removing conncetions tring and openai sdk

Author: aahill

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

@@ -320,10 +320,10 @@ agentClient.Administration.DeleteAgent(agent.Id);
 :::zone pivot="javascript"
 
 ## Create an Azure AI Client
-First, create an Azure AI Client using the connection string of your project.
+First, create an Azure AI Client using the endpoint your project.
 
 ```javascript
-const projectEndpoint = process.env["PROJECT_ENDPOINT"] || "<project connection string>";
+const projectEndpoint = process.env["PROJECT_ENDPOINT"];
 
 if (!projectString) {
   throw new Error("AZURE_AI_PROJECTS_CONNECTION_STRING must be set in the environment variables");

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

@@ -49,7 +49,7 @@ Use this article to find step-by-step instructions and code samples for Groundin
 
 ## Create a project client
 
-Create a client object, which will contain the connection string for connecting to your AI project and other resources.
+Create a client object, which will contain the endpoint for connecting to your AI project and other resources.
 
 ```python
 import os
@@ -315,7 +315,7 @@ agentClient.Administration.DeleteAgent(agentId: agent.Id);
 
 ## Create a project client
 
-Create a client object, which will contain the connection string for connecting to your AI project and other resources.
+Create a client object, which will contain the endpoint for connecting to your AI project and other resources.
 
 ```javascript
 const { AgentsClient, ToolUtility, isOutputOfType } = require("@azure/ai-agents");
@@ -324,7 +324,7 @@ const { DefaultAzureCredential } = require("@azure/identity");
 
 require("dotenv/config");
 
-const projectEndpoint = process.env["PROJECT_ENDPOINT"] || "<project connection string>";
+const projectEndpoint = process.env["PROJECT_ENDPOINT"];
 
 // Create an Azure AI Client
 const client = new AgentsClient(projectEndpoint, new DefaultAzureCredential());

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

@@ -259,7 +259,7 @@ Finally, delete the thread and the agent to clean up the resources created in th
 
 ## Create a project client 
 
-To use code interpreter, first you need to create a project client, which will contain a connection string to your AI project, and will be used to authenticate API calls.
+To use code interpreter, first you need to create a project client, which will contain an endpoint to your AI project, and will be used to authenticate API calls.
 
 ```javascript
 const { AgentsClient, isOutputOfType, ToolUtility } = require("@azure/ai-agents");
@@ -269,7 +269,7 @@ const fs = require("fs");
 const path = require("node:path");
 require("dotenv/config");
 
-const projectEndpoint = process.env["PROJECT_ENDPOINT"] || "<project connection string>";
+const projectEndpoint = process.env["PROJECT_ENDPOINT"];
 
 // Create an Azure AI Client
 const client = new AgentsClient(projectEndpoint, new DefaultAzureCredential());

articles/ai-services/agents/how-to/tools/file-search-upload-files.md

@@ -45,7 +45,7 @@ Use this article to find step-by-step instructions and code samples for uploadin
 
 ## Create a project client
 
-Create a client object that contains the connection string for connecting to your AI project and other resources.
+Create a client object that contains the endpoint for connecting to your AI project and other resources.
 
 ```python
 import os
@@ -154,7 +154,7 @@ for message in messages.data:
 
 ## Create a project client
 
-Create a client object that contains the connection string for connecting to your AI project and other resources.
+Create a client object that contains the endpoint for connecting to your AI project and other resources.
 
 ```csharp
 using Azure;
@@ -346,7 +346,7 @@ agentClient.Administration.DeleteAgent(agent.Id);
 
 ## Create a project client
 
-Create a client object that contains the connection string for connecting to your AI project and other resources.
+Create a client object that contains the endpoint for connecting to your AI project and other resources.
 
 ```javascript
 const { AgentsClient, isOutputOfType, ToolUtility } = require("@azure/ai-agents");
@@ -356,7 +356,7 @@ const { DefaultAzureCredential } = require("@azure/identity");
 const fs = require("fs");
 require("dotenv/config");
 
-const projectEndpoint = process.env["PROJECT_ENDPOINT"] || "<project connection string>";
+const projectEndpoint = process.env["PROJECT_ENDPOINT"];
 
 // Create an Azure AI Client
 const client = new AgentsClient(projectEndpoint, new DefaultAzureCredential());

articles/ai-services/agents/how-to/tools/function-calling.md

@@ -490,7 +490,7 @@ const { DefaultAzureCredential } = require("@azure/identity");
 
 require("dotenv/config");
 
-const projectEndpoint = process.env["PROJECT_ENDPOINT"] || "<project connection string>";
+const projectEndpoint = process.env["PROJECT_ENDPOINT"];
 
 const client = new AgentsClient(projectEndpoint, new DefaultAzureCredential());
 const functionToolExecutor = new FunctionToolExecutor();

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

@@ -183,7 +183,7 @@ After the interaction is complete, the script performs cleanup by deleting the c
 
 ## Create a project client
 
-Create a client object that contains the connection string for connecting to your AI project and other resources.
+Create a client object that contains the endpoint for connecting to your AI project and other resources.
 
