Research Repository

A comprehensive collection of research, experiments, and production-ready implementations in AI/ML agents, decentralized computing, blockchain integration, and GPU performance optimization.

🎯 Research Focus Areas

• AI/ML Agents & Autonomous Systems: Research and implementation of autonomous agent architectures, multi-agent collaboration, and learning systems.
• Decentralized Computing & Blockchain: Exploration of blockchain integration, decentralized storage (IPFS), and decentralized identity.
• GPU Performance & LLM Optimization: Analysis of LLM performance, GPU profitability, and optimization techniques.

📁 Project Structure

research/
├── docs/
│   └── research/
│       ├── AI_Billing_Agent_Pipeline.md
│       ├── Future_of_AI_Billing_Agent.md
│       ├── Manta_Modular_RP_Model_Family.md
│       └── Research_Roadmap.md
├── sample_code/
│   ├── blockchain_and_storage/
│   │   ├── blockchain/
│   │   ├── mcp_nebula_block/
│   │   └── nebula_block_storage/
│   ├── llm_infra/
│   │   └── llm_perfomance/
│   └── billing_and_webhooks/
│       ├── team_billing/
│       └── webhook/
├── LICENSE
└── README.md

🚀 Quick Start

Prerequisites

• Python 3.8+
• Git
• Docker (optional, for containerized deployments)

Installation

1. Clone the repository:

   git clone https://github.com/flyworker/research.git
   cd research

2. Set up Python environment:

   python -m venv venv
   source venv/bin/activate  # On Unix/macOS
   # or
   .\venv\Scripts\activate   # On Windows

3. Install project dependencies:

   # Install dependencies for specific components as needed
   pip install -r sample_code/<category>/<component>/requirements.txt

Run a component

• LLM Performance Calculator:

  cd sample_code/llm_infra/llm_perfomance
  pip install -r requirements.txt
  python gpu_profit_calculator.py  # http://localhost:8001

• Team Billing API:

  cd sample_code/billing_and_webhooks/team_billing
  pip install -r requirements.txt
  python server.py  # http://localhost:8000

📚 Documentation

• Research Documents: The docs/research directory contains detailed research documents on various topics.
• Implementation Guides: Each sample code project in the sample_code directory has its own README.md file with detailed instructions.

🤝 Contributing

We welcome contributions from researchers, developers, and enthusiasts! Feel free to open issues or submit pull requests.

📄 License

This project is licensed under the terms included in the LICENSE file.