# SPDX-License-Identifier: GPL-3.0-only
"""Server configuration, loaded from environment / .env (see .env.example).

Everything points at self-hosted services by default: local object storage, a local
Ollama, and a local faster-whisper model. Nothing here requires a proprietary cloud.
"""
from __future__ import annotations

from pydantic_settings import BaseSettings, SettingsConfigDict


class Settings(BaseSettings):
    model_config = SettingsConfigDict(env_prefix="OPENSCRIBE_", env_file=".env")

    # API
    api_token: str = "change-me"          # bearer token for write endpoints

    # Storage: "local" | "s3" | "webdav"
    storage_backend: str = "local"
    local_media_dir: str = "./media"

    # S3-compatible (MinIO) - used when storage_backend == "s3"
    s3_endpoint: str = "http://localhost:9000"
    s3_bucket: str = "openscribe"
    s3_access_key: str = ""
    s3_secret_key: str = ""

    # Metadata DB (SQLite to start; Postgres URL later)
    database_url: str = "sqlite:///./openscribe.db"

    # --- AI providers (see docs/ai-providers.md) --------------------------------------
    # Transcription provider: "local_whisper" (self-hosted) | "openai_compatible"
    transcription_provider: str = "local_whisper"
    transcription_base_url: str = ""      # e.g. https://api.openai.com/v1 or a Groq/local URL
    transcription_api_key: str = ""
    transcription_model: str = ""         # e.g. whisper-1, whisper-large-v3

    # LLM provider for summaries + Ask-AI:
    #   "ollama" (default, self-hosted) | "openai_compatible" | "anthropic"
    llm_provider: str = "ollama"
    llm_base_url: str = "https://api.openai.com/v1"   # used by openai_compatible
    llm_api_key: str = ""
    llm_model: str = ""                   # per-provider default applied if empty

    # Local faster-whisper (used when transcription_provider == local_whisper)
    whisper_model: str = "base"           # tiny|base|small|medium|large-v3
    whisper_device: str = "cpu"           # cpu|cuda
    whisper_compute_type: str = "int8"

    # Local Ollama (used when llm_provider == ollama)
    ollama_url: str = "http://localhost:11434"
    ollama_model: str = "llama3.1"


settings = Settings()