A visual playground for agentic workflows: Iterate over your agents 10x faster
 <p align="center"><strong>Iterate over your agents 10x faster. AI engineers use PySpur to iterate over AI agents visually without reinventing the wheel.</strong></p> <p align="center"> <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-blue"></a> <a href="./README_CN.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-blue"></a> <a href="./README_JA.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-blue"></a> <a href="./README_KR.md"><img alt="README in Korean" src="https://img.shields.io/badge/한국어-blue"></a> <a href="./README_DE.md"><img alt="Deutsche Version der README" src="https://img.shields.io/badge/Deutsch-blue"></a> <a href="./README_FR.md"><img alt="Version française du README" src="https://img.shields.io/badge/Français-blue"></a> <a href="./README_ES.md"><img alt="Versión en español del README" src="https://img.shields.io/badge/Español-blue"></a> </p> <p align="center"> <a href="https://docs.pyspur.dev/" target="_blank"> <img alt="Docs" src="https://img.shields.io/badge/Docs-green.svg?style=for-the-badge&logo=readthedocs&logoColor=white"> </a> <a href="https://forms.gle/5wHRctedMpgfNGah7" target="_blank"> <img alt="Cloud" src="https://img.shields.io/badge/Cloud-orange.svg?style=for-the-badge&logo=cloud&logoColor=white"> </a> </p> https://github.com/user-attachments/assets/54d0619f-22fd-476c-bf19-9be083d7e710 # 🕸️ Why PySpur? ## Problem: It takes a 1,000 tiny paper cuts to make AI reliable AI engineers today face three problems of building agents: * **Prompt Hell**: Hours of prompt tweaking and trial-and-error frustration. * **Workflow Blindspots**: Lack of visibility into step interactions causing hidden failures and confusion. * **Terminal Testing Nightmare** Squinting at raw outputs and manually parsing JSON. We've been there ourselves, too. We launched a graphic design agent early 2024 and quickly reached thousands of users, yet
HAL 分层混合模型工作流 — 强模型(Claude)负责理解/拆解/验收,低成本模型(DeepSeek)负责检索/提取/清洗。Hermes Agent skill。
An LLM agent fine-tuned on DeepSeek for spaced repetition, dynamically integrating knowledge points based on the Ebbinghaus forgetting curve.
基于 STM32F103 构建的端到端 AI 智能手表生态。自研“零重定位”原生机器码动态加载引擎与页面栈式 UI 框架;集成生产级 OTA 回滚保护机制与高带宽(921600 baud)串口协议栈。通过 Node.js 中继实现 DeepSeek AI 语义控制及 ASRPRO 语音全双工交互,是一个集成了分布式计算、现代存储管理与 AI Agent 的嵌入式全栈工程。
A Meta-Agent-Driven Self-Evolving Multi-Agent System for UAV Detection and Tracking
One command to run Hermes AI Agent with a browser UI. Zero prerequisites. 一行命令,AI 就位。
网页应用Agent,接入DeepSeek、Mimo等模型