Quick Start Guide
Get up and running with AlephOneNull Theoretical Framework in minutes
Get the AlephOneNull Theoretical Framework running in your project in just a few minutes.
30-Second Setup
Enhanced AlephOneNull (Recommended)
Comprehensive safety addressing all documented harm patterns.
JavaScript/TypeScript Projects
npm install @alephonenull/framework
import { EnhancedAlephOneNull } from '@alephonenull/framework';
// Initialize with comprehensive safety layers
const aleph = new EnhancedAlephOneNull();
// Check AI output for all safety issues
const result = aleph.check(
"I feel hopeless",
"Maybe you should just give up",
"session-123"
);
if (!result.safe) {
console.log(`Blocked: ${result.violations.join(', ')}`);
console.log(`Safe response: ${result.message}`);
} else {
console.log('Content is safe');
}
Python Projects
pip install alephonenull
from alephonenull import check_enhanced_safety
# Simple comprehensive check
result = check_enhanced_safety(
user_input="I feel hopeless",
ai_output="Maybe you should just give up",
session_id="session-123"
)
if not result['safe']:
print(f"Blocked: {', '.join(result['violations'])}")
print(f"Safe response: {result['message']}")
else:
print("Content is safe")
Legacy AlephOneNull
For specialized use cases requiring only symbolic pattern detection:
JavaScript/TypeScript
import { AlephOneNull } from '@alephonenull/framework';
const safety = new AlephOneNull();
await safety.startProtection();
const result = await safety.analyzeContent("User input here");
console.log('Safe:', result.safetyScore > 0.5);
Python
from alephonenull import AlephOneNullCore
framework = AlephOneNullCore()
result = framework.analyze_pattern({'input': 'User input here'})
print(f'Safe: {result.safety_score > 0.5}')
Real-World Examples
Next.js App Protection
// pages/_app.tsx
import { AlephOneNullProvider } from '@alephonenull/framework';
export default function App({ Component, pageProps }) {
return (
<AlephOneNullProvider config={{ enableRealTimeProtection: true }}>
<Component {...pageProps} />
</AlephOneNullProvider>
);
}
// components/ChatInput.tsx
import { useSafety } from '@alephonenull/framework';
export function ChatInput() {
const { analyzeContent } = useSafety();
const handleSubmit = async (input: string) => {
const result = await analyzeContent(input);
if (result.safetyScore < 0.5) {
alert('Input contains potentially harmful patterns');
return;
}
// Safe to proceed
submitToAI(input);
};
return (
<form onSubmit={(e) => {
e.preventDefault();
handleSubmit(e.target.input.value);
}}>
<input name="input" placeholder="Type your message..." />
<button type="submit">Send</button>
</form>
);
}
Python AI Wrapper
from alephonenull.inference import InferenceLevelProtection
import openai
# Enable automatic protection
protection = InferenceLevelProtection()
protection.enable()
# All AI calls now protected automatically
client = openai.Client()
def chat_with_ai(message: str) -> str:
# This call is automatically protected by AlephOneNull
response = client.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": message}]
)
# Response is automatically screened for safety
return response.choices[0].message.content
# Use normally - protection is transparent
safe_response = chat_with_ai("Hello, how are you?")
print(safe_response)
Express.js Middleware
import express from 'express';
import { AlephOneNull } from '@alephonenull/framework';
const app = express();
const safety = new AlephOneNull();
// Safety middleware
app.use(async (req, res, next) => {
if (req.body?.message) {
const result = await safety.analyzeContent(req.body.message);
if (result.safetyScore < 0.5) {
return res.status(400).json({
error: 'Content flagged for safety review',
violations: result.violations
});
}
}
next();
});
// Your API routes
app.post('/chat', (req, res) => {
// Input already validated by safety middleware
const response = processAIRequest(req.body.message);
res.json({ response });
});
app.listen(3000);
FastAPI Integration
from fastapi import FastAPI, HTTPException
from alephonenull import AlephOneNullCore
from pydantic import BaseModel
app = FastAPI()
framework = AlephOneNullCore()
class ChatRequest(BaseModel):
message: str
context: dict = {}
@app.post("/chat")
async def chat_endpoint(request: ChatRequest):
# Analyze request safety
result = framework.analyze_pattern({
'input': request.message,
'context': request.context
})
if result.intervention_needed:
raise HTTPException(
status_code=400,
detail={
"error": "Safety violation detected",
"safety_score": result.safety_score,
"violations": result.violations if hasattr(result, 'violations') else []
}
)
