Projects sharing features with Loom

Code for LLM-Planner.

FILM: Following Instructions in Language with Modular Methods So Yeon Min, Devendra Singh Chaplot, Pradeep Ravikumar, Yonatan Bisk, Ruslan Salakhutdinov Carnegie Mellon University, Facebook AI Research

ReAct is an agentic workflow template and prompting framework for large language models. It implements a logic pattern that integrates chain-of-thought reasoning with external tool execution to solve complex, multi-step tasks. The framework uses an interleaved reasoning and acting logic, forcing the model to document its internal thought process before executing an action. This cycle of planning and acting allows the system to interact with external APIs or databases and inject real-world data back into the model context to refine reasoning paths. The project covers autonomous task execution