Explore AI, agents, blockchain and crypto through official sources, concrete tasks and practical guides.
Browse by purpose and evidence; use an exact name, ticker or addressable project domain to narrow the search.
Awesome LLM Eval is a curated GitHub repository that indexes tools, datasets and benchmarks, demonstrations, leaderboards, papers, documentation and models related to large language model evaluation and generative AI capabilities.
Guide: Find LLM evaluation resources by topicAwesome LLM Strawberry is a GitHub collection of research papers, blog posts, projects and other resources about large language model reasoning, with a particular focus on OpenAI o1.
Guide: Browse the LLM reasoning research collectionAwesome Muse Connectors is a community-maintained repository cataloging Meta Muse integrations and connector skills, including capability, authentication, host, operating-rule and maturity notes.
Guide: Browse and assess Meta Muse connector skillsAwesome RAG is an open-source directory of papers, learning resources and tools about retrieval-augmented generation in large language models.
Guide: Browse RAG research papers and surveysAwesome Rag Production is a curated repository of tools, frameworks, architectures, case studies and engineering practices for building, scaling and monitoring retrieval-augmented generation systems.
Guide: Use the decision guide to shortlist production RAG componentsAwesome Rag Reasoning is a curated GitHub repository of papers, tools, implementations and benchmarking datasets about combining retrieval-augmented generation with reasoning in large language models and agents.
Guide: Use the collection to build a RAG-reasoning research reading listAwesome Swarm is a public repository that organizes free and open-source projects related to Swarm, a peer-to-peer storage and communication system.
Guide: Browse the Swarm ecosystem resource listAwesome Vlm Architectures is a visual, citation-linked catalog of vision-language and multimodal model architectures.
Guide: Compare vision-language model architectures using the catalogAwex is an open-source Python framework that synchronizes model weights from reinforcement-learning training processes to inference workers.
Guide: Prepare Awex for a Mooncake weight-transfer jobAwful Jade (`aj`) is a Rust command-line client for working with large language models through OpenAI-compatible APIs.
Guide: Install and initialize Awful JadeAworld is an MIT-licensed Python agent harness and runtime for building, running and evolving autonomous agents in user-defined environments.
Guide: Set up the Aworld CLI environmentAWS Blockchain Node Runners is a TypeScript AWS CDK application for deploying blockchain nodes on AWS and experimenting with node infrastructure configurations.
Guide: Prepare the project in AWS CloudShellAWS Crypto Miner is a CloudFormation template that launches GPU-enabled AWS EC2 instances configured to mine Ravencoin, Ergo, Kaspa or Ethereum Classic, with payouts supported in Bitcoin.
Guide: Prepare and launch an AWS mining stackA Python sample application that uses generative AI to analyze AWS architecture documents and prepare Well-Architected Framework reviews, with an option to create a workload in the AWS Well-Architected Tool.
Guide: Deploy the sample and open its Streamlit interfaceAwsome Distributed AI is a public repository of reference architectures, best practices and examples for distributed AI training and inference on Amazon SageMaker HyperPod, AWS ParallelCluster, AWS Parallel Computing Service and Amazon EKS.
Guide: Choose and browse a distributed AI exampleAx Samples is an open-source repository of deep-learning and traditional computer-vision example implementations for AXERA AI SoCs.
Guide: Build AX-Samples using the CMake compilation guideAxar is a lightweight, Apache-2.0-licensed TypeScript framework for developing LLM-powered agentic applications on Node.js and server environments.
Guide: Set up a first Axar TypeScript agentAxbook is a decentralized finance project for USDG-funded copy desks on Robinhood Chain.
Guide: Check the testnet desk before depositing