Show my user agent

Author: m | 2025-04-24

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Show what’s my user agent string. User Agents. Home; Download; Browsers; Bots; Devices; Lookup; Parser; My User Agent; Random; Contribute; Contacts; My User Agent. Sometimes users ask, what is my user agent string, my browser id or just my ua. Well, if you have the same question, then know that your user agent is:

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My User Agent - What's my browser's user agent? My UA finds

And removing the leading https:// and trailing /discovery. To find your discovery_url, run this CLI command:az ml workspace show -n {project_name} --resource-group {resource_group_name} --query discovery_urlFor example, your connection string may look something like:eastus.api.azureml.ms;12345678-abcd-1234-9fc6-62780b3d3e05;my-resource-group;my-project-nameSet this connection string as an environment variable named PROJECT_CONNECTION_STRING.import osfrom azure.ai.projects import AIProjectClientfrom azure.ai.projects.models import CodeInterpreterToolfrom azure.identity import DefaultAzureCredentialfrom typing import Anyfrom pathlib import Path# Create an Azure AI Client from a connection string, copied from your Azure AI Foundry project.# At the moment, it should be in the format ";;;"# HostName can be found by navigating to your discovery_url and removing the leading " and trailing "/discovery"# To find your discovery_url, run the CLI command: az ml workspace show -n {project_name} --resource-group {resource_group_name} --query discovery_url# Project Connection example: eastus.api.azureml.ms;12345678-abcd-1234-9fc6-62780b3d3e05;my-resource-group;my-project-name# Customer needs to login to Azure subscription via Azure CLI and set the environment variablesproject_client = AIProjectClient.from_connection_string( credential=DefaultAzureCredential(), conn_str=os.environ["PROJECT_CONNECTION_STRING"])with project_client: # Create an instance of the CodeInterpreterTool code_interpreter = CodeInterpreterTool() # The CodeInterpreterTool needs to be included in creation of the agent agent = project_client.agents.create_agent( model="gpt-4o-mini", name="my-agent", instructions="You are helpful agent", tools=code_interpreter.definitions, tool_resources=code_interpreter.resources, ) print(f"Created agent, agent ID: {agent.id}") # Create a thread thread = project_client.agents.create_thread() print(f"Created thread, thread ID: {thread.id}") # Create a message message = project_client.agents.create_message( thread_id=thread.id, role="user", content="Could you please create a bar chart for the operating profit using the following data and provide the file to me? Company A: $1.2 million, Company B: $2.5 million, Company C: $3.0 million, Company D: $1.8 million", ) print(f"Created message, message ID: {message.id}") # Run the agent run = project_client.agents.create_and_process_run(thread_id=thread.id, agent_id=agent.id) print(f"Run finished with status: {run.status}") if run.status == "failed": # Check if you got "Rate limit is exceeded.", then you want to get more quota print(f"Run failed: {run.last_error}") # Get messages from the thread messages = project_client.agents.list_messages(thread_id=thread.id) print(f"Messages: {messages}") # Get the last message from the

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What's My User Agent? - Check your User Agent

OpenSUSE User Agent: Modify Your User-Agent String on ChromeopenSUSE User Agent is a free Chrome extension developed by sirvin.dev. This extension allows Linux users to modify their User-Agent string to include the name of the openSUSE Linux distribution. It is similar to other extensions available for Fedora and Debian Linux.With openSUSE User Agent, Linux users can easily customize their User-Agent string to reflect their preferred distribution. By including the name of openSUSE in the User-Agent string, users can identify themselves as openSUSE users when accessing websites or web applications. This can be particularly useful for openSUSE enthusiasts who want to show their support for the distribution.The extension is easy to install and use. Once installed, users can simply enable it and the User-Agent string will be automatically modified to include the name of openSUSE. There are no complicated settings or configurations to worry about.If you are a Linux user and a fan of openSUSE, openSUSE User Agent is a handy tool to have. It allows you to personalize your browsing experience and proudly display your affiliation with openSUSE. Give it a try and enhance your online presence as an openSUSE user.Program available in other languagesダウンロードopenSUSE User Agent [JA]Tải xuống openSUSE User Agent [VI]openSUSE User Agent herunterladen [DE]下载openSUSE User Agent [ZH]تنزيل openSUSE User Agent [AR]Unduh openSUSE User Agent [ID]Descargar openSUSE User Agent [ES]Download do openSUSE User Agent [PT]Télécharger openSUSE User Agent [FR]Download openSUSE User Agent [NL]Ladda ner openSUSE User Agent [SV]openSUSE User Agent 다운로드 [KO]Скачать openSUSE User Agent [RU]Scarica openSUSE User Agent [IT]openSUSE User Agent indir [TR]ดาวน์โหลด openSUSE User Agent [TH]Pobierz openSUSE User Agent [PL]Explore MoreLatest articlesLaws concerning the use of this software vary from country to country. We do not encourage or condone the use of this program if it is in violation of these laws.

