Structure

• server/: Orchestrator, resource manager, and result aggregator (FastAPI).
• client/: "Weaver" client application that executes tasks.
• task_submitter/: "Requester" script to submit tasks to the server.

How to Run

1. Install dependencies for each module: Open your terminal and navigate to the project's root directory.

   pip install -r server/requirements.txt
   pip install -r client/requirements.txt
   pip install -r task_submitter/requirements.txt

2. Start the Server: Open a terminal, navigate to the server/ directory, and run:

   python main.py
   # or for development: uvicorn main:app --reload

   The server will listen on http://localhost:8000.

3. Start one or more Clients ("Weavers"): Open a new terminal (or multiple terminals) for each client. Navigate to the client/ directory and run:

   python client.py

   Each client will register with the server and start polling for work. Client IDs are generated automatically.

4. Submit a Task using the "Requester" script: Open another terminal, navigate to the task_submitter/ directory, and run:

   python submit_task.py

   This script will submit a sample task to the server. You should see logs in the server and client terminals as the task is broken down into work units, distributed, and executed. The submit_task.py script will periodically poll for the task's status.

What's Next? (Directions for Development)

This skeleton is just a starting point. A real system would require:

• Database: Replace in-memory dictionaries with a persistent database (e.g., PostgreSQL, MongoDB).
• Real Sandbox: Use Docker or another containerization technology for secure code execution on clients.
• Actual ML Tasks: Integrate PyTorch/TensorFlow for model training.
• Robustness: Error handling, retries, fault tolerance.
• Security: Authentication, authorization, encryption, protection against malicious code.
• Scalability: Optimization for a large number of clients and tasks.
• Advanced Orchestrator: Smarter task distribution, considering client GPU capabilities.
• Incentive System: Tokenomics, reputation.
• User Interface: GUI for clients and a web portal for requesters.
• Asynchronous Communication: Use WebSockets or message queues (Kafka, RabbitMQ) for more efficient communication instead of constant polling.