```
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## Create a run and check the output
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```javascript
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// Create and execute a run
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let run = await client.runs.create(thread.id, agent.id);
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while (run.status === "queued" || run.status === "in_progress") {
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await delay(1000);
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run = await client.runs.get(thread.id, run.id);
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}
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if (run.status === "failed") {
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// Check if you got "Rate limit is exceeded.", then you want to get more quota
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console.log(`Run failed: ${run.lastError}`);
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}
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console.log(`Run finished with status: ${run.status}`);
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// Get most recent message from the assistant
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const messagesIterator = client.messages.list(thread.id);
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const messages = [];
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for await (const m of messagesIterator) {
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messages.push(m);
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}
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const assistantMessage = messages.find((msg) => msg.role === "assistant");
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if (assistantMessage) {
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const textContent = assistantMessage.content.find((content) => isOutputOfType(content, "text"));
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if (textContent) {
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console.log(`Last message: ${textContent.text.value}`);
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}
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}
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// Delete the agent once done
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await client.deleteAgent(agent.id);
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console.log(`Deleted agent, agent ID: ${agent.id}`);
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```
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:::zone-end
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:::zone pivot="python"
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## Initialization
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:::zone-end
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:::zone-pivot="javascript"
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## Create a project client
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Create a client object that contains the connection string for connecting to your AI project and other resources.
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```javascript
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const { AgentsClient, isOutputOfType, ToolUtility } = require("@azure/ai-agents");
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const { delay } = require("@azure/core-util");
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const { DefaultAzureCredential } = require("@azure/identity");
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const fs = require("fs");
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require("dotenv/config");
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const projectEndpoint = process.env["PROJECT_ENDPOINT"] || "<project connection string>";
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// Create an Azure AI Client
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const client = new AgentsClient(projectEndpoint, new DefaultAzureCredential());
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```
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## Read in the OpenAPI spec
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```javascript
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// Read in OpenApi spec
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const filePath = "./data/weatherOpenApi.json";
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const openApiSpec = JSON.parse(fs.readFileSync(filePath, "utf-8"));
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// Define OpenApi function
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const openApiFunction = {
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name: "getWeather",
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spec: openApiSpec,
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description: "Retrieve weather information for a location",
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auth: {
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type: "anonymous",
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},
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default_params: ["format"], // optional
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};
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```
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## Create an agent and enable the OpenAPI tool
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```javascript
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// Create OpenApi tool
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const openApiTool = ToolUtility.createOpenApiTool(openApiFunction);
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// Create agent with OpenApi tool
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const agent = await client.createAgent(modelDeploymentName, {
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name: "myAgent",
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instructions: "You are a helpful agent",
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tools: [openApiTool.definition],
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});
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console.log(`Created agent, agent ID: ${agent.id}`);
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```
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## Create a thread
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```javascript
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// Create a thread
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const thread = await client.threads.create();
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console.log(`Created thread, thread ID: ${thread.id}`);
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// Create a message
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const message = await client.messages.create(thread.id, "user", "What's the weather in Seattle?");
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console.log(`Created message, message ID: ${message.id}`);
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```
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## Create a run and check the output
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```javascript
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// Create and execute a run
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let run = await client.runs.create(thread.id, agent.id);
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while (run.status === "queued" || run.status === "in_progress") {
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await delay(1000);
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run = await client.runs.get(thread.id, run.id);
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}
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if (run.status === "failed") {
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// Check if you got "Rate limit is exceeded.", then you want to get more quota
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console.log(`Run failed: ${run.lastError}`);
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}
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console.log(`Run finished with status: ${run.status}`);
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// Get most recent message from the assistant
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const messagesIterator = client.messages.list(thread.id);
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const messages = [];
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for await (const m of messagesIterator) {
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messages.push(m);
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}
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const assistantMessage = messages.find((msg) => msg.role === "assistant");
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if (assistantMessage) {
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const textContent = assistantMessage.content.find((content) => isOutputOfType(content, "text"));
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if (textContent) {
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console.log(`Last message: ${textContent.text.value}`);
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}
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}
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// Delete the agent once done
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await client.deleteAgent(agent.id);
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console.log(`Deleted agent, agent ID: ${agent.id}`);
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```
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:::zone-end
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:::zone pivot="csharp"
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## Configure client and OpenAPI tool

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