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Starlet #8 Prompt flow - Developer Tool for Building High-Quality LLM Applications

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rel="noopener noreferrer" href="/blog/mockoon"><span class="inline -ml-2 text-sm text-blue-700 hover:underline">Issue #3 - Mockoon</span></a></li><li class="mb-2 leading-3"><a class="cursor-pointer" rel="noopener noreferrer" href="/blog/dlta-ai"><span class="inline -ml-2 text-sm text-blue-700 hover:underline">Issue #2 - DLTA-AI</span></a></li><li class="mb-2 leading-3"><a class="cursor-pointer" rel="noopener noreferrer" href="/blog/sniffnet"><span class="inline -ml-2 text-sm text-blue-700 hover:underline">Issue #1 - Sniffnet</span></a></li></ul></div></div></div><div class="w-full flex flex-col justify-start items-center"><div class="w-full p-4 md:p-0 mt-6 md:w-5/6 lg:max-w-6xl h-full flex flex-col justify-start items-center self-center"><img class="hidden md:block w-auto max-w-full object-scale-down" src="/assets/blog/prompt-flow/banner.webp" alt=""/><div class="w-auto max-w-6xl mt-4 md:mt-12 prose prose-indigo prose-xl md:prose-2xl flex flex-col justify-center items-center"><h1 class="leading-16">Starlet #8 Prompt flow - Developer Tool for Building High-Quality LLM Applications</h1></div><div class="w-full mt-8 mb-2 max-w-6xl px-2 flex flex-row items-center justify-center text-sm text-gray-900 font-semibold trackingwide uppercase"><div class="flex space-x-1 text-gray-500"><span class="text-gray-900">Jie Tong</span><span aria-hidden="true"> · </span><time dateTime="2023-09-26T00:00:00.000Z">Sep 26, 2023</time><span aria-hidden="true"> · </span><span> <!-- -->3<!-- --> min read </span></div></div><div class="mt-8 w-full max-w-5xl prose prose-indigo prose-xl md:prose-2xl"><p><em>This is the eighth issue of The Starlet List. If you want to prompt your open source project on star-history.com for free, please check out our <a href="/blog/list-your-open-source-project">announcement</a>.</em></p> <hr> <p>Open-sourced by Microsoft recently, <a href="https://github.com/microsoft/promptflow">Prompt flow</a> is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.</p> <h2>Why</h2> <p>The utilization of Large Language Models (LLMs), such as ChatGPT and GPT-4, to enhance existing software or create new applications has become a pivotal strategy for many developers. This trend has been largely catalyzed by the early access Microsoft had to OpenAI&#39;s models, which allowed them to pioneer in this domain. One significant shift that LLMs introduce to application development is the increased stochastic nature of applications. This means that traditional testing methods may not be adequate or even applicable. The project &#39;prompt flow&#39; represents Microsoft&#39;s efforts to incorporate their insights on building quality into the process of LLM application development.</p> <h2>How</h2> <p>Prompt flow provides a suite of developer tools including:</p> <ul> <li>A <a href="https://marketplace.visualstudio.com/items?itemName=prompt-flow.prompt-flow">VS Code extension</a> that allows for visual development and testing of the flow within VS Code. Although it may initially appear as a low-code solution for creating static &quot;graphs&quot;, it actually allows you to program within different Python nodes with as much flexibility as you need. This enables you to fully utilize the quality assurance capabilities that Prompt Flow offers.</li> </ul> <p><img src="/assets/blog/prompt-flow/vs-code.webp" alt="vs-code"></p> <ul> <li>A <a href="https://pypi.org/project/promptflow/">Python SDK/CLI</a> that facilitates experimentation with batch tests and evaluations, and offers a clear visualization of test results and intermediate outcomes. This tool can also be integrated into your CI/CD process.</li> </ul> <p><img src="/assets/blog/prompt-flow/python-sdk.webp" alt="python-sdk"></p> <ul> <li><a href="https://microsoft.github.io/promptflow/how-to-guides/tune-prompts-with-variants.html">Built-in support for prompt tuning</a> is another feature that simplifies the process of testing multiple prompts. It allows you to easily select the best prompt using metrics.</li> <li><a href="https://microsoft.github.io/promptflow/how-to-guides/deploy-a-flow/index.html">Flexible deployment support</a> that enables you to package your flow as a Docker container, which can then be run on various cloud platforms. Additionally, you can integrate the flow into your existing Python application using the SDK.9/17/2023, 12:42:47 PMSend</li> </ul> <p>Moreover, a cloud-based version of Prompt flow is available in Azure AI, which incorporates enterprise features and facilitates team collaboration on Azure. It is currently in public preview. You can find more details <a href="https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/overview-what-is-prompt-flow?view=azureml-api-2">here</a>.</p> <h2>Star growth</h2> <p>As for its popularity, Prompt flow was publicly released in early September and witnessed a significant increase in interest, accumulating 2,000 stars within the first two weeks🚀.