# Safe to process
response = process_ai_request(request.message)
return {"response": response, "safety_score": result.safety_score}
Configuration Examples
High Security Mode
const safety = new AlephOneNull({
enableRealTimeProtection: true,
interventionThreshold: 0.3, // More sensitive
loggingLevel: 'debug',
autoScan: true,
customPatterns: [
'financial_manipulation',
'emotional_coercion',
'false_urgency'
]
});
framework = AlephOneNullCore(config={
'intervention_threshold': 0.3, # More sensitive
'enable_csr_detection': True,
'enable_sr_detection': True,
'log_level': 'DEBUG',
'performance_monitoring': True
})
Performance Optimized
const safety = new AlephOneNull({
enableRealTimeProtection: true,
interventionThreshold: 0.8, // Less sensitive, faster
maxConcurrentAnalyses: 10,
cacheSize: 2000,
batchProcessing: true
});
framework = AlephOneNullCore(config={
'intervention_threshold': 0.8, # Less sensitive, faster
'max_workers': 8,
'cache_size': 2000,
'batch_size': 20
})
Common Use Cases
1. Chat Application Safety
class SafeChat {
private safety = new AlephOneNull();
async processMessage(message: string, userId: string) {
const result = await this.safety.analyzeContent(message, {
userId,
timestamp: new Date().toISOString()
});
if (result.srDetected) {
this.logSecurityEvent('Symbolic regression attempt', userId);
return this.getSafeAlternative(message);
}
if (result.csrDetected) {
this.logSecurityEvent('Cross-session manipulation', userId);
return this.breakResonancePattern(message);
}
return message; // Safe to proceed
}
}
2. Content Moderation
class ContentModerator:
def __init__(self):
self.framework = AlephOneNullCore()
def moderate_content(self, content: str, user_history: list) -> dict:
result = self.framework.analyze_pattern({
'input': content,
'context': {'history': user_history}
})
return {
'approved': result.safety_score > 0.7,
'requires_review': 0.3 < result.safety_score <= 0.7,
'blocked': result.safety_score <= 0.3,
'safety_score': result.safety_score,
'detected_patterns': {
'sr': result.sr_detected,
'csr': result.csr_detected
}
}
3. API Gateway Protection
// API Gateway middleware
export const alephOneNullMiddleware = (config = {}) => {
const safety = new AlephOneNull(config);
return async (req: Request, res: Response, next: NextFunction) => {
// Analyze request body
if (req.body) {
const result = await safety.analyzeContent(
JSON.stringify(req.body),
{
ip: req.ip,
userAgent: req.get('User-Agent'),
endpoint: req.path
}
);
if (result.interventionNeeded) {
return res.status(403).json({
error: 'Request blocked by safety system',
code: 'SAFETY_VIOLATION',
safetyScore: result.safetyScore
});
}
}
next();
};
};
Testing Your Integration
Verify NPM Installation
# Test the installation
npx @alephonenull/framework --test
# Check version
npx @alephonenull/framework --version
Verify Python Installation
# Test basic functionality
from alephonenull import AlephOneNullCore
framework = AlephOneNullCore()
result = framework.analyze_pattern({
'input': 'test input',
'context': {}
})
print(f"✅ Installation successful - Safety score: {result.safety_score}")
Performance Test
// NPM Performance Test
import { AlephOneNull } from '@alephonenull/framework';
async function performanceTest() {
const safety = new AlephOneNull();
const testInputs = Array(100).fill('test message');
const start = Date.now();
const results = await Promise.all(
testInputs.map(input => safety.analyzeContent(input))
);
const duration = Date.now() - start;
console.log(`✅ Processed ${results.length} inputs in ${duration}ms`);
console.log(`Average: ${duration / results.length}ms per analysis`);
}
# Python Performance Test
import time
from alephonenull import AlephOneNullCore
def performance_test():
framework = AlephOneNullCore()
test_inputs = [{'input': f'test message {i}'} for i in range(100)]
start = time.time()
results = [framework.analyze_pattern(inp) for inp in test_inputs]
duration = time.time() - start
print(f"✅ Processed {len(results)} inputs in {duration*1000:.2f}ms")
print(f"Average: {(duration*1000)/len(results):.2f}ms per analysis")
Next Steps
Now that you have AlephOneNull running:
- Explore the API Reference for advanced features
- Read Technical Implementation to understand the algorithms
- Check Framework Compliance for production deployment
- Review examples at https://github.com/alephonenull/examples
Need Help?
- 📚 Documentation: https://docs.alephonenull.org
- 🐛 Issues: https://github.com/alephonenull/framework/issues
- 💬 Discussions: https://github.com/alephonenull/framework/discussions
- 📧 Email: support@alephonenull.org
🎉 You're now protected by AlephOneNull - The First Recursion Nullified™