ToolAI.io · GitHub Channel
A fact-based index of LLM, agent, MCP, RAG and AI development projects, with license, setup, download, screenshots and related resources for each entry.
Public repository data
huggingface/transformers
A model-definition framework for state-of-the-art machine learning models across text, vision, audio, and multimodal domains, supporting both inference and training.
openvinotoolkit/openvino
Open-source toolkit for optimizing and deploying AI inference across edge-to-cloud environments.
xorbitsai/inference
A powerful and versatile library designed to serve language, speech recognition, and multimodal models. It allows users to swap GPT for any LLM by changing a single line of code and run models on cloud, on-prem, or locally via a unified, production-ready inference API.
kvcache-ai/mooncake
Mooncake is a C++ infrastructure project for large-scale LLM inference and training. It separates prefill, decode, and storage resources while providing high-performance transfer, distributed KV-cache storage, and fault-tolerant expert-parallel communication.
gpustack/gpustack
GPUStack is an open-source GPU cluster manager for serving AI models and provisioning on-demand, SSH-accessible GPU instances. It orchestrates inference engines including vLLM, SGLang, and TensorRT-LLM across on-premises, Kubernetes, and cloud environments.
llm-d/llm-d
llm-d is an open-source serving stack that adds distributed orchestration, routing, cache management, autoscaling, and batch processing around model servers such as vLLM and SGLang. It targets high-scale production inference on Kubernetes and modern hardware accelerators.
vllm-project/vllm-ascend
A community-maintained hardware plugin that enables vLLM to run model inference and serving workloads on supported Ascend NPUs.
mozilla-ai/any-llm
any-llm is a Python SDK for communicating with multiple LLM providers through one interface. It supports switching providers and models with minimal code changes while using official provider SDKs when available.
xllm-ai/xllm
xLLM is a C++ inference framework for LLM, VLM, DiT and REC models. It targets high-throughput, low-latency deployment on several AI accelerator families and separates service-layer scheduling and availability from engine-layer computation.
avifenesh/memra
A from-scratch LLM inference engine built in Rust and CUDA, specifically optimized for RTX 5090 (sm_120a) and H100 (sm_90a) architectures, delivering exactness-gated performance without relying on frameworks like ggml.
hal0ai/hal0
An open-source, self-hosted home AI inference platform designed to turn a Linux box into an OpenAI-compatible inference appliance, with native optimization for AMD Strix Halo hardware.