</p> <p><img src="/assets/blog/prompt-flow/star-history.webp" alt="star-history"></p> </div></div><div class="mt-12"><iframe src="https://embeds.beehiiv.com/2803dbaa-d8dd-4486-8880-4b843f3a7da6?slim=true" data-test-id="beehiiv-embed" height="52" frameBorder="0" scrolling="no" style="margin:0;border-radius:0px !important;background-color:transparent"></iframe></div></div><div class="w-full hidden lg:block"></div></div><footer class="relative w-full shrink-0 h-auto mt-6 flex flex-col justify-end items-center"><div class="w-full py-2 px-3 md:w-5/6 lg:max-w-7xl flex flex-row flex-wrap justify-between items-center 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crossorigin="">{"props":{"pageProps":{"blog":{"title":"Starlet #8 Prompt flow - Developer Tool for Building High-Quality LLM Applications","slug":"prompt-flow","author":"Jie Tong","featured":true,"featureImage":"/assets/blog/prompt-flow/banner.webp","publishedDate":"2023-09-26T00:00:00.000Z","excerpt":"Fresh open-sourced by Microsoft, Prompt flow is a suite of devtools designed to streamline the end-to-end development cycle of LLM-based AI applications.","readingTime":3},"parsedBlogHTML":"\u003cp\u003e\u003cem\u003eThis is the eighth issue of The Starlet List. If you want to prompt your open source project on star-history.com for free, please check out our \u003ca href=\"/blog/list-your-open-source-project\"\u003eannouncement\u003c/a\u003e.\u003c/em\u003e\u003c/p\u003e\n\u003chr\u003e\n\u003cp\u003eOpen-sourced by Microsoft recently, \u003ca href=\"https://github.com/microsoft/promptflow\"\u003ePrompt flow\u003c/a\u003e is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.\u003c/p\u003e\n\u003ch2\u003eWhy\u003c/h2\u003e\n\u003cp\u003eThe utilization of Large Language Models (LLMs), such as ChatGPT and GPT-4, to enhance existing software or create new applications has become a pivotal strategy for many developers. This trend has been largely catalyzed by the early access Microsoft had to OpenAI\u0026#39;s models, which allowed them to pioneer in this domain. One significant shift that LLMs introduce to application development is the increased stochastic nature of applications. This means that traditional testing methods may not be adequate or even applicable. The project \u0026#39;prompt flow\u0026#39; represents Microsoft\u0026#39;s efforts to incorporate their insights on building quality into the process of LLM application development.\u003c/p\u003e\n\u003ch2\u003eHow\u003c/h2\u003e\n\u003cp\u003ePrompt flow provides a suite of developer tools including:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eA \u003ca href=\"https://marketplace.visualstudio.com/items?itemName=prompt-flow.prompt-flow\"\u003eVS Code extension\u003c/a\u003e that allows for visual development and testing of the flow within VS Code. Although it may initially appear as a low-code solution for creating static \u0026quot;graphs\u0026quot;, it actually allows you to program within different Python nodes with as much flexibility as you need. This enables you to fully utilize the quality assurance capabilities that Prompt Flow offers.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cimg src=\"/assets/blog/prompt-flow/vs-code.webp\" alt=\"vs-code\"\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eA \u003ca href=\"https://pypi.org/project/promptflow/\"\u003ePython SDK/CLI\u003c/a\u003e that facilitates experimentation with batch tests and evaluations, and offers a clear visualization of test results and intermediate outcomes. This tool can also be integrated into your CI/CD process.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cimg src=\"/assets/blog/prompt-flow/python-sdk.webp\" alt=\"python-sdk\"\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://microsoft.github.io/promptflow/how-to-guides/tune-prompts-with-variants.html\"\u003eBuilt-in support for prompt tuning\u003c/a\u003e is another feature that simplifies the process of testing multiple prompts. It allows you to easily select the best prompt using metrics.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://microsoft.github.io/promptflow/how-to-guides/deploy-a-flow/index.html\"\u003eFlexible deployment support\u003c/a\u003e that enables you to package your flow as a Docker container, which can then be run on various cloud platforms. Additionally, you can integrate the flow into your existing Python application using the SDK.9/17/2023, 12:42:47 PMSend\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eMoreover, a cloud-based version of Prompt flow is available in Azure AI, which incorporates enterprise features and facilitates team collaboration on Azure. It is currently in public preview. You can find more details \u003ca href=\"https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/overview-what-is-prompt-flow?view=azureml-api-2\"\u003ehere\u003c/a\u003e.\u003c/p\u003e\n\u003ch2\u003eStar growth\u003c/h2\u003e\n\u003cp\u003eAs for its popularity, Prompt flow was publicly released in early September and witnessed a significant increase in interest, accumulating 2,000 stars within the first two weeks🚀.\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"/assets/blog/prompt-flow/star-history.webp\" alt=\"star-history\"\u003e\u003c/p\u003e\n"},"__N_SSG":true},"page":"/blog/[slug]","query":{"slug":"prompt-flow"},"buildId":"xKX4ZiOi_N7h3OBOEsSZu","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>

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