This repo is the official implementation of the MiroMind Research Agent Project. It is a leading-performance, fully open-source system designed to perform multi-step internet research for addressing complex challenges such as future event prediction. The project currently comprises four key components:

• 🤖 MiroFlow: an open-source research agent framework that offers reproducible state-of-the-art performance on representative benchmarks (e.g., FutureX, GAIA, HLE, xBench-DeepSearch, and BrowserComp benchmarks), included in this repo. See [Get Started in Under 5 Minutes] for a quick start.
• 🤔 MiroThinker: an open-source agent foundation model that natively supports tool-assisted reasoning. See MiroThinker.
• 📊 MiroVerse: 147k premium open-source training data supporting research agent training. See MiroVerse.
• 🚧 MiroTrain / MiroRL: The training infra that supports stable and efficient training for the research agent models. See MiroTrain / MiroRL

• 📰 News & Updates
• 🚀 Get Started in Under 5 Minutes
• 🤖 What is MiroFlow?
• 🌟 Highlights
• 📈 Performance on Benchmarks
• 🔧 Supported Models & Tools
• ❓ FAQ
• 🤝 Contributing
• 📄 License
• 🙏 Acknowledgments

• [2025-09-15]: 🎉🎉 MiroFlow v0.3: Enhanced codebase architecture and significantly improved benchmark performance, boosting GPT-5's prediction accuracy for future events by 11%. MiroFlow now ranks #1 in the future prediction benchmark. See FutureX.
• [2025-08-27]: MiroFlow v0.2: Achieves state-of-the-art performance across multiple agentic benchmarks, including HLE (27.2%), HLE-Text-Only (29.5%), BrowserComp-EN (33.2%), BrowserComp-ZH (47.1%), and xBench-DeepSearch (72.0%).
• [2025-08-26]: Released GAIA Validation Trace (73.94% pass@1) and Gradio Demo for local deployment.
• [2025-08-08]: MiroFlow v0.1: Complete open-source release of framework.

• Python: 3.12 or higher
• Package Manager: uv
• Operating System: Linux, macOS

Example: Intelligent document analysis with file processing capabilities.

# 1. Clone and setup
git clone https://github.com/MiroMindAI/MiroFlow && cd MiroFlow
uv sync

# 2. Configure API key
cp .env.template .env
# Edit .env and add your OPENROUTER_API_KEY

# 3. Run your first agent
uv run main.py trace --config_file_name=agent_quickstart_1 --task="What is the first country listed in the XLSX file that have names starting with Co?" --task_file_name="data/FSI-2023-DOWNLOAD.xlsx"

🎉 Expected Output: Your agent should return \boxed{Congo Democratic Republic} 😊

💡 Tip: If you encounter issues, check that your API key is correctly set in the .env file and that all dependencies are installed.

MiroFlow is a high-performance, modular framework for building intelligent AI agents that deliver state-of-the-art results on complex reasoning tasks like future event prediction. The framework features advanced multi-turn conversation capabilities, extensive tool ecosystem integration, and hierarchical sub-agent orchestration for optimal task completion. Learn more about our agent framework.

• Reproducible State-of-the-Art Performance: #1 ranking across multiple agentic benchmarks, including FutureX, GAIA, HLE, xBench-DeepSearch, and BrowserComp benchmarks)
• High Concurrency & Reliability: Built with robust concurrency management and fault-tolerant design, MiroFlow efficiently handles rate-limited APIs and unstable networks, ensuring seamless trajectory collection and reliable execution of complex tasks.
• Cost-Effective Deployment: Powered by the open-source MiroThinker model, MiroFlow can run a research agent service on a single RTX 4090. The entire stack relies on free, open-source tools, making it simple to deploy, scale, and reproduce.

• Models: GPT, Claude, Gemini, Qwen, MiroThinker
• Tools: Audio Transcription, Python, File Reading, Reasoning, Google Search, VQA, E2B

We achieved the #1 ranking on the FutureX Benchmark Leaderboard as of September 10, 2025, boosting GPT-5's prediction accuracy for future events by 11%.

We benchmark MiroFlow on a series of benchmarks, including GAIA, HLE, BrowseComp, and xBench-DeepSearch, and achieved SOTA results.

Follow our detailed guides to reproduce benchmark results in our Benchmarks Documentation

We welcome contributions from the community! Whether you're fixing bugs, adding features, or improving documentation, your help is appreciated.

• 📋 Issues: Report bugs or request features via GitHub Issues

• 🔀 Pull Requests: Submit improvements via pull requests

• 💬 Discussions: Join our Discord community for questions and discussions

This project is licensed under the Apache License 2.0.

Benchmark Contributors for the comprehensive evaluation datasets

Open Source Community for the tools and libraries that make this possible

We thank all contributors who have helped make MiroFlow better:

Join our community and help us build the future of AI agents!

The technical report is coming soon!

@misc{2025mirothinker,
    title={MiroFlow: A High-Performance Open-Source Research Agent Framework},
    author={MiroMind AI Team},
    howpublished={\url{https://github.com/MiroMindAI/MiroFlow}},
    year={2025}
}