d9a86c10e8
Citations:
- In shouldShowCitationLoading, treat any unreplaced [cite-N] in cleanContent
as show-loading (no body). Fixes Ultra and other modes when refs arrive
before the <citations> block in the stream.
- Single rule: hasUnreplacedCitationRefs(cleanContent) => true forces loading;
then isLoading && hasCitationsBlock(rawContent) for streaming indicator.
SSE end state:
- When stream finishes, SDK may set isLoading=false before client state has
the final message content, so UI stayed wrong until refresh.
- Store onFinish(state) as finalState in chat page; clear when stream starts.
- Pass messagesOverride={finalState.messages} to MessageList when not loading
so the list uses server-complete messages right after SSE ends (no refresh).
Chore:
- Stop tracking .githooks/pre-commit; add .githooks/ to .gitignore (local only).
Co-authored-by: Cursor <cursoragent@cursor.com>
---
fix(前端): 杜绝半成品引用，SSE 结束时展示正确状态
引用：
- shouldShowCitationLoading 中只要 cleanContent 仍含未替换的 [cite-N] 就
只显示加载、不渲染正文，解决流式时引用块未到就出现 [cite-1] 的问题。
- 规则：hasUnreplacedCitationRefs(cleanContent) 为真则一律显示加载；
此外 isLoading && hasCitationsBlock 用于流式时显示「正在整理引用」。
SSE 结束状态：
- 流结束时 SDK 可能先置 isLoading=false，客户端 messages 尚未包含
最终内容，导致需刷新才显示正确。
- 在对话页保存 onFinish(state) 为 finalState，流开始时清空。
- 非加载时向 MessageList 传入 messagesOverride={finalState.messages}，
列表在 SSE 结束后立即用服务端完整消息渲染，无需刷新。
杂项：
- 取消跟踪 .githooks/pre-commit，.gitignore 增加 .githooks/（仅本地）。
🦌 DeerFlow - v2
Originated from Open Source, give back to Open Source.
A LangGraph-based AI agent backend with sandbox execution capabilities.
Quick Start
Option 1: Docker (Recommended)
The fastest way to get started with a consistent environment:
-
Configure the application:
cp config.example.yaml config.yaml # Edit config.yaml and set your API keys -
Initialize and start:
make docker-init # First time only make docker-dev # Start all services -
Access: http://localhost:2026
See CONTRIBUTING.md for detailed Docker development guide.
Option 2: Local Development
If you prefer running services locally:
-
Check prerequisites:
make check # Verifies Node.js 22+, pnpm, uv, nginx -
Configure and install:
cp config.example.yaml config.yaml make install -
(Optional) Pre-pull sandbox image:
# Recommended if using Docker/Container-based sandbox make setup-sandbox -
Start services:
make dev -
Access: http://localhost:2026
See CONTRIBUTING.md for detailed local development guide.
Features
- 🤖 LangGraph-based Agents - Multi-agent orchestration with sophisticated workflows
- 🧠 Persistent Memory - LLM-powered context retention across conversations with automatic fact extraction
- 🔧 Model Context Protocol (MCP) - Extensible tool integration
- 🎯 Skills System - Reusable agent capabilities
- 🛡️ Sandbox Execution - Safe code execution environment
- 🌐 Unified API Gateway - Single entry point with nginx reverse proxy
- 🔄 Hot Reload - Fast development iteration
- 📊 Real-time Streaming - Server-Sent Events (SSE) support
Documentation
- Contributing Guide - Development environment setup and workflow
- Configuration Guide - Setup and configuration instructions
- Architecture Overview - Technical architecture details
- Backend Architecture - Backend architecture and API reference
Contributing
We welcome contributions! Please see CONTRIBUTING.md for development setup, workflow, and guidelines.
License
This project is open source and available under the MIT License.
Acknowledgments
DeerFlow is built upon the incredible work of the open-source community. We are deeply grateful to all the projects and contributors whose efforts have made DeerFlow possible. Truly, we stand on the shoulders of giants.
We would like to extend our sincere appreciation to the following projects for their invaluable contributions:
- LangChain: Their exceptional framework powers our LLM interactions and chains, enabling seamless integration and functionality.
- LangGraph: Their innovative approach to multi-agent orchestration has been instrumental in enabling DeerFlow's sophisticated workflows.
These projects exemplify the transformative power of open-source collaboration, and we are proud to build upon their foundations.
Key Contributors
A heartfelt thank you goes out to the core authors of DeerFlow, whose vision, passion, and dedication have brought this project to life:
Your unwavering commitment and expertise have been the driving force behind DeerFlow's success. We are honored to have you at the helm of this journey.