MiroFlow is a research agent framework that performs multi-step internet research to address complex challenges such as future event prediction.
The tool solves the problem of conducting comprehensive research across multiple sources and reasoning steps by combining an agent framework with support for multiple language models including MiroThinker, Claude, Kimi, and OpenAI. It uses a state-based architecture that coordinates tool use, web browsing, and reasoning to gather and synthesize information for complex queries. The framework is designed to be reproducible and achieves performance on benchmarks including FutureX, GAIA, HLE, xBench-DeepSearch, and BrowserComp.
Developers should choose this tool if they need to build research agents that can handle multi-step reasoning and internet search tasks. It suits projects requiring future event prediction, complex information synthesis, or benchmark-competitive agent performance. The tool is fully open-source and includes a web UI for interaction, making it accessible for both development and deployment scenarios.
The project shows active development with multiple versioned releases introducing architectural improvements and performance enhancements. The codebase has been refined across iterations with significant benchmark performance gains. Documentation includes quick-start guides, benchmark validation traces, and local deployment options through Gradio. The project maintains support for multiple language models and provides training data through a companion dataset resource.
