ACIP (Adaptive Contextual Intelligence Protocol)

Overview

The Adaptive Contextual Intelligence Protocol (ACIP) is a next-generation AI application protocol designed to overcome the limitations of existing protocols like MCP (Model Context Protocol). ACIP aims to provide a more flexible, secure, and efficient framework for AI applications with a focus on differentiation and rapid development.

ACIP introduces a decentralized architecture with blockchain integration, modular design, native edge computing support, federated learning, and privacy computing capabilities. It targets a wide range of applications including vertical industries (healthcare, finance, manufacturing), edge AI applications, and privacy-sensitive use cases.

Key Features

• Decentralized Architecture: Leverage blockchain technology for transparent, secure, and trustworthy protocol operation
• Modular & Pluggable Design: Flexible component combination to meet diverse requirements
• Edge Computing Support: Optimized for resource-constrained environments
• Federated Learning Integration: Privacy-preserving model training across devices/institutions
• Multi-Protocol Compatibility: Support for REST API, GraphQL, gRPC and compatibility with MCP
• Adaptive Context Management: Dynamic adjustment of context window size based on task complexity
• Intelligent Model Scheduling: Automatic selection of optimal AI models based on requirements
• Security and Authentication: Decentralized identity (DID) based secure authentication

Project Structure

ACIP/
├── core/                           # Core protocol components
│   ├── src/                        # Core source code
│   ├── tests/                      # Tests for core functionality
│   └── README.md                   # Core module documentation
├── modules/                        # Modular components of the protocol
│   ├── context_management/         # Adaptive context management
│   ├── data_access/                # Dynamic data access and governance
│   ├── security_authentication/    # Secure identity and authorization
│   ├── model_invocation/           # Intelligent model scheduling
│   └── payment_settlement/         # Incentive mechanisms and value distribution
├── integrations/                   # Integration with external systems
│   ├── rest_api/                   # REST API integration
│   └── graphql/                    # GraphQL integration
├── docs/                           # Documentation
│   ├── installation.md             # Installation guide
│   ├── usage.md                    # Usage documentation
│   └── architecture.md             # Architectural documentation
├── examples/                       # Example applications
├── tests/                          # System and integration tests
├── scripts/                        # Utility scripts
├── CONTRIBUTING.md                 # Contribution guidelines
├── GOVERNANCE.md                   # Project governance
└── LICENSE                         # License information

Getting Started

See installation.md for detailed setup instructions.

Use Cases

ACIP is designed for a variety of AI applications, including:

• Healthcare: Privacy-preserving medical data sharing and model training
• Finance: Secure and trusted financial risk control systems
• Smart Manufacturing: Edge-computing driven monitoring and optimization
• Smart Homes: Local voice control and device interconnection
• Personalized Recommendations: Privacy-protecting recommendation systems

Community and Governance

ACIP follows an open governance model with community-driven development. The protocol specifications, standards, code, and documentation are all open source and welcome community contributions.

License

This project is licensed under LICENSE.