llms

A library for prompt engineering and optimization (SAMMO = Structure-aware Multi-Objective Metaprompt Optimization)

Generative AI Examples is a collection of GenAI examples such as ChatQnA, Copilot, which illustrate the pipeline capabilities of the Open Platform for Enterprise AI (OPEA) project.

Aligning Large Language Models with Human: A Survey

Extend existing LLMs way beyond the original training length with constant memory usage, without retraining

Your Company Agentic Operating System

Machine learning Guide. Learn all about Machine Learning Tools, Libraries, Frameworks, Large Language Models (LLMs), and Training Models.

LLMFlows - Simple, Explicit and Transparent LLM Apps

A NestJS module to effortlessly create Model Context Protocol (MCP) servers for exposing AI tools, resources, and prompts.

Give your AI agents persistent, collective memory — with deduplicating absorb, supersession lineage, semantic search, and a graph UI. Speaks MCP.

Build LLM-powered Dart/Flutter applications.

one sentence generates any graph

Editable, part-aware 3D generation from text or reference images. Open-source client for nova3d.xyz.

GPU environment and cluster management with LLM support

Active Learning for Text Classification in Python

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(Accepted by IJCV) Liquid: Language Models are Scalable and Unified Multi-modal Generators

In Generative AI with Large Language Models (LLMs), you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.

An application for running LLMs locally on your device, with your documents, facilitating detailed citations in generated responses.

An AI-app that allows you to upload a PDF and ask questions about it. It uses OpenAI's LLMs to generate a response.

a magical LLM desktop client that makes it easy for *anyone* to use LLMs and MCP