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Tip: To install an agent silently on Windows, see Install a Tenable Nessus Agent on Windows > Deploy and Link via the Command Line in the Tenable Nessus Agent User Guide. To install an agent on Windows: Open the agent installation file that you downloaded from the Tenable Downloads site. Agree to the EULA. Select the Typical installation method. The installation wizard prompts you to enter in your Tenable Vulnerability Management linking key and a server for the agent to link to. In the Key box, cut and paste your Tenable Vulnerability Management linking key. In the Server box, enter cloud.tenable.com:443. (Optional) In the Group box, enter an agent group to add your agent to. Tip: You can also add the agent to a group from the Tenable Vulnerability Management user interface. For more information, see the Create an Agent Group section of this guide. Click Next. The agent should now show as linked in the Tenable Vulnerability Management user interface. You can confirm this in the Settings > Sensors > Linked Agents section of Tenable Vulnerability Management. The agent may go into an offline status as a result of the agent doing a plugin update and compilation. This is expected behavior, and the agent returns the online status once the process completes.. Show what’s my user agent string. User Agents. Home; Download; Browsers; Bots; Devices; Lookup; Parser; My User Agent; Random; Contribute; Contacts; My User Agent. Sometimes users ask, what is my user agent string, my browser id or just my ua. Well, if you have the same question, then know that your user agent is:

What Is My User Agent? Unveiling the Secrets of User Agents

Connection string using information from your project. This string is in the format:;;;TipYou can also find your connection string in the overview for your project in the Azure AI Foundry portal, under Project details > Project connection string.HostName can be found by navigating to your discovery_url and removing the leading https:// and trailing /discovery. To find your discovery_url, run this CLI command:az ml workspace show -n {project_name} --resource-group {resource_group_name} --query discovery_urlFor example, your connection string may look something like:eastus.api.azureml.ms;12345678-abcd-1234-9fc6-62780b3d3e05;my-resource-group;my-project-nameSet this connection string as an environment variable named PROJECT_CONNECTION_STRING.// index.tsimport type { MessageDeltaChunk, MessageDeltaTextContent, MessageTextContentOutput,} from "@azure/ai-projects";import { AIProjectsClient, DoneEvent, ErrorEvent, isOutputOfType, MessageStreamEvent, RunStreamEvent, ToolUtility,} from "@azure/ai-projects";import { DefaultAzureCredential } from "@azure/identity";const connectionString = process.env["AZURE_AI_PROJECTS_CONNECTION_STRING"] || "";if (!connectionString) { throw new Error("AZURE_AI_PROJECTS_CONNECTION_STRING must be set in the environment variables");}export async function main(): Promise { const client = AIProjectsClient.fromConnectionString( connectionString || "", new DefaultAzureCredential(), ); // Step 1: Create code interpreter tool const codeInterpreterTool = ToolUtility.createCodeInterpreterTool(); // Step 2: Create an agent const agent = await client.agents.createAgent("gpt-4o-mini", { name: "my-agent", instructions: "You are a helpful agent", tools: [codeInterpreterTool.definition], toolResources: codeInterpreterTool.resources, }); // Step 3: Create a thread const thread = await client.agents.createThread(); // Step 4: Add a message to thread await client.agents.createMessage( thread.id, { role: "user", content: "I need to solve the equation `3x + 11 = 14`. Can you help me?", }); // Intermission: message is now correlated with thread // Intermission: listing messages will retrieve the message just added // Step 5: Run the agent 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 as MessageDeltaChunk; messageDelta.delta.content.forEach((contentPart) => { if (contentPart.type === "text") { const textContent = contentPart as MessageDeltaTextContent; const textValue = textContent.text?.value || "No text"; } }); } break; case RunStreamEvent.ThreadRunCompleted:

What's My User Agent?

