Probly – Spreadsheets, Python, and AI in the browser
https://github.com/PragmaticMachineLearning/probly
https://github.com/PragmaticMachineLearning/probly
GitHub
GitHub - PragmaticMachineLearning/probly
Contribute to PragmaticMachineLearning/probly development by creating an account on GitHub.
Visualizing F1 race results using Polars and Great Tables
Programmatically create an F1 race analysis table using the FastF1 API, the Great Tables library, and Polars.
https://jimmieyoo.com/posts/F1_Race_Result_Tables_Using_Python_and_Polars_2024_Australian_GP.html
Programmatically create an F1 race analysis table using the FastF1 API, the Great Tables library, and Polars.
https://jimmieyoo.com/posts/F1_Race_Result_Tables_Using_Python_and_Polars_2024_Australian_GP.html
Design of Everyday APIs
What makes a good API for a library? How can you design an API that is delightful to use? This post walks through the principles of what goes into user-centered design and how best to apply those principles when writing a Python library for fellow developers.
https://roguelynn.com/words/everyday-apis
What makes a good API for a library? How can you design an API that is delightful to use? This post walks through the principles of what goes into user-centered design and how best to apply those principles when writing a Python library for fellow developers.
https://roguelynn.com/words/everyday-apis
roguelynn
Design of Everyday APIs
What makes a good API for a library? How can you design an API that is delightful to use? This post walks through the principles of what goes into user-centered design and how best to apply those principles when writing a Python library for fellow developers.
FlashMLA
FlashMLA is an efficient MLA decoding kernel for Hopper GPUs, optimized for variable-length sequences serving.
https://github.com/deepseek-ai/FlashMLA
FlashMLA is an efficient MLA decoding kernel for Hopper GPUs, optimized for variable-length sequences serving.
https://github.com/deepseek-ai/FlashMLA
GitHub
GitHub - deepseek-ai/FlashMLA: FlashMLA: Efficient MLA decoding kernels
FlashMLA: Efficient MLA decoding kernels. Contribute to deepseek-ai/FlashMLA development by creating an account on GitHub.
Creating drum machines, effects, sequencers, samplers, and synths with Python
I created a subreddit where I post scripts showing how to make drum machines, sequencers, samplers, and synths with Python.
https://www.reddit.com/r/supriya_python/s/wFMjENJQ02
I created a subreddit where I post scripts showing how to make drum machines, sequencers, samplers, and synths with Python.
https://www.reddit.com/r/supriya_python/s/wFMjENJQ02
Reddit
r/supriya_python
A place to learn and share information about Supriya, the Python API for SuperCollider.
vlmrun-hub
A hub for various industry-specific schemas to be used with VLMs.
https://github.com/vlm-run/vlmrun-hub
A hub for various industry-specific schemas to be used with VLMs.
https://github.com/vlm-run/vlmrun-hub
GitHub
GitHub - vlm-run/vlmrun-hub: A hub for various industry-specific schemas to be used with VLMs.
A hub for various industry-specific schemas to be used with VLMs. - vlm-run/vlmrun-hub
Ditching Django Admin for FastHTML with HTMX
Building a Django Admin-like dashboard with automatic refresh using FastHTML and HTMX.
https://simn.fr/posts/dicthing-django-admin-for-fasthtml
Building a Django Admin-like dashboard with automatic refresh using FastHTML and HTMX.
https://simn.fr/posts/dicthing-django-admin-for-fasthtml
simn.fr
Ditching Django Admin for FastHTML with HTMX
Building a Django Admin-like dashboard with automatic refresh using FastHTML and HTMX
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Building AI Agents for JupyterLab using Notebook Intelligence
This post introduces Notebook Intelligence (NBI), an AI coding assistant framework for JupyterLab, and demonstrates how to build AI Agents using NBI's tool-calling capabilities with examples of tools for geo-coordinate lookup, map generation, notebook creation, and sharing. It provides a guide for developers to integrate custom AI-powered functionalities into JupyterLab's Copilot Chat.
https://blog.jupyter.org/building-ai-agents-for-jupyterlab-using-notebook-intelligence-0515d4c41a61
This post introduces Notebook Intelligence (NBI), an AI coding assistant framework for JupyterLab, and demonstrates how to build AI Agents using NBI's tool-calling capabilities with examples of tools for geo-coordinate lookup, map generation, notebook creation, and sharing. It provides a guide for developers to integrate custom AI-powered functionalities into JupyterLab's Copilot Chat.
https://blog.jupyter.org/building-ai-agents-for-jupyterlab-using-notebook-intelligence-0515d4c41a61
Medium
Building AI Agents for JupyterLab using Notebook Intelligence
It is now possible to build AI Agents for JupyterLab and access from Copilot Chat UI, using Notebook Intelligence!
