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Awesome List
A curated list of awesome Machine Learning frameworks, libraries and software.
GitHub stars and default-branch commits for josephmisiti/awesome-machine-learning.
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🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
Test your prompts, agents, and RAGs. Red teaming/pentesting/vulnerability scanning for AI. Compare performance of GPT, Claude, Gemini, DeepSeek, and more. Simple declarative configs with command line and CI/CD integration. Used by OpenAI and Anthropic.
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
🧠 Make your agents learn from experience. Now available as a hosted solution at kayba.ai
Build, run and scale AI agents like API and microservices - observable,auditable and identity-aware from day one.
A security scanner for your LLM agentic workflows