To create a connection string using information from your project. This string is in the format:;;;TipYou can also find your connection string in the overview for your project in the Azure AI Foundry portal, under Project details > Project connection string.HostName can be found by navigating to your discovery_url and removing the leading https:// and trailing /discovery. To find your discovery_url, run this CLI command:az ml workspace show -n {project_name} --resource-group {resource_group_name} --query discovery_urlFor example, your connection string may look something like:eastus.api.azureml.ms;12345678-abcd-1234-9fc6-62780b3d3e05;my-resource-group;my-project-nameSet this connection string as an environment variable named PROJECT_CONNECTION_STRING.import os, timefrom azure.ai.projects import AIProjectClientfrom azure.identity import DefaultAzureCredentialfrom openai import AzureOpenAIwith AIProjectClient.from_connection_string( credential=DefaultAzureCredential(), conn_str=os.environ["PROJECT_CONNECTION_STRING"],) as project_client: # Explicit type hinting for IntelliSense client: AzureOpenAI = project_client.inference.get_azure_openai_client( # The latest API version is 2024-10-01-preview api_version = os.environ.get("AZURE_OPENAI_API_VERSION"), ) with client: agent = client.beta.assistants.create( model="gpt-4o-mini", name="my-agent", instructions="You are a helpful agent" ) print(f"Created agent, agent ID: {agent.id}") thread = client.beta.threads.create() print(f"Created thread, thread ID: {thread.id}") message = client.beta.threads.messages.create(thread_id=thread.id, role="user", content="Hello, tell me a joke") print(f"Created message, message ID: {message.id}") run = client.beta.threads.runs.create(thread_id=thread.id, assistant_id=agent.id) # Poll the run while run status is queued or in progress while run.status in ["queued", "in_progress", "requires_action"]: time.sleep(1) # Wait for a second run = client.beta.threads.runs.retrieve(thread_id=thread.id, run_id=run.id) print(f"Run status: {run.status}") client.beta.assistants.delete(agent.id) print("Deleted agent") messages = client.beta.threads.messages.list(thread_id=thread.id) print(f"Messages: {messages}")| Reference documentation | Samples | Library source code | Package (npm) |PrerequisitesAn Azure subscription - Create one for free.Node.js LTSEnsure that the individual deploying the template has the Azure AI Developer role assigned at the resource group level where the template is being deployed.Additionally, to deploy the template, you need to have the preset Role Based Access Administrator role at the subscription level.The Owner role at the subscription level satisfies this requirement.The specific admin role that is needed is Microsoft.Authorization/roleAssignments/writeEnsure that each team member who wants to use the

What's my user agent?

A "me too" - and a poor one at that in terms of feature set. 40tude Dialog gives me everything Agent *2.1* is *supposed* to have *later on* - and it's *free* to boot. Sorry Forte - in this case it's "too little too late". YES / NO --> --> It works amazingly, but there's just something about the windows 3.1 looking interface that makes me want to puke YES / NO --> bobad reviewed v1.91 on Mar 23, 2002 --> Agent is one of those rare "must have" programs. If my computer were crippled and I could only have 4 programs on it, Agent would be in that elite group. Agent is not only the best news reader by far, but highly under rated as a mail client. Usenet itself is under rated. I prefer it to the Web. The Web is like watching TV, Usenet is like sitting with a group of experts on any subject you can dream up. Agent tames Usenet and makes it logical and user friendly. The addition of yEnc solidified Agent's leadership position for the foreseeable future. (bobad@charter.net) YES / NO --> hfk reviewed v1.9 on Jan 27, 2002 --> Agent was, is, and, at least in the forseeable future, will be the greatest windows usenet client. While 1.9 isn't a spectacular leap forward from 1.8, it's still a sign that Agent lives, and that Agent's developers are still interested in it. 2.0 is in the works but, until it releases, 1.9 is the best there is. Get it (and do the usenet community a favor-pay for it and show the developers that 2.0 has money-making potential) YES / NO --> --> Forté Agent is a good program, but interface still sucks YES / NO --> NYC60 reviewed v1.9 on Jan 27, 2002 --> The very best. If you do Usenet, you need Agent. YES / NO -->

