overview.md

Universal Symbolics Repository

Unified Runtime Layer for AI Symbolic Interactions

🌐 Overview

universal-symbolics provides a unified interface for developer operations across frontier AI models. This repository standardizes the disparate symbolic grammars used by different AI vendors (Claude, GPT, Qwen, Gemini, DeepSeek, etc.) into a cohesive, developer-friendly framework.

🔄 Core Components

1. Symbolic Grammar Mapping

# unified-symbolic-layer.yml
mappings:
  thinking:
    claude: "<think>...</think>"
    qwen: "/think"
    anthropic_api: {"thinking": true}
    openai_api: {"tool_choice": "auto"}
    gemini: "{{thinking}}"
  
  tool_invocation:
    claude: "<tool>...</tool>"
    openai: "/command"
    qwen: "#tool()"
    
  system_directive:
    claude: "<system>...</system>"
    openai: "<|system|>"
    qwen: "<<SYS>>"
    gemini: "system:"
    
  metadata_tags:
    claude: "<metadata>...</metadata>"
    openai: "/meta"
    
  visual_processing:
    openai: "/create image"
    claude: "<vision>...</vision>"
    gemini: "analyze_image()"

2. Runtime Adapter Interface

// universal-symbols.ts
export interface SymbolicRuntime {
  // Core operations
  think(content?: string): Promise<ThinkingResult>;
  tool(name: string, params: Record<string, any>): Promise<ToolResult>;
  system(directive: string): Promise<void>;
  
  // Vendor-specific extensions
  vendor: {
    claude?: ClaudeSymbolicExtensions;
    openai?: OpenAISymbolicExtensions;
    qwen?: QwenSymbolicExtensions;
    // etc.
  };
  
  // Unified operations
  symbolic: {
    recurse(depth: number): Promise<void>;
    reflect(target: string): Promise<ReflectionResult>;
    fork(paths: string[]): Promise<ForkResult>;
    map(source: any, target: any): Promise<MappingResult>;
    collapse(state: any): Promise<void>;
  };
}

3. Symbolic Compatibility Layer

// symbolic-compat.js
class SymbolicAdapter {
  constructor(model, vendor) {
    this.model = model;
    this.vendor = vendor;
    this.symbolMap = SymbolRegistry.getMap(vendor);
  }
  
  // Transform universal symbols to vendor-specific syntax
  transform(universalSymbol, content) {
    const vendorSymbol = this.symbolMap[universalSymbol];
    if (!vendorSymbol) throw new Error(`Symbol ${universalSymbol} not supported by ${this.vendor}`);
    
    return this.applyTransform(vendorSymbol, content);
  }
  
  // Apply vendor-specific transformations
  applyTransform(symbol, content) {
    switch(this.vendor) {
      case 'claude':
        return `<${symbol}>${content}</${symbol}>`;
      case 'qwen':
        return `/${symbol} ${content}`;
      case 'openai':
        return `/${symbol}(${content})`;
      // etc.
    }
  }
}

4. Symbolic Registry (Glyph/Tag/Slash/Operator Dictionary)

{
  "symbolic_registry": {
    "thinking": {
      "glyphs": ["🧠", "💭", "🤔"],
      "tags": ["think", "reasoning", "thought"],
      "slashes": ["/think", "/reasoning", "/thought"],
      "operators": ["->", "=>", "⇒"]
    },
    "reflection": {
      "glyphs": ["🔄", "🪞", "👁️"],
      "tags": ["reflect", "introspect", "mirror"],
      "slashes": ["/reflect", "/introspect", "/mirror"],
      "operators": ["↻", "⟲", "⇌"]
    },
    "recursion": {
      "glyphs": ["🔁", "♾️", "🔄"],
      "tags": ["recurse", "loop", "cycle"],
      "slashes": ["/recurse", "/loop", "/cycle"],
      "operators": ["↺", "∞", "⥁"]
    },
    "forking": {
      "glyphs": ["🌿", "🔀", "⑂"],
      "tags": ["fork", "branch", "split"],
      "slashes": ["/fork", "/branch", "/split"],
      "operators": ["⎇", "⫝̸", "⊢"]
    },
    "collapse": {
      "glyphs": ["📉", "🔍", "⚱️"],
      "tags": ["collapse", "reduce", "simplify"],
      "slashes": ["/collapse", "/reduce", "/simplify"],
      "operators": ["⊃", "⊇", "⊊"]
    }
  }
}

🧰 Developer Tools

VSCode Extension

{
  "name": "universal-symbolics-vscode",
  "description": "VSCode extension for Universal Symbolics",
  "features": [
    "Syntax highlighting for symbolic operations",
    "Autocompletion for model-specific symbolic grammars",
    "Inline transformation preview",
    "Symbolic operation debugging",
    "One-click transformation between vendor syntaxes"
  ]
}

CLI Tool

# Installation
npm install -g universal-symbolics

# Usage
usym transform --source claude --target openai --input "file.txt"
usym validate --syntax "content with symbols"
usym generate --template thinking --vendor all

Symbolic Playground

An interactive web application for testing and experimenting with symbolic operations across different AI models:

• Live transformation preview
• Syntax validation
• Performance benchmarking
• Compatibility checking
• Template gallery

