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Take any Python code and build a dynamic GUI on top of it by dragging and dropping components. Python is already the most popular language in the world. This makes it even better! The attached video is only 45 seconds. It will show you how it works. Here is... show more

Santiago

451,998 subscribers

155,179 просмотров • 1 год назад •via X (Twitter)

Здоровье и велнес Образование Наука и технологии

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Комментарии: 10

Фото профиля Roman B. 🇺🇦

Roman B. 🇺🇦1 год назад

I bookmark way to many of your post 😁

Фото профиля Santiago

Santiago1 год назад

That's good. It means I'm doing a good job of bringing you things that you think are useful 😉

Фото профиля DatJot

DatJot1 год назад

When you have Tableau + Power BI at the fraction of the cost, IMHO, it is not worth the price tag. Don't get me wrong, it looks nice, but I am trying to figure out why someone would switch from Tableau to Taipy with that type of price tag. Does the Community Edition have the designer? Does not appear to have the designer. Maybe there is something I am missing but I don't see a WOW factor compared to software like Tableau that would make me switch products.

Фото профиля whynesspower ⟠

whynesspower ⟠1 год назад

From the looks of it Rip streamlit and gradio

Фото профиля JoJo Ventures

JoJo Ventures1 год назад

Nice share, this is really good. It would be amazing if the drag-and-drop GUI feature could be applied to @streamlit and @Gradio too, so data scientists could focus on the ML model and dataset instead.

Фото профиля Tomer Nosrati

Tomer Nosrati1 год назад

Have you seen @anvil_works ? It appears to be a more robust implementation of a GUI designer for Python.

Фото профиля Haider.

Haider.1 год назад

you think this kind of tool could be used to create more user-friendly interfaces for complex Python libraries or frameworks?

Фото профиля Santiago

Santiago1 год назад

Yes, that's exactly the goal. You have some Python code that you want to make accessible through an interface. Instead of having to learn HTML/CSS, etc, you can use Taipy Designer to build an interface for it.

Фото профиля MasterChief

MasterChief1 год назад

Machine learning apps

Фото профиля Hesam

Hesam1 год назад

This is a killer data science tool! Already there are amazing libraries to add visuals to the data but this is fascinating 🔥

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Santiago

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Santiago

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Santiago

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Santiago

51,012 просмотров • 1 год назад

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English is the most powerful language in the world. MongoDB just added support for MCP, and literally anyone can now query data without knowing anything about databases. If you know English, you are all set. I recorded a quick video to show you how I connect to a sample Airbnb database and run different queries: • How many listings? • How many listings in the US? • What's the list of countries in these listings? It takes 10 seconds to configure Claude, Cursor, WindSurf, or any other AI assistant to connect to MongoDB's MCP Server. By the way, the server supports much more than queries: • You can explore your collections • You can fetch schema information • You can generate app code snippets • You can manage your databases • You can handle cluster/user/admin tasks Here is a link to the MCP server GitHub repository: This is huge for developers. It's even bigger for non-developers. Thanks to the MongoDB team for collaborating with me on this post.

Santiago

44,818 просмотров • 11 месяцев назад

An LLM with native access to find and run agents is a huge thing! This large language model (called ASI:One and developed by Fetch.ai) can do this natively when you show it a problem: • Reason about the problem • Identify live agents and tools that can help solve it • Dynamically invoke these agents and tools Honestly, this is pretty nuts! You don't need to set up anything beforehand. You don't need to write any code. Here is the best part: ASI:One has access to any agent published on Agentverse, an open directory of agents! This gives the model access to *millions* of tools it can execute dynamically when solving a task. Here is a simple example (the one in the attached video): • I went to Google Maps • I copied the latitude and longitude of a location • I asked ASI:One about relevant places around that location • ASI:One went to the marketplace • It identified and called the Google Places agent • It returned a list of museums, restaurants, and landmarks near my location Pretty awesome! You can try this now by going to You don't need to pay or register to test it out. If you want to get ideas of what's possible, check Agentverse, the agent marketplace: The model will have access to all of those tools. This is pretty awesome and opens up a whole new world of possibilities! Thanks to the team for partnering with me on this post!

An LLM with native access to find and run agents is a huge thing! This large language model (called ASI:One and developed by Fetch.ai) can do this natively when you show it a problem: • Reason about the problem • Identify live agents and tools that can help solve it • Dynamically invoke these agents and tools Honestly, this is pretty nuts! You don't need to set up anything beforehand. You don't need to write any code. Here is the best part: ASI:One has access to any agent published on Agentverse, an open directory of agents! This gives the model access to millions of tools it can execute dynamically when solving a task. Here is a simple example (the one in the attached video): • I went to Google Maps • I copied the latitude and longitude of a location • I asked ASI:One about relevant places around that location • ASI:One went to the marketplace • It identified and called the Google Places agent • It returned a list of museums, restaurants, and landmarks near my location Pretty awesome! You can try this now by going to You don't need to pay or register to test it out. If you want to get ideas of what's possible, check Agentverse, the agent marketplace: The model will have access to all of those tools. This is pretty awesome and opens up a whole new world of possibilities! Thanks to the team for partnering with me on this post!

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43,782 просмотров • 1 год назад