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| # ============================================================================= | |
| # utils/domain_configs.py | |
| # ============================================================================= | |
| from typing import Dict, List | |
| from core.config import MambaConfig | |
| class DomainConfigs: | |
| """Configurations for different specialist domains""" | |
| DOMAINS = { | |
| # STEM domains | |
| "mathematics": { | |
| "keywords": ["equation", "theorem", "proof", "calculate", "derivative", "integral", "matrix", "algebra", "geometry", "statistics"], | |
| "description": "Mathematical reasoning and computation" | |
| }, | |
| "physics": { | |
| "keywords": ["force", "energy", "momentum", "quantum", "relativity", "particle", "wave", "thermodynamics", "mechanics"], | |
| "description": "Physics concepts and problems" | |
| }, | |
| "chemistry": { | |
| "keywords": ["molecule", "atom", "reaction", "compound", "bond", "element", "organic", "inorganic", "catalyst"], | |
| "description": "Chemistry and molecular science" | |
| }, | |
| "biology": { | |
| "keywords": ["cell", "DNA", "protein", "organism", "evolution", "genetics", "ecology", "anatomy", "physiology"], | |
| "description": "Biological sciences" | |
| }, | |
| # Programming domains | |
| "python": { | |
| "keywords": ["def", "class", "import", "python", "pandas", "numpy", "matplotlib", "sklearn", "tensorflow"], | |
| "description": "Python programming and data science" | |
| }, | |
| "javascript": { | |
| "keywords": ["function", "var", "let", "const", "javascript", "react", "node", "async", "promise"], | |
| "description": "JavaScript and web development" | |
| }, | |
| "systems": { | |
| "keywords": ["linux", "server", "network", "database", "docker", "kubernetes", "cloud", "devops"], | |
| "description": "Systems programming and infrastructure" | |
| }, | |
| # Language domains | |
| "writing": { | |
| "keywords": ["essay", "article", "story", "paragraph", "thesis", "narrative", "prose", "literature"], | |
| "description": "Creative and technical writing" | |
| }, | |
| "translation": { | |
| "keywords": ["translate", "language", "spanish", "french", "german", "chinese", "japanese", "korean"], | |
| "description": "Language translation and linguistics" | |
| }, | |
| # Business domains | |
| "business": { | |
| "keywords": ["market", "strategy", "finance", "management", "revenue", "profit", "customer", "sales"], | |
| "description": "Business and economics" | |
| }, | |
| "legal": { | |
| "keywords": ["law", "contract", "court", "legal", "attorney", "judge", "case", "statute", "regulation"], | |
| "description": "Legal reasoning and analysis" | |
| }, | |
| # Other domains | |
| "history": { | |
| "keywords": ["war", "empire", "civilization", "century", "ancient", "medieval", "revolution", "dynasty"], | |
| "description": "Historical knowledge and analysis" | |
| }, | |
| "philosophy": { | |
| "keywords": ["ethics", "moral", "logic", "metaphysics", "epistemology", "consciousness", "existence"], | |
| "description": "Philosophical reasoning" | |
| }, | |
| "medical": { | |
| "keywords": ["patient", "diagnosis", "treatment", "disease", "medicine", "surgery", "therapy", "symptom"], | |
| "description": "Medical knowledge and healthcare" | |
| }, | |
| "arts": { | |
| "keywords": ["painting", "music", "sculpture", "artist", "gallery", "museum", "aesthetic", "culture"], | |
| "description": "Arts and cultural topics" | |
| } | |
| } | |
| def get_domain_configs(cls, num_specialists: int = 100) -> List[Dict]: | |
| """Generate configurations for specialist domains""" | |
| configs = [] | |
| base_domains = list(cls.DOMAINS.keys()) | |
| # Create configurations | |
| for i in range(num_specialists): | |
| if i < len(base_domains): | |
| # Use predefined domains | |
| domain_name = base_domains[i] | |
| domain_info = cls.DOMAINS[domain_name] | |
| else: | |
| # Create sub-specializations or general domains | |
| base_idx = i % len(base_domains) | |
| domain_name = f"{base_domains[base_idx]}_sub_{i}" | |
| domain_info = cls.DOMAINS[base_domains[base_idx]] | |
| config = { | |
| "id": i, | |
| "name": domain_name, | |
| "keywords": domain_info["keywords"], | |
| "description": domain_info["description"], | |
| "weight": 1.0 # Can be adjusted based on importance | |
| } | |
| configs.append(config) | |
| return configs | |
| def create_specialist_config(cls, base_config: MambaConfig, domain_id: int) -> MambaConfig: | |
| """Create a specialist configuration for a specific domain""" | |
| specialist_config = MambaConfig(**base_config.__dict__) | |
| specialist_config.specialist_id = domain_id | |
| return specialist_config |