llms
48 repositories with 10k+ stars are tagged llms.
Open in the explorer to search, filter and sort all of them.
- 1

Get up and running with Kimi, GLM, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.
- 2

- 3

100+ AI Agents, Agent Skills and RAG Apps - Free and Open Source.
- 4

21 Lessons, Get Started Building with Generative AI
- 5

A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎,预测万物
- 6

🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
- 7

Local UI to run and train LLMs and diffusion models. Supports GGUF, MLX, Qwen3.8, DeepSeek-V4, MiniMax-H3, Gemma 4, FLUX and more.
- 8

Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
- 9

Learn how to develop, deploy and iterate on production-grade ML applications.
- 10

Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat apps
- 11

微舆:人人可用的多Agent舆情分析助手,打破信息茧房,还原舆情原貌,预测未来走向,辅助决策!从0实现,不依赖任何框架。
- 12

- 13

In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
- 14

A modular graph-based Retrieval-Augmented Generation (RAG) system
- 15

Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.
- 16

- 17

- 18

An autonomous agent that conducts deep research on any data using any LLM providers
- 19

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
- 20

A one stop repository for generative AI research updates, interview resources, notebooks and much more!
- 21

Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
- 22

- 23

- 24

What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?
- 25

An open-source RAG-based tool for chatting with your documents.
- 26

50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
- 27

✅(已完结)超级全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】【大飞 大模型Agent】
- 28

Local, open-source AI app builder for power users ✨ v0 / Lovable / Replit / Bolt alternative 🌟 Star if you like it!
- 29

An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
- 30

End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
- 31

- 32

- 33

- 34

20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
- 35

LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing tool calling (including MCP support), agents and RAG easy. It integrates seamlessly with enterprise Java frameworks like Quarkus and Spring Boot.
- 36

A blazing fast AI Gateway with integrated guardrails. Route to 1,600+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.
- 37

📋 A list of open LLMs available for commercial use.
- 38

Pocket Flow: Codebase to Tutorial
- 39

- 40

YuE2: frontier music generation with symbolic planning, zero-shot covers, and agentic music editing.
- 41

The official GitHub page for the survey paper "A Survey of Large Language Models".
- 42

- 43
tensorzero/tensorzeroArchivedTensorZero is an open-source LLMOps platform that unifies an LLM gateway, observability, evaluation, optimization, and experimentation.
- 44

The best way to get AI coding agents to solve hard problems in complex codebases.
- 45

- 46

A curated list of 120+ LLM libraries category wise.
- 47

Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen3.6, GPT-OSS, Llama, and more!
- 48

The fullstack MCP framework to develop MCP Apps for ChatGPT / Claude & MCP Servers for AI Agents.