AI & Machine Learning

Open-source framework for research and building systems of multiple communicating, role-playing AI agents that collaborate autonomously.

• AI & Machine Learning

Multi-agent orchestration framework for building teams of collaborating, role-based AI agents that work together autonomously to complete complex tasks.

• AI & Machine Learning

Open-source testing framework for evaluating LLM outputs, treating LLM application quality checks like conventional unit tests.

• AI & Machine Learning

Deep learning optimization library from Microsoft for training and running very large models efficiently across multiple GPUs.

• AI & Machine Learning

Document parsing library that converts PDFs, Word docs, and other formats into clean, structured data ready for LLM and RAG pipelines.

• AI & Machine Learning

Programming paradigm and library for controlling LLM generation with interleaved prompting, control flow, and constrained output in one program.

• AI & Machine Learning

Open-source framework for building production-ready search and RAG (retrieval-augmented generation) applications with LLMs.

• AI & Machine Learning

Library for getting reliable, structured data output from LLMs using function-calling APIs and Pydantic models for validation.

• AI & Machine Learning

Kubernetes-native platform for serving machine learning models at scale, standardizing model deployment across frameworks.

• AI & Machine Learning

Machine learning platform for Kubernetes that bundles pipelines, model training, hyperparameter tuning, and serving into one toolkit.

• AI & Machine Learning

Framework for developing applications powered by large language models, agents and retrieval-augmented generation.

• AI & Machine Learning

High-performance C/C++ implementation for running LLM inference locally on consumer hardware, including CPUs, with minimal dependencies.

• AI & Machine Learning

Data framework for connecting large language models to your own data - documents, databases, APIs - for retrieval-augmented applications.

• AI & Machine Learning

Open source vector database built for scalable similarity search and AI applications.

• AI & Machine Learning
• Database

Open-source platform for managing the machine learning lifecycle: experiment tracking, model packaging, versioning, and deployment.

• AI & Machine Learning

Toolkit for adding programmable safety and behavioral guardrails to LLM-powered conversational applications.

• AI & Machine Learning

Run large language models locally with a simple command-line interface and API.

• AI & Machine Learning

The standard open-source computer vision library, providing algorithms for image and video processing, analysis, and understanding.

• AI & Machine Learning

Library for constraining LLM output to a specific structure - JSON schema, regex, grammar - guaranteeing valid, parseable results.

• AI & Machine Learning

Open-source tool for testing and evaluating LLM prompts, comparing outputs across models and catching quality regressions before deployment.

• AI & Machine Learning

Type-safe agent framework from the team behind Pydantic, bringing familiar Python typing and validation patterns to LLM application development.

• AI & Machine Learning

Open source machine learning framework that accelerates the path from research prototyping to production deployment.

• AI & Machine Learning

Vector database and similarity search engine for building AI applications with embeddings.

• AI & Machine Learning
• Database

Microsoft's open-source SDK for integrating large language models into applications, with support for plugins, memory, and planning.

• AI & Machine Learning

Fast serving framework for large language models and vision-language models, with a structured generation language for complex LLM programs.

• AI & Machine Learning

End-to-end open source platform for machine learning, from research to production.

• AI & Machine Learning

Library for fine-tuning large language models significantly faster and with less memory than standard training approaches.

• AI & Machine Learning

High-throughput, memory-efficient inference and serving engine for large language models, built for running LLMs in production at scale rather than on a single local machine.

• AI & Machine Learning

Optimized, distributed gradient boosting library widely used for structured/tabular data problems, a staple of applied machine learning.

• AI & Machine Learning