Category: Azure – What’s New

Microsoft Sales Copilot: Sales Team Empowerment

Overview

Do you want to streamline your sales process and improve your customer relationships? If you do, you should check out Microsoft Sales Copilot, the AI assistant designed for sellers.

Microsoft Sales Copilot is a smart CRM companion with Dynamics 365 Sales or Salesforce Sales Cloud. It helps you automate and simplify tasks, personalize customer interactions, and stay in the flow of work by integrating with Microsoft 365 apps, such as Outlook and Teams.

In this blog post, we will explore some of the features and advantages of Sales Copilot. We will also show you how to get started with this powerful tool.

What You Can Do with Microsoft Sales Copilot

The Sales Copilot offers a range of AI capabilities to help you drive efficiency and effectiveness in your sales process. With Sales Copilot, you can:

  • Draft emails and set up meetings in Outlook with data from your CRM and Microsoft 365 using AI.
  • Save AI-generated email and meeting summaries in Teams, Outlook, and Dynamics 365 Sales directly to your CRM.
  • Eliminate note-taking with AI-generated meeting transcriptions, competitor mentions, and action items in Teams and Dynamics 365 Sales.
  • Get AI assistance for suggested tips, related information, and answers to customers’ questions during Teams calls.
  • Build stronger customer relationships with real-time call insights, content recommendations, and post-call analysis to improve future interactions.
  • Sync updates in Teams and Outlook to your CRM automatically to maintain accurate customer records.
  • View a summary of your customer information in Microsoft 365 apps using data from your CRM.
  • Work together with disparate sales teams using Teams collaboration spaces that offer integrated access to Dynamics 365 Sales and Salesforce data.

How Sales Copilot Benefits You

The Sales Copilot can help you achieve several benefits for your sales performance and customer satisfaction. Using it, you can:

  • Save time and reduce errors by automating and simplifying tasks that would otherwise require manual data entry or context switching.
  • Increase productivity and focus by eliminating distractions and staying in the apps you use daily.
  • Enhance communication and collaboration by sharing relevant information and insights with your team members and managers.
  • Improve customer experience and loyalty by delivering personalized and timely responses, suggestions, and follow-ups.
  • Boost sales effectiveness and outcomes by leveraging AI insights and recommendations to optimize your sales strategy and tactics.

How to Get Started

If you are interested in trying out Sales Copilot, here are some steps you can take to get started:

  • Check if you have the required licenses for Microsoft Sales Copilot. You need a product license for Microsoft 365 for enterprise or Office 365 for enterprise and a subscription for Dynamics 365 Sales Enterprise or Premium or Salesforce Sales Cloud.
  • Install Microsoft Sales Copilot from this link.
  • Connect your CRM account (Dynamics 365 or Salesforce) to Microsoft Sales Copilot.
  • Start using Microsoft Sales Copilot in Outlook or Teams.

For more information on installing and using Sales Copilot, click support page.

Conclusion

Microsoft Sales Copilot is a powerful AI assistant that can help you streamline your sales process and improve customer relationships. It works with Dynamics 365 Sales or Salesforce Sales Cloud and integrates with Microsoft 365 apps, such as Outlook and Teams, to help you automate and simplify tasks, personalize customer interactions, and stay in the flow of work.

If you want to boost your sales productivity and effectiveness, try it. You can start by installing Microsoft Sales Copilot from this link and connecting your CRM account.

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Microsoft Security Copilot: Fortifying Digital Defenses

Microsoft Security Copilot: Fortifying Digital Defenses

Microsoft Security Copilot: Overview

Cybersecurity is crucial to any business, especially in the digital age. However, managing security risks and threats can be challenging and time-consuming. That’s why Microsoft has developed Security Copilot, an AI-powered tool that helps you protect your data and devices from cyberattacks.

Security Copilot is a cloud-based service that integrates with Microsoft 365 and Azure. It provides you with a comprehensive and personalized security dashboard where you can monitor your security posture, identify vulnerabilities, and take action to remediate them. Security Copilot also leverages AI to analyze your security data and provide insights and recommendations on improving your security.

