Splits LLM inference into separate prefill and decode GPU pools, then routes requests with KV-cache awareness to cut redundant recomputation. Reports up to 30x throughput on DeepSeek-R1 (GB200 NVL72) and works across TensorRT-LLM, vLLM, and SGLang.
Centralized enterprise platform to manage org-wide MCP servers with a private MCP registry, security guardrails, cost controls, and observability. Offers a Kubernetes-native orchestrator, built-in RAG knowledge base, security sub-agents, and tools for governed AI adoption.
Composes AI agent teams from a Ghost+Shell+Model formula: each Bot pairs a prompt/MCP/Skills Ghost with a Chat, ClaudeCode, or Dify shell and a model like Claude or DeepSeek. Bots form Teams that run as traceable Tasks, wired to GitHub and DingTalk.
Extends vLLM beyond text to serve omni-modal models — Qwen3-Omni, TTS like CosyVoice3, and diffusion image/video/audio generators — in one engine, adding the non-autoregressive Diffusion Transformer support the core project never targeted.
Declares and installs agent dependencies from an apm.yml manifest—skills, prompts, agents, plugins and MCP servers—with transitive resolution, security auditing, plugin packaging, and cross-host registries so agents are reproducible across repos.
Turns papers, repositories, or natural-language research goals into local-first executable 'quests' that automate reproducible experiments, branching, and result-to-paper workflows. Preserves experiment history, supports web/TUI/connectors, and keeps human takeover and inspection simple.
Drives an LLM-powered agent to autonomously research, write, and ship ML code by accessing Hugging Face docs, datasets, repos, and cloud compute. Provides interactive CLI and headless modes, approval gates, tool routing, and integrations for HF, GitHub, and Anthropic models.
Provides adaptive workflow steering rules for AI coding agents to guide development across Inception, Construction, and Operations phases. Includes opt-in extensions (security, testing), IDE/agent integrations (Cursor, Kiro, Amazon Q, Copilot, Claude), and human-in-the-loop approval points.
Turns a PC, Mac, or Linux machine into a private AI server with one-command installers: local LLM inference, a ChatGPT-style web UI, voice, agents, RAG, workflows, image generation, hardware-aware model selection, and optional cloud/hybrid modes.
Runs durable, checkpointed SQL workflows inside PostgreSQL so long-running data and AI pipelines can resume after crashes without external orchestrators. Provides a SQL DSL, in-process background worker, and Postgres-backed state—useful for embeddings, ETL, scheduling, and fan-out jobs when you can install extensions.
Aggregates and deduplicates stories from Hacker News, Reddit, RSS, Telegram, GitHub and more, then uses LLMs to score, enrich, and produce bilingual (EN/CN) daily briefings. Supports customizable sources, comment summarization, multi-provider scoring, and delivery via GitHub Pages, email, or webhooks — designed for self-hosted, configurable news digests.