ASearcher is an open-source framework designed for large-scale online reinforcement learning (RL) training of search agents. Our mission is to advance Search Intelligence to expert-level performance. We are fully committed to open-source by releasing model weights, detailed training methodologies, and data construction pipelines. Additionally, we provide comprehensive guidance on building and training customized agents based on AReaL. ASearcher empowers developers to build their own high-performance search agents easily and cost-effectively.
We have released multiple models trained with different settings and based on foundation models of varying sizes. These models have achieved outstanding performance on Single-Hop / Multi-Hop QA and more challenging tool-augmented benchmarks like GAIA, Xbench.
We also release our full
training data and
test data, you can easily get them and reproduce our result.
If you want to learn more details, please refer to our GitHub repository:
ASearcher
