no-code-architects-toolkit

The NCA Toolkit API eliminates monthly subscription fees by consolidating common API functionalities into a single FREE API. Designed for businesses, creators, and developers, it streamlines advanced media processing, including video editing and captioning, image transformations, cloud storage, and Python code execution.

https://github.com/stephengpope/no-code-architects-toolkit

adk-python

An open-source, code-first Python toolkit by Google for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

https://github.com/google/adk-python

Build a Desktop Sticky Notes Application with PySide6 & SQLAlchemy

This post provides a step-by-step guide to creating a desktop sticky notes application using PySide6, covering GUI setup, styling, and adding functionality like movable notes and a system tray icon. It explains how to build a simple, frameless note window, enable dragging, and manage multiple notes, with code examples for each stage.

https://www.pythonguis.com/examples/pyside6-desktop-sticky-notes/

Reproducing word2vec with JAX

This article reproduces the word2vec model using JAX, explaining the CBOW architecture and its implementation. It trains word embeddings and demonstrates how to find word similarities and analogies using the trained model, comparing it to modern text embeddings used in LLMs.

https://eli.thegreenplace.net/2025/reproducing-word2vec-with-jax/

nano-aha-moment

Single File, Single GPU, From Scratch, Efficient, Full Parameter Tuning library for "RL for LLMs"

https://github.com/McGill-NLP/nano-aha-moment

arxiv-mcp-server

A Model Context Protocol server for searching and analyzing arXiv papers.

https://github.com/blazickjp/arxiv-mcp-server

memo

Memo is a simple command-line interface (CLI) tool for managing your Apple Notes (and eventually Apple Reminders). It’s written in Python and aims to offer a fast, keyboard-driven way to create, search, and organize notes and reminders straight from your terminal.

https://github.com/antoniorodr/memo

curl-impersonate

A special build of curl that can impersonate Chrome & Firefox.

https://github.com/lwthiker/curl-impersonate

Code DeepSeek V3 From Scratch in Python

This video provides a comprehensive, step-by-step coding guide to understanding and implementing DeepSeek V3, a cutting-edge deep learning model. It covers key concepts like the attention mechanism, multihead latent attention (MLA), rotary positional embeddings (RoPE), and the mixture of experts (MoE) architecture, explaining the science behind it all.

https://www.youtube.com/watch?v=5avSMc79V-w

llm-compressor

Transformers-compatible library for applying various compression algorithms to LLMs for optimized deployment with vLLM.

https://github.com/vllm-project/llm-compressor

VeOmni

Scaling any Modality Model Training to any Accelerators with PyTorch native Training Framework.

https://github.com/ByteDance-Seed/VeOmni

OpenAlgo

Open Source Algo Trading Platform for Everyone.

https://github.com/marketcalls/openalgo

User Onboarding Tips and Tricks for Django Developers

This video explains how to implement anonymous onboarding in Django apps, allowing users to try the app without creating an account. It covers storing temporary data in the session and seamlessly transferring it to a user account once created, enhancing the initial user experience.

https://www.youtube.com/watch?v=gFnE6a9-kLw

MedReason

Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs.

https://github.com/UCSC-VLAA/MedReason

meta-llama / llama-models

Utilities intended for use with Llama models.

https://github.com/meta-llama/llama-models

Python 3.14 | Upcoming Changes

This video discusses the upcoming features, performance improvements, and other changes in Python 3.14, including the tail call interpreter, JIT compiler, and free threading. It also covers minor updates and deprecations, providing a comprehensive overview of the new release.

https://www.youtube.com/watch?v=hzys1_xmLPc

How to Extract GPS Coordinates from a Photo: The USAID Mystery

This post explains how to extract GPS coordinates from a photo using Python and plot them on a map, using libraries like Pillow, ExifRead, and Folium. It challenges the reader to analyze the location of a USAID nutrition pack to determine if the aid is being distributed appropriately.

https://www.marsja.se/how-to-extract-gps-coordinates-from-a-photo-the-usaid-mystery/

open-rag-eval

Evaluate and improve your Retrieval-Augmented Generation (RAG) pipelines with open-rag-eval, an open-source Python evaluation toolkit.

https://github.com/vectara/open-rag-eval