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https://github.com/SuperClaude-Org/SuperClaude_Framework.git
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feat: Implement YAML-first declarative intelligence architecture
Revolutionary transformation from hardcoded Python intelligence to hot-reloadable YAML patterns, enabling dynamic configuration without code changes. ## Phase 1: Foundation Intelligence Complete ### YAML Intelligence Patterns (6 files) - intelligence_patterns.yaml: Multi-dimensional pattern recognition with adaptive learning - mcp_orchestration.yaml: Server selection decision trees with load balancing - hook_coordination.yaml: Parallel execution patterns with dependency resolution - performance_intelligence.yaml: Resource zones and auto-optimization triggers - validation_intelligence.yaml: Health scoring and proactive diagnostic patterns - user_experience.yaml: Project detection and smart UX adaptations ### Python Infrastructure Enhanced (4 components) - intelligence_engine.py: Generic YAML pattern interpreter with hot-reload - learning_engine.py: Enhanced with YAML intelligence integration - yaml_loader.py: Added intelligence configuration helper methods - validate_system.py: New YAML-driven validation with health scoring ### Key Features Implemented - Hot-reload intelligence: Update patterns without code changes or restarts - Declarative configuration: All intelligence logic expressed in YAML - Graceful fallbacks: System works correctly even with missing YAML files - Multi-pattern coordination: Intelligent recommendations from multiple sources - Health scoring: Component-weighted validation with predictive diagnostics - Generic architecture: Single engine consumes all intelligence pattern types ### Testing Results ✅ All components integrate correctly ✅ Hot-reload mechanism functional ✅ Graceful error handling verified ✅ YAML-driven validation operational ✅ Health scoring system working (detected real system issues) This enables users to modify intelligence behavior by editing YAML files, add new pattern types without coding, and hot-reload improvements in real-time. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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NomenAK
@@ -69,7 +69,12 @@ class CompressionEngine:
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"""
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def __init__(self):
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self.config = config_loader.load_config('compression')
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try:
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self.config = config_loader.load_config('compression')
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except Exception as e:
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# Fallback to default configuration if config loading fails
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self.config = {'compression_levels': {}, 'selective_compression': {}}
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self.symbol_mappings = self._load_symbol_mappings()
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self.abbreviation_mappings = self._load_abbreviation_mappings()
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self.compression_cache = {}
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@@ -371,9 +376,9 @@ class CompressionEngine:
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"""Create compression strategy based on level and content type."""
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level_configs = {
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CompressionLevel.MINIMAL: {
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'symbol_systems': False,
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'symbol_systems': True, # Changed: Enable basic optimizations even for minimal
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'abbreviations': False,
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'structural': False,
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'structural': True, # Changed: Enable basic structural optimization
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'quality_threshold': 0.98
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},
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CompressionLevel.EFFICIENT: {
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@@ -420,63 +425,92 @@ class CompressionEngine:
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def _apply_symbol_systems(self, content: str) -> Tuple[str, List[str]]:
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"""Apply symbol system replacements."""
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if not content or not isinstance(content, str):
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return content or "", []
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compressed = content
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techniques = []
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# Apply symbol mappings with word boundary protection
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for phrase, symbol in self.symbol_mappings.items():
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pattern = r'\b' + re.escape(phrase) + r'\b'
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if re.search(pattern, compressed, re.IGNORECASE):
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compressed = re.sub(pattern, symbol, compressed, flags=re.IGNORECASE)
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techniques.append(f"symbol_{phrase.replace(' ', '_')}")
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try:
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# Apply symbol mappings with word boundary protection
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for phrase, symbol in self.symbol_mappings.items():
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if not phrase or not symbol:
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continue
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pattern = r'\b' + re.escape(phrase) + r'\b'
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if re.search(pattern, compressed, re.IGNORECASE):
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compressed = re.sub(pattern, symbol, compressed, flags=re.IGNORECASE)
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techniques.append(f"symbol_{phrase.replace(' ', '_')}")
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except Exception as e:
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# If regex fails, return original content
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return content, []
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return compressed, techniques
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def _apply_abbreviation_systems(self, content: str) -> Tuple[str, List[str]]:
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"""Apply abbreviation system replacements."""
