OS-Symphony: A Holistic Framework for Robust and Generalist Computer-Using Agents

While Vision-Language Models (VLMs) have significantly advanced Computer-Using Agents (CUAs), current frameworks struggle with robustness in long-horizon workflows and generalization in novel domains. These limitations stem from a lack of granular control over historical visual context curation and the absence of visual-aware tutorial retrieval. To bridge these gaps, we introduce OS-SYMPHONY, a holistic framework that comprises an Orchestrator coordinating two key innovations for robust automation: 1) a Reflection-Memory Agent that utilizes milestone-driven long-term memory to enable trajectory-level self-correction, effectively mitigating visual context loss in longhorizon tasks; 2) Versatile Tool Agents featuring a Multimodal Searcher that adopts a See-Act paradigm to navigate a browser-based sandbox to synthesize live, visually aligned tutorials, thereby resolving fidelity issues in unseen scenarios. Experimental results demonstrate that OS-SYMPHONY delivers substantial performance gains across varying model scales, establishing new state-of-the-art results on three online benchmarks, notably achieving 65.84% on OSWorld. Our code and project are publicly available at OS-Copilot/OS-Symphony and OS-Symphony Homepage.