Features and Benefits

Some of the features and benefits of Security Copilot are:

  • Gives you a single view of your security status across your Microsoft products, services, and third-party applications and devices.
  • Alerts you of any security incidents or anomalies and helps you investigate and respond quickly and effectively.
  • Uses AI to prioritize the most critical security issues and suggest the best actions.
  • Helps you comply with industry standards and regulations, such as GDPR, HIPAA, PCI DSS, etc.
  • Enables you to create and enforce security policies and controls across your organization.
  • Allows you to customize your security settings and preferences according to your needs and preferences.

Getting Started with Microsoft Security Copilot

To use Security Copilot, you need to follow these steps:

  • Sign up for a free trial or a paid subscription on the Microsoft Security Copilot website.
  • Connect your Microsoft 365 account to the service using the Azure Active Directory (AAD) authentication.
  • Configure your security settings and preferences on the Security Copilot dashboard.
  • Start monitoring and managing your data security with the service.

Microsoft Security Copilot is a powerful and easy-to-use service that can help you protect your data from cyber threats. It leverages the advanced capabilities of Microsoft 365 and Azure to provide a comprehensive and integrated data security solution. Try it today and see how it can enhance your data security. To learn more, click here.

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Microsoft GitHub Copilot: AI-Driven Code Assistance

Microsoft GitHub Copilot: AI-Driven Code Assistance

Overview

Are you looking for a way to speed up your coding process and improve your productivity? If yes, then you should check out Microsoft GitHub Copilot, a new AI-powered tool that can help you write better code faster.

What is Microsoft GitHub Copilot?

Microsoft GitHub Copilot is a Visual Studio Code extension that uses artificial intelligence to suggest code snippets as you type. It can generate whole functions, tests, comments, and more based on your context and intent. It can also adapt to your coding style and preferences, learning from your feedback and edits.

What are the advantages?

The GitHub Copilot can help you save time and effort by automating some of the tedious and repetitive coding tasks. It can also help you discover new ways of solving problems, learn new APIs and frameworks, and avoid common errors and bugs. Moreover, it can enhance your creativity and innovation by suggesting alternative approaches and solutions you might not have considered.

How to use Microsoft GitHub Copilot?

To use GitHub Copilot, you must have a Visual Studio Code editor and a GitHub account. You can install the extension from the Visual Studio Code Marketplace or from the GitHub Copilot website. Once installed, you can start using it by typing some code in your editor and waiting for the suggestions to appear in a pop-up window. You can accept, reject, or modify the suggestions as you wish. You can also use keyboard shortcuts or voice commands to interact with the tool.

Some points to consider while using Microsoft GitHub Copilot:

  • Microsoft GitHub Copilot is not a replacement for human programmers. It is a tool that can assist you, but not do everything for you. You must still write some code, review the suggestions carefully, and test the output thoroughly.
  • GitHub Copilot is not a source of truth. It does not guarantee the correctness, completeness, or quality of the code it generates. It may sometimes produce inaccurate, inappropriate, or insecure code. You are responsible for verifying the validity and legality of your code.
  • GitHub Copilot is not a plagiarism tool. It does not copy code from existing sources but synthesizes new code from a large corpus of public code and natural language data. However, some of the code it generates may be similar to existing code, so you should always cite the sources if you use any code snippets from Microsoft GitHub Copilot.

Conclusion

Microsoft GitHub Copilot is a groundbreaking tool that can revolutionize how developers code. It can help you write better code faster, with less hassle and more fun. However, it is not a magic wand that can solve all your coding problems. You still need to use your judgment, skills, and ethics when using it. To learn more about GitHub Copilot, visit its official website or read its documentation.

