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DeepCode: Open Agentic Coding

Advancing Code Generation with Multi-Agent Systems

🖥️ Interface Showcase

#### 🖥️ **CLI Interface** **Terminal-Based Development** 🚀 Advanced Terminal Experience ⚡ Fast command-line workflow 🔧 Developer-friendly interface 📊 Real-time progress tracking *Professional terminal interface for advanced users and CI/CD integration*

#### 🌐 **Web Interface** **Visual Interactive Experience** 🎨 Modern Web Dashboard 🖱️ Intuitive drag-and-drop 📱 Responsive design 🎯 Visual progress tracking *Beautiful web interface with streamlined workflow for all skill levels*

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🎬 Introduction Video

🎯 Watch our complete introduction - See how DeepCode transforms research papers and natural language into production-ready code

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"Where AI Agents Transform Ideas into Production-Ready Code"

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📑 Table of Contents

• 📰 News
• 🚀 Key Features
• 🏗️ Architecture
• 📊 Experimental Results
• 🚀 Quick Start
• 🤖 nanobot Integration (Feishu Chatbot)
• 💡 Examples
• 🎬 Live Demonstrations
• ⭐ Star History
• 📄 License

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📰 News

🎉 [2025-02] DeepCode + nanobot Integration — Chat with DeepCode via Feishu Bot!

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• nanobot now connects to DeepCode — send messages in Feishu and get auto-generated code back
• Supports Paper-to-Code and Chat-to-Code, plus real-time task tracking, all from your chat app
• One-command deploy: ./nanobot/run_nanobot.sh → Setup Guide →

_{Feishu Bot in Action — Natural language → Full code generation with setup instructions}

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🎉 [2025-02] New Web UI Experience Upgrade!

• 🔄 User-in-Loop Interaction: Support real-time user interaction during workflows - AI asks clarifying questions directly in the chat
• 💬 Inline Interaction Design: Interaction prompts appear naturally within the chat flow for a seamless experience
• 🚀 One-Click Launch: Simply run deepcode to start the new UI (cross-platform: Windows/macOS/Linux)
• 🔧 Improved Process Management: Enhanced service start/stop mechanism with automatic port cleanup
• 📡 WebSocket Real-time Communication: Fixed message loss issues, ensuring proper interaction state synchronization

_{DeepCode New Web UI - Modern React-based Interface}

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🎉 [2025-10-28] DeepCode Achieves SOTA on PaperBench!

DeepCode sets new benchmarks on OpenAI's PaperBench Code-Dev across all categories:

• 🏆 Surpasses Human Experts: 75.9% (DeepCode) vs Top Machine Learning PhDs 72.4% (+3.5%).
• 🥇 Outperforms SOTA Commercial Code Agents: 84.8% (DeepCode) vs Leading Commercial Code Agents (+26.1%) (Cursor, Claude Code, and Codex).
• 🔬 Advances Scientific Coding: 73.5% (DeepCode) vs PaperCoder 51.1% (+22.4%).
• 🚀 Beats LLM Agents: 73.5% (DeepCode) vs best LLM frameworks 43.3% (+30.2%).

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🚀 Key Features

🚀 Paper2Code Automated Implementation of Complex Algorithms Effortlessly converts complex algorithms from research papers into high-quality, production-ready code, accelerating algorithm reproduction.

🎨 Text2Web Automated Front-End Web Development Translates plain textual descriptions into fully functional, visually appealing front-end web code for rapid interface creation.

⚙️ Text2Backend Automated Back-End Development Generates efficient, scalable, and feature-rich back-end code from simple text inputs, streamlining server-side development.

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📊 Experimental Results

<img src='./assets/result_main02.jpg' />

We evaluate DeepCode on the PaperBench benchmark (released by OpenAI), a rigorous testbed requiring AI agents to independently reproduce 20 ICML 2024 papers from scratch. The benchmark comprises 8,316 gradable components assessed using SimpleJudge with hierarchical weighting.

Our experiments compare DeepCode against four baseline categories: (1) Human Experts, (2) State-of-the-Art Commercial Code Agents, (3) Scientific Code Agents, and (4) LLM-Based Agents.

① 🧠 Human Expert Performance (Top Machine Learning PhD)

**DeepCode: 75.9% vs. Top Machine Learning PhD: 7