Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
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Agentic components of the Llama Stack APIs.
LLMFlows is a framework for building simple, explicit, and transparent LLM applications such as chatbots, question-answering systems, and agents.
JARVIS, a system to connect LLMs with ML community.
500+ ML/AI interview Q&A with runnable code — covers ML fundamentals, deep learning, NLP, PyTorch, scikit-learn pipelines, and system design.
Ultra-lightweight personal AI assistant framework (~4,000 lines of Python). Supports MCP, 9+ chat channels, and extensible skills system.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
An open-source framework by NVIDIA for building speech AI systems, including automatic speech recognition and text-to-speech. opensource.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Pachyderm is a version control system for data.
Pixray is an image generation system.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
A Python library for implementing a Recommender System.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Extensible system for analyzing and manipulating natural language.
Easily compute CLIP embeddings and build a CLIP retrieval system with them.
Enterprise-grade Voice AI simulation SDK for scenario-driven stress testing of multimodal and agentic systems.
A Twitch web client that works on Android TVs and web base systems
A system for quickly generating training data with weak supervision.
Tooling for giving AI systems richer capabilities and more flexible action patterns in practical workflows.
Flexible, high-performance serving system for machine learning models.