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Azure Container Apps: What's New - August 2023

Azure Container Apps: What’s New – August 2023

Azure Container Apps: What’s New and Why You Should Care

Azure Container Apps is a service that enables you to deploy and run containerized applications and microservices without managing the underlying infrastructure. It is a serverless hosting service that supports any container and any programming model. You can scale your apps in response to HTTP request events or run them as always-on background jobs.

This blog post will explore some of the latest features and enhancements announced for Azure Container Apps on August 30, 2023.

Workload Profiles Environment

Workload profiles are designed to optimize spend and performance for microservices by selecting either serverless Consumption compute or customized Dedicated compute. These determine the amount of compute and memory resources available to your apps in an Azure Container Apps environment.

You can have multiple workload profiles of varying sizes within the same Container Apps environment and select the optimal compute size for each of your applications’ resource requirements. This is ideal for developers when deploying a microservice solution.

A Consumption workload profile is available by default and provides serverless scale all the way to zero, and bills only for resources your apps use.

Dedicated workload profiles provide dedicated compute resources for your apps and are ideal for running apps requiring more compute and/or memory resources. You can select from a range of compute sizes and types up to 32 vCPUs and 256 GiB of memory. Apps running in these dedicated workload profiles use the new Dedicated pricing plan which bills per compute instance and provides better cost predictability.

Azure Container Apps Dedicated Plan

Dedicated plan is a new option to run your apps on dedicated compute resources, select from a range of compute sizes, and types up to 32 vCPUs and 256 GiB of memory. You can choose from general-purpose or memory-optimized workload profiles depending on your apps’ needs.

The Dedicated plan offers several benefits, such as:

  • Better cost predictability as you are billed per compute instance rather than per app.
  • Higher performance and scalability as you can allocate more resources to your apps.
  • Greater flexibility as you can mix and match Consumption and Dedicated plans within the same Container Apps environment.

Additional Networking Features

Azure Container Apps also supports additional networking features that enable you to configure your apps’ connectivity and security. These include:

  • User defined routes (UDR) – Specify custom routes for outbound traffic from your apps.
  • Smaller subnet sizes – Use smaller subnets for your Container Apps environments, reducing IP address consumption.
  • Network address translation (NAT) gateway – Use a single public IP address for outbound traffic from your apps.

Azure Container Apps Jobs

Jobs are a new feature that allow you to run containerized jobs on demand, on a schedule, or in response to events. These are ideal for scenarios such as data processing, batch processing, or scheduled tasks.

There are certain characteristics that can be attributed to jobs:

  • Run until completion or until a specified timeout.
  • Configured with retries, concurrency limits, and dependencies.
  • Triggered by HTTP requests, events from Event Grid or Service Bus, or cron expressions.
  • Access secrets from Azure Key Vault or environment variables.
  • Use any container image from any registry.

Conclusion

Azure Container Apps is a powerful and flexible service that enables you to run your containerized applications and microservices without having to worry about the infrastructure. With the latest features and enhancements, you can optimize your costs, performance, and scalability and run jobs for various scenarios.

If you want to try out Azure Container Apps, you can get started with the following resources:

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Azure Virtual Machines: Updates for August 2023

Azure Virtual Machines: Updates for August 2023

Azure VM Updates in August 2023

Azure Virtual Machines (VMs) are undeniably one of the cornerstones of Azure, offering flexible and scalable compute resources for a multitude of workloads. In this blog post, we’ll delve into the latest updates and features for Azure VMs that were unveiled in August 2023.

Azure Advisor’s Availability Zone Recommendation

Azure Advisor now offers an Availability Zone recommendation feature to enhance VM resiliency. This capability assists you in migrating VMs to availability zones within an Azure region, ensuring high availability and fault tolerance for your applications. Azure Advisor takes a deep dive into your VMs, considering performance, cost, and compliance factors. Once the analysis is complete, you can effortlessly implement the recommendation with just a few clicks. Alternatively, Azure Resource Manager templates or PowerShell scripts can automate the process. The good news is that this feature is now generally available.