What is my user agent

Context.MessageA message created by an agent or a user. Messages can include text, images, and other files. Messages are stored as a list on the Thread.RunActivation of an agent to begin running based on the contents of Thread. The agent uses its configuration and Thread’s Messages to perform tasks by calling models and tools. As part of a Run, the agent appends Messages to the Thread.Run StepA detailed list of steps the agent took as part of a Run. An agent can call tools or create Messages during its run. Examining Run Steps allows you to understand how the agent is getting to its results.First, initialize a new project by running:npm init -yRun the following commands to install the npm packages required.npm install @azure/ai-projectsnpm install @azure/identitynpm install dotenvNext, to authenticate your API requests and run the program, use the az login command to sign into your Azure subscription.az loginUse the following code to create and run an agent. To run this code, you will need to create a connection string using information from your project. This string is in the format:;;;TipYou can also find your connection string in the overview for your project in the Azure AI Foundry portal, under Project details > Project connection string.HostName can be found by navigating to your discovery_url and removing the leading https:// and trailing /discovery. To find your discovery_url, run this CLI command:az ml workspace show -n {project_name} --resource-group {resource_group_name} --query discovery_urlFor example, your connection string may look something like:eastus.api.azureml.ms;12345678-abcd-1234-9fc6-62780b3d3e05;my-resource-group;my-project-nameSet this connection string as an environment variable named PROJECT_CONNECTION_STRING in a .env file.ImportantThis 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.Remember: If you accidentally commit sensitive information, consider those credentials compromised and rotate them immediately.Next,. Show what’s my user agent string. User Agents. Home; Download; Browsers; Bots; Devices; Lookup; Parser; My User Agent; Random; Contribute; Contacts; My User Agent. Sometimes users ask, what is my user agent string, my browser id or just my ua. Well, if you have the same question, then know that your user agent is:

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What is my User Agent?

Tom Hallunread,May 29, 2009, 1:28:54 PM5/29/09to I've just bought a new computer and will be getting it in a few days. Can someone advise me on how to make the Agent transition to the newmachine as painless as possible? The new box will be running 64-bit VistaHome Premium. TIA,Tom-- remove .spoo to reply by emailA Little Bitunread,May 29, 2009, 4:28:01 PM5/29/09to On Fri, 29 May 2009 12:28:54 -0600, Tom Hall wrote: > I've just bought a new computer and will be getting it in a few days. > > Can someone advise me on how to make the Agent transition to the new> machine as painless as possible? The new box will be running 64-bit Vista> Home Premium. Just copy the Agent folder to the new computer.Charles Gallowayunread,May 29, 2009, 7:25:35 PM5/29/09to Actually I would suggest looking at: says:"Does Agent work with Windows Vista?As of Agent 4.2, it works in Windows Vista. When you upgrade, it willprompt you to let it move your database to the new Vista requiredlocation.For older versions, Agent does also work with Windows Vista, with somemanual setup needed unless you're using an Admin level account on yourcomputer.If you are using the default access level, you will need to manuallymove Agent's database location from its default location of C:\ProgramFiles\Agent\data to your computer account's user data area. This isbecause as a security measure, normal account in Vista does not havefull write access to the Program Files location and Agent has been inexistence long before Vista. Don't forget to fix the shortcut detailsto match the new "start in" location.Also, if you are installing Agent onto Vista as a "new" application,uncheck the option to run Agent when the installer finishes, or Vistawill confuse the action as being part of the installation process and,with its user-access controls, disallow access to the files later on.Run Agent manually after the installer closes. Upgrade installs do nothave this option.This FAQ Entry was updated on 03.05.09, please give us your feedback."============================================and "Where is my Agent database? I can't find the filesAs of version 4.2, Agent will by default place its data files in theWindows default location for program data. In Windows XP, this is"C:\Documents and Settings\\Application Data\Forte\Agent" and inWindows Vista this is "C:\Users\\AppData\Roaming\Forte\Agent" or"C:\Users\\AppData\Local\Forte\Agent" (NOTE: If your system wasoriginally XP and upgraded to Vista, it's probably the XP path.)By default, these are hidden folders in Windows, which is why youcannot find them. To get Windows to show them, go to your systemControl Panel and open up Folder Options, click the View tab, and thenenable the Show hidden files and folders setting. If using Vista andyou are not using the "Classic View", then from the Control Panelfirst open up Appearance and Personalization.This FAQ Entry was updated on 11.12.07, please give us your feedback."============================================A Little Bitunread,May 30, 2009, 3:44:50 AM5/30/09to That is not required. I run Agent 4.2 under both Vista and XP and Vista has never tried to move anything.nob...@nowhere.comunread,May 31, 2009, 2:38:41 PM5/31/09to On Sun, 31 May 2009 17:37:34 +0200, FredW fr...@blackholespam.net>wrote:>I am using Agent

