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# Universal Symbolics: Meta-Runtime Architecture
<p align="center">
<img src="https://via.placeholder.com/800x200/0d1117/ffffff?text=Universal+Symbolics+Meta-Runtime" alt="Universal Symbolics Meta-Runtime"/>
</p>
## 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.
```mermaid
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
```typescript
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
```typescript
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
```typescript
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
```typescript
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
```mermaid
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:**
```typescript
// 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:**
```typescript
// 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:**
```typescript
// 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
```json
{
"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
```bash
# 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
```http
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>"
}
```
```http
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
// 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
# 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
---
<p align="center">
<strong>Universal Symbolics</strong> | Unifying the symbolic layer across AI models
</p>
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