Cross Subscription Restore for Azure Virtual Machines

Another exciting feature that has become generally available is Cross Subscription Restore for Azure VMs. This capability lets you restore your VMs from a backup to a different subscription within the same Azure Active Directory tenant. It’s an incredibly useful tool, especially in disaster recovery, testing, or migration scenarios. Whether you prefer the Azure portal, Azure CLI, or PowerShell, you have the flexibility to perform cross-subscription restore operations.

Retirement of ND-series and NC-series VMs

In a significant move, Azure will be retiring ND-series and NC-series VMs, powered by NVIDIA Tesla P40 and K80 GPUs, on August 31, 2023. These VMs are making way for newer GPU VMs that offer higher performance and support newer CUDA compute capability levels. If your operations rely on ND-series or NC-series VMs, planning your migration to these newer GPU VMs before the retirement date arrives is essential. To assist you in this transition, you can utilize Azure Migrate or other similar tools to assess your readiness for migration and facilitate the process.

Azure NetApp Files Cloud Backup for Virtual Machines

Introducing Azure NetApp Files Cloud Backup for Virtual Machines is a noteworthy development. This feature empowers you to back up and restore your Azure VMs leveraging Azure NetApp Files as their storage solution. Azure NetApp Files is a fully managed file storage service known for its high performance, scalability, and robust security for file-based workloads. Cloud Backup protects your data from accidental deletion, corruption, or even ransomware attacks. You can configure backup policies, set schedules, and define retention periods per your business needs. Moreover, you can restore your data to any point within the retention period. As of now, this feature is in the public preview stage.

In conclusion, these are just some of the highlights of the Azure VM updates that unfolded in August 2023. For a comprehensive look at these updates and more, please explore the Azure updates page or check out the Azure blog.

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Exploring the Exciting Azure SQL Updates Unveiled in August 2023

Azure SQL Updates for August 2023

Azure SQL Updates

Azure SQL offers secure SQL database engines for applications. This post highlights August 2023 updates.

External REST Endpoint Invocation

Now, let’s explore External REST Endpoint Invocation. Microsoft Build 2023 introduced it—a way to integrate Azure Services into Azure SQL Database effortlessly with just one line of code. This feature enriches data, handles complex calculations, and invokes machine learning models. For instance, you can analyze customer reviews by calling an Azure Function via an external REST endpoint.

XML Compression for Azure SQL

Next, focus on the second feature, available since August 2023. XML compression reduces storage needs for Azure SQL Database and Azure SQL Managed Instance by compressing off-row XML data. Using ALTER INDEX, apply XML compression to existing XML indexes to reduce storage space by up to 75%.

Always Encrypted with Intel SGX Enclaves

Always Encrypted secures sensitive data within client applications. Extend it with secure enclaves, enabling computations on encrypted data within the database server’s protected memory region. You can perform operations like pattern matching and sorting on encrypted data without decryption.

In August 2023, Always Encrypted with Intel SGX enclaves entered public preview for Azure SQL Database on DC-series hardware with up to 40 vCores, offering better performance.

New JSON Type and JSON Aggregates

Without delay, explore Azure SQL’s latest JSON features. Since 2016, Azure SQL has supported JSON as a native data type. It lets you store and query JSON documents using standard SQL operators and functions. August 2023 introduced two new features: a lightweight JSON type and JSON aggregates.

Currently in public preview, the new JSON type outperforms NVARCHAR(MAX) by offering faster parsing, better storage efficiency, JSON Schema support, partial updates using JSON Patch, and change tracking with JSON Diff.

The JSON aggregates are a set of new aggregate functions that allow you to perform calculations on JSON values and return JSON results. These functions include:

  • JSON_ARRAYAGG: This returns a JSON array containing the aggregated values.
  • JSON_OBJECTAGG: It Returns a JSON object containing the aggregated key-value pairs.
  • JSON_QUOTE: Function returns a JSON string containing the quoted value.
  • JSON_MERGE: Returns a JSON value that results from merging two or more JSON values.