What is my user agent?

Tasks by calling models and tools. As part of a Run, the agent appends Messages to the Thread.Run StepA detailed list of steps the agent took as part of a Run. An agent can call tools or create Messages during its run. Examining Run Steps allows you to understand how the agent is getting to its results.To authenticate your API requests, use the az login command to sign into your Azure subscription.az loginNext, you will need to fetch the Entra ID token to provide as authorization to the API calls. Fetch the token using the CLI command:az account get-access-token --resource ' | jq -r .accessToken | tr -d '"'Set the access token as an environment variable named AZURE_AI_AGENTS_TOKEN.To successfully make REST API calls to Azure AI Agents Service, you will need to use the endpoint as below: can be found by navigating to your discovery_url and removing the leading https:// and trailing /discovery. To find your discovery_url, run this CLI command:az ml workspace show -n {project_name} --subscription {subscription_name} --resource-group {resource_group_name} --query discovery_urlFor example, your endpoint may look something like: this endpoint as an environment variable named AZURE_AI_AGENTS_ENDPOINT.Create an agentNoteWith Azure AI Agents Service the model parameter requires model deployment name. If your model deployment name is different than the underlying model name then you would adjust your code to "model": "{your-custom-model-deployment-name}".curl $AZURE_AI_AGENTS_ENDPOINT/assistants?api-version=2024-12-01-preview \ -H "Authorization: Bearer $AZURE_AI_AGENTS_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "instructions": "You are a helpful agent.", "name": "my-agent", "tools": [{"type": "code_interpreter"}], "model": "gpt-4o-mini" }'Create a threadcurl $AZURE_AI_AGENTS_ENDPOINT/threads?api-version=2024-12-01-preview \ -H "Authorization: Bearer $AZURE_AI_AGENTS_TOKEN" \ -H "Content-Type: application/json" \ -d ''Add a user question to the threadcurl $AZURE_AI_AGENTS_ENDPOINT/threads/thread_abc123/messages?api-version=2024-12-01-preview \ -H "Authorization: Bearer $AZURE_AI_AGENTS_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "role": "user", "content": "I need to solve the equation `3x + 11 = 14`. Can you help me?". Show what’s my user agent string. User Agents. Home; Download; Browsers; Bots; Devices; Lookup; Parser; My User Agent; Random; Contribute; Contacts; My User Agent. Sometimes users ask, what is my user agent string, my browser id or just my ua. Well, if you have the same question, then know that your user agent is: Is it possible to load an iframe with different user agent ? Using a mobile user agent for an iframe will help my app to show mobile sites as hover popup. For example

