| # Universal Symbolics: Meta-Runtime Architecture |
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| <p align="center"> |
| <img src="https://via.placeholder.com/800x200/0d1117/ffffff?text=Universal+Symbolics+Meta-Runtime" alt="Universal Symbolics Meta-Runtime"/> |
| </p> |
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| ## 1. Core Runtime Architecture |
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| 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. |
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| ```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 |
| ``` |
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| ## 2. Symbolic Grammar Equivalence Map |
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| The core of the Universal Symbolics Meta-Runtime is a comprehensive mapping between different symbolic grammar formats used by various LLM vendors: |
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| | 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 | |
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| ## 3. Meta-Operation Types |
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| The Universal Symbolics Meta-Runtime supports several categories of symbolic operations: |
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| ### 3.1 Native Operations |
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| These operations have direct equivalents in at least some vendor implementations: |
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| - **Thinking**: Explicit reasoning trace |
| - **Tool Use**: Function/tool invocation |
| - **System**: System-level directives |
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| ### 3.2 Simulated Operations |
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| These operations are emulated through prompt engineering when no native support exists: |
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| - **Reflection**: Self-examination of reasoning |
| - **Fork**: Multiple reasoning paths |
| - **Attention**: Focus control |
| - **Collapse**: Error handling |
| - **Uncertainty**: Confidence expression |
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| ### 3.3 Extended Operations |
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| These operations extend the capabilities of the underlying models: |
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| - **Memory**: State persistence |
| - **Attribution**: Source tracking |
| - **Context**: Context window management |
| - **Metacognition**: Higher-order reasoning |
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| ## 4. Runtime Implementation |
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| The Universal Symbolics Meta-Runtime implements these symbolic operations through a layered architecture: |
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| ### 4.1 Core Runtime Layer |
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| ```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>; |
| } |
| ``` |
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| ### 4.2 Vendor Adapter Layer |
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| ```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; |
| } |
| ``` |
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| ### 4.3 Symbolic Registry |
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| ```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>; |
| } |
| ``` |
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| ### 4.4 Telemetry System |
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| ```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; |
| } |
| ``` |
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| ## 5. Symbolic Grammar Translation |
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| The Universal Symbolics Meta-Runtime provides bidirectional translation between different symbolic grammars: |
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| ### 5.1 Translation Process |
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| ```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] |
| ``` |
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| ### 5.2 Translation Examples |
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| **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>'; |
| ``` |
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| **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"}}'; |
| ``` |
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| **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." |
| } |
| ] |
| }; |
| ``` |
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| ## 6. Developer Tools Interface |
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| The Universal Symbolics Meta-Runtime provides several developer-facing interfaces: |
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| ### 6.1 VSCode Extension |
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| ```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" |
| } |
| ] |
| } |
| } |
| ``` |
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| ### 6.2 CLI Tool |
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| ```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 |
| ``` |
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| ### 6.3 REST API |
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| ```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>" |
| } |
| ``` |
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| ```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." |
| } |
| ``` |
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| ### 6.4 SDK Libraries |
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| ```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); |
| ``` |
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| ```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) |
| ``` |
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| ## 7. Implementation Roadmap |
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| The Universal Symbolics Meta-Runtime will be implemented in phases: |
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| ### Phase 1: Core Runtime Foundation |
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| 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 |
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| ### Phase 2: Expanded Vendor Support |
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| 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 |
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| ### Phase 3: Extended Capabilities |
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| 1. Implement extended operations |
| 2. Add support for local LLMs |
| 3. Develop telemetry system |
| 4. Create symbolic playground |
| 5. Publish additional language SDKs |
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| ### Phase 4: Enterprise Integration |
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| 1. Implement enterprise features |
| 2. Develop compliance tools |
| 3. Create integration adapters for popular frameworks |
| 4. Launch symbolic marketplace |
| 5. Establish standards organization |
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| ## 8. Meta-Runtime Architecture Principles |
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| The Universal Symbolics Meta-Runtime is built on several key architectural principles: |
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| 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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| --- |
|
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| <p align="center"> |
| <strong>Universal Symbolics</strong> | Unifying the symbolic layer across AI models |
| </p> |
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