All Hands AI has released OpenHands CodeAct 2.1, an open-source software development agent that can solve over 50% of real GitHub issues in SWE-Bench. The agent uses Anthropic’s Claude-3.5 model, function calling, and improved directory traversal to achieve this milestone.
AI agent helping write and fix code, running tests and iterating till code passes tests or matches designs. Uses OpenAI API and aims to make coding easier.
Micro Agent is an AI agent that assists with coding, helping with code generation and iteration processes. It's a focused agent that aims to write code based on provided test cases or design screenshots. It can work in tandem with OpenAI and Anthropic APIs for better visual matching. The agent is designed with a specific focus - creating a clear test case and providing feedback on code that helps improve the generated code. Installation requires Node.js v14 or later, and it can be installed globally using npm. To get started, running the agent in interactive mode is recommended. Micro Agent can work in both unit test matching mode and visual matching mode for coding assistance. It uses a multi-agent approach and connects with Figma for high fidelity design-to-code conversions. Configuration options are available via CLI or UI.
Micro Agent is an AI agent that assists with coding, helping with code generation and iteration processes. It's a focused agent that aims to write code based on provided test cases or design screenshots. It can work in tandem with OpenAI and Anthropic APIs for better visual matching. The agent is designed with a specific focus - creating a clear test case and providing feedback on code that helps improve the generated code. Installation requires Node.js v14 or later, and it can be installed globally using npm. To get started, running the agent in interactive mode is recommended. Micro Agent can work in both unit test matching mode and visual matching mode for coding assistance. It uses a multi-agent approach and connects with Figma for high fidelity design-to-code conversions. Configuration options are available via CLI or UI.
The llama-cpp-agent framework is a tool designed for easy interaction with Large Language Models (LLMs). It provides a simple yet robust interface using llama-cpp-python, allowing users to chat with LLM models, execute structured function calls and get structured output.
