#llm

A Rails agent framework for RubyLLM — define AI agents with prompts, schemas, caching, logging, cost tracking, and a built-in dashboard for monitoring LLM usage in production.

Persistent memory & RAG engine for AI agents — SQLite + FTS5 + embeddings, multi-stage recall, sleep maintenance, multi-host hooks

跨设备的开源Agent工作台

The open-source agentic framework to build, orchestrate, and operate production AI agents.

Multi-agent orchestration harness for Claude Code + Codex — task lifecycle, handoff protocol, dashboard, and autonomous dispatch

TypeScript SDK for orchestrating Agentic Systems — concurrency, structured output, cost control, and consensus as first-class primitives.

TypeScript LLM Abstraction Layer for Multi-Provider AI Systems. Multi-provider routing, fallback chains, USD cost gating, capability factories, tool-use security.

Command line artificial intelligence - Context engineering for terminal powerusers

A general-purpose semantic systems programming language. Describe a system once; real compilers lower the same source into engine builds, backend services, robots, web runtimes, and headset apps. Not a scripting language.

Production plumbing for LLM apps: context, cost, testing & governance — composable, framework-agnostic Python libraries.

occlusion for agent CLIs and APIs. Declare what an agent may run, and everything you did not name stays unreachable.

Context.dev Go SDK: scrape any URL to LLM-ready markdown, crawl sites, search the web and extract structured JSON with one API key.

Self-hosted MCP server to index and search any documentation site—public or private

Coding agent overseer

MCP Data Bridge for Java. Enabling safe Text-to-Query via a semantic layer, making enterprise data accessible to AI Agents.

AI code sessions over your git repos run Claude Code / Codex / Cursor remotely, stream progress live, inspect diffs, open PRs, automate PR reviews. Go + React, ships as server or GitHub Action.

a fast, rootless sandbox and virtual resource runtime. Run any workload in a real container, including an agent's tool-call or LLM-generated code.

A powerful CLI tool that brings AI assistance directly to your terminal. Gokin understands your codebase and helps with file operations, code search, shell commands, git workflows, task management, and more - all through natural language.

Gives agents a think→act loop — plus recursive decomposition (RLM): break a hard task down, fan out, verify, synthesize. Goal in, coordinated actions out. Replaces LangChain, CrewAI, AutoGen. Zero required deps.

The AI team that never forgets — persistent Memory Bank, 45 specialist agents, and 109 commands that survive every session reset. Install once via npx @hanzlaa/rcode. Works with Claude Code and compatible AI harnesses.

Agent-first CLI for Proton Mail. Local AI inbox classification, search, and Q&A via Proton Mail Bridge and Ollama. Nothing leaves your machine.

An open-source visual programming environment for battle-testing prompts to LLMs.

No repository description published.

Train and serve LLMs at extreme speed and massive throughput.

.NET pipeline framework for enterprise AI applications — multi-provider LLM integration, RAG pipelines, and multi-agent orchestration with a fluent builder API.

.NET library for on-demand local AI model inference — zero bundled models, lazy loading, hardware-aware GPU/CPU selection, 10 task types including embeddings, generation, vision, and audio.

Continuously Looping Engineering Machines. docker-compose for Claude Code agents - persistent teams, 24/7, on any Linux host.

📐 Fast token estimation with 95%+ average accuracy in a 2kB bundle

Terminal based project management solution

One persistent MCP terminal your AI drives — and launches other coding agents (Codex/Grok/Composer) into. SSH, containers, and REPLs nest as text you send in. tmux-backed, token-reduced reads, headless over MCP.