meta-layer.md

Universal Symbolics: Meta-Runtime Architecture

1. Core Runtime Architecture

The Universal Symbolics Meta-Runtime acts as a unified translation layer between various LLM symbolic grammars, allowing developers to use a consistent interface regardless of the underlying model vendor.

graph TD
    A[Developer Interface] --> B[Universal Symbolics Runtime]
    B --> C1[Claude Adapter]
    B --> C2[OpenAI Adapter]
    B --> C3[Qwen Adapter]
    B --> C4[Gemini Adapter]
    B --> C5[DeepSeek Adapter]
    B --> C6[Local LLM Adapter]
    
    C1 --> D1[XML Tags]
    C2 --> D2[Slash Commands]
    C3 --> D3[Slash Commands]
    C4 --> D4[System Prompts]
    C5 --> D5[System Prompts]
    C6 --> D6[Multiple Formats]
    
    B --> E[Telemetry System]
    B --> F[Symbolics Registry]
    
    G[VSCode Extension] --> A
    H[CLI Tool] --> A
    I[REST API] --> A
    J[SDK Libraries] --> A

2. Symbolic Grammar Equivalence Map

The core of the Universal Symbolics Meta-Runtime is a comprehensive mapping between different symbolic grammar formats used by various LLM vendors:

Universal Format	Claude	OpenAI	Qwen	Gemini	DeepSeek	Local LLMs
.p/think{content}	<think>content</think>	Tool choice parameter	/think content	System prompt	System prompt	Model-specific
.p/reflect{target}	<reflect>target</reflect>	Chain-of-thought prompt	System prompt	System prompt	System prompt	Model-specific
.p/tool{name, params}	<tool>name(params)</tool>	/command or Function call	Function call	Function call	Function call	Model-specific
.p/system{directive}	<s>directive</s>	System message	<<SYS>>directive	System instruction	System prompt	Model-specific
.p/fork{paths}	Simulated	Simulated	Simulated	Simulated	Simulated	Simulated
.p/attention{focus}	Simulated	Simulated	Simulated	Simulated	Simulated	Simulated
.p/collapse{trigger}	Simulated	Simulated	Simulated	Simulated	Simulated	Simulated
.p/uncertainty{level}	Simulated	Simulated	Simulated	Simulated	Simulated	Simulated

3. Meta-Operation Types

The Universal Symbolics Meta-Runtime supports several categories of symbolic operations:

3.1 Native Operations

These operations have direct equivalents in at least some vendor implementations:

• Thinking: Explicit reasoning trace
• Tool Use: Function/tool invocation
• System: System-level directives

3.2 Simulated Operations

These operations are emulated through prompt engineering when no native support exists:

• Reflection: Self-examination of reasoning
• Fork: Multiple reasoning paths
• Attention: Focus control
• Collapse: Error handling
• Uncertainty: Confidence expression

3.3 Extended Operations

These operations extend the capabilities of the underlying models:

• Memory: State persistence
• Attribution: Source tracking
• Context: Context window management
• Metacognition: Higher-order reasoning

4. Runtime Implementation

The Universal Symbolics Meta-Runtime implements these symbolic operations through a layered architecture:

4.1 Core Runtime Layer

interface SymbolicRuntime {
  // Native operations
  think(content?: string): Promise<ThinkResult>;
  tool(name: string, params?: Record<string, any>): Promise<ToolResult>;
  system(directive: string): Promise<SystemResult>;
  
  // Simulated operations
  reflect(target: string, depth?: number): Promise<ReflectResult>;
  fork(paths: string[], weights?: number[]): Promise<ForkResult>;
  attention(focus: string, weight?: number): Promise<AttentionResult>;
  collapse(trigger?: string, threshold?: number): Promise<CollapseResult>;
  uncertainty(level?: number, reason?: string): Promise<UncertaintyResult>;
  
  // Extended operations
  memory(key: string, value?: string, operation?: string): Promise<MemoryResult>;
  attribution(source: string, confidence?: number): Promise<AttributionResult>;
  context(window: string, priority?: number): Promise<ContextResult>;
  metacognition(level: number, target?: string): Promise<MetacognitionResult>;
}