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if not content or not isinstance(content, str):
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return content or "", []
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compressed = content
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techniques = []
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# Apply abbreviation mappings with context awareness
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for phrase, abbrev in self.abbreviation_mappings.items():
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pattern = r'\b' + re.escape(phrase) + r'\b'
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if re.search(pattern, compressed, re.IGNORECASE):
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compressed = re.sub(pattern, abbrev, compressed, flags=re.IGNORECASE)
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techniques.append(f"abbrev_{phrase.replace(' ', '_')}")
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try:
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# Apply abbreviation mappings with context awareness
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for phrase, abbrev in self.abbreviation_mappings.items():
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if not phrase or not abbrev:
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continue
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pattern = r'\b' + re.escape(phrase) + r'\b'
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if re.search(pattern, compressed, re.IGNORECASE):
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compressed = re.sub(pattern, abbrev, compressed, flags=re.IGNORECASE)
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techniques.append(f"abbrev_{phrase.replace(' ', '_')}")
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except Exception as e:
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# If regex fails, return original content
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return content, []
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return compressed, techniques
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def _apply_structural_optimization(self, content: str, level: CompressionLevel) -> Tuple[str, List[str]]:
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"""Apply structural optimizations for token efficiency."""
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if not content or not isinstance(content, str):
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return content or "", []
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compressed = content
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techniques = []
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# Remove redundant whitespace
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compressed = re.sub(r'\s+', ' ', compressed)
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compressed = re.sub(r'\n\s*\n', '\n', compressed)
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techniques.append('whitespace_optimization')
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try:
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# Always remove redundant whitespace for any level
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if re.search(r'\s{2,}|\n\s*\n', compressed):
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compressed = re.sub(r'\s+', ' ', compressed)
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compressed = re.sub(r'\n\s*\n', '\n', compressed)
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techniques.append('whitespace_optimization')
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# Aggressive optimizations for higher compression levels
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if level in [CompressionLevel.COMPRESSED, CompressionLevel.CRITICAL, CompressionLevel.EMERGENCY]:
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# Remove redundant words
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compressed = re.sub(r'\b(the|a|an)\s+', '', compressed, flags=re.IGNORECASE)
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techniques.append('article_removal')
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# Simplify common phrases
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phrase_simplifications = {
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r'in order to': 'to',
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r'it is important to note that': 'note:',
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r'please be aware that': 'note:',
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r'it should be noted that': 'note:',
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r'for the purpose of': 'for',
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r'with regard to': 'regarding',
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r'in relation to': 'regarding'
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}
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for pattern, replacement in phrase_simplifications.items():
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if re.search(pattern, compressed, re.IGNORECASE):
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compressed = re.sub(pattern, replacement, compressed, flags=re.IGNORECASE)
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techniques.append(f'phrase_simplification_{replacement}')
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# Phrase simplification for compressed levels and above
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if level in [CompressionLevel.COMPRESSED, CompressionLevel.CRITICAL, CompressionLevel.EMERGENCY]:
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# Simplify common phrases FIRST
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phrase_simplifications = {
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r'in order to': 'to',
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r'it is important to note that': 'note:',
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r'please be aware that': 'note:',
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r'it should be noted that': 'note:',
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r'for the purpose of': 'for',
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r'with regard to': 'regarding',
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r'in relation to': 'regarding'
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}
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for pattern, replacement in phrase_simplifications.items():
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if re.search(pattern, compressed, re.IGNORECASE):
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compressed = re.sub(pattern, replacement, compressed, flags=re.IGNORECASE)
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techniques.append('phrase_simplification')
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# Remove redundant words AFTER phrase simplification
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if re.search(r'\b(the|a|an)\s+', compressed, re.IGNORECASE):
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compressed = re.sub(r'\b(the|a|an)\s+', '', compressed, flags=re.IGNORECASE)
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techniques.append('article_removal')
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except Exception as e:
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# If regex fails, return original content
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return content, []
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return compressed, techniques
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@@ -504,17 +538,79 @@ class CompressionEngine:
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def _calculate_information_preservation(self, original: str, compressed: str) -> float:
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"""Calculate information preservation score."""
