llm-engineering 开源项目推荐（129 个）

algorithmicsuperintelligence /openevolve

AlphaEvolve 的开源实现

shyamsaktawat /OpenAlpha_Evolve

OpenAlpha_Evolve是一个开源Python框架，其灵感来自DeepMind的AlphaEvolve等自主编码代理的突破性研究。

amitshekhariitbhu /llm-inference-engineering

Learn LLM Inference Engineering step by step - from KV cache, PagedAttention, and continuous batching to vLLM, SGLang, and GPUs.

mchittineni /ultimate-ai-engineering-guide

200+ AI, Gen AI, LLM, agentic AI, Forward Deployed Engineer (FDE), AI systems architect, applied AI, LLMOps and AI platform engineering interview questions across 10 topics. Each has a short answer, in-depth detail, a worked example and interview tips.

itsmostafa /llm-engineering-skills

LLM Engineering Claude Skills

Burakkylmz /llm-token-economics-lab

An experiment-driven LLM engineering lab with 9 reproducible Python experiments exploring token economics, API costs, caching, context growth, latency, model routing, rate limits, concurrency, and batching using Groq.

lucianoon /llm-course

Open course on LLM engineering and customization, in Portuguese, from scratch to production, with reproducible labs.

burgonet-eu /gateway

Burgonet Gateway is an enterprise LLM gateway that provides secure access and compliance controls for AI systems

linny006 /prompt-tools-live

Live-updating tracker of prompt engineering tools, libraries, and techniques — refreshed every 15 mi

mlane /llm-engineering-cheatsheet

Timeless principles and best practices for working with language models - tooling-agnostic, future-proof, and clear.

sanad-source /cave-agents

Build software with AI agent teams that use fewer tokens than a single agent.

Md-Emon-Hasan /Complete-Agentic-AI-Bootcamp-With-LangGraph-and-Langchain

Complete hands-on Agentic AI bootcamp repository covering LangGraph, LangChain, AI Agents, multi-agent workflows, RAG pipelines, tool-augmented LLM systems, memory architectures, and production-grade AI application engineering for real-world intelligent systems.

zangshulens-star /aed-quantamental-harness-kit

该项目在 GitHub 上没有填写描述

edaaydinea /llm_engineering

This course provides a comprehensive guide to mastering AI, focusing on Large Language Models (LLMs) and agents. It covers essential concepts, practical coding exercises, and comparisons of leading LLMs to equip participants with the skills needed to build and deploy LLM-based solutions.

AdilShamim8 /Build-with-Claude-Code

Everything you need to learn Claude Code: deep notes, real assignments, working solutions. From agentic loops to parallel multi-agent systems.

huidev2025 /CSF

一个人机协作框架，顺应而非绕开 LLM 的本质——自然语言和目的使 RAG 与 agent 编排变得不再必要。Pang Principle 的所在地。

edofransisco011 /Digital_Twin_Agent

A proactive AI assistant using Qwen-Agent to learn your writing style and manage Google Calendar & Gmail.

Hamna-Munir /03-AI-PDF-Assistant

AI PDF Assistant that extracts, chunks, and answers questions grounded strictly in an uploaded document — with built-in hallucination control. Week 3 of a 90-day AI Engineering roadmap.

Sparkience-AI /DSSential-The-AI-Chief

DSSential is an advanced decision support system that leverages AI, time series forecasting, and scenario analysis to empower businesses with data-driven insights and optimization. Make smarter decisions with cutting-edge tools for forecasting, sensitivity analysis, and goal setting.

weicyang /llm-eng-cards

A decision-oriented LLM engineering knowledge base — from Attention to production. 291 cards, 36-card path: fundamentals, RAG, Agents, and shipping.