# =============================================================================
# REQUIRED SECRETS - You MUST change these before starting!
# =============================================================================

# PostgreSQL password - REQUIRED
# Generate: openssl rand -base64 24
POSTGRES_PASSWORD=CHANGE_ME_REQUIRED

# JWT secret for authentication - REQUIRED (min 32 characters)
# Generate: openssl rand -hex 32
JWT_SECRET=CHANGE_ME_REQUIRED_MIN_32_CHARS

# Initial admin account (created on first startup if no admin exists)
INITIAL_ADMIN_EMAIL=admin@example.com
INITIAL_ADMIN_PASSWORD=ChangeMe123!

# SMTP Configuration (required for email verification and password reset)
# Leave empty to disable email features (admin approval will be used instead)
SMTP_HOST=smtp.example.com
SMTP_PORT=587
SMTP_SECURE=false
SMTP_USER=your-smtp-username
SMTP_PASS=your-smtp-password
SMTP_FROM=noreply@example.com
SMTP_FROM_NAME=Media Manager

# Email settings
EMAIL_VERIFICATION_EXPIRY_HOURS=24
PASSWORD_RESET_EXPIRY_HOURS=1

# Application URL (used in email links)
APP_BASE_URL=http://localhost:3080

# CORS allowed origins (comma-separated)
# Add your production domains here
ALLOWED_ORIGINS=http://localhost:3080,http://localhost:8080

# Timezone for API server (logs and server-side timestamps)
# See: https://en.wikipedia.org/wiki/List_of_tz_database_time_zones
TZ=UTC

# Locale for date/time formatting (optional, defaults to browser locale)
# Examples: en-US, en-GB, de-DE, fr-FR
VITE_DEFAULT_LOCALE=

# =============================================================================
# MAXMIND GEOIP CONFIGURATION (optional)
# =============================================================================
# Provides geographic location data for session analytics
# Download GeoLite2-City.mmdb from: https://dev.maxmind.com/geoip/geolite2-free-geolocation-data
# Place the file in ./data/GeoLite2-City.mmdb (mounted to /app/data in container)
# Register for free account to download: https://www.maxmind.com/en/geolite2/signup

# =============================================================================
# CONTENT SAFETY CONFIGURATION (requires --profile safety)
# =============================================================================
# Set to false to disable LLM-based content safety checking
SAFETY_CHECK_ENABLED=true

# Admin email for high-severity content alerts (e.g., S4 Child Sexual Exploitation)
# If not set, falls back to SMTP_FROM
# Leave empty to disable high-severity email alerts
ADMIN_ALERT_EMAIL=

# =============================================================================
# OLLAMA CONFIGURATION
# =============================================================================
# Base URL for Ollama API (shared by safety and digest features)
OLLAMA_BASE_URL=http://ollama:11434

# Content Safety Model (Llama Guard for chat moderation)
OLLAMA_MODEL=llama-guard3:1b

# =============================================================================
# DIGEST FEATURE MODELS (requires --profile digest)
# =============================================================================
# Video analysis pipeline using vision-language models and speech recognition
#
# Vision Model - analyzes video frames (requires vision-language model)
# Used for: frame description, visual element detection, scene classification
# Options:
#   - huihui_ai/qwen3-vl-abliterated:2b  (uncensored, ~2GB VRAM) [RECOMMENDED]
#   - qwen2-vl:7b                         (censored, ~7GB VRAM)
#   - llava:7b                            (censored, ~7GB VRAM)
DIGEST_VISION_MODEL=huihui_ai/qwen3-vl-abliterated:2b

# Text Model - synthesizes analysis results (text-only LLM)
# Used for: tag extraction, transcript analysis, final synthesis
# Options:
#   - huihui_ai/qwen3-abliterated:4b     (uncensored, ~4GB VRAM) [RECOMMENDED]
#   - qwen2.5:7b                          (censored, ~7GB VRAM)
#   - llama3.1:8b                         (censored, ~8GB VRAM)
DIGEST_TEXT_MODEL=huihui_ai/qwen3-abliterated:4b

# Digest service URLs
DIGEST_OLLAMA_URL=http://ollama:11434
DIGEST_WHISPER_URL=http://whisper:5000

# Frame extraction interval (seconds between frames)
DIGEST_FRAME_INTERVAL=30

# =============================================================================
# JOYCAPTION VISION BACKEND (requires --profile joycaption)
# =============================================================================
# Alternative to Ollama vision models - uses JoyCaption GGUF via llama.cpp
# Better quality image captioning, fits on 6GB VRAM with Q3_K_M quantization
#
# Vision backend type: 'ollama' (default) or 'llama-server' (JoyCaption)
DIGEST_VISION_BACKEND=ollama

