Valkey

In-memory data store

In-memory data structure store used as database, cache, message broker, and streaming engine. Supports strings, hashes, lists, sets, sorted sets, streams, geospatial indexes, and HyperLogLog. Features pub/sub messaging, Lua scripting, transactions, persistence (RDB/AOF), replication, and Redis Cluster for horizontal scaling. Redis Stack adds JSON, search, time series, and graph capabilities. Sub-millisecond latency. Available as open-source or managed (Redis Cloud, AWS ElastiCache).

Enterprise RAG framework by Tencent

WeKnora is a Tencent-developed LLM-powered knowledge management and Q&A framework for enterprise document understanding and semantic retrieval. Supports 10+ document formats including PDF, Word, Excel, and images with seamless IM platform integration for WeCom, Feishu, Slack, and Telegram. Offers Quick Q&A mode using RAG pipelines and Intelligent Reasoning mode with ReACT agents for complex multi-step reasoning tasks across organizational knowledge bases.

Heterogeneous CPU-GPU inference and SFT for large MoE models

Open-source framework for running and fine-tuning large Mixture-of-Experts models with heterogeneous CPU-GPU execution, optimized kernels, limited VRAM and SGLang or LLaMA-Factory integrations.

Official Kubernetes and Helm reference stack built on the vLLM inference engine

Official vLLM reference implementation for scaling the existing inference engine on Kubernetes with Helm, request routing, KV-cache offload, autoscaling and Prometheus/Grafana observability.

Distributed inference orchestration above vLLM, SGLang and TensorRT-LLM

Open-source, datacenter-scale orchestration layer that coordinates vLLM, SGLang and TensorRT-LLM across nodes with disaggregated serving, KV-aware routing, multi-tier cache management and automatic scaling.

Open-source GPU control plane for scalable AI model serving

Open-source GPU cluster manager that configures vLLM, SGLang, TensorRT-LLM or custom engines, serves models through compatible APIs, and provisions SSH-accessible GPU instances across on-premises, Kubernetes and cloud environments.

Disaggregated KV cache storage and transfer for LLM serving

Open-source infrastructure for disaggregated LLM serving that pools KV caches across prefill and decode workers, with high-performance transfer, distributed storage and integrations for vLLM and SGLang.

Reusable KV cache infrastructure for scalable LLM inference

Open-source KV cache management layer that persists, offloads and reuses model key-value caches across requests and serving engines to reduce repeated prefill work and improve inference throughput.