"""
App-wide configuration. Everything is either an environment variable (set once,
at deploy time) or a row in the `settings` table (editable at runtime via the
setup wizard / settings page) - never a hardcoded path or host.
"""
import os
from pathlib import Path

# Deploy-time config (env vars) - where things live on disk inside the container.
DATA_DIR = Path(os.environ.get("APP_DATA_DIR", "/data"))
UPLOAD_DIR = DATA_DIR / "uploads"
AUDIO_DIR = DATA_DIR / "audio"
TRANSCRIPT_DIR = DATA_DIR / "transcriptions"
NOTES_DIR = DATA_DIR / "notes"
DB_PATH = DATA_DIR / "app.db"

CAMPAIGNS_DIR = DATA_DIR / "campaigns"

def campaign_dir(campaign_id: str) -> Path:
    return CAMPAIGNS_DIR / campaign_id

def campaign_audio_dir(campaign_id: str) -> Path:
    return campaign_dir(campaign_id) / "audio"

def campaign_transcript_dir(campaign_id: str) -> Path:
    return campaign_dir(campaign_id) / "transcriptions"

def campaign_notes_dir(campaign_id: str) -> Path:
    return campaign_dir(campaign_id) / "notes"

for d in (UPLOAD_DIR, AUDIO_DIR, TRANSCRIPT_DIR, NOTES_DIR):
    d.mkdir(parents=True, exist_ok=True)

# Runtime-editable global settings (stored in the `settings` table).
# Only onboarding state lives here; everything else is per-campaign.
GLOBAL_SETTINGS = {
    "onboarding_completed": "false",
}

# Per-campaign settings — seeded into campaign_settings on creation.
# Every layer (frontend, router, pipeline) reads these from the campaign.
CAMPAIGN_SETTINGS = {
    # Transcription
    "whisper_model": "medium",       # tiny|base|small|medium|large-v3 - user picks based on their hardware
    "whisper_compute_type": "int8",
    "hf_token": "",                  # required for diarization (pyannote gated models)

    # Summarization backend: "ollama" (local) or "api" (hosted, OpenAI-compatible)
    "llm_mode": "ollama",
    "ollama_host": "http://localhost:11434",
    "ollama_model": "qwen2.5:7b",
    "api_base_url": "https://api.openai.com/v1",
    "api_key": "",
    "api_model": "gpt-4o-mini",

    # Chunking for long transcripts (map-reduce summarization)
    "chunk_word_target": "2500",

    # Optional world context injected into every summarization prompt
    "world_context": "",
    "world_context_path": "",

    # Player recap style: "story" | "diary" | "bullets" | "custom"
    "player_recap_style": "story",
    "player_recap_custom_prompt": "",
}