Conclusion

In summary, these updates and enhancements from August 2023 strengthen Azure SQL, helping you build more powerful, secure applications.

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Azure PostgreSQL Updates for August 2023

Azure PostgreSQL Updates for August 2023

Azure PostgreSQL Updates: Overview

If you are using Azure PostgreSQL, you might be interested in the latest updates and enhancements released in August 2023. It is a fully managed service that offers high availability, scalability, security, and performance for PostgreSQL applications.

Minor Version Updates

Azure PostgreSQL supports multiple minor versions of PostgreSQL, from 11 to 15. In August 2023, PostgreSQL released the latest minor version updates for all supported major versions. These updates include bug fixes, security patches, and performance improvements. You can find the detailed release notes for each minor version on the official PostgreSQL website.

The latest minor versions are:

  • 11.21
  • 12.16
  • 13.12
  • 14.9
  • 15.4

You can upgrade your PostgreSQL server to the latest minor version using the Azure portal, Azure CLI, or PowerShell. Upgrading to the latest minor version is recommended to ensure optimal performance and security for your PostgreSQL server.

Azure PostgreSQL: PgBouncer Support

PgBouncer is a lightweight connection pooler for PostgreSQL that reduces the overhead of opening and closing connections. It can improve the scalability and throughput of your PostgreSQL applications by reusing existing connections and balancing the load among them.

PostgreSQL now supports PgBouncer version 1.20 for all PostgreSQL versions in all supported regions. You can enable PgBouncer for your Azure PostgreSQL server using the Azure portal, Azure CLI, or PowerShell. Also, configure various PgBouncer settings, such as pool mode, max connections, idle timeout, and more.

PgBouncer provides metrics that you can monitor using Azure Monitor or other tools. You can view metrics such as active connections, waiting requests, server latency, etc. These metrics can help you troubleshoot issues and optimize your PgBouncer performance.

Conclusion

The Azure PostgreSQL is constantly adding new features and updates to provide the best experience for PostgreSQL users. In August 2023, it released minor version updates and PgBouncer support for all PostgreSQL versions. These features can help you enhance your PostgreSQL applications with high availability, scalability, security, and performance.

To learn more, visit the official documentation or sign up for a free trial today.

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Azure LUIS: Mastering Language Understanding

Azure LUIS: Mastering Language Understanding

Overview

Azure LUIS is a cloud-based service that enables you to build natural language understanding into your applications. With Azure LUIS, you can create custom models that recognize the intents and entities of your users’ queries and commands. You can also use pre-built models for common scenarios such as booking, calendar, email, etc.

Benefits of Azure LUIS

Some of the benefits are, you can:

  • Easily integrate it with other Azure services such as Bot Framework, Cognitive Services, and Speech Services.
  • Create and manage your models using a graphical interface or a REST API.
  • Train and test your models with real data and feedback.
  • Deploy your models to multiple regions and scale them as needed.
  • Monitor and improve your models with analytics and suggestions.

Use Cases for Azure LUIS

Some of the use cases are:

  • Chatbots and virtual assistants that can handle natural language conversations with your customers or employees.
  • Voice-enabled applications that can understand spoken commands and queries.
  • Search engines and knowledge bases that can provide relevant results based on natural language queries.
  • Text analysis and extraction that can identify key information and insights from unstructured text.

Getting Started

To get started, you need to:

  • Create an Azure account and a LUIS resource in the Azure portal.
  • Create a LUIS app and define your intents and entities in the LUIS portal or using the REST API.
  • Train your app with example utterances and label them with intents and entities.
  • Test your app using the LUIS portal or the REST API.
  • Publish your app to an endpoint and integrate it with your application.

For more information, visit the official documentation: https://docs.microsoft.com/en-us/azure/cognitive-services/luis/.

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Azure Text Analytics for Customer Feedback Sentiment

Azure Text Analytics for Customer Feedback Sentiment

In this blog post, we will show you how to use Azure Text Analytics for sentiment analysis of customer feedback.

