Aegis

Aegis is a modular Python framework for composing controlled agent workflows, registries, memory, tool execution, policies, and evaluation.

The project currently provides a runnable command-line interface that executes tasks through the built-in Aegis orchestration layer.

Current capabilities

  • Typed agent and tool registries
  • Planner, task agent, and evaluator workflow
  • Runtime orchestration layer
  • User-facing aegis run CLI
  • Human-readable and structured JSON output
  • Agent and workflow selection
  • Execution step limits
  • Stable process exit codes
  • Pydantic-based contracts
  • Ruff, mypy, and pytest validation
  • Deterministic evaluation of task results

Installation

Clone from Hugging Face

This repository is currently private. You must authenticate with Hugging Face before cloning it.

hf auth login

git clone https://huggingface.co/jayc1978/aegis
cd aegis

python -m venv .venv
source .venv/bin/activate

pip install -e ".[dev]"

Verify the installation:

aegis run --help
aegis run "Run the default Aegis workflow"

CLI usage

Run the default workflow:

aegis run "Review this repository"

Run a specific agent:

aegis run --agent default-task "Review this repository"

Return structured JSON:

aegis run --output json "Review this repository"

Limit execution steps:

aegis run --max-steps 10 "Review this repository"

Development

Run the full validation suite:

pytest
ruff check .
mypy src

Current verified baseline:

  • 56 tests passed
  • Ruff passed
  • mypy passed

Current limitations

  • Memory is currently in-process only.
  • No Ollama or Hugging Face inference provider is connected yet.
  • The default workflow is deterministic.
  • Tool integrations and policy enforcement remain limited.
  • No persistent database, API server, or web interface is included yet.

Project direction

Aegis is intended to become an auditable, policy-controlled runtime for AI-agent automation.

Its purpose is to control:

  • which tools an agent may use
  • what data an agent may access
  • when human approval is required
  • how agent actions are evaluated
  • how execution history is recorded

License

This project is licensed under the MIT License. See LICENSE for details.

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