Instruction

Deep Learning Protocol Instruction Wiki Architecture Overview The Deep Learning Protocol is built on a hierarchical, multi-interface architecture consisting of four core components:

1. Abstract Core The foundational base for all protocol operations. Provides core functionality and abstract methods that define the protocol's behavior.

Key Responsibilities:

Define core protocol operations Establish base functionality Provide abstract methods for child implementations Manage state and configuration 2. Aim Interface Defines the purpose and objectives of the protocol. Specifies what goals the system is trying to achieve.

Key Responsibilities:

Define strategic objectives Set goals and targets Guide decision-making processes Establish success criteria 3. Depth Interface Manages the depth and complexity of processing. Controls how deep the analysis or learning goes.

Key Responsibilities:

Control processing depth Manage complexity levels Handle recursive operations Optimize performance based on depth requirements 4. State Interface Tracks and manages the current state of the protocol at any given time.

Key Responsibilities:

Track system state Manage state transitions Maintain state history (optional) Ensure state consistency Implementation Requirements All components must follow these principles:

Hierarchy: AbstractCore → Interface implementations (AimInterface, DepthInterface, StateInterface) Separation of Concerns: Each interface handles one specific aspect Abstraction: Use abstract classes and interfaces for extensibility Cohesion: Components work together seamlessly Flexibility: Easy to extend and modify Architecture Diagram ┌─────────────────────────────────────┐ │ AbstractCore (Base) │ │ - Core functionality │ │ - Base operations │ └──────────────┬──────────────────────┘ │ ┌───────┴───────┬───────────┬─────────┐ │ │ │ │ ▼ ▼ ▼ ▼ ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌──────────┐ │ Aim │ │ Depth │ │ State │ │ Abstract │ │Interface│ │Interface│ │Interface│ │ Core │ └─────────┘ └─────────┘ └─────────┘ └──────────┘ │ │ │ │ └───────┬───────┴───────┬───┴─────────┘ │ │ ┌─────▼──────┬────────▼────┐ │ Implement │ Integrate │ │ Features │ with Core │ └────────────┴─────────────┘ Usage in Program.cs The Program.cs must implement all four components:

// 1. Define AbstractCore base abstract class AbstractCore { }

// 2. Define Interfaces interface IAimInterface { } interface IDepthInterface { } interface IStateInterface { }

// 3. Implement concrete classes class DeepLearningProtocol : AbstractCore, IAimInterface, IDepthInterface, IStateInterface { }

// 4. Use in Program.Main() DeepLearningProtocol protocol = new(); Integration Points With Interactive Menu StateInterface tracks menu state and selections AimInterface defines menu goals (FAQ, settings, etc.) DepthInterface manages menu depth (main menu → submenu → options) With DLP (Data Loss Prevention) StateInterface captures DLP state AimInterface prevents data loss objectives DepthInterface controls scan depth With FAQ System AimInterface provides FAQ goals StateInterface tracks current FAQ question/answer DepthInterface manages FAQ traversal depth Version History v2.0.0.3: Protocol architecture refined v2.0.0.2: Multi-interface support added v2.0.0.1: Core protocol established v2.0.0.0: Initial release See Also Architecture.md - Detailed architecture Getting-Started.md - Setup instructions Program.cs - Implementation