Overview

Customer feedback is a valuable source of information for any business. It can help you understand your customers’ needs, preferences, and satisfaction levels. However, analyzing customer feedback manually can be time-consuming and prone to errors. That’s why you need a tool to automate the process and provide insights in minutes.

Azure Text Analytics is a cloud-based service that offers natural language processing capabilities, such as sentiment analysis, keyphrase extraction, language detection, and more. You can easily analyze customer feedback from various sources, such as surveys, reviews, social media, and emails. You can integrate it with other Azure services like Power BI, Logic Apps, and Cognitive Search.

What is Sentiment Analysis and Why is it Important?

Sentiment analysis is identifying and extracting a text’s emotional tone and attitude. It can help you measure customers’ feelings about your products, services, or brand. For example, you can use sentiment analysis to:

  • Monitor customer satisfaction and loyalty.
  • Identify customer pain points and areas of improvement.
  • Detect customer complaints and issues.
  • Discover customer advocates and influencers.
  • Enhance customer experience and retention.

Sentiment analysis can also help you gain a competitive advantage by understanding how your customers perceive your competitors. You can use this information to improve your marketing strategies, product development, and customer service.

Features and Benefits of Azure Text Analytics for Sentiment Analysis

Azure Text Analytics for sentiment analysis provides you with the following features and benefits:

  • Accurate and reliable sentiment scores: It uses advanced machine learning models to assign a sentiment score to each text. The score ranges from 0 (negative) to 1 (positive), with 0.5 being neutral. You can also get sentiment scores at the document, sentence, or aspect level.
  • Multilingual support: Supports over 20 languages for sentiment analysis, including English, Spanish, French, German, Chinese, Japanese, and more. You can also detect the language of the text automatically.
  • Customizable models: You can customize the sentiment models to suit your domain or industry. You can use the Custom Text feature to train your models with your data and labels.
  • Scalable and secure service: It can handle large volumes of text with high performance and availability. You can also rest assured that your data is secure and compliant with Azure’s privacy and security standards.

How to Get Started with Azure Text Analytics for Sentiment Analysis?

Getting started with Text Analytics for sentiment analysis is easy and fast. Here are the steps you need to follow:

  1. Create an Azure account: If you don’t yet have one, you can create one for free here.
  2. Create a Cognitive Services resource: To use Azure Text Analytics, you must create a Cognitive Services resource in your Azure portal. You can follow this tutorial to learn how.
  3. Get your endpoint and key: Once you create your Cognitive Services resource, you will get an endpoint URL and a subscription key that you will need to access the service.
  4. Choose your preferred method: You can use Azure Text Analytics for sentiment analysis in different ways, such as:
    • Web interface: Text Analytics demo page to test the service with your own or sample text.
    • REST API: Text Analytics REST API to send HTTP requests and get JSON responses. You can follow this tutorial to learn how.
    • SDKs: Text Analytics SDKs to integrate the service with your preferred programming languages, such as Python, C#, Java, or JavaScript. You can follow this tutorial to learn how.
    • Connectors: Text Analytics connectors to integrate the service with other Azure services or third-party applications, such as Power BI, Logic Apps, or Cognitive Search. You can follow this tutorial to learn how.

We hope this blog post has given you an overview of how to use Azure Text Analytics for sentiment analysis of customer feedback. You can visit the official documentation page here to learn more about Azure Text Analytics. If you have any questions or feedback, please comment below or contact us here.

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Plugins for Azure OpenAI Service: How-to Guide

Plugins for Azure OpenAI Service: How-to Guide

Use Plugins for Azure OpenAI Service

In this blog post, we will explore different types of plugins for Azure OpenAI Service and how to use them for your projects.

Azure OpenAI Service is a cloud-based platform that lets you access the powerful capabilities of OpenAI models. You can create natural language applications, generate text and images, and analyze data. But did you know that you can also extend the functionality of Azure OpenAI Service with plugins?