# JoyCaption server URL (when using llama-server backend)
JOYCAPTION_URL=http://joycaption:8080
JOYCAPTION_MODEL=llama-joycaption-beta-one-hf-llava

# Fall back to Ollama vision if JoyCaption fails
JOYCAPTION_FALLBACK_TO_OLLAMA=true

# JoyCaption model files (place in ./models directory)
# Download from: https://huggingface.co/Mungert/llama-joycaption-beta-one-hf-llava-GGUF
# Quantization options:
#   - Q2_K: ~3.2GB model, ~4GB VRAM (good quality, safest for 6GB GPU)
#   - Q3_K_M: ~4GB model, ~5GB VRAM (better quality, tight fit on 6GB)
#   - Q4_K_M: ~5GB model, ~6GB VRAM (best quality, needs 8GB+ GPU)
JOYCAPTION_MODEL_PATH=/models/llama-joycaption-beta-one-hf-llava.Q2_K.gguf
JOYCAPTION_MMPROJ_PATH=/models/llama-joycaption-beta-one-llava-mmproj-model-f16.gguf

# llama-server configuration
JOYCAPTION_CTX_SIZE=4096
JOYCAPTION_GPU_LAYERS=999
JOYCAPTION_PARALLEL=1

# =============================================================================
# WHISPER TRANSCRIPTION
# =============================================================================
# Model sizes: tiny, base, small, medium, large-v2, large-v3
# Larger = more accurate but slower and more VRAM
WHISPER_MODEL=base
WHISPER_DEVICE=cuda
WHISPER_COMPUTE=float16

# =============================================================================
# OLLAMA AUTO-PULL MODELS
# =============================================================================
# Comma-separated list of models to pull on Ollama container startup
# Include all models needed for your enabled features
#
# Safety profile only:
#   OLLAMA_MODELS=llama-guard3:1b
#
# Digest profile only:
#   OLLAMA_MODELS=huihui_ai/qwen3-vl-abliterated:2b,huihui_ai/qwen3-abliterated:4b
#
# Both profiles (recommended):
OLLAMA_MODELS=llama-guard3:1b,huihui_ai/qwen3-vl-abliterated:2b,huihui_ai/qwen3-abliterated:4b

# =============================================================================
# JOB QUEUE CONFIGURATION
# =============================================================================
# GPU resource management for preventing job conflicts
# The system automatically queues GPU-intensive jobs to prevent VRAM exhaustion

# Maximum GPU VRAM in MB (default: 6000 for RTX 4050)
# Adjust based on your GPU: RTX 3090 = 24000, RTX 4080 = 16000, etc.
MAX_GPU_VRAM=6000

# =============================================================================
# FFMPEG ENCODING CONCURRENCY
# =============================================================================
# Number of parallel FFmpeg encode sessions for clip/scene generation.
# NVENC supports 3-5 concurrent sessions on consumer RTX GPUs (~200-400MB VRAM each).
# Set to 1 to restore sequential behavior.
FFMPEG_ENCODE_CONCURRENCY=2

# Disable job queue for immediate execution (legacy behavior)
# Set to 'true' to bypass the queue manager entirely
# DISABLE_JOB_QUEUE=false

# =============================================================================
# INBOX FILE WATCHER CONFIGURATION
# =============================================================================
# Automatically watches inbox directory for new video files.
# When a new file is fully written, it's scanned into the library
# and optionally triggers auto-digest if auto_digest_enabled is true.

# Enable/disable file watcher (default: false, can also enable via admin UI)
# Set to 'true' to auto-detect new files added to inbox directory
FILE_WATCHER_ENABLED=false

# Time in ms to wait for file size to stabilize before processing (default: 2000)
# Increase for slower network drives or when copying large files
FILE_WATCHER_DEBOUNCE_MS=2000

# =============================================================================
# CONTAINER LIFECYCLE CONFIGURATION
# =============================================================================
# By default, the system starts AI containers on-demand and stops them after use
# to minimize VRAM usage. Set to 'true' to disable this behavior when all AI
# containers are configured to run continuously (e.g., models fit in VRAM).
#
# When enabled:
# - ensureContainerRunning() only checks health, doesn't start containers
# - stopContainer() becomes a no-op, containers keep running
# - You must manually start containers: docker compose --profile ai up -d
DISABLE_CONTAINER_LIFECYCLE=false

