{"repo":"frontier-ai-next/gMAS","free":true,"listed":false,"github":"https://github.com/frontier-ai-next/gMAS","clone":"git clone https://github.com/frontier-ai-next/gMAS.git","description":"Dynamic graph runtime for building, adapting, and observing multi-agent LLM systems in Python.","language":"Python","stars":25,"topics":["agentic-ai","ai-agents","graph","graph-neural-networks","llm","mcp","multi-agent-systems","python","rustworkx","workflow-automation"],"license":"MIT","category":"ai-agents","readme_excerpt":"gMAS Build multi-agent systems whose roles and connections can change while they run. Documentation · Quick start · API reference · Benchmarks · Releases gMAS is an open-source Python framework for building and running graph-based multi-agent systems with LLMs. Nodes hold roles and tasks; edges carry work and context; the runner schedules model and tool calls. Budgets, memory, events, and changes to the remaining plan stay visible in the same execution model. Project status: gMAS is an early release for developers and researchers. The public API is tested on Python 3.12 and 3.13. Pin a version for production experiments and expect some advanced APIs to evolve. What stays explicit Agent workflows quickly accumulate dependencies, parallel branches, tool permissions, budgets, and failure paths. gMAS keeps them in the graph and runner configuration instead of spreading them across prompt templates and callbacks: - the team is stored in RoleGraph ; - the scheduler derives execution order and parallel groups from the graph; - each role can have its own instructions, model, tools, and local state; - the runner records outputs, token use, latency, errors, and topology changes; - typed policies can stop, skip, reroute, or recover work during the same run; - the graph can be exported for routing, pruning, and graph analysis. Core capabilities Area What gMAS provides --- --- Graph model Agents, task nodes, weighted communication edges, conditions, execution boundaries, node state, and g","default_branch":null,"files":null,"tree":[],"storefront":"/r/frontier-ai-next","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/frontier-ai-next/gMAS/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}