4.2 Vendor Adapter Layer

interface VendorAdapter {
  // Vendor identification
  getVendor(): ModelVendor;
  
  // Native operation translation
  translateThinking(content?: string): string;
  translateToolUse(name: string, params?: Record<string, any>): string;
  translateSystem(directive: string): string;
  
  // Simulated operation translation
  translateReflection(target: string, depth?: number): string;
  translateFork(paths: string[], weights?: number[]): string;
  translateAttention(focus: string, weight?: number): string;
  translateCollapse(trigger?: string, threshold?: number): string;
  translateUncertainty(level?: number, reason?: string): string;
  
  // Extended operation translation
  translateMemory(key: string, value?: string, operation?: string): string;
  translateAttribution(source: string, confidence?: number): string;
  translateContext(window: string, priority?: number): string;
  translateMetacognition(level: number, target?: string): string;
}

4.3 Symbolic Registry

interface SymbolicRegistry {
  // Mapping functions
  getUniversalSymbol(vendorSymbol: string, vendor: ModelVendor): string;
  getVendorSymbol(universalSymbol: string, vendor: ModelVendor): string;
  
  // Registration functions
  registerSymbol(universalSymbol: string, vendorSymbol: string, vendor: ModelVendor): void;
  unregisterSymbol(universalSymbol: string, vendor: ModelVendor): void;
  
  // Query functions
  isSupported(universalSymbol: string, vendor: ModelVendor): boolean;
  getSupportedSymbols(vendor: ModelVendor): string[];
  getVendorCapabilities(vendor: ModelVendor): Record<string, boolean>;
}

4.4 Telemetry System

interface SymbolicTelemetry {
  // Tracking functions
  trackOperation(operation: string, vendor: ModelVendor, params?: any): void;
  trackTransformation(source: ModelVendor, target: ModelVendor, success: boolean): void;
  trackError(operation: string, vendor: ModelVendor, error: Error): void;
  
  // Reporting functions
  getOperationStats(): Record<string, number>;
  getVendorStats(): Record<string, number>;
  getTransformationStats(): Record<string, Record<string, number>>;
  getErrorStats(): Record<string, number>;
  
  // Configuration
  enableTelemetry(enabled: boolean): void;
  setAnonymizationLevel(level: 'none' | 'partial' | 'full'): void;
  configureReporting(options: TelemetryOptions): void;
}

5. Symbolic Grammar Translation

The Universal Symbolics Meta-Runtime provides bidirectional translation between different symbolic grammars:

5.1 Translation Process

flowchart TD
    A[Universal Format] -->|Translate To Vendor| B[Vendor-Specific Format]
    B -->|Translate To Universal| A
    
    C[Parse] --> A
    B --> D[Generate]
    
    E[Developer Input] --> C
    D --> F[LLM Input]
    
    G[LLM Output] --> C
    A --> H[Developer Output]

5.2 Translation Examples

Universal to Claude:

// Universal Format
const universalFormat = '.p/think{content: "Let me solve this step by step..."}';

// Translated to Claude
const claudeFormat = '<think>Let me solve this step by step...</think>';

Claude to Universal:

// Claude Format
const claudeFormat = '<tool>search({"query": "quantum computing"})</tool>';

// Translated to Universal
const universalFormat = '.p/tool{name: "search", params: {"query": "quantum computing"}}';

Universal to OpenAI:

// Universal Format
const universalFormat = '.p/system{directive: "You are a helpful assistant."}';

// Translated to OpenAI API
const openaiFormat = {
  messages: [
    {
      role: "system",
      content: "You are a helpful assistant."
    }
  ]
};

6. Developer Tools Interface

The Universal Symbolics Meta-Runtime provides several developer-facing interfaces:

