# =========================================================
# BreakPilot Lehrer — Environment Variables
# =========================================================
# Copy to .env and adjust values
# NOTE: Core must be running! These vars reference Core services.

# Database (same as Core)
POSTGRES_USER=breakpilot
POSTGRES_PASSWORD=breakpilot123
POSTGRES_DB=breakpilot_db

# Security
JWT_SECRET=your-super-secret-jwt-key-change-in-production
VAULT_TOKEN=breakpilot-dev-token

# MinIO (from Core)
MINIO_ROOT_USER=breakpilot
MINIO_ROOT_PASSWORD=breakpilot123
MINIO_BUCKET=breakpilot-rag

# Environment
ENVIRONMENT=development
TZ=Europe/Berlin

# LLM (Ollama on host)
OLLAMA_BASE_URL=http://host.docker.internal:11434
OLLAMA_ENABLED=true
OLLAMA_DEFAULT_MODEL=llama3.2
OLLAMA_VISION_MODEL=llama3.2-vision
OLLAMA_CORRECTION_MODEL=llama3.2
OLLAMA_TIMEOUT=120

# OCR-Pipeline: LLM-Review (Schritt 6)
# Kleine Modelle reichen fuer Zeichen-Korrekturen (0->O, 1->l, 5->S)
# Optionen: qwen3:0.6b, qwen3:1.7b, gemma3:1b, qwen3.5:35b-a3b
OLLAMA_REVIEW_MODEL=qwen3:0.6b
# Eintraege pro Ollama-Call. Groesser = weniger HTTP-Overhead.
OLLAMA_REVIEW_BATCH_SIZE=20

# OCR-Pipeline: Engine fuer Schritt 5 (Worterkennung)
# Optionen: auto (bevorzugt RapidOCR), rapid, tesseract,
#           trocr-printed, trocr-handwritten, lighton
OCR_ENGINE=auto

# Klausur-HTR: Primaerem Modell fuer Handschriftenerkennung (qwen2.5vl bereits auf Mac Mini)
OLLAMA_HTR_MODEL=qwen2.5vl:32b
# HTR Fallback: genutzt wenn Ollama nicht erreichbar (auto-download ~340 MB)
HTR_FALLBACK_MODEL=trocr-large

# Anthropic (optional)
ANTHROPIC_API_KEY=

# vast.ai GPU (optional)
VAST_API_KEY=
VAST_INSTANCE_ID=

# Game
GAME_USE_DATABASE=true
GAME_REQUIRE_AUTH=false
GAME_REQUIRE_BILLING=false
GAME_LLM_MODEL=llama3.2

# Frontend URLs
NEXT_PUBLIC_API_URL=https://macmini:8001
NEXT_PUBLIC_KLAUSUR_SERVICE_URL=https://macmini:8086
NEXT_PUBLIC_VOICE_SERVICE_URL=wss://macmini:8091

# Session
SESSION_TTL_HOURS=24

# SMTP (uses Core Mailpit)
SMTP_HOST=bp-core-mailpit
SMTP_PORT=1025
