Through my travels I've discovered it's possible to write a fully functional Terminal User Interface in BASH. The object of this guide is to document and teach the concepts in a simple way.

As of February 10th, 2025, this repository is read-only. Please visit github.com/NVIDIA/Cosmos for the latest updates and support on Cosmos Tokenizer.

This is a proof of concept for an AI-powered hedge fund. The goal of this project is to explore the use of AI to make trading decisions.

Robust Go framework for building intelligent multi-agent AI systems The most productive way to build AI agents in Go. AgenticGoKit provides a unified, streaming-first API for creating intelligent agents with built-in workflow orchestration, tool integration, and memory management.

![badge][badge-android] ![badge][badge-ios] ![badge][badge-mac] ![badge][badge-watchos] ![badge][badge-tvos] ![badge][badge-jvm] ![badge][badge-js] ![badge][badge-windows] ![badge][badge-linux] This is a Kotlin Multiplatform library that provides architecture components of Model-View-ViewModel for UI applications. root build.gradle project build.gradle Also required export of dependency to iOS framework.

A collection of prompts for AI-assisted development with Claude Code. https://www.youtube.com/watch?v=KVOZ9s1S9Gk&lc=UgzfwxvFjo6pKEyPo1R4AaABAg Found value in these resources?

An open-source visual environment for battle-testing prompts to LLMs. ChainForge is a data flow prompt engineering environment for analyzing and evaluating LLM responses.

This repository is a collection of reference implementations for the Model Context Protocol (MCP), as well as references to community-built servers and additional resources. The servers in this repository showcase the versatility and extensibility of MCP, demonstrating how it can be used to give Large Language Models (LLMs) secure, controlled access to tools and data sources.

English| 简体中文 Official Website | Docs | Contribution Guide RuleGo is a lightweight, high-performance, embedded, orchestrable component-based rule engine built on the Go language. It can help you quickly build loosely coupled and flexible systems that can respond and adjust to changes in business requirements in real time.

• Documentation • PowerShell-Native AI Agents & Multi-Agent Orchestration PSAI is a high-agency framework designed to bridge the gap between robust systems engineering and Large Language Models. Built for developers and architects, it transforms AI from a "chatbot" into a functional engineering component within your existing PowerShell ecosystem.

    API Dash is a beautiful AI powered open-source cross-platform API Client that can help you easily create & customize your API requests, visually inspect responses (full list of supported mime-types) and generate API integration code (full list) on the go. Dashbot is the AI assistant available in API Dash (powered by local or cloud LLM) so that you can interact with your requests to debug it, generate code, generate doc, and many more.

pg-mem is an experimental in-memory emulation of a postgres database. ⭐ this repo if you like this package, it helps to motivate me :) 👉 See it in action with pg-mem playground As always, it starts with an: Then, assuming you're using something like webpack, if you're targeting a browser: Pretty straightforward :) ❤ Head to the pgsql-ast-parser repo The sql syntax parser is home-made.

The LLM ecosystem has amazing infrastructure (LoRAX, PEFT, vLLM), but lacks standardized, high-quality capability adapters. Problem: Base models limited to 32K context, need 2M tokens for large repositories Solution: Progressive curriculum learning with vLLM + Unsloth hybrid approach Key Innovation: Hybrid optimization combining vLLM's inference speed with Unsloth's training efficiency - achieving 61x context extension with minimal compute!

LLM Finetuning toolkit is a config-based CLI tool for launching a series of LLM fine-tuning experiments on your data and gathering their results. From one single yaml config file, control all elements of a typical experimentation pipeline - prompts, open-source LLMs, optimization strategy and LLM testing.

中文 Rainbond helps teams build, deploy, upgrade, operate, and privately deliver applications without deeply learning Kubernetes. It is better suited for private deployment, offline delivery, Xinchuang adaptation, application marketplace delivery, and AI application privatization scenarios.

![alt text][logo] ![alt text][overview] To start using POCO, see the Guided Tour and Getting Started documents. Most Unix/Linux systems already have OpenSSL preinstalled.

Training and inference code for audio generation models Requires PyTorch 2.5 or later for Flash Attention and Flex Attention support. Development for the repo is done in Python 3.10.

This is the official repository for ICLR 2025 paper "Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing". Magpie generates high-quality alignment data by prompting aligned LLMs with their pre-query templates.

Version, test, and monitor every prompt and agent with robust evals, tracing, and regression sets. --- This library provides convenient access to the PromptLayer API from applications written in python.

A quick reminder of all relevant SQL queries and examples on how to use them. This repository is constantly being updated and added to by the community.