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Split LLM & GAI out
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‎index.html‎

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@@ -1189,9 +1189,9 @@ <h5 class="card-title mt-3"><a href="https://github.com/strawberry-graphql/straw
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<hr class="my-4">
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<!--Content Managment System-->
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<div class="category" id="Content Managment System">
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<h3 class="mt-4 display-6">Content Managment System</h3>
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<!--Content Managment System (CMS)-->
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<div class="category" id="Content Managment System (CMS)">
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<h3 class="mt-4 display-6">Content Managment System (CMS)</h3>
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<p>
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Content Management System (CMS) frameworks in Python are software platforms designed to facilitate the creation,
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management, and publication of digital content, making it easier for users to build and maintain websites
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</div>
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</div>
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<!--End of Content Managment System-->
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<!--End of Content Managment System (CMS)-->
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<hr class="my-4">
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<!--ML, DL, & AI-->
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<div class="category" id="ML,DL, & AI">
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<h3 class="mt-4 display-6">ML, DL, & AI</h3>
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<!--ML, DL, and AI-->
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<div class="category" id="ML, DL, and AI">
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<h3 class="mt-4 display-6">ML, DL, and AI</h3>
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<p>
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Python frameworks are exceptionally well-suited for machine learning (ML), deep learning (DL), and artificial intelligence (AI) applications.
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Python's popularity in this domain is driven by its rich ecosystem of specialized
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</div>
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</div>
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<div class="col-12 col-6 col-sm-6 col-lg-3 mb-4">
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<div class="card">
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<div class="card-body text-center">
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<a href="https://openai.com/" target="_blank">
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<img class="card-img-top" src="static/image/logos/mindsdb.png" alt="mindsdb">
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</a>
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<figure class="p-3 mb-0">
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<blockquote class="blockquote">
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<p class="text-muted">
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<a href="https://github.com/openai/openai-python" target="_blank">Build AI applications fast</a>
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</p>
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</blockquote>
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</figure>
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<p class="card-text">MindsDB's AI Virtual Database empowers developers to connect any AI/ML model to any datasource.</p>
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</div>
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</div>
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</div>
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</div>
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</div>
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<!--End of ML, DL, and AI-->
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<hr class="my-4">
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<!--LLM & Generative AI-->
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<div class="category" id="LLM and Generative AI">
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<h3 class="mt-4 display-6">LLM and Generative AI</h3>
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<p>
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Python frameworks for large language models (LLMs), generative AI, and AI agents
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empower developers to create applications in text generation, image synthesis,
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code generation, and more. Leveraging Python's vast library ecosystem
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and its central role in LLM and Generative AI research, these tools simplify building,
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orchestrating, deploying, and serving state-of-the-art models.
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</p>
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<div class="row grids mt-4" data-masonry='{"percentPosition": true }'>
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<div class="col-12 col-6 col-sm-6 col-lg-3 mb-4">
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<div class="card">
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</div>
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</div>
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<div class="col-12 col-6 col-sm-6 col-lg-3 mb-4">
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<div class="card">
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<div class="card-body text-center">
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<a href="https://www.llamaindex.ai/" target="_blank">
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<img class="card-img-top" src="static/image/logos/llamaindex.svg" alt="llamaindex">
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</a>
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<hr>
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<p class="card-text">
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<small>
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<a href="https://github.com/run-llama/llama_index" target="_blank">LlamaIndex</a>
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is a data framework for your LLM applications.
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</small>
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</p>
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<p>Turn your enterprise data into production-ready LLM applications.</p>
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</div>
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</div>
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</div>
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<div class="col-12 col-6 col-sm-6 col-lg-3 mb-4">
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<div class="card">
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<a class="text-center p-2" href="https://superagi.com/" target="_blank">
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</div>
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</div>
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<div class="col-12 col-6 col-sm-6 col-lg-3 mb-4">
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<div class="card">
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<div class="card-body text-center">
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<a href="https://www.llamaindex.ai/" target="_blank">
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<img class="card-img-top" src="static/image/logos/llamaindex.svg" alt="llamaindex">
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</a>
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<hr>
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<p class="card-text">
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<small>
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<a href="https://github.com/run-llama/llama_index" target="_blank">LlamaIndex</a>
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is a data framework for your LLM applications.