My User Agent - What's my browser's user agent? My UA finds

User agent is removed. So from now on, websites will believe that the browser you use is Google Chrome and treat the browser as fully supported.“The primary reason to show Vivaldi in the user agent is a level of pride. That pride, however, is hurting us, as our competitors and others are using this to block us from their services. That is why with today’s update, we’ve drawn a line in the sand so that you can browse more websites without a glitch,” Vivaldi explains.This change translates to more compatible websites, which for the end user is nothing but good news. After all, using a custom user agent specific to Vivaldi didn’t bring any real benefit to the end user, especially because the browser is based on Chrome in the first place anyway.If you want to see how websites treat Vivaldi when its original user agent is detected, you can just switch Google Chrome to the Vivaldi user agent and then load websites like WhatsApp Web and Netflix to get the compatibility warnings. To do this on Windows, Linux and Mac, close Google Chrome, and then in your terminal app type the following command for your operating system:Windows"%PROGRAMFILES(X86)%\Google\Chrome\Application\chrome.exe" --user-agent="Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.94 Safari/537.36 Vivaldi/2.10.1745.21"Linuxgoogle-chrome --user-agent='Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.94 Safari/537.36 Vivaldi/2.10.1745.21'Macopen -a Google\ Chrome.app --args --user-agent='Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_2) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.94 Safari/537.36 Vivaldi/2.10.1745.21'Once you update to Vivaldi 2.10, the Chrome user agent is enabled and no compatibility issues should occur.

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And removing the leading https:// and trailing /discovery. To find your discovery_url, run this CLI command:az ml workspace show -n {project_name} --resource-group {resource_group_name} --query discovery_urlFor example, your connection string may look something like:eastus.api.azureml.ms;12345678-abcd-1234-9fc6-62780b3d3e05;my-resource-group;my-project-nameSet this connection string as an environment variable named PROJECT_CONNECTION_STRING.import osfrom azure.ai.projects import AIProjectClientfrom azure.ai.projects.models import CodeInterpreterToolfrom azure.identity import DefaultAzureCredentialfrom typing import Anyfrom pathlib import Path# Create an Azure AI Client from a connection string, copied from your Azure AI Foundry project.# At the moment, it should be in the format ";;;"# HostName can be found by navigating to your discovery_url and removing the leading " and trailing "/discovery"# To find your discovery_url, run the CLI command: az ml workspace show -n {project_name} --resource-group {resource_group_name} --query discovery_url# Project Connection example: eastus.api.azureml.ms;12345678-abcd-1234-9fc6-62780b3d3e05;my-resource-group;my-project-name# Customer needs to login to Azure subscription via Azure CLI and set the environment variablesproject_client = AIProjectClient.from_connection_string( credential=DefaultAzureCredential(), conn_str=os.environ["PROJECT_CONNECTION_STRING"])with project_client: # Create an instance of the CodeInterpreterTool code_interpreter = CodeInterpreterTool() # The CodeInterpreterTool needs to be included in creation of the agent agent = project_client.agents.create_agent( model="gpt-4o-mini", name="my-agent", instructions="You are helpful agent", tools=code_interpreter.definitions, tool_resources=code_interpreter.resources, ) print(f"Created agent, agent ID: {agent.id}") # Create a thread thread = project_client.agents.create_thread() print(f"Created thread, thread ID: {thread.id}") # Create a message message = project_client.agents.create_message( thread_id=thread.id, role="user", content="Could you please create a bar chart for the operating profit using the following data and provide the file to me? Company A: $1.2 million, Company B: $2.5 million, Company C: $3.0 million, Company D: $1.8 million", ) print(f"Created message, message ID: {message.id}") # Run the agent run = project_client.agents.create_and_process_run(thread_id=thread.id, agent_id=agent.id) print(f"Run finished with status: {run.status}") if run.status == "failed": # Check if you got "Rate limit is exceeded.", then you want to get more quota print(f"Run failed: {run.last_error}") # Get messages from the thread messages = project_client.agents.list_messages(thread_id=thread.id) print(f"Messages: {messages}") # Get the last message from the

