A framework for making agents more aware of their environment through explicit modeling of pre and post effects
Project description
Agent-Log
Overview
Agent-Log is a framework aiming to make agents more aware of their enviroment through the explicit modeling of pre and post effects. The approach is inspired by logic-based AI theory such as the "AI Frame Problem".
Repository Overview
This repository implements the Agent-Log framework, providing utility methods that are usable across agentic workflows. Specifically, the following are included:
- Prompt template to ellicit change-logs
- Pre-defined change-log template
- Currently supports JSON. Future temoplates could include: XML, git diff based
- Extraction methods to decompose set of change-logs from output response to structured objects
- Evaluation or sanity check methods for change-logs
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