Popular GitHub Repositories for Vllm Production Stack

Dify is an open-source LLM app development platform. Dify's intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.

?? - a deep learning toolkit for Text-to-Speech, battle-tested in research and production

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

? Assemble, configure, and deploy autonomous AI Agents in your browser.

? Papers & tech blogs by companies sharing their work on data science & machine learning in production.

AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

?? Build multimodal AI applications with cloud-native stack

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

Turns Data and AI algorithms into production-ready web applications in no time.

Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services

Multi-lingual large voice generation model, providing inference, training and deployment full-stack ability.

Open deep learning compiler stack for cpu, gpu and specialized accelerators

Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.

Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.

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?

Build high-quality LLM apps - from prototyping, testing to production deployment and monitoring.

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"

TensorZero creates a feedback loop for optimizing LLM applications — turning production data into smarter, faster, and cheaper models.

This repository delivers end-to-end, code-first tutorials covering every layer of production-grade GenAI agents, guiding you from spark to scale with proven patterns and reusable blueprints for real-world launches.