《Designing Data-Intensive Application》DDIA 第一版 / 第二版 中文翻译
《深入理解 AI Infra:量化分析与系统设计》(李博杰 著)开源书稿:从硬件约束和模型架构出发,量化推导 LLM 推理与训练系统设计。含全书正文、PDF、配套计算工具与实验
Asynchronous Python framework for event-driven services. A thin client for Kafka, RabbitMQ, NATS, Redis and MQTT with full access to native broker features, plus AsyncAPI docs, in-memory tests and observability out of the box.
Symbolic Learning in Python and Julia
Python Stream Processing. A Faust fork
A library for event sourcing in Python.
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
Fault tolerance for PyTorch (HSDP, LocalSGD, DiLoCo, Streaming DiLoCo)
👋 Hello Agent System — learn enterprise AI agent system design by building every production layer from scratch. 17 bilingual lessons (EN/中文) with tested exercises: tools, architectures, reliability, security, evals, distributed execution, cost, RAG, release ops. 企业级 Agent 系统设计训练营
Bicameral deterministic AI runtime: Zero-hallucination System 1/2 reasoning engine with cryptographic audit trails (RFC 8785, Ed25519) and PoSP consensus arbitration.
Durable per-application work queue with named queues, fenced leases, and atomic follow-up tasks.