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📊 公开数据一览
| 📦 榜单安装量 | 3.3K |
| ⭐ GitHub Stars | 79,245（fork 10821） |
| 🗓️ 最近推送 | 2026-08-04 |
| 🌱 项目创建 | 2025-05-07 |
| 💻 语言 / License | Python · MIT |
| 🐛 开放Issue | 958 |
📝 工具简介
开源长周期SuperAgent框架，结合沙箱、记忆、工具和子agent，处理耗时数分钟到数小时的任务
📖 怎么用
先克隆仓库：`git clone https://github.com/bytedance/deer-flow.git`，然后 `cd deer-flow` 进入目录，执行 `make setup` 完成初始化。接着在配置文件里添加模型，比如用 `gpt-4o` 就写 `model: gpt-4o` 和 `api_key: $OPENAI_API_KEY`，想用 Gemini 就配 `openrouter-gemini-2.5-flash`，或者用 `gpt-5.4` 配 `supports_thinking: true`。配好后启动服务就能用了，它会自动编排子代理、记忆和沙箱来干活。
📋 迷你测评
开源长周期SuperAgent框架，结合沙箱、记忆、工具和子agent。专门处理耗时几分钟到几小时的任务，适合复杂工作流。
📄 README 要点
DeerFlow是一个开源超级代理框架，全称是Deep Exploration and Efficient Research Flow，在2026年2月28日发布2.0版本后登上GitHub趋势榜第一。这个项目是彻底重写的，与1.x版本不共享代码，原版深度研究框架保留在1.x分支继续维护。2.0版本的核心能力是编排子代理、记忆和沙箱环境，通过可扩展的技能来执行各种任务。项目有官方网站展示真实演示，还有一个姊妹项目LLM Space作为幕后支持。适合需要构建复杂AI代理工作流、进行深度研究自动化的开发者和研究团队。
查看英文原文
🦌 DeerFlow 2.0 English 中文 日本語 Français Русский On February 28th, 2026, DeerFlow claimed the 🏆 1 spot on GitHub Trending following the launch of version 2. Thanks a million to our incredible community — you made this happen! 💪🔥 DeerFlow ( D eep E xploration and E fficient R esearch Flow ) is an open source super agent harness that orchestrates sub agents , memory , and sandboxes to do almost anything — powered by extensible skills . https://github.com/user attachments/assets/a8bcadc4 e040 4cf2 8fda dd768b999c18 [!NOTE] DeerFlow 2.0 is a ground up rewrite. It shares no code with v1. If you're looking for the original Deep Research framework, it's maintained on the 1.x branch — contributions there are still welcome. Active development has moved to 2.0. Official Website Learn more and see real demos on our official website . Sister Projects LLM Space Meet our secret weapon behind DeerFlow — one desktop tool to prototype agent ideas, inspect each harness step, replay failures, and benchmark performance. Coding Plan from ByteDance Volcengine We strongly recommend using Doubao Seed 2.0 Code, DeepSeek v3.2 and Kimi 2.5 to run DeerFlow Learn more 中国大陆地区的开发者请点击这里 InfoQuest DeerFlow has newly integrated the intelligent search and crawling toolset independently developed by BytePlus InfoQuest (supports free online experience) Table of Contents 🦌 DeerFlow 2.0 Official Website Coding Plan from ByteDance Volcengine InfoQuest Table of Contents One Line Agent Setup Quick Start Configuration Running the Application Deployment Sizing Option 1: Docker (Recommended) Option 2: Local Development Advanced Sandbox Mode MCP Server IM Channels LangSmith Tracing Langfuse Tracing Monocle Tracing Using Multiple Providers From Deep Research to Super Agent Harness Core Features Skills \& Tools Claude Code Integration Session Goals Manual Context Compaction Sub Agents Sandbox \& File System Context Engineering Long Term Memory Recommended Models Embedded Python Client Scheduled Tasks Terminal Workb
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