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Stack 2.9 Enhancement Configuration
Central configuration for all enhancement features.
"""
from dataclasses import dataclass, field
from typing import Optional
import os
@dataclass
class NLPConfig:
"""Configuration for NLP enhancements."""
use_bert_embeddings: bool = True
bert_model: str = "bert-base-uncased"
use_entity_recognition: bool = True
use_intent_detection: bool = True
max_context_length: int = 512
embedding_cache_size: int = 1000
@dataclass
class KnowledgeGraphConfig:
"""Configuration for knowledge graph."""
enabled: bool = True
backend: str = "networkx" # or "neo4j"
max_nodes: int = 10000
max_edges: int = 50000
similarity_threshold: float = 0.7
rag_enabled: bool = True
rag_top_k: int = 5
@dataclass
class EmotionalIntelligenceConfig:
"""Configuration for emotional intelligence."""
enabled: bool = True
sentiment_model: str = "distilbert-base-uncased-finetuned-sst-2-english"
detect_emotions: bool = True
empathetic_responses: bool = True
emotion_sensitivity: float = 0.5
@dataclass
class CollaborationConfig:
"""Configuration for collaboration features."""
mcp_enabled: bool = True
conversation_state_enabled: bool = True
max_sessions: int = 10
session_timeout_minutes: int = 60
@dataclass
class LearningConfig:
"""Configuration for learning and adaptation."""
enabled: bool = True
feedback_storage_path: str = "data/feedback"
auto_finetune: bool = False
finetune_every_n_feedback: int = 100
performance_monitoring: bool = True
@dataclass
class EnhancementConfig:
"""Main configuration for all enhancements."""
nlp: NLPConfig = field(default_factory=NLPConfig)
knowledge_graph: KnowledgeGraphConfig = field(default_factory=KnowledgeGraphConfig)
emotional_intelligence: EmotionalIntelligenceConfig = field(default_factory=EmotionalIntelligenceConfig)
collaboration: CollaborationConfig = field(default_factory=CollaborationConfig)
learning: LearningConfig = field(default_factory=LearningConfig)
# Global enable/disable
all_enabled: bool = True
@classmethod
def from_env(cls) -> "EnhancementConfig":
"""Create config from environment variables."""
config = cls()
# NLP settings
if os.getenv("NLP_USE_BERT"):
config.nlp.use_bert_embeddings = os.getenv("NLP_USE_BERT").lower() == "true"
if os.getenv("NLP_BERT_MODEL"):
config.nlp.bert_model = os.getenv("NLP_BERT_MODEL")
# Knowledge graph settings
if os.getenv("KG_ENABLED"):
config.knowledge_graph.enabled = os.getenv("KG_ENABLED").lower() == "true"
if os.getenv("KG_RAG_ENABLED"):
config.knowledge_graph.rag_enabled = os.getenv("KG_RAG_ENABLED").lower() == "true"
# Emotional intelligence settings
if os.getenv("EI_ENABLED"):
config.emotional_intelligence.enabled = os.getenv("EI_ENABLED").lower() == "true"
# Learning settings
if os.getenv("LEARNING_ENABLED"):
config.learning.enabled = os.getenv("LEARNING_ENABLED").lower() == "true"
return config
# Global config instance
_default_config: Optional[EnhancementConfig] = None
def get_config() -> EnhancementConfig:
"""Get the global enhancement config instance."""
global _default_config
if _default_config is None:
_default_config = EnhancementConfig.from_env()
return _default_config
def set_config(config: EnhancementConfig) -> None:
"""Set the global enhancement config instance."""
global _default_config
_default_config = config |