deer-flow

DeerFlow is an open-source SuperAgent harness designed for long-horizon tasks that involve deep research, coding, and content creation. It utilizes sandboxes, memories, tools, skills, subagents, and a message gateway to manage complex workflows spanning minutes to hours. The framework operates in a secure Docker-based runtime environment, including an All-in-One Sandbox with browser, shell, file management, VSCode server, and persistent file systems, enabling safe execution of commands, long-running processes, and file persistence. Users benefit from its extensibility, allowing custom skill files or built-in libraries, and multi-model support for providers like Doubao, DeepSeek, OpenAI, and Gemini.

DeerFlow 2.0 enhances capabilities with context engineering via long- and short-term memory, advanced planning and sub-tasking for sequential or parallel execution, and plug-and-play tools. Case studies illustrate its versatility, such as generating webpages with research forecasts, videos and images from novels like Pride and Prejudice, comic strips explaining AI concepts like MOE architecture, exploratory data analysis on datasets like Titanic with visualizations, deep research from YouTube videos, and podcast summarization. This makes it suitable for researchers, developers, content creators, and data analysts seeking a self-hosted, controllable agent platform.

As a fully open-source project under MIT license, DeerFlow emphasizes community collaboration, with GitHub contributions welcomed for shaping its evolution from a deep research agent to a full-stack SuperAgent.