12 Factor Agents
humanlayer
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?
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17–32 / 75
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Results: 75
humanlayer
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?
yichuan-w
[MLsys2026]: RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.
ConardLi
A powerful tool for creating datasets for LLM fine-tuning 、RAG and Eval
dataease
🔥 基于大模型和 RAG 的智能问数系统,对话式数据分析神器。Text-to-SQL Generation via LLMs using RAG.
alvinreal
Curated list of the best truly open-source AI projects, models, tools, and infrastructure.
Marker-Inc-Korea
AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation
NVIDIA
Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
Meirtz
🔥 Comprehensive survey on Context Engineering: from prompt engineering to production-grade AI systems. hundreds of papers, frameworks, and implementation guides for LLM…
modelscope
A streamlined and customizable framework for efficient large model (LLM, VLM, AIGC) evaluation and performance benchmarking.
spiceai
A portable accelerated SQL query, search, and LLM-inference engine, written in Rust, for data-grounded AI apps and agents.