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Alternatives to Ray AI Framework

P
Petals AIPetals is an open-source framework for distributed LLM inference. Run Llama 3.1 (405B), Mixtral, Falcon, and BLOOM collaboratively across a peer-to-peer GPU network using a consumer GPU or Google Colab.
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OmniParser
OmniParserOmniParser by Microsoft is an open-source tool that parses UI screenshots into structured elements, enabling accurate vision-based GUI automation agents powered by GPT-4V and other VLMs.
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MLflow
MLflowMLflow is the largest open source AI engineering platform. Debug, evaluate, monitor, and deploy AI agents, LLMs, and ML models with 30M+ monthly downloads.
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Milvus AI Vector DB
Milvus AI Vector DBMilvus is an open-source vector database built for GenAI applications. Perform high-speed similarity searches and scale to tens of billions of vectors with minimal performance loss.
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R
Ray ServeRay Serve is an open-source, scalable model serving framework built on Ray for deploying ML models, LLMs, and multi-model pipelines in production.
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Argilla Data Platform
Argilla Data PlatformArgilla is an open-source platform where AI engineers and domain experts collaborate to build high-quality datasets for LLM fine-tuning, RLHF, and NLP model evaluation.
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Qdrant
QdrantQdrant is a high-performance, open-source vector search engine and database written in Rust. Build production-ready RAG pipelines, recommendation systems, and semantic search at scale.
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Quivr
QuivrQuivr is an opinionated open-source RAG framework supporting any LLM (GPT-4, Groq, Llama) and vectorstore (PGVector, Faiss). Build AI-powered apps faster without reinventing retrieval pipelines.
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AI2 (Allen Institute for AI)
AI2 (Allen Institute for AI)Ai2 is a nonprofit AI research institute offering fully open LLMs, multimodal models, and AI platforms for science, environment, and robotics. Explore OLMo, Molmo, Semantic Scholar, and more.
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StarCoder AI
StarCoder AIStarCoder AI provides open-source large language models for code generation, trained on 600+ programming languages and trillions of tokens from The Stack v2.
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