🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.

Next-generation Punkt sentence boundary detection with zero dependencies

Fast and Accurate ML in 3 Lines of Code

AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation

The official Python SDK for Model Context Protocol servers and clients

Jobs scraper library for LinkedIn, Indeed, Glassdoor, Google, ZipRecruiter & more

📦 Repomix is a powerful tool that packs your entire repository into a single, AI-friendly file. Perfect for when you need to feed your codebase to Large Language Models (LLMs) or other AI tools lik…

Collection of awesome LLM apps with AI Agents and RAG using OpenAI, Anthropic, Gemini and opensource models.

An invisible desktop application to help you pass your technical interviews.

Python SDK, Proxy Server (AI Gateway) to call 100+ LLM APIs in OpenAI (or native) format, with cost tracking, guardrails, loadbalancing and logging. [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthr…

An extremely fast Python package and project manager, written in Rust.

Streamlit — A faster way to build and share data apps.

VSCode Extension that shows token count of the selected text

Build resilient language agents as graphs.

Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

The official Python library for the OpenAI API

The most comprehensive Python package for evaluating survival analysis models.

A couple survival evaluation metrics.

Flexible and modular implementation of multi-task logistic regression in PyTorch.

An implementation of the MTLR algorithm for survival prediction using TensorFlow with Keras.

🎤 quick library to extract pause lengths from audio files.

A list of papers/resources in Survival Analysis that I have read or would like to read.

Machine Learning and Artificial Intelligence for Medicine.

The best way to write secure and reliable applications. Write nothing; deploy nowhere.

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

This repository contains my implementations of the algorithms which MoNuSAC participants could use for data preparation to train their models at ISBI 2020.

SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners

Python bindings to OpenSlide