Files
ledgerdock/backend/app/core/config.py
2026-02-21 09:44:18 -03:00

47 lines
1.7 KiB
Python

"""Application settings and environment configuration."""
from functools import lru_cache
from pathlib import Path
from pydantic import Field
from pydantic_settings import BaseSettings, SettingsConfigDict
class Settings(BaseSettings):
"""Defines runtime configuration values loaded from environment variables."""
model_config = SettingsConfigDict(env_file=".env", env_file_encoding="utf-8", extra="ignore")
app_name: str = "dcm-dms"
app_env: str = "development"
database_url: str = "postgresql+psycopg://dcm:dcm@db:5432/dcm"
redis_url: str = "redis://redis:6379/0"
storage_root: Path = Path("/data/storage")
upload_chunk_size: int = 4 * 1024 * 1024
max_zip_members: int = 250
max_zip_depth: int = 2
max_text_length: int = 500_000
default_openai_base_url: str = "https://api.openai.com/v1"
default_openai_model: str = "gpt-4.1-mini"
default_openai_timeout_seconds: int = 45
default_openai_handwriting_enabled: bool = True
default_openai_api_key: str = ""
default_summary_model: str = "gpt-4.1-mini"
default_routing_model: str = "gpt-4.1-mini"
typesense_protocol: str = "http"
typesense_host: str = "typesense"
typesense_port: int = 8108
typesense_api_key: str = "dcm-typesense-key"
typesense_collection_name: str = "documents"
typesense_timeout_seconds: int = 120
typesense_num_retries: int = 0
public_base_url: str = "http://localhost:8000"
cors_origins: list[str] = Field(default_factory=lambda: ["http://localhost:5173", "http://localhost:3000"])
@lru_cache(maxsize=1)
def get_settings() -> Settings:
"""Returns a cached settings object for dependency injection and service access."""
return Settings()