SCOUT-2 is an open-source framework that orchestrates hierarchical autonomous AI agents to break down complex goals into sub-tasks, execute actions using LLMs, track progress, and iteratively refine results through a planning-execution-reflection loop.
SCOUT-2 is an open-source framework that orchestrates hierarchical autonomous AI agents to break down complex goals into sub-tasks, execute actions using LLMs, track progress, and iteratively refine results through a planning-execution-reflection loop.
SCOUT-2 provides a modular architecture for building autonomous agents powered by large language models. It includes goal decomposition, task planning, an execution engine, and a feedback-driven reflection module. Developers define a top-level objective, and SCOUT-2 automatically generates a task tree, dispatches worker agents for execution, monitors progress, and refines tasks based on outcomes. It integrates with OpenAI APIs and can be extended with custom prompts and templates to support a wide range of workflows.
Who will use SCOUT-2?
AI researchers
Software developers
Automation engineers
Business analysts
AI hobbyists
How to use the SCOUT-2?
Step1: Clone the SCOUT-2 repository from GitHub.
Step2: Install Python dependencies via pip install -r requirements.txt.
Step3: Set your OPENAI_API_KEY environment variable.
Step4: Configure your project by defining goals and templates in the config files.
Step5: Run SCOUT-2, monitor console output, and review generated task artifacts.