API Endpoints Thesis

The endpoints.py module defines the advanced API endpoint collection for ResonanceOS v6, providing specialized functionality beyond basic CRUD operations. This module includes progressive generation, profile cloning, similarity matrix analysis, system management, and detailed health monitoring - all designed for enterprise-grade API interactions with comprehensive error handling and async support.

Technical Specifications

  • Framework: FastAPI Router Architecture
  • Prefix: /api/v1 with resonance tags
  • Features: Progressive Generation, Profile Cloning, Similarity Analysis
  • Monitoring: Detailed Health Checks & System Management
  • Architecture: Modular Router Design with Dependency Injection

Router Architecture

# Create router router = APIRouter(prefix="/api/v1", tags=["resonance"]) # Dependencies profile_persistence = ProfilePersistence() adaptive_writer = AdaptiveWriter() async def get_profile_by_name(profile_name: str) -> StyleProfile: """Get profile by name or raise HTTPException""" profile = profile_persistence.load_profile_by_name(profile_name) if not profile: raise HTTPException(status_code=404, detail=f"Profile '{profile_name}' not found") return profile
Request Routing
↓
Dependency Injection
↓
Business Logic
↓
Response Formatting

Endpoint Categories

Profile Management
Advanced profile operations including creation from text, detailed analysis, and cloning with modifications
Progressive Generation
Paragraph-by-paragraph generation with real-time feedback and progress tracking
Comparison Analysis
Multi-profile generation comparison and similarity matrix analysis
System Management
Component reset operations and detailed health monitoring

Advanced Profile Endpoints

Profile Creation & Analysis

POST /api/v1/profiles/create
Create profile directly from text input without corpus files
Parameters: name, text_content, description?, tier=1
GET /api/v1/profiles/{profile_name}/analyze
Get detailed dimension analysis with confidence levels
Returns: dimension_analysis, emotional_curve, cadence_pattern
POST /api/v1/profiles/{profile_name}/clone
Clone profile with optional dimensional modifications
Parameters: new_name, modifications? (dimension: value)

Profile Cloning Implementation

@router.post("/profiles/{profile_name}/clone", response_model=APIResponse) async def clone_profile( profile_name: str, new_name: str, modifications: Optional[Dict[str, float]] = None ): """Clone a profile with optional modifications""" # Apply modifications if provided if modifications: values = cloned_vector.values.copy() dimensions = cloned_vector.dimensions.copy() for dim_name, new_value in modifications.items(): if dim_name in dimensions: idx = dimensions.index(dim_name) values[idx] = max(0.0, min(1.0, new_value)) cloned_vector.values = values

Advanced Generation Endpoints

Progressive Generation Features

📃
Paragraph-by-Paragraph
Real-time generation with progress tracking
✏️
Live Corrections
Dynamic similarity adjustments during generation
📈
Progress Monitoring
Detailed progress data and metrics
⚡
Drift Detection
Real-time drift rate monitoring

Progressive Generation Implementation

@router.post("/generate/progressive", response_model=APIResponse) async def generate_progressive( topic: str, profile_name: str, target_paragraphs: int = 5, similarity_threshold: float = 0.92, enable_corrections: bool = True ): """Generate text with progressive paragraph-by-paragraph feedback""" # Track progress progress_data = [] def progress_callback(progress): progress_data.append(progress) # Generate text result = await adaptive_writer.generate_article(config, progress_callback)

Multi-Profile Comparison

@router.post("/generate/comparison", response_model=APIResponse) async def generate_comparison( topic: str, profile_names: List[str], similarity_threshold: float = 0.92 ): """Generate text using multiple profiles for comparison""" results = [] for profile_name in profile_names: profile = await get_profile_by_name(profile_name) result = await adaptive_writer.generate_article(config) results.append({ "profile_name": profile_name, "content": result.content, "similarity_score": result.metrics.similarity_score })

Analysis & Similarity Endpoints

Similarity Matrix Analysis

@router.post("/analyze/similarity-matrix", response_model=APIResponse) async def create_similarity_matrix( profile_names: List[str], method: SimilarityMethod = SimilarityMethod.COSINE ): """Create similarity matrix for multiple profiles""" # Calculate similarity matrix calculator = SimilarityCalculator(method) matrix = [] for i, profile1 in enumerate(profiles): row = [] for j, profile2 in enumerate(profiles): if i == j: similarity = 1.0 else: similarity = calculator.calculate_similarity( profile1.resonance_vector, profile2.resonance_vector ) row.append(similarity) matrix.append(row)

Example Similarity Matrix

1.00
Profile A → A
0.87
Profile A → B
0.73
Profile A → C
0.91
Profile B → C

Dimension Importance Analysis

@router.get("/analyze/dimension-importance", response_model=APIResponse) async def get_dimension_importance(): """Get importance weights for different resonance dimensions""" return APIResponse( success=True, message="Dimension importance retrieved", data={ "feature_weights": FEATURE_WEIGHTS, "dimensions": list(FEATURE_WEIGHTS.keys()), "total_weight": sum(FEATURE_WEIGHTS.values()) } )

System Management Endpoints

Component Reset Operations

@router.post("/system/reset", response_model=APIResponse) async def reset_system( component: str = "all", background_tasks: BackgroundTasks = None ): """Reset system components""" reset_tasks = [] if component in ["all", "generation"]: def reset_generation(): adaptive_writer.reset_state() logger.info("Generation system reset") if background_tasks: background_tasks.add_task(reset_generation) else: reset_generation() reset_tasks.append("generation")

Component Health Status

127
Active Profiles
3,847
Total Generations
98.7%
Success Rate
45ms
Response Time

Detailed Health Monitoring

@router.get("/system/health/detailed", response_model=APIResponse) async def detailed_health_check(): """Detailed health check with component status""" health_status = { "api": "healthy", "components": {} } # Check each component try: profile_count = len(profile_persistence.list_profiles()) health_status["components"]["profiles"] = { "status": "healthy", "profile_count": profile_count } except Exception as e: health_status["components"]["profiles"] = { "status": "unhealthy", "error": str(e) } health_status["api"] = "degraded"

Technical Implementation Thesis

The endpoints.py module represents the advanced API endpoint collection for ResonanceOS v6, providing sophisticated functionality beyond basic operations with enterprise-grade features like progressive generation, profile cloning, similarity matrix analysis, and comprehensive system monitoring. This implementation demonstrates advanced understanding of FastAPI router architecture, async programming, and production API design patterns.

Design Philosophy

  • Modular Architecture: Clean separation of endpoint categories
  • Advanced Features: Progressive generation and real-time monitoring
  • Enterprise Ready: Comprehensive health checks and system management
  • Developer Friendly: Detailed analysis tools and comparison features

Key Innovations

Progressive Generation

Real-time paragraph-by-paragraph generation with progress tracking.

Profile Cloning

Advanced profile duplication with dimensional modifications.

Similarity Matrix

Multi-profile similarity analysis with statistical insights.

System Management

Component-level reset operations and detailed health monitoring.