# Telegram MTProto credentials — get from https://my.telegram.org
TG_API_ID=
TG_API_HASH=
TG_PHONE=

# --- ONE OF THE TWO BELOW IS REQUIRED ---
# Preferred (no volumes, k8s-friendly): get the string by running
#   docker compose run --rm -it app python -m parser_bot.auth
# It prints `TG_SESSION_STRING=...` — paste that line here.
TG_SESSION_STRING=

# Fallback (file-based): only used if TG_SESSION_STRING is empty.
# Requires mounting ./data/session as a volume.
TG_SESSION_PATH=/data/session/parser.session

# Postgres
POSTGRES_USER=parser
POSTGRES_PASSWORD=parser
POSTGRES_DB=parser
POSTGRES_HOST=db
POSTGRES_PORT=5432

# Polling
POLL_INTERVAL_SECONDS=60
POLL_HISTORY_LIMIT=50

# API
API_HOST=0.0.0.0
API_PORT=8000

# Media (downloaded photos / small videos / docs from parsed messages)
MEDIA_DIR=/data/media
MEDIA_MAX_BYTES=20971520

# OpenAI-compatible LLM endpoint. In production this can point to the same
# vLLM server/model used by telephony.
LLM_ENABLED=true
LLM_BASE_URL=http://10.2.3.5:8002
LLM_API_KEY=
LLM_MODEL=qwen2.5-14b
LLM_TIMEOUT_SECONDS=120
LLM_MAX_TOKENS=600
LLM_MIN_TEXT_LENGTH=20
# How often the background classifier wakes up and how many messages it
# processes per tick. With 5/20s ≈ 900 messages/hour at ~3-6s per call.
LLM_CLASSIFY_INTERVAL_SECONDS=20
LLM_CLASSIFY_BATCH_SIZE=5

# Optional local fallback for admin-only UI/API operations. In production the
# portal forwards X-User-Is-Admin=1, so no local password is required.
ADMIN_PASSWORD=