Reverse Dependencies of ray

The following projects have a declared dependency on ray:

• farm-haystack — LLM framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data.
• fastckpt — A fast gradient checkpointing strategy for training with memory-efficient attention (e.g., FlashAttention).
• fastphase — Python implementation of the fastPHASE model
• fastprop — Fast Molecular Property Prediction with mordredcommunity
• fcmaesray — A multi-node Python 3 gradient-free optimization library.
• fedgraph — Federated Graph Learning
• fedlib — A Scalable Federated Learning Library
• felipe-teste — A teste package
• fftvis — An FFT-based visibility simulator
• figaro — FIGARO: Fast Inference for GW Astronomy, Research & Observations
• finae — A simple Python library
• finrl-meta — FinRL­-Meta: A Universe of ­ Market En­vironments for Data­-Driven Financial Reinforcement Learning
• fintorch — AI4FinTech project repository
• fitsmap — Turn fits files/catalogs into a leafletjs map
• flambe — Pytorch based library for robust prototyping, standardized benchmarking, and effortless experiment management
• flamingo-ray — Ray-centric job library for training and evaluation.
• FLAML — A fast library for automated machine learning and tuning
• flowdapt — A generalized framework for robust modular deployments of large-scale, real-time adaptive modeling on chaotic data.
• FlowerPower — A simple workflow framework. Hamilton + APScheduler = FlowerPower
• fluidexec — Resource-aware hyperparameter tuning execution engine
• flwr — Flower: A Friendly Federated AI Framework
• flwr-nightly — Flower: A Friendly Federated AI Framework
• flytekitplugins-ray — This package holds the Ray plugins for flytekit
• fmbench — Benchmark performance of **any Foundation Model (FM)** deployed on **any AWS Generative AI service**, be it **Amazon SageMaker**, **Amazon Bedrock**, **Amazon EKS**, or **Amazon EC2**. The FMs could be deployed on these platforms either directly through `FMbench`, or, if they are already deployed then also they could be benchmarked through the **Bring your own endpoint** mode supported by `FMBench`.
• fmcore — A specialized toolkit for scaling experimental research with Foundation Models.
• fmeval — Amazon Foundation Model Evaluations
• fold-core — A Time Series Cross-Validation library that lets you build, deploy and update composite models easily. An order of magnitude speed-up, combined with flexibility and rigour.
• foxes — Farm Optimization and eXtended yield Evaluation Software
• fragile — Framework for developing FractalAI based algorithms.
• fschat — An open platform for training, serving, and evaluating large language model based chatbots.
• fugue — An abstraction layer for distributed computation
• furiosa-llm — Furiosa LLM
• fuzzylearn — no summary
• gatenlp — GATE NLP implementation in Python.
• geneva — Geneva - Multimodal Data Lake for AI
• geniz — A simple Python library
• genni — GENNI: Visualising the Geometry of Equivalences for Neural Network Identifiability
• genv — GPU environment and cluster management
• geochemistrypi — A highly automated machine learning Python framework dedicating to build up MLOps level 1 software product for data-driven geochemistry discovery
• getdaft — A Distributed DataFrame library for large scale complex data processing.
• ggfm — no summary
• gins — A simple Python library
• gobbli — Uniform interface to deep learning approaches via Docker containers.
• godot-rl — A Deep Reinforcement Learning package for the Godot game engine
• goldenretriever-core — Dense Retriever
• google-cloud-aiplatform — Vertex AI API client library
• google-vizier — Open Source Vizier: Distributed service framework for blackbox optimization and research.
• google-vizier-dev — Open Source Vizier: Distributed service framework for blackbox optimization and research.
• gplugins — gdsfactory plugins
• gradsflow — An open-source AutoML Library based on PyTorch
• graphbook — The AI-driven data pipeline and workflow framework for data scientists and machine learning engineers.
• graphenv — Reinforcement learning on directed graphs
• graphiq — GraphiQ is a Python library for the simulation, design, and optimization of quantum photonic circuits.
• greenflow-gquant-plugin — no summary
• GreenLightPlus — Greenhouse Simulation and Optimization Toolkit
• greylock — A Python package for measuring the composition of complex datasets
• GWXtreme — Tools for inferences on extreme matter using gravitational wave parameter estimation data.
• gym-jiminy-rllib — Specialized Reinforcement learning toolbox based on Ray RLlib for Gym Jiminy.
• gym-recorder — A simple and ubiquitous transition recorder wrapper for Gym Environments to facilitate offline reinforcement learning dataset manufacturing.
• hepynet — High energy physics, python based, neural network framework
• hermespy — The Heterogeneous Radio Mobile Simulator
• HeuristAI — Evolve heuristics using LLM-driven Genetic Programming.
• hiclass — Hierarchical Classification Library.
• hipscat-import — no summary
• honcaml — Holistic and No Code Auto Machine Learning
• hy-tools — HyTools: Hyperspectral image processing library
• hydra-ray-jobs-launcher — Hydra Ray Jobs Launcher plugin
• hydra-ray-launcher — Hydra Ray launcher plugin
• hydroecolstm — A python package for HydroEcological Modelling using LSTM
• hyfi — Hydra Fast Interface (Hydra and Pydantic based interface framework)
• hyperparameters — Define your Hyperparameters once and use in argparse, hypertunning libraries, and as strongly-typed attributes in code!
• ibquant — A Python Framework for Interactive Brokers TWS API
• ilpyt — The imitation learning toolbox (ilpyt) is an open-source Python code library developed at MITRE. The toolbox contains modular, optimized implementations of common deep imitation learning algorithms in PyTorch, with unified infrastructure supporting key imitation learning and reinforcement learning algorithms.
• imitation — Implementation of modern reward and imitation learning algorithms.
• infractl — API driven Machine Learning suite
• innocuous-magic — innocuous library
• inspirai-fps — An intelligent agent learning platform based on a 3D open-world FPS game
• instill-sdk — python sdk for Instill AI products
• instruct-goose — Implementation of Reinforcement Learning from Human Feedback (RLHF)
• InsurAutoML — Automated Machine Learning/AutoML pipeline.
• intersection-control — An environment-agnostic framework for implementing and comparing intersection control algorithms
• investigraph — etl pipeline for investigations with follow the money data
• isofit — Imaging Spectrometer Optimal FITting
• isopod — A middle layer for creating modular data processing pipelines and automating their parallel execution over various multiprocessing backends.
• ist-pulse-data-extractor — Pulse Data Extractor
• itp-interface — Generic interface for hooking up to any Interactive Theorem Prover (ITP) and collecting data for training ML models for AI in formal theorem proving.
• itwinai — AI and ML workflows module for scientific digital twins.
• joyrl — A Library for Deep Reinforcement Learning
• just-distribute — Provides a @distribute decorator that enables concurrent execution of functions without boilerplate code.
• kazu — Biomedical Named Entity Recognition and Entity Linking for Enterprise use cases
• keyvec — For storing mapping from keys to vectors in your disk
• kfserving — KFServing Python SDK
• kgdata — Library to process dumps of knowledge graphs (Wikipedia, DBpedia, Wikidata)
• kithara — LLM post-training library
• kma-url-api — KMA URL-API
• kozmo-supervisor — Algorithms for monitoring and explaining machine learning models
• kserve — KServe Python SDK
• kserve-mathking — KServe Python SDK
• kts — A framework for fast and interactive conducting machine learning experiments on tabular data
• langchain-ray — LangChain leveraging Ray.