This project is a self-contained system that emulates an LLM operating autonomously: it continuously generates prompts for itself, plans required sub-tasks, executes them, and iterates.

The Autonomous LLM Simulator is designed to simulate an autonomous Large Language Model (LLM) agent. Its core capabilities include:

• Self-Prompting: Generates its own prompts based on an initial objective.
• Task Planning: Creates a plan of tasks to achieve the goal of a prompt.
• Sandboxed Execution: Executes tasks in a simulated environment.
• Iterative Loop: Observes results and continues to self-prompt and execute until a completion condition is met.
• Safe & Observable: Ensures safe execution and provides clear, structured logging.

This project is currently in a mock phase, using a MockLLMClient to simulate LLM interactions without needing an actual API key.

To get a local copy up and running, follow these simple steps.

• Python 3.10+

1. Clone the repo

   git clone https://github.com/your-org/autonomous-llm-simulator.git
   cd autonomous-llm-simulator

2. Create and activate a virtual environment

   python -m venv venv
   source venv/bin/activate

3. Install dependencies

   pip install -r requirements.txt

   (Note: Currently, no external dependencies are required for the mock version.)

The simulator is run from the command line. You must provide a high-level objective for the agent to accomplish.

python -m src.cli.run_simulator "Develop a plan to learn a new programming language"

• objective (required): The high-level objective for the simulator.
• --max-iterations (optional): The maximum number of tasks to execute. Default: 5.
• --llm-provider (optional): The LLM provider to use. Default: mock.

To run the test suite, use pytest:

pytest

The project is organized as follows:

.
├── docs/                  # Documentation and architectural diagrams
├── src/                   # Source code
│   ├── cli/               # Command-line interface
│   ├── error_handling/    # Global error handling
│   ├── llms/              # LLM client integrations (currently mock)
│   ├── models/            # Database schemas
│   ├── workflow/          # Core simulation logic
│   └── logger.py          # Centralized logging configuration
├── tests/                 # Unit and integration tests
├── requirements.txt       # Python dependencies
└── README.md              # This file

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Distributed under the MIT License. See LICENSE for more information.

Project Link: https://github.com/your-org/autonomous-llm-simulator