FunClip

Open-source, accurate and easy-to-use video speech recognition & clipping tool, LLM based AI clipping intergrated.

https://github.com/alibaba-damo-academy/FunClip

llama3.np

A pure NumPy implementation for Llama 3 model.

https://github.com/likejazz/llama3.np

LLM Models and RAG Hands-on Guide

This guide is designed for technical teams interested in developing basic conversational AI solutions using Retrieval-Augmented Generation (RAG).

https://github.com/zahaby/intro-llm-rag

Replacing pyinstaller with 100 lines of code

A tale of how I accidentally stumbled upon some interesting tech over time.

https://tushar.lol/post/packaged/

llama3-from-scratch

llama3 implementation one matrix multiplication at a time.

https://github.com/naklecha/llama3-from-scratch

Llama 3 implemented in pure NumPy

Understand the exact structure with working implementation of the Llama 3 model.

https://docs.likejazz.com/llama3.np/

College Precalculus – Full Course with Python Code

Learn college Precalculus from an experienced university mathematics professor. You will also learn how to implement all the Precalculus concepts using the Python programming language.

https://www.youtube.com/watch?v=Y8oZtFYweTY

A Beginner's Guide to Unit Testing with Pytest

In this guide, we will explore the core principles of unit testing, delve into Pytest's powerful capabilities, and equip you with the knowledge and skills to write clean, maintainable, and effective tests.

https://betterstack.com/community/guides/testing/pytest-guide/

Kafka Consumers in Python - A Walkthrough

Getting data out of Apache Kafka is easy if you know how, so let's go through an example step-by-step. In this walkthrough we take you through the process of creating a simple Kafka Consumer using the Quix Streams library.

https://www.youtube.com/watch?v=eCsSAzTy5cE

Simple Pretty Maps That Will Better Your Python Streamlit Skills

A simple tutorial on creating beautiful maps using the prettymapp library.

https://johnloewen.substack.com/p/simple-pretty-maps-that-will-better

AgentOps

Open source Python SDK for agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks like CrewAI, Langchain, and Autogen.

https://github.com/AgentOps-AI/agentops

cover-agent

An AI-Powered Tool for Automated Test Generation and Code Coverage Enhancement!

https://github.com/Codium-ai/cover-agent

Curating Custom Datasets for LLM Training with NVIDIA NeMo Curator

NeMo Curator, which is part of NVIDIA NeMo, offers workflows to download and curate data from various public sources out of the box such as Common Crawl, Wikipedia, and arXiv. It also provides flexibility for developers to customize data curation pipelines to address their unique requirements and create custom datasets. This post walks you through creating a custom data curation pipeline...

https://developer.nvidia.com/blog/curating-custom-datasets-for-llm-training-with-nvidia-nemo-curator/

Signals, shells, and docker: an onion of footguns

The post discusses potential security risks and "footguns" that can arise when using Docker containers, signals, and shells together in a development environment. It highlights how certain combinations of these tools can inadvertently grant excessive permissions or expose sensitive data, emphasizing the need for caution and proper configuration.

https://benchling.engineering/signals-shells-and-docker-an-onion-of-footguns-ee592e2b587b

How Python Compares Floats and Ints: When Equals Isn’t Really Equal

Another Python gotcha and an investigation into its internals to understand why this happens.

https://blog.codingconfessions.com/p/how-python-compares-floats-and-ints

Gloe

Gloe is a general-purpose library made to help developers create, maintain, document, and test both operational and flow-oriented code.

https://github.com/ideos/gloe

How good is GPT-4o at generating Flask apps? Surprisingly promising

This article summarizes the findings when asking GPT-4o to generate Flask applications, ranging from a simple "Hello, World!" app to a full-fledged CRUD app with three database models and HTML pages with Tailwind. With careful prompting, GPT-4o can produce working Flask applications and follow (some) best coding practices.

https://ploomber.io/blog/gpt-4o-flask/