2025-03-28
User9553

OpenSUSE User Agent: Modify Your User-Agent String on ChromeopenSUSE User Agent is a free Chrome extension developed by sirvin.dev. This extension allows Linux users to modify their User-Agent string to include the name of the openSUSE Linux distribution. It is similar to other extensions available for Fedora and Debian Linux.With openSUSE User Agent, Linux users can easily customize their User-Agent string to reflect their preferred distribution. By including the name of openSUSE in the User-Agent string, users can identify themselves as openSUSE users when accessing websites or web applications. This can be particularly useful for openSUSE enthusiasts who want to show their support for the distribution.The extension is easy to install and use. Once installed, users can simply enable it and the User-Agent string will be automatically modified to include the name of openSUSE. There are no complicated settings or configurations to worry about.If you are a Linux user and a fan of openSUSE, openSUSE User Agent is a handy tool to have. It allows you to personalize your browsing experience and proudly display your affiliation with openSUSE. Give it a try and enhance your online presence as an openSUSE user.Program available in other languagesダウンロードopenSUSE User Agent [JA]Tải xuống openSUSE User Agent [VI]openSUSE User Agent herunterladen [DE]下载openSUSE User Agent [ZH]تنزيل openSUSE User Agent [AR]Unduh openSUSE User Agent [ID]Descargar openSUSE User Agent [ES]Download do openSUSE User Agent [PT]Télécharger openSUSE User Agent [FR]Download openSUSE User Agent [NL]Ladda ner openSUSE User Agent [SV]openSUSE User Agent 다운로드 [KO]Скачать openSUSE User Agent [RU]Scarica openSUSE User Agent [IT]openSUSE User Agent indir [TR]ดาวน์โหลด openSUSE User Agent [TH]Pobierz openSUSE User Agent [PL]Explore MoreLatest articlesLaws concerning the use of this software vary from country to country. We do not encourage or condone the use of this program if it is in violation of these laws.

2025-04-24
User2528

Connection string using information from your project. This string is in the format:;;;TipYou can also find your connection string in the overview for your project in the Azure AI Foundry portal, under Project details > Project connection string.HostName can be found by navigating to your discovery_url and removing the leading https:// and trailing /discovery. To find your discovery_url, run this CLI command:az ml workspace show -n {project_name} --resource-group {resource_group_name} --query discovery_urlFor example, your connection string may look something like:eastus.api.azureml.ms;12345678-abcd-1234-9fc6-62780b3d3e05;my-resource-group;my-project-nameSet this connection string as an environment variable named PROJECT_CONNECTION_STRING.// index.tsimport type { MessageDeltaChunk, MessageDeltaTextContent, MessageTextContentOutput,} from "@azure/ai-projects";import { AIProjectsClient, DoneEvent, ErrorEvent, isOutputOfType, MessageStreamEvent, RunStreamEvent, ToolUtility,} from "@azure/ai-projects";import { DefaultAzureCredential } from "@azure/identity";const connectionString = process.env["AZURE_AI_PROJECTS_CONNECTION_STRING"] || "";if (!connectionString) { throw new Error("AZURE_AI_PROJECTS_CONNECTION_STRING must be set in the environment variables");}export async function main(): Promise { const client = AIProjectsClient.fromConnectionString( connectionString || "", new DefaultAzureCredential(), ); // Step 1: Create code interpreter tool const codeInterpreterTool = ToolUtility.createCodeInterpreterTool(); // Step 2: Create an agent const agent = await client.agents.createAgent("gpt-4o-mini", { name: "my-agent", instructions: "You are a helpful agent", tools: [codeInterpreterTool.definition], toolResources: codeInterpreterTool.resources, }); // Step 3: Create a thread const thread = await client.agents.createThread(); // Step 4: Add a message to thread await client.agents.createMessage( thread.id, { role: "user", content: "I need to solve the equation `3x + 11 = 14`. Can you help me?", }); // Intermission: message is now correlated with thread // Intermission: listing messages will retrieve the message just added // Step 5: Run the agent 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 as MessageDeltaChunk; messageDelta.delta.content.forEach((contentPart) => { if (contentPart.type === "text") { const textContent = contentPart as MessageDeltaTextContent; const textValue = textContent.text?.value || "No text"; } }); } break; case RunStreamEvent.ThreadRunCompleted:

