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Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.

Neural network inference from the command line, implemented in CHICKEN Scheme.

A lightweight, portable pure C99 onnx inference engine for embedded devices with hardware acceleration support.

Algorithms for learning and inference with discrete probabilistic models.

LifeArchitect supports machine learning models, deployment, inspection, datasets, or AI development workflows.

A model gateway and unified interface for multiple model providers.

A hub of integrations for LlamaIndex including data loaders, tools, vector databases, LLMs and more.

LLM App is a Python library that helps you build real-time AI-powered data pipelines with few lines of code.

Open-source project that provides machine-learning models, research, training resources, or evaluation tools.

LLMSTXT.NEW provides machine-learning models, research, training resources, or evaluation tools.

Open-source project that provides machine-learning models, research, training resources, or evaluation tools.

Observability and prompt management platform for LLM-based apps. Take your LLMs to the next level.

Ship AI agents that reason, remember, and act in TypeScript. Mastra provides memory, tools, MCP, and observability to go from prototype to production.

Helps teams build, deploy, observe or operate machine-learning systems.

A platform for deploying and serving machine learning models.

Metorial supports deploying, serving, monitoring, or operating AI and machine-learning systems.

Milvus is open source vector database for production AI, written in Go and C++, scalable and blazing fast for billions of embedding vectors.

MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.

Intuitive convenience tooling for lightning-fast, efficient development and ensuring quality in LLM-based applications.

ML Resources supports machine learning models, deployment, inspection, datasets, or AI development workflows.

ML Visualized supports machine learning models, deployment, inspection, datasets, or AI development workflows.

Version and deploy your ML models following GitOps principles.

An open-source platform for tracking ML experiments, evaluating models and prompts, deploying models, and adding LLM observability. opensource.

MLOps Community supports deploying, serving, monitoring, or operating AI and machine-learning systems.