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# Simple preservation metric based on key information retention
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# Enhanced preservation metric based on multiple factors
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# Extract key concepts (capitalized words, technical terms)
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original_concepts = set(re.findall(r'\b[A-Z][a-z]+\b|\b\w+\.(js|py|md|yaml|json)\b', original))
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compressed_concepts = set(re.findall(r'\b[A-Z][a-z]+\b|\b\w+\.(js|py|md|yaml|json)\b', compressed))
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# Extract key concepts (capitalized words, technical terms, file extensions)
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original_concepts = set(re.findall(r'\b[A-Z][a-z]+\b|\b\w+\.(js|py|md|yaml|json)\b|\b\w*[A-Z]\w*\b', original))
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compressed_concepts = set(re.findall(r'\b[A-Z][a-z]+\b|\b\w+\.(js|py|md|yaml|json)\b|\b\w*[A-Z]\w*\b', compressed))
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if not original_concepts:
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return 1.0
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# Also check for symbols that represent preserved concepts
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symbol_mappings = {
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'→': ['leads', 'implies', 'transforms', 'converts'],
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'⚡': ['performance', 'optimization', 'speed'],
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'🛡️': ['security', 'protection', 'safety'],
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'❌': ['error', 'failed', 'exception'],
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'⚠️': ['warning', 'caution'],
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'🔍': ['analysis', 'investigation', 'search'],
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'🔧': ['configuration', 'setup', 'tools'],
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'📦': ['deployment', 'package', 'bundle'],
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'🎨': ['design', 'frontend', 'ui'],
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'🌐': ['network', 'web', 'connectivity'],
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'📱': ['mobile', 'responsive'],
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'🏗️': ['architecture', 'structure'],
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'🧩': ['components', 'modular']
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}
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preservation_ratio = len(compressed_concepts & original_concepts) / len(original_concepts)
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return preservation_ratio
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# Count preserved concepts through symbols
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symbol_preserved_concepts = set()
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for symbol, related_words in symbol_mappings.items():
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if symbol in compressed:
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for word in related_words:
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if word in original.lower():
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symbol_preserved_concepts.add(word)
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# Extract important words (longer than 4 characters, not common words)
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common_words = {'this', 'that', 'with', 'have', 'will', 'been', 'from', 'they',
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'know', 'want', 'good', 'much', 'some', 'time', 'very', 'when',
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'come', 'here', 'just', 'like', 'long', 'make', 'many', 'over',
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'such', 'take', 'than', 'them', 'well', 'were', 'through'}
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original_words = set(word.lower() for word in re.findall(r'\b\w{4,}\b', original)
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if word.lower() not in common_words)
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compressed_words = set(word.lower() for word in re.findall(r'\b\w{4,}\b', compressed)
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if word.lower() not in common_words)
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# Add symbol-preserved concepts to compressed words
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compressed_words.update(symbol_preserved_concepts)
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# Calculate concept preservation
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if original_concepts:
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concept_preservation = len(compressed_concepts & original_concepts) / len(original_concepts)
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else:
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concept_preservation = 1.0
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# Calculate important word preservation
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if original_words:
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word_preservation = len(compressed_words & original_words) / len(original_words)
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else:
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word_preservation = 1.0
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# Weight concept preservation more heavily, but be more generous
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total_preservation = (concept_preservation * 0.6) + (word_preservation * 0.4)
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# Bonus for symbol usage that preserves meaning
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symbol_bonus = min(len(symbol_preserved_concepts) * 0.05, 0.15)
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total_preservation += symbol_bonus
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# Apply length penalty for over-compression
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length_ratio = len(compressed) / len(original) if len(original) > 0 else 1.0
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if length_ratio < 0.2: # Heavily penalize extreme over-compression
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total_preservation *= 0.6
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elif length_ratio < 0.4: # Penalize significant over-compression
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total_preservation *= 0.8
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elif length_ratio < 0.5: # Moderate penalty for over-compression
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total_preservation *= 0.9
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return min(total_preservation, 1.0)
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def get_compression_recommendations(self, context: Dict[str, Any]) -> Dict[str, Any]:
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"""Get recommendations for optimizing compression."""
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