 ```javascript
 const { AgentsClient, isOutputOfType, ToolUtility } = require("@azure/ai-agents");
@@ -192,7 +192,7 @@ const { DefaultAzureCredential } = require("@azure/identity");
 const fs = require("fs");
 require("dotenv/config");
 
-const projectEndpoint = process.env["PROJECT_ENDPOINT"] || "<project connection string>";
+const projectEndpoint = process.env["PROJECT_ENDPOINT"];
 
 // Create an Azure AI Client
 const client = new AgentsClient(projectEndpoint, new DefaultAzureCredential());

articles/ai-services/agents/includes/endpoint-string-portal.md

@@ -8,5 +8,5 @@ ms.date: 12/11/2024
 ---
 
 > [!TIP]
-> You can also find your connection string in the **overview** for your project in the [Azure AI Foundry portal](https://ai.azure.com/), under **Libraries** > **Azure AI Foundry**.
-> :::image type="content" source="../media/quickstart/portal-endpoint-string.png" alt-text="A screenshot showing the connection string in the Azure AI Foundry portal." lightbox="../media/quickstart/portal-endpoint-string.png":::
+> You can also find your endpoint in the **overview** for your project in the [Azure AI Foundry portal](https://ai.azure.com/), under **Libraries** > **Azure AI Foundry**.
+> :::image type="content" source="../media/quickstart/portal-endpoint-string.png" alt-text="A screenshot showing the endpoint in the Azure AI Foundry portal." lightbox="../media/quickstart/portal-endpoint-string.png":::

articles/ai-services/agents/includes/quickstart-csharp.md

@@ -31,11 +31,8 @@ dotnet new console
 
 Install the .NET package to your project. For example if you're using the .NET CLI, run the following command.
 
->[!Note]
-> Azure.AI.Agents.Persistent is only available as a prelease version. Please use the "-prerelease" flag to add the package until a release version becomes available.
-
 ```console
-dotnet add package Azure.AI.Agents.Persistent --prerelease
+dotnet add package Azure.AI.Agents.Persistent
 dotnet add package Azure.Identity
 ```
 
@@ -51,11 +48,11 @@ Use the following code to create and run an agent. To run this code, you will ne
 
 [!INCLUDE [endpoint-string-portal](endpoint-string-portal.md)]
 
-For example, your connection string may look something like:
+For example, your endpoint may look something like:
 
 `https://myresource.services.ai.azure.com/api/projects/myproject`
 
-Set this connection string in an appsetting variable named `ProjectEndpoint`.
+Set this endpoint in an appsetting variable named `ProjectEndpoint`.
 
 
 ```csharp

articles/ai-services/agents/includes/quickstart-javascript.md

@@ -59,11 +59,11 @@ Use the following code to create and run an agent. To run this code, you will ne
 
 [!INCLUDE [endpoint-string-portal](endpoint-string-portal.md)]
 
-For example, your connection string may look something like:
+For example, your endpoint may look something like:
 
 `https://myresource.services.ai.azure.com/api/projects/myproject`
 
-Set this connection string as an environment variable named `PROJECT_ENDPOINT` in a `.env` file.
+Set this endpoint as an environment variable named `PROJECT_ENDPOINT` in a `.env` file.
 
 > [!IMPORTANT] 
 > * This quickstart code uses environment variables for sensitive configuration. Never commit your `.env` file to version control by making sure `.env` is listed in your `.gitignore` file.
@@ -92,7 +92,7 @@ const fs = require("fs");
 const path = require("node:path");
 require("dotenv/config");
 
-const projectEndpoint = process.env["PROJECT_ENDPOINT"] || "<project connection string>";
+const projectEndpoint = process.env["PROJECT_ENDPOINT"];
 const modelDeploymentName = process.env["MODEL_DEPLOYMENT_NAME"] || "gpt-4o";
 
 async function main() {