{"repo":"GoogleCloudPlatform/race-condition","free":true,"listed":false,"github":"https://github.com/GoogleCloudPlatform/race-condition","clone":"git clone https://github.com/GoogleCloudPlatform/race-condition.git","description":"The open source multi-agent simulation from the Developer Keynote at Google Cloud Next '26. A deployable reference architecture for autonomous AI agents using Gemini and ADK.","language":"Python","stars":221,"topics":["agent-development-kit","ai-agents","angular","cloud-run","gemini","golang","google-cloud","multi-agent-systems","python","reference-architecture"],"license":null,"category":"ai-agents","readme_excerpt":"Race Condition A multi-agent marathon simulation built with Google ADK and Gemini. AI agents plan a marathon route through Las Vegas, simulate the environment around it (weather, traffic, crowds), and run the race autonomously. Everything talks over the A2A protocol. Originally demoed at the Google Cloud Next '26 Developer Keynote. What this repo is good for This is the open-source release of the multi-agent simulation we ran at the Google Cloud Next '26 Developer Keynote. It is also a working reference architecture for a few patterns that are hard to study in isolation: - Cached vs live replay. The frontend can replay NDJSON streams recorded from real agent runs, indistinguishable from a live session. We use it for keynote reliability; you can use it to demo, test UI changes, or teach without paying for LLM calls. - A deterministic runner variant. runner autopilot makes the same shape of decisions a real LLM-powered runner would, but with zero API calls. It is the right baseline when you want to measure the simulator under load without your bill becoming the experiment. - A planner ladder. Three variants of the planner ( planner , planner with eval , planner with memory ) show what each layer actually adds — eval gating, persistent memory in AlloyDB — as separate agents instead of feature flags. - The Hub session pattern. A Go gateway routes WebSocket traffic to and from Python ADK agents over A2A, with batching to keep the system from thundering-herding itself when hundreds","default_branch":null,"files":null,"tree":[],"storefront":"/r/GoogleCloudPlatform","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/GoogleCloudPlatform/race-condition/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."}