# =============================================================================
# COMBINED SCENE DETECTION CONFIGURATION
# =============================================================================
# Uses three methods: TransNetV2 (neural), PySceneDetect (histogram), CLIP (semantic)
# Results are merged using configurable strategies for more accurate scene boundaries.
#
# Enable/disable combined detection (default: true)
# When disabled, falls back to PySceneDetect only
ENABLE_COMBINED_SCENE_DETECTION=true

# Merge strategy for combining cuts from multiple detectors
# Options: weighted (default), union, intersection, majority
#   - weighted: Uses detector confidence weights (best balance)
#   - union: Include all cuts (most comprehensive, may over-segment)
#   - intersection: Only cuts from all 3 detectors (highest confidence)
#   - majority: Cuts from 2+ detectors
SCENE_MERGE_STRATEGY=weighted

# Tolerance window for grouping cuts (seconds)
# Cuts within this window are considered "the same" cut
SCENE_MERGE_TOLERANCE=0.75

# Run GPU detectors in parallel (requires >12GB VRAM)
# When false (default), runs sequentially: PyScene -> TransNet -> CLIP
SCENE_DETECTION_PARALLEL=false

# Detector weights for weighted merge strategy
# Higher weight = more trusted detector
SCENE_WEIGHT_TRANSNET=1.0      # Neural network, best for soft transitions
SCENE_WEIGHT_PYSCENEDETECT=0.8 # Histogram-based, fast, good for hard cuts
SCENE_WEIGHT_CLIP=0.9          # Visual embeddings, semantic/content changes

# CLIP boundary detection configuration
# Extracts frames at interval, computes embeddings, detects similarity drops
CLIP_BOUNDARY_FRAME_INTERVAL=0.5   # Seconds between frames (0.5 = 2 fps)
CLIP_BOUNDARY_SIMILARITY_THRESHOLD=0.7  # Below this = scene boundary (0-1)
CLIP_BOUNDARY_MIN_GAP=2.0          # Minimum seconds between boundaries

# CLIP embeddings GPU batch size (default: 128)
# Higher = faster processing, more VRAM usage
# RTX 4050 6GB: safe up to 512, recommended 256
# RTX 3090 24GB: can use 1024+
CLIP_GPU_BATCH_SIZE=256

# Database path (inside container)
DATABASE_URL=/app/data/library.db

# Media library paths (host paths)
MEDIA_ROOT=/media/bunker-admin/Internal/plex/xxx/media
MEDIA_LOCAL=/media/bunker-admin/Internal/plex/xxx/media/local
MEDIA_PUBLIC=/media/bunker-admin/Internal/plex/xxx/media/public
STUDIOS_PATH=/media/bunker-admin/Internal/plex/xxx/media/local/studios
GIFS_PATH=/media/bunker-admin/Internal/plex/xxx/media/local/gifs
PLAYBACK_PATH=/media/bunker-admin/Internal/plex/xxx/media/public/playback
COMPILATIONS_PATH=/media/bunker-admin/Internal/plex/xxx/media/public/compilations
PUBLIC_CURATED_PATH=/media/bunker-admin/Internal/plex/xxx/media/public/curated
QUICKIES_PATH=/media/bunker-admin/Internal/plex/xxx/media/public/quickies

# =============================================================================
# PAYMENT SYSTEM CONFIGURATION
# =============================================================================
# IMAP settings for automatic e-transfer email parsing
# Leave empty to disable automatic payment polling (manual entry only)
#
# For Proton Mail: Requires Proton Mail Bridge running locally
#   PAYMENT_IMAP_HOST=127.0.0.1 (or host.docker.internal from container)
#   PAYMENT_IMAP_PORT=1143
#   PAYMENT_IMAP_TLS=false (Bridge uses STARTTLS)
#
# For Gmail: Enable "Less secure app access" or use App Password
#   PAYMENT_IMAP_HOST=imap.gmail.com
#   PAYMENT_IMAP_PORT=993
#   PAYMENT_IMAP_TLS=true
#
PAYMENT_IMAP_HOST=
PAYMENT_IMAP_PORT=993
PAYMENT_IMAP_USER=
PAYMENT_IMAP_PASS=
PAYMENT_IMAP_TLS=true

# How often to check for new payment emails (milliseconds)
# Default: 60000 (1 minute)
PAYMENT_POLL_INTERVAL_MS=60000

# Folder to move processed emails to (created automatically)
PAYMENT_PROCESSED_FOLDER=Processed