SudalaiMuthu/aeos-env

AEOS: Autonomous Enterprise Operations Simulator 🚀

AEOS is a production-grade, autonomous environment for simulating and evaluating enterprise-level operational workflows. Designed for the OpenEnv ecosystem, it features a robust FastAPI backend, deterministic reward shaping, and multi-tier task evaluation.

🏗️ Project Architecture

AEOS/
├── app.py              # FastAPI server (API layer)
├── inference.py        # Automated agent runner (Inference layer)
├── openenv.yaml        # OpenEnv compliance specification
├── Dockerfile          # Scalable deployment container
├── requirements.txt    # Dependency manifest
└── env/
    ├── environment.py  # Core simulation logic & state machine
    ├── models.py       # Pydantic data schemas
    ├── tasks.py        # Task difficulty definitions
    └── graders.py      # Deterministic evaluation algorithms

🧠 Key Features

• —Dynamic State Management: Tracks real-time emails, tickets, and agent workloads.
• —Advanced Reward Engineering: Multi-faceted rewards including immediate action signals, efficiency bonuses, and long-term system stability incentives.
• —SLA Decay Simulation: Realistic time-sensitive penalties for pending tasks.
• —OpenEnv Compliant: Fully supports openenv validate and standardized logging formats.
• —Production-Ready: Includes Docker support for seamless deployment to platforms like Hugging Face Spaces.

🚀 Getting Started

1. Install Dependencies

python -m pip install -r requirements.txt

2. Run the Server

python -m uvicorn app:app --host 0.0.0.0 --port 8000 --reload

3. Execute Inference & Scoring

python inference.py

🌐 Decision Intelligence

AEOS uses a hybrid decision engine:

• —Rule-based prioritization for SLA-sensitive tasks
• —LLM-based reasoning for adaptive decisions
• —Dynamic workload balancing
• —Anti-loop stability mechanism

This ensures consistent and realistic enterprise simulation.

🧪 Evaluation System

AEOS evaluates agents across three difficulty levels:

• —Triage (Easy): Correct classification of incoming data.
• —Resolution (Medium): Proficiency in responding to entities.
• —Ops Management (Hard): Balancing workloads and mastering SLA deadlines.

🐳 Docker Deployment

Build and run your container locally:

docker build -t aeos-env .
docker run -p 7860:7860 aeos-env

Built with ❤️ for the Advanced Agentic Coding community.