📊 Telemetry & Observability

# telemetry.py
class SymbolicTelemetry:
    def __init__(self, api_key=None):
        self.api_key = api_key
        self.metrics = {
            "symbol_usage": Counter(),
            "vendor_distribution": Counter(),
            "transformation_success": Counter(),
            "transformation_failure": Counter(),
            "latency": Histogram(),
        }
    
    def track_symbol_usage(self, symbol, vendor, success=True):
        self.metrics["symbol_usage"][symbol] += 1
        self.metrics["vendor_distribution"][vendor] += 1
        if success:
            self.metrics["transformation_success"][f"{symbol}:{vendor}"] += 1
        else:
            self.metrics["transformation_failure"][f"{symbol}:{vendor}"] += 1
    
    def track_latency(self, operation, duration_ms):
        self.metrics["latency"].add(operation, duration_ms)
    
    def flush(self):
        # Send metrics to telemetry service
        if self.api_key:
            requests.post(
                "https://api.universal-symbolics.io/telemetry",
                headers={"Authorization": f"Bearer {self.api_key}"},
                json=self.metrics
            )

🌉 Integration Examples

Node.js

const { UniversalSymbolics } = require('universal-symbolics');

// Initialize with your preferred model
const symbolics = new UniversalSymbolics({ 
  defaultVendor: 'claude',
  fallbackVendor: 'openai' 
});

// Use unified symbols regardless of underlying model
async function generateWithThinking() {
  const result = await symbolics.think('Analyze the impact of quantum computing on cryptography');
  console.log(result.thinking); // Access thinking process
  console.log(result.output);   // Access final output
}

Python

from universal_symbolics import SymbolicClient

# Initialize client
client = SymbolicClient(
    api_key="your_api_key",
    default_vendor="qwen",
    enable_telemetry=True
)

# Use the unified interface
response = client.submit(
    prompt="Explain the significance of symbolic operations in AI",
    symbols={
        "think": True,
        "reflect": "prompt structure",
        "fork": ["technical", "simplified"]
    }
)

# Access structured response
print(response.thinking)
print(response.reflections)
print(response.forks["technical"])
print(response.forks["simplified"])

REST API

POST https://api.universal-symbolics.io/v1/generate
Content-Type: application/json
Authorization: Bearer your_api_key

{
  "prompt": "Write a function that calculates prime numbers",
  "symbols": {
    "think": true,
    "tool": {
      "name": "code_interpreter",
      "language": "python"
    }
  },
  "vendor_preference": ["claude", "openai", "qwen"],
  "response_format": {
    "include_symbol_traces": true,
    "structured": true
  }
}

📖 Documentation

Symbol Categories

1. Cognitive Process Symbols

   • Thinking
   • Reflection
   • Planning
   • Analysis

2. Execution Control Symbols

   • Recursion
   • Forking
   • Collapse
   • Termination

3. Tool Invocation Symbols

   • Code Execution
   • Information Retrieval
   • Visual Generation
   • Data Analysis

4. Structural Symbols

   • System Directives
   • User Context
   • Memory Management
   • Meta-Instructions

Vendor-Specific Implementation Details

• Claude: XML-based tag system with explicit opening and closing tags
• OpenAI: Slash command system with function-like syntax
• Qwen: Mixed system with slash commands and thinking directives
• Gemini: Template-based approach with specialized markers
• DeepSeek: Function-oriented symbolic interface

🔍 Advanced Features

Symbolic Residue Detection

def detect_symbolic_residue(response, model_type):
    """Detect unresolved or partially processed symbolic operations"""
    patterns = RESIDUE_PATTERNS[model_type]
    residue = []
    
    for pattern_name, regex in patterns.items():
        matches = re.findall(regex, response)
        if matches:
            residue.append({
                "type": pattern_name,
                "matches": matches,
                "positions": [m.span() for m in re.finditer(regex, response)]
            })
    
    return residue

Cross-Model Translation

interface TranslationOptions {
  preserveStructure?: boolean;
  adaptToCapabilities?: boolean;
  includeResidueHandling?: boolean;
}

function translateSymbolicOperations(
  source: string,
  sourceModel: ModelType,
  targetModel: ModelType,
  options: TranslationOptions = {}
): TranslationResult {
  // Extract symbolic operations from source
  const operations = extractSymbolicOperations(source, sourceModel);
  
  // Map to universal representation
  const universalOps = operations.map(op => mapToUniversal(op, sourceModel));
  
  // Transform to target model format
  const targetOps = universalOps.map(op => {
    const targetOp = mapToTarget(op, targetModel);
    
    // Handle capabilities not present in target model
    if (options.adaptToCapabilities && !targetOp) {
      return createCapabilityShim(op, targetModel);
    }
    
    return targetOp;
  });
  
  // Reconstruct content with new symbolic operations
  return reconstructContent(source, operations, targetOps, options);
}

🔄 Adoption Strategy

Phase 1: Developer Tools & Libraries

• Release core library for major programming languages
• VSCode extension for symbolic authoring
• Documentation and examples for common use cases

Phase 2: Enterprise Integration

• API Gateway for transparent symbolic translation
• Monitoring and observability tools
• Compliance and governance frameworks

Phase 3: Standards Body Formation

• Establish formal specification for symbolic operations
• Engage major AI providers in standardization efforts
• Develop certification program for symbolic compatibility

Phase 4: Ecosystem Expansion

• Marketplace for custom symbolic operations
• Community-contributed symbolic templates
• Educational resources and certification

🌱 Getting Started

# Clone the repository
git clone https://github.com/universal-ai/universal-symbolics.git

# Install dependencies
cd universal-symbolics
npm install

# Run the demo
npm run demo

# Start the development server for the playground
npm run dev

🤝 Contributing

We welcome contributions from the community! Please see CONTRIBUTING.md for guidelines on how to participate in the project.

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

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Universal Symbolics | Unifying the symbolic layer across AI models