AutoBrowse is a developer library enabling LLM-driven web automation. By leveraging large language models, it plans and executes browser actions—searching, navigating, interacting, and extracting information from web pages. Using a planner-executor pattern, it breaks down high-level tasks into step-by-step actions, handling JavaScript rendering, form inputs, link traversal, and content parsing. It outputs structured data or summaries, making it ideal for research, data collection, automated testing, and competitive intelligence workflows.

Multi-Agent LLM Recipe Prices orchestrates a suite of specialized AI agents to break down recipes into ingredients, query external price databases or APIs for real-time market rates, perform unit conversions, and sum up total costs by currency. Built in Python, it uses a recipe parsing agent to extract items, a price lookup agent to fetch current prices, and a currency conversion agent to handle international pricing. The framework logs each step, supports plugin extensions for new data providers, and outputs detailed cost breakdowns in JSON or CSV formats for further analysis.