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KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain knowledge bases. It can effectively overcome the shortcomings of the traditional RAG vector similarity calculation model.

PraisonAI 🦞 — Hire a 24/7 AI Workforce. Stop writing boilerplate and start shipping autonomous self-improving agents that research, plan, code, and execute tasks. Deployed in 5 lines of code with built-in memory, RAG, and support for 100+ LLMs.

Complete Open Source and Modular solution for MMO

Pupy is an opensource, cross-platform (Windows, Linux, OSX, Android) C2 and post-exploitation framework written in python and C

A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch

Speech recognition module for Python, supporting several engines and APIs, online and offline.

An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs

🐍🎮 pygame (the library) is a Free and Open Source python programming language library for making multimedia applications like games built on top of the excellent SDL library. C, Python, Native, OpenGL.

Open Source HR and Payroll Software

Reads key-value pairs from a .env file and can set them as environment variables. It helps in developing applications following the 12-factor principles.

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Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

Build an agent harness and control it end-to-end. Open-source SDK for production AI agents in Python & TypeScript - any model, any cloud.

Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, DeepSeek, Mixtral, Gemma, Phi, MiniCPM, Qwen-VL, MiniCPM-V, etc.) on Intel XPU (e.g., local PC with iGPU and NPU, discrete GPU such as Arc, Flex and Max); seamlessly integrate with llama.cpp, Ollama, HuggingFace, LangChain, LlamaIndex, vLLM, DeepSpeed, Axolotl, etc.

The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!

🧙 Build, run, and manage data pipelines for integrating and transforming data.

A free & open modern, fast email client with user-friendly encryption and privacy features

vits2 backbone with multilingual-bert

Kata Containers is an open source project and community working to build a standard implementation of lightweight Virtual Machines (VMs) that feel and perform like containers, but provide the workload isolation and security advantages of VMs. https://katacontainers.io/

yewtube, forked from mps-youtube , is a Terminal based YouTube player and downloader. No Youtube API key required.

[NeurIPS 2024] Depth Anything V2. A More Capable Foundation Model for Monocular Depth Estimation

bottle.py is a fast and simple micro-framework for python web-applications.

Fancy stream processing made operationally mundane

A template for PostgreSQL High Availability with Etcd, Consul, ZooKeeper, or Kubernetes

A Super Mario 64 decompilation, brought to you by a bunch of clever folks.

FreeAskInternet is a completely free, PRIVATE and LOCALLY running search aggregator & answer generate using MULTI LLMs, without GPU needed. The user can ask a question and the system will make a multi engine search and combine the search result to LLM and generate the answer based on search results. It's all FREE to use.

[NeurIPS 2024 Best Paper Award][GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction". An *ultra-simple, user-friendly yet state-of-the-art* codebase for autoregressive image generation!

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

A Python implementation of global optimization with gaussian processes.

👀 Train a 65M-parameter VLM from scratch in just 2h!