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</small>
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</p>
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<p>Turn your enterprise data into production-ready LLM applications.</p>
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</div>
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</div>
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</div>
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<div class="col-12 col-6 col-sm-6 col-lg-3 mb-4">
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<div class="card">
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<a class="text-center p-2" href="https://github.com/OpenBMB/ChatDev" target="_blank">
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</div>
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</div>
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<div class="col-12 col-6 col-sm-6 col-lg-3 mb-4">
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<div class="card">
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<div class="card-body text-center">
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<a href="https://mindsdb.com/" target="_blank">
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<img class="card-img-top" src="static/image/logos/mindsdb.png" alt="mindsdb">
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</a>
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<figure class="p-3 mb-0">
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<blockquote class="blockquote">
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<p class="text-muted">
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<a href="https://github.com/mindsdb/mindsdb" target="_blank">The platform for building AI from enterprise data.</a>
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</p>
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</blockquote>
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</figure>
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<p class="card-text">You can create, serve, and fine-tune models in real-time from your database, vector store, and application data.</p>
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</div>
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</div>
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</div>
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</div>
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</div>
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<!--End of ML, DL, & AI-->
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<!--End of LLM & Generative AI-->
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<hr class="my-4">
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<!--Task Queues & Messages-->
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<div class="category" id="Task Queues & Messaging">
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<h3 class="mt-4 display-6">Task Queues & Messaging</h3>
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<!--Task Queue and Messages-->
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<div class="category" id="Task Queue and Messaging">
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<h3 class="mt-4 display-6">Task Queue and Messaging</h3>
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<p>
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Python offers robust frameworks for task queues and messaging systems, facilitating the creation of scalable, asynchronous, and event-driven applications.
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Python's extensive libraries for message handling and serialization, along with its readability and simplicity,
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</div>
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</div>
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<!--End of Task Queue and Messaging-->
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<!--Parallel & Distributed Computing-->
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<div class="category" id="Parallel & Distributed Computing">
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<h3 class="mt-4 display-6">Parallel & Distributed Computing</h3>
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<!--Parallel and Distributed Computing-->
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<div class="category" id="Parallel and Distributed Computing">
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<h3 class="mt-4 display-6">Parallel and Distributed Computing</h3>
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<p>
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Python frameworks (including bindings) are often used to create applications that distribute workloads across multiple nodes or machines,
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enabling parallel processing, task scheduling, and distributed data processing.
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<!--Workflow & Pipelines-->
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<h3 class="mt-4 display-6">Workflow & Pipelines</h3>
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<!--Workflow and Pipelines-->
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<div class="category" id="Worflow and Pipelines">
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<h3 class="mt-4 display-6">Workflow and Pipelines</h3>
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<p>
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Python provides abroad of frameworks and packages for workflow management, data pipelines, and job scheduling, making it a strong choice for data engineering and job automation.
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Python's flexibility, rich ecosystem, and ease of use make it well-suited for developing and maintaining data pipelines and workflow automation systems.
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</div>
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<!--End of Workflows & Pipeline-->
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<!--End of Workflow and Pipelines-->
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<!--Web Crawling & Scraping-->
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<div class="category" id="Web Crawling & Scraping">
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<h3 class="mt-4 display-6">Web Crawling & Scraping</h3>
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<!--Web Crawling and Scraping-->
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<div class="category" id="Web Crawling and Scraping">
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<h3 class="mt-4 display-6">Web Crawling and Scraping</h3>
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<p>
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Web crawling/scraping using Python frameworks is a highly effective approach for extracting data from websites and web-based sources.
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Python offers powerful frameworks that streamline the web crawling/scraping and data acquisition process.
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</div>
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</div>
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<!--End of Web Crawling and Scraping-->
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<div class="category" id="GUI & TUI">
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<h3 class="mt-4 display-6">GUI & TUI</h3>
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<!--GUI and TUI-->
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<div class="category" id="GUI and TUI">
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<h3 class="mt-4 display-6">GUI and TUI</h3>
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<p>
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Python frameworks are an excellent choice for graphical user interface (GUI) and text-based user interface (TUI) development,
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as they provide developers with versatile tools for creating cross-platform desktop applications.
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<!--End of GUI and GUI-->
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