2025-04-15
User5618

To create a connection string using information from your project. This string is in the format:;;;TipYou can also find your connection string in the overview for your project in the Azure AI Foundry portal, under Project details > Project connection string.HostName can be found by navigating to your discovery_url and removing the leading https:// and trailing /discovery. To find your discovery_url, run this CLI command:az ml workspace show -n {project_name} --resource-group {resource_group_name} --query discovery_urlFor example, your connection string may look something like:eastus.api.azureml.ms;12345678-abcd-1234-9fc6-62780b3d3e05;my-resource-group;my-project-nameSet this connection string as an environment variable named PROJECT_CONNECTION_STRING.import os, timefrom azure.ai.projects import AIProjectClientfrom azure.identity import DefaultAzureCredentialfrom openai import AzureOpenAIwith AIProjectClient.from_connection_string( credential=DefaultAzureCredential(), conn_str=os.environ["PROJECT_CONNECTION_STRING"],) as project_client: # Explicit type hinting for IntelliSense client: AzureOpenAI = project_client.inference.get_azure_openai_client( # The latest API version is 2024-10-01-preview api_version = os.environ.get("AZURE_OPENAI_API_VERSION"), ) with client: agent = client.beta.assistants.create( model="gpt-4o-mini", name="my-agent", instructions="You are a helpful agent" ) print(f"Created agent, agent ID: {agent.id}") thread = client.beta.threads.create() print(f"Created thread, thread ID: {thread.id}") message = client.beta.threads.messages.create(thread_id=thread.id, role="user", content="Hello, tell me a joke") print(f"Created message, message ID: {message.id}") run = client.beta.threads.runs.create(thread_id=thread.id, assistant_id=agent.id) # Poll the run while run status is queued or in progress while run.status in ["queued", "in_progress", "requires_action"]: time.sleep(1) # Wait for a second run = client.beta.threads.runs.retrieve(thread_id=thread.id, run_id=run.id) print(f"Run status: {run.status}") client.beta.assistants.delete(agent.id) print("Deleted agent") messages = client.beta.threads.messages.list(thread_id=thread.id) print(f"Messages: {messages}")| Reference documentation | Samples | Library source code | Package (npm) |PrerequisitesAn Azure subscription - Create one for free.Node.js LTSEnsure that the individual deploying the template has the Azure AI Developer role assigned at the resource group level where the template is being deployed.Additionally, to deploy the template, you need to have the preset Role Based Access Administrator role at the subscription level.The Owner role at the subscription level satisfies this requirement.The specific admin role that is needed is Microsoft.Authorization/roleAssignments/writeEnsure that each team member who wants to use the

2025-04-21
User1482

Context.MessageA message created by an agent or a user. Messages can include text, images, and other files. Messages are stored as a list on the Thread.RunActivation of an agent to begin running based on the contents of Thread. The agent uses its configuration and Thread’s Messages to perform tasks by calling models and tools. As part of a Run, the agent appends Messages to the Thread.Run StepA detailed list of steps the agent took as part of a Run. An agent can call tools or create Messages during its run. Examining Run Steps allows you to understand how the agent is getting to its results.First, initialize a new project by running:npm init -yRun the following commands to install the npm packages required.npm install @azure/ai-projectsnpm install @azure/identitynpm install dotenvNext, to authenticate your API requests and run the program, use the az login command to sign into your Azure subscription.az loginUse the following code to create and run an agent. To run this code, you will need to create a connection string using information from your project. This string is in the format:;;;TipYou can also find your connection string in the overview for your project in the Azure AI Foundry portal, under Project details > Project connection string.HostName can be found by navigating to your discovery_url and removing the leading https:// and trailing /discovery. To find your discovery_url, run this CLI command:az ml workspace show -n {project_name} --resource-group {resource_group_name} --query discovery_urlFor example, your connection string may look something like:eastus.api.azureml.ms;12345678-abcd-1234-9fc6-62780b3d3e05;my-resource-group;my-project-nameSet this connection string as an environment variable named PROJECT_CONNECTION_STRING in a .env file.ImportantThis 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.Remember: If you accidentally commit sensitive information, consider those credentials compromised and rotate them immediately.Next,

2025-04-03

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