Level-Navi Agent is an open-source general-purpose web search agent framework that can decompose complex problems and progressively search for information on the internet until it answers user questions. By providing the Web24 dataset, covering five major fields: finance, games, sports, movies, and events, it provides a benchmark for evaluating model performance on search tasks. The framework supports zero-shot and few-shot learning, providing an important reference for the application of large language models in the field of Chinese web search agents.