Plugins are optional components you can install on your Azure OpenAI Service account. They allow you to customize the behavior of the OpenAI models, add new features, and integrate with other services. In this blog post, we will explore the different types of plugins available for Azure OpenAI Service and how to use them for your projects.

Types of Plugins for Azure OpenAI Service

There are three main types of plugins: model plugins, feature plugins, and integration plugins.

Model plugins let you modify the parameters and settings of the OpenAI models. For example, you can use a model plugin to change the text generation model’s temperature, frequency, or presence penalty. You can also use a model plugin to fine-tune the model on your data or add custom tokens.

Feature plugins let you add new capabilities to the OpenAI models. For example, a feature plugin can enable sentiment analysis, summarization, or translation for the natural language model. You can also use a feature plugin to generate different images, such as faces, logos, or landscapes.

Integration plugins let you connect the OpenAI models with other services and platforms. For example, you can use an integration plugin to send and receive data from Microsoft Power BI, Google Sheets, or Slack. You can also use an integration plugin to deploy your applications on Azure App Service, Azure Functions, or Azure Kubernetes Service.

How to Use Plugins for Azure OpenAI Service

To use Azure OpenAI Service plugins, you need an active account and a subscription plan. You can sign up for a free trial or choose from one of the paid plans on the Azure portal.

Once you have an account and a subscription plan, you can browse and install plugins from the Azure Marketplace. The Azure Marketplace is an online store where you can find and buy software and services from Microsoft and third-party providers.

To Install Plugins

  1. Go to the Azure portal and click Create a resource.
  2. Search for OpenAI and choose OpenAI Service.
  3. In the next page, click Plugins to see a list of available plugins for Azure OpenAI Service.
  4. Click the required plugin name and click Get it now.
  5. You must agree to the terms and conditions and provide some basic information.
  6. Click Create and wait for the installation to complete.

Using the Dashboard

After installing a plugin, you can use it from the Azure OpenAI Service dashboard. The dashboard allows you to manage your account, create projects, and access the OpenAI models.

  1. To open the dashboard, go to the Azure portal and click OpenAI Service under All resources.
  2. In the dashboard, you will see a tab for each plugin you have installed.
  3. Click a tab to open the plugin interface and start using it. Depending on the type of plugin, you may need to provide some inputs, such as text, images, or data sources.
  4. Then, click Run or Generate to see the output from the OpenAI model.
  5. You can also use plugins from code by using the Azure OpenAI Service SDK. The SDK library lets you interact with the OpenAI models programmatically. You can use it with Python, C#, Java, or Node.js.

Using Plugin from Code

To use plugins from code, you need to import the SDK and initialize an instance of the OpenAI client. Then, you need to specify the name of the plugin you want to use and pass it as an argument to the corresponding method. If you want to use OpenAI for sentiment analysis, you can use the OpenAI API. Here’s an example:

import openai
openai.api_key = 'your-api-key'
response = openai.Completion.create(
  engine="text-davinci-002",
  prompt="Sentiment analysis of the following text:\nI love Azure OpenAI Service!\n",
  temperature=0.5,
  max_tokens=1
)
print(response.choices[0].text.strip())

Replace ‘your-api-key’ with your actual OpenAI API key. This script will return the sentiment of the text as a string (e.g., “Positive”, “Negative”, or “Neutral”).

Conclusion

Azure OpenAI Service is a powerful platform that lets you leverage the capabilities of OpenAI models for your projects. With plugins, you can further enhance and customize your experience with Azure OpenAI Service. You can choose from various plugins that suit your needs and goals.

To start with Azure OpenAI Service plugin, sign up for a free trial or choose a subscription plan on the Azure portal. Then, browse and install plugins from the Azure Marketplace and use them from the dashboard or code.

We hope this blog post has given you an overview of the different types of plugins for Azure OpenAI Service and how to use them. Please let us know in the comments below if you have any questions or feedback. Happy coding!

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