6.1 VSCode Extension

{
  "name": "universal-symbolics-vscode",
  "displayName": "Universal Symbolics",
  "version": "1.0.0",
  "engines": {
    "vscode": "^1.60.0"
  },
  "categories": [
    "Programming Languages",
    "Snippets",
    "Other"
  ],
  "activationEvents": [
    "onLanguage:markdown",
    "onLanguage:json",
    "onLanguage:typescript",
    "onLanguage:python"
  ],
  "main": "./dist/extension.js",
  "contributes": {
    "commands": [
      {
        "command": "universal-symbolics.translateSymbols",
        "title": "Translate Symbols"
      },
      {
        "command": "universal-symbolics.previewResponse",
        "title": "Preview Symbolic Response"
      }
    ],
    "languages": [
      {
        "id": "symbolic",
        "extensions": [".sym", ".symbolic"],
        "aliases": ["Symbolic", "symbolic"]
      }
    ],
    "grammars": [
      {
        "language": "symbolic",
        "scopeName": "source.symbolic",
        "path": "./syntaxes/symbolic.tmLanguage.json"
      }
    ]
  }
}

6.2 CLI Tool

# Installation
npm install -g universal-symbolics-cli

# Usage examples
usym translate --source claude --target openai --file prompt.txt
usym generate --vendor claude --symbol think --content "Let me solve this step by step..."
usym validate --file prompt.sym
usym test --vendor all --symbol think

6.3 REST API

POST /api/v1/transform
Host: api.universal-symbolics.io
Content-Type: application/json
Authorization: Bearer YOUR_API_KEY

{
  "source": "claude",
  "target": "openai",
  "content": "<think>Let me solve this step by step...</think>"
}

POST /api/v1/execute
Host: api.universal-symbolics.io
Content-Type: application/json
Authorization: Bearer YOUR_API_KEY

{
  "vendor": "claude",
  "model": "claude-3-opus-20240229",
  "symbols": {
    "think": {
      "content": "Let me analyze this problem..."
    },
    "tool": {
      "name": "search",
      "params": {
        "query": "quantum computing"
      }
    }
  },
  "prompt": "Explain quantum computing."
}

6.4 SDK Libraries

// TypeScript/JavaScript
import { UniversalSymbolics } from 'universal-symbolics';

const symbolics = new UniversalSymbolics({
  defaultVendor: 'claude',
  apiKey: process.env.CLAUDE_API_KEY
});

const result = await symbolics.think('Let me solve this step by step...');
console.log(result.thinking);
console.log(result.output);

# Python
from universal_symbolics import SymbolicsClient

client = SymbolicsClient(
    default_vendor="claude",
    api_key=os.environ.get("CLAUDE_API_KEY")
)

result = client.think("Let me solve this step by step...")
print(result.thinking)
print(result.output)

7. Implementation Roadmap

The Universal Symbolics Meta-Runtime will be implemented in phases:

Phase 1: Core Runtime Foundation

1. Define universal symbolic schema
2. Implement core runtime layer
3. Create adapters for Claude and OpenAI
4. Develop basic VSCode extension
5. Publish initial NPM package

Phase 2: Expanded Vendor Support

1. Add adapters for Qwen, Gemini, and DeepSeek
2. Implement simulated operations
3. Create Python SDK
4. Develop CLI tool
5. Launch REST API service

Phase 3: Extended Capabilities

1. Implement extended operations
2. Add support for local LLMs
3. Develop telemetry system
4. Create symbolic playground
5. Publish additional language SDKs

Phase 4: Enterprise Integration

1. Implement enterprise features
2. Develop compliance tools
3. Create integration adapters for popular frameworks
4. Launch symbolic marketplace
5. Establish standards organization

8. Meta-Runtime Architecture Principles

The Universal Symbolics Meta-Runtime is built on several key architectural principles:

1. Universal Interface: Provide a consistent interface across all LLM vendors
2. Bidirectional Translation: Support translation between any vendor formats
3. Extensibility: Allow for new vendors and symbolic operations to be added
4. Compatibility: Work with existing tools and frameworks
5. Telemetry: Collect anonymous usage data to guide development
6. Standards: Establish standards for symbolic operations
7. Developer Experience: Prioritize ease of use for developers
8. Performance: Minimize overhead and maximize throughput

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Universal Symbolics | Unifying the symbolic layer across AI models