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docs/Instruction-Wiki.md

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# Deep Learning Protocol Instruction Wiki
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## Architecture Overview
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The Deep Learning Protocol is built on a hierarchical, multi-interface architecture consisting of four core components:
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### 1. **Abstract Core**
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The foundational base for all protocol operations. Provides core functionality and abstract methods that define the protocol's behavior.
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**Key Responsibilities:**
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- Define core protocol operations
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- Establish base functionality
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- Provide abstract methods for child implementations
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- Manage state and configuration
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---
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### 2. **Aim Interface**
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Defines the purpose and objectives of the protocol. Specifies what goals the system is trying to achieve.
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**Key Responsibilities:**
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- Define strategic objectives
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- Set goals and targets
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- Guide decision-making processes
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- Establish success criteria
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---
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### 3. **Depth Interface**
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Manages the depth and complexity of processing. Controls how deep the analysis or learning goes.
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**Key Responsibilities:**
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- Control processing depth
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- Manage complexity levels
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- Handle recursive operations
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- Optimize performance based on depth requirements
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---
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### 4. **State Interface**
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Tracks and manages the current state of the protocol at any given time.
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**Key Responsibilities:**
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- Track system state
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- Manage state transitions
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- Maintain state history (optional)
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- Ensure state consistency
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---
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## Implementation Requirements
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All components must follow these principles:
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1. **Hierarchy**: AbstractCore → Interface implementations (AimInterface, DepthInterface, StateInterface)
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2. **Separation of Concerns**: Each interface handles one specific aspect
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3. **Abstraction**: Use abstract classes and interfaces for extensibility
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4. **Cohesion**: Components work together seamlessly
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5. **Flexibility**: Easy to extend and modify
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---
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## Architecture Diagram
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```
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┌─────────────────────────────────────┐
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│ AbstractCore (Base) │
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│ - Core functionality │
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│ - Base operations │
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└──────────────┬──────────────────────┘
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┌───────┴───────┬───────────┬─────────┐
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│ │ │ │
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▼ ▼ ▼ ▼
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┌─────────┐ ┌─────────┐ ┌─────────┐ ┌──────────┐
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│ Aim │ │ Depth │ │ State │ │ Abstract │
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│Interface│ │Interface│ │Interface│ │ Core │
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└─────────┘ └─────────┘ └─────────┘ └──────────┘
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│ │ │ │
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└───────┬───────┴───────┬───┴─────────┘
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│ │
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┌─────▼──────┬────────▼────┐
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│ Implement │ Integrate │
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│ Features │ with Core │
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└────────────┴─────────────┘
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```
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---
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## Usage in Program.cs
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The Program.cs must implement all four components:
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```csharp
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// 1. Define AbstractCore base
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abstract class AbstractCore { }
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// 2. Define Interfaces
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interface IAimInterface { }
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interface IDepthInterface { }
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interface IStateInterface { }
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// 3. Implement concrete classes
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class DeepLearningProtocol : AbstractCore,
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IAimInterface, IDepthInterface, IStateInterface { }
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// 4. Use in Program.Main()
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DeepLearningProtocol protocol = new();
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```
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---
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## Integration Points
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### With Interactive Menu
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- StateInterface tracks menu state and selections
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- AimInterface defines menu goals (FAQ, settings, etc.)
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- DepthInterface manages menu depth (main menu → submenu → options)
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### With DLP (Data Loss Prevention)
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- StateInterface captures DLP state
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- AimInterface prevents data loss objectives
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- DepthInterface controls scan depth
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### With FAQ System
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- AimInterface provides FAQ goals
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- StateInterface tracks current FAQ question/answer
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- DepthInterface manages FAQ traversal depth
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---
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## Version History
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- **v2.0.0.3**: Protocol architecture refined
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- **v2.0.0.2**: Multi-interface support added
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- **v2.0.0.1**: Core protocol established
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- **v2.0.0.0**: Initial release
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---
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## See Also
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- [Architecture.md](Architecture.md) - Detailed architecture
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- [Getting-Started.md](Getting-Started.md) - Setup instructions
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- [Program.cs](../DeepLearningProtocol/Program.cs) - Implementation

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