#Llm-orchestration
Showing 23 of 23 repositories tagged #llm-orchestration, ranked by stars
Agent OS: Stop prompting. Start specifying.
🚀 MassGen is an open-source multi-agent scaling system that runs in your terminal, autonomously orchestrating frontier models and agents to collaborate, reason, and produce high-quality results. | Join us on Discord: discord.massgen.ai
Coordinate your coding agents like a group chat — read receipts, delivery tracking, and remote ops from your phone. One pip install, zero infrastructure. A production‑minded orchestrator for 24/7 workflow
AINL helps turn AI from "a smart conversation" into "a structured worker." It is designed for teams building AI workflows that need multiple steps, state and memory, tool use, repeatable execution, validation and control, and lower dependence on long prompt loops. AINL is a compact, graph-canonical, AI-native programming system for (READ: README)
Production-ready development workflows for Claude Code, powered by specialized AI agents.
TypeScript AI agent framework: cognitive memory, runtime tool forging, multi-agent orchestration, 11 LLM providers.
Production-grade Go SDK for building AI agents with long-term memory, knowledge retrieval, and voice — runnable as a library, a daemon, or a real-time pipeline.
Orchestrate an entire AI dev team on 5GB VRAM. Ephemeral subagents, exact-match diffs. Single static binary, any model. Zero config, zero context bloat.
Your one-click scientific research lab for Opencode - with seamless .ipynb and REPL integration
Agentic coding TypeScript boilerplate for Claude Code — sub-agent workflows with built-in quality checks and context engineering.
A lightweight workflow engine
The scaffold for your multi-model, personalized Natural Language AI Harness (NLAH) .
A collection of 2025 agentic workflows built in n8n. Showcases manual multi-model orchestration, RAG-to-SQL, and autonomous research pipelines developed before the era of standardized agentic protocols (MCP).
Portable AI runtime inspired by docker-compose. Compose agents, RAG pipelines, and MCP servers in one YAML file and run them anywhere.
AI agents that write code, review each other's work, and coordinate across your machines
Fractalic: Build and version-control AI systems using Markdown & YAML. Combine LLM calls, shell commands, and modular workflows in a human-readable format. Docker-first installation, Git-native tracking.
Cross-LLM sub-agent orchestration as an Agent Skills. Route tasks to Codex, Claude Code, Cursor, or Gemini from any compatible tool.
Claude Code best practices -- applied to application design. Interactive HLD/LLD visualization, implementation example. LLM-agnostic, DB-governed, GDPR-ready.
Agentic coding framework powered by AGENTS.md — systematic, test-first workflows with quality gates for Cursor, Codex, Gemini CLI, and AI coding agents.
Open-source RAG pipeline with multihop reasoning - 8-stage flow
Spring AI framework for Java that plans, executes, and improves itself — agents detect capability gaps at runtime and generate validated skills on the fly.
Structured agentic coding workflows for OpenAI Codex CLI with specialized AI subagents, planning, and quality gates.
Framework agnóstico de orquestração multi-agente para integrar uma squad autônoma de IA (PO, Tech Lead, Dev, QA e Ops) diretamente no seu repositório de software.