import os import json import configparser import uuid from typing import Optional, List, Dict, Any from dataclasses import dataclass, field from pathlib import Path from dotenv import load_dotenv base_dir = Path(__file__).resolve().parent.parent # Load the .env file from the base directory dotenv_path = base_dir / ".env" load_dotenv(dotenv_path=dotenv_path) @dataclass class Config: # Paths and Directories memgpt_dir: str = field( default_factory=lambda: os.getenv("COG_ARCH_DIR", "cognitive_achitecture") ) config_path: str = field( default_factory=lambda: os.path.join( os.getenv("COG_ARCH_DIR", "cognitive_achitecture"), "config" ) ) vectordb: str = "lancedb" # Model parameters model: str = "gpt-4-1106-preview" model_endpoint: str = "openai" openai_key: Optional[str] = os.getenv("OPENAI_API_KEY") openai_temperature: float = float(os.getenv("OPENAI_TEMPERATURE", 0.0)) # Embedding parameters embedding_model: str = "openai" embedding_dim: int = 1536 embedding_chunk_size: int = 300 # Database parameters if ( os.getenv("ENV") == "prod" or os.getenv("ENV") == "dev" or os.getenv("AWS_ENV") == "dev" or os.getenv("AWS_ENV") == "prd" ): graph_database_url: str = os.getenv("GRAPH_DB_URL_PROD") graph_database_username: str = os.getenv("GRAPH_DB_USER") graph_database_password: str = os.getenv("GRAPH_DB_PW") else: graph_database_url: str = os.getenv("GRAPH_DB_URL") graph_database_username: str = os.getenv("GRAPH_DB_USER") graph_database_password: str = os.getenv("GRAPH_DB_PW") weaviate_url: str = os.getenv("WEAVIATE_URL") weaviate_api_key: str = os.getenv("WEAVIATE_API_KEY") postgres_user: str = os.getenv("POSTGRES_USER") postgres_password: str = os.getenv("POSTGRES_PASSWORD") postgres_db: str = os.getenv("POSTGRES_DB") if ( os.getenv("ENV") == "prod" or os.getenv("ENV") == "dev" or os.getenv("AWS_ENV") == "dev" or os.getenv("AWS_ENV") == "prd" ): postgres_host: str = os.getenv("POSTGRES_PROD_HOST") elif os.getenv("ENV") == "docker": postgres_host: str = os.getenv("POSTGRES_HOST_DOCKER") elif os.getenv("ENV") == "local": postgres_host: str = os.getenv("POSTGRES_HOST_LOCAL") # Client ID anon_clientid: Optional[str] = field(default_factory=lambda: uuid.uuid4().hex) def load(self): """Loads the configuration from a file or environment variables.""" config = configparser.ConfigParser() config.read(self.config_path) # Override with environment variables if they exist for attr in self.__annotations__: env_value = os.getenv(attr.upper()) if env_value is not None: setattr(self, attr, env_value) # Load from config file if config.sections(): for section in config.sections(): for key, value in config.items(section): if hasattr(self, key): setattr(self, key, value) def save(self): """Saves the current configuration to a file.""" config = configparser.ConfigParser() # Save the current settings to the config file for attr, value in self.__dict__.items(): section, option = attr.split("_", 1) if not config.has_section(section): config.add_section(section) config.set(section, option, str(value)) with open(self.config_path, "w") as configfile: config.write(configfile) def to_dict(self) -> Dict[str, Any]: """Returns a dictionary representation of the configuration.""" return {attr: getattr(self, attr) for attr in self.__annotations__} @classmethod def from_dict(cls, config_dict: Dict[str, Any]) -> "Config": """Creates a Config instance from a dictionary.""" config = cls() for attr, value in config_dict.items(): if hasattr(config, attr): setattr(config, attr, value) return config