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daily-ai-summary/.env.example
2026-07-11 16:26:41 +02:00

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# --- AI Configuration ---
OLLAMA_API_URL=http://localhost:11434/api/generate
OLLAMA_MODEL=llama3.2:1b
# How long to wait for the (CPU-only) model to respond before giving up
OLLAMA_TIMEOUT_SECONDS=300
# The script now feeds the AI pre-extracted, structured facts (not raw log
# lines), so this prompt only needs to tell it HOW to write, not what to look
# for -- the analysis itself happens in Python before the AI ever runs.
# A sensible default is baked into daily_summary.py; override here only if
# you want different tone/length.
# AI_SYSTEM_PROMPT="..."
# --- Email Reporting Configuration ---
REPORT_TO_EMAIL=admin@yourdomain.com
REPORT_FROM_EMAIL=system@yourdomain.com
SMTP_SERVER=mail.yourdomain.com
SMTP_PORT=587
SMTP_USER=
SMTP_PASS=
# --- Log Analysis Configuration ---
JOURNAL_UNIT=mailserver
# Comma-separated CIDR ranges allowed to log in to mailboxes. Logins from
# outside these ranges are flagged in the report as noteworthy.
TRUSTED_LOGIN_NETWORKS=10.0.0.0/24
# --- Multi-day repeat-offender tracking ---
# Requires the /data mount added to the systemd unit (bind-mounted, read-write)
# so this state survives across container restarts/daily runs.
STATE_FILE=/data/offender_state.json
# An IP gets called out as a repeat offender once seen on this many distinct days
REPEAT_OFFENDER_THRESHOLD_DAYS=3
# IPs not seen again within this many days are dropped from tracking
OFFENDER_RETENTION_DAYS=30
# --- Execution Options ---
# Set to 'true' to see detailed background processes, 'false' for clean logs
DEBUG=true
# Set to 'true' to run also immediately when the container starts, 'false' to wait for the schedule
# NOTE: leave this 'false' in production. Combined with the systemd unit's
# Restart=always, an immediate run on every container (re)start can cause
# duplicate/rapid-fire reports if the container is restarting frequently.
RUN_NOW=true
# Time format must be HH:MM in 24-hour format
REPORT_TIME=08:00