How to add an object in Django Admin with a bookmarklet
The article explains how to create a Django Admin bookmarklet that pre-fills form fields when adding new items, like bookmarks, using a web page's URL, title, and selected text. It walks through setting up the JavaScript snippet, customizing it for your Django app, and adding it as a browser bookmark for quick data entry.
https://www.gyford.com/phil/writing/2025/02/14/django-admin-bookmarklet
The article explains how to create a Django Admin bookmarklet that pre-fills form fields when adding new items, like bookmarks, using a web page's URL, title, and selected text. It walks through setting up the JavaScript snippet, customizing it for your Django app, and adding it as a browser bookmark for quick data entry.
https://www.gyford.com/phil/writing/2025/02/14/django-admin-bookmarklet
Phil Gyford’s website
How to add an object in Django Admin with a bookmarklet
How to create a bookmarklet to pre-fill a Django Admin form with information about a web page.
Minions
Minions is a communication protocol that enables small on-device models to collaborate with frontier models in the cloud. By only reading long contexts locally, we can reduce cloud costs with minimal or no quality degradation.
https://github.com/HazyResearch/minions
Minions is a communication protocol that enables small on-device models to collaborate with frontier models in the cloud. By only reading long contexts locally, we can reduce cloud costs with minimal or no quality degradation.
https://github.com/HazyResearch/minions
GitHub
GitHub - HazyResearch/minions: Big & Small LLMs working together
Big & Small LLMs working together. Contribute to HazyResearch/minions development by creating an account on GitHub.
AIBrix
Cost-efficient and pluggable Infrastructure components for GenAI inference.
https://github.com/vllm-project/aibrix
Cost-efficient and pluggable Infrastructure components for GenAI inference.
https://github.com/vllm-project/aibrix
GitHub
GitHub - vllm-project/aibrix: Cost-efficient and pluggable Infrastructure components for GenAI inference
Cost-efficient and pluggable Infrastructure components for GenAI inference - vllm-project/aibrix
Craw4LLM
CRAW4LLM is an efficient web crawling method that prioritizes webpages based on their potential influence on LLM pretraining, replacing traditional graph-connectivity-based priorities. By crawling only 21% of URLs, it achieves the same downstream performance as previous methods, significantly reducing data waste and website burden.
https://github.com/cxcscmu/Craw4LLM
CRAW4LLM is an efficient web crawling method that prioritizes webpages based on their potential influence on LLM pretraining, replacing traditional graph-connectivity-based priorities. By crawling only 21% of URLs, it achieves the same downstream performance as previous methods, significantly reducing data waste and website burden.
https://github.com/cxcscmu/Craw4LLM
GitHub
GitHub - cxcscmu/Craw4LLM: Official repository for "Craw4LLM: Efficient Web Crawling for LLM Pretraining"
Official repository for "Craw4LLM: Efficient Web Crawling for LLM Pretraining" - cxcscmu/Craw4LLM
Part 2 - Building an LLM RAG with PyFlyde & LangChain
https://blog.kodigy.com/post/visual-ai-engineering-with-pyflyde-pt2-rag/
https://blog.kodigy.com/post/visual-ai-engineering-with-pyflyde-pt2-rag/
A system brought to life
AI Engineering Goes Visual: Building an LLM RAG with PyFlyde & LangChain
This part builds upon the Scraper app that we created in the part 1 and uses our visual programming skills to dive deeper in the LLM engineering world. This time we turn our article database into a RAG app, making use of LangChain, Vector Store and local…
How Python Evolves: From PEP to Feature
Explore how Python gets new functionality and how PEPs have a huge role in this, by looking at PEP484 and its interesting backstory.
https://www.youtube.com/watch?v=TzpOdpdX7pE
Explore how Python gets new functionality and how PEPs have a huge role in this, by looking at PEP484 and its interesting backstory.
https://www.youtube.com/watch?v=TzpOdpdX7pE
YouTube
How Python Evolves: From PEP to Feature
👉 Visit https://brilliant.org/ArjanCodes/ to try Brilliant for free for 30 days. You’ll also get 20% off an annual premium subscription.
In this video, I’ll explore how Python gets new functionality and how PEPs have a huge role in this, by looking at PEP484…
In this video, I’ll explore how Python gets new functionality and how PEPs have a huge role in this, by looking at PEP484…
CCTV_YOLO
Fast Real-time Object Detection with High-Res Output
https://github.com/SanshruthR/CCTV_YOLO
Fast Real-time Object Detection with High-Res Output
https://github.com/SanshruthR/CCTV_YOLO
GitHub
GitHub - SanshruthR/CCTV_YOLO: Fast Real-time Object Detection with High-Res Output https://x.com/_akhaliq/status/1840213012818329826…
Fast Real-time Object Detection with High-Res Output https://x.com/_akhaliq/status/1840213012818329826 https://x.com/githubprojects/status/1891370506537910724 https://www.threads.net/@githubproject...
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