AI DevOps

LiteLLM — a leading open-source project in the AI/LLM ecosystem.

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

Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

Composio powers 1000+ toolkits, tool search, context management, authentication, and a sandboxed workbench to help you build AI agents that turn intent into action.

Label Studio is a multi-type data labeling and annotation tool with standardized output format

☁️ 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.

Machine Learning Engineering Open Book

<⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.

The absolute trainer to light up AI agents.

Workflow Engine for Kubernetes

Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view

An orchestration platform for the development, production, and observation of data assets.

Free MLOps course from DataTalks.Club

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

Supercharge Your LLM Application Evaluations 🚀

A curated list of references for MLOps

A blazing fast AI Gateway with integrated guardrails. Route to 200+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.

Always know what to expect from your data.

TensorZero is an open-source stack for industrial-grade LLM applications. It unifies an LLM gateway, observability, optimization, evaluation, and experimentation.

BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more.

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

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.