A review of Google's Auto Browse agent, testing its ability to perform various online tasks, from playing web games to managing playlists and scanning emails. The agent shows promise but requires significant supervision and struggles with certain tasks, particularly those involving prolonged monitoring or complex interfaces.
This document provides guidelines for maintaining high-quality Python code, specifically for AI coding agents. It covers principles, tools, style, documentation, testing, and security best practices.
Get LLMs to do things from Emacs with gptel. The project seeks testers to help evolve tool use within the gptel interface for Emacs.
Ensuring the quality and stability of Large Language Models (LLMs) is crucial. This article explores four open-source repositories - DeepEval, OpenAI SimpleEvals, OpenAI Evals, and RAGAs - each providing special tools and frameworks for assessing LLMs and RAG applications.
