server:
  host: 127.0.0.1
  port: 9000

# ── Global timezone ─────────────────────────────────────────────────────────────
# IANA timezone name applied globally to:
#   - cron expression evaluation (next_run_at computation)
#   - the date/time string injected into the LLM context each turn
# When omitted, the server's local system timezone is used.
# Examples: Europe/Rome, Europe/London, America/New_York, Asia/Tokyo
#
# timezone: Europe/Rome
# ────────────────────────────────────────────────────────────────────────────────

web:
  static_dir: ./web

# ── Connector marketplace ──────────────────────────────────────────────────────
# The feed of vetted connectors the admin browses under Connectors → Marketplace.
# It is *consultative*: the feed proposes, the admin installs into the local
# catalog, and only then can a connector be enabled globally or activated by a
# user. The trust anchor stays on this box.
#
# Point it at a self-hosted mirror or a local copy to run fully offline — the feed
# is plain static files (`connectors.json` + `<folder>/connector.json`).
marketplace:
  url: https://connectors.skaldagent.net

# The database lives at ./database/system.db — fixed, not configurable.


# ── LLM clients ────────────────────────────────────────────────────────────────
# LLM clients (providers, models, API keys, strength) are configured
# via the web app and stored in the database — not in this file.
# ───────────────────────────────────────────────────────────────────────────────
llm:
  # ── History window (DISABLED by default) ────────────────────────────────────
  # Hard cap on the number of history messages sent to the LLM, applied as a
  # sliding tail window: past the cap, the oldest messages are dropped.
  #
  # Off by default, for two reasons:
  #   1. Cache. Once history exceeds the cap, every turn shifts the window's
  #      start, so the prompt prefix changes on every single request and the
  #      provider's prompt cache (Anthropic breakpoints, OpenAI automatic prefix
  #      caching) misses every time. Append-only history keeps the prefix stable
  #      for the whole conversation.
  #   2. Memory. The window drops messages with no summary standing in for them,
  #      so the assistant silently forgets. `/compact` replaces them with a
  #      summary instead.
  #
  # With this off and automatic compaction off (the shipped default), the context
  # grows until the model's own limit — use `/compact` to summarise it.
  # Ignored when automatic compaction is enabled (see `compaction` below).
  #
  # max_history_messages: 30
  # ───────────────────────────────────────────────────────────────────────────
  max_tool_rounds: 100
  # Max synchronous sub-agents dispatched concurrently when the LLM emits a
  # homogeneous batch (≥2) of sub-agent calls (execute_task mode=sync /
  # execute_subtask) in a single response. Bounds fan-out to avoid provider
  # rate-limit storms. Omit for the default (4); set to 1 to force sequential.
  max_parallel_subagents: 4
  # Injects "Current date and time: Sunday 2026-08-02 17:00 +02:00 (Europe/Rome)"
  # as the last system message of each request. The time is always truncated to
  # the hour and the block tells the model so, pointing it at `date` when it
  # needs the exact minute — there is no rounding setting.
  datetime:
    enabled: true

  # ── Tool result size limit ──────────────────────────────────────────────────
  # When set, tool results from *previous* turns that exceed this character
  # count are replaced (at context-build time) with a short placeholder:
  #   "[Tool response hidden: N chars. Call the tool again if you need it.]"
  # The original result is always preserved in the database and shown in the
  # frontend; only what the LLM receives in subsequent turns is affected.
  # The current turn always sees full results regardless of this limit.
  # Omit or comment out to disable (no limit).
  max_tool_result_chars: 10000
  # ───────────────────────────────────────────────────────────────────────────

  # ── Context compaction (AUTOMATIC pass disabled by default) ─────────────────
  # Compaction summarises old history into a single block, persisted to the DB
  # and injected at the start of subsequent turns in place of the messages it
  # covers, keeping the last `keep_recent` raw messages for immediate context.
  #
  # The `/compact` command works ALWAYS and needs nothing here — this whole
  # section is optional and only tunes it.
  #
  # `threshold_tokens` is what arms the AUTOMATIC pass: set it, and history is
  # compacted on its own once the previous turn exceeded that many input tokens.
  # It is COMMENTED OUT by default: every compaction rewrites the prompt prefix
  # and so costs a prompt-cache miss, and doing it unprompted trades away context
  # the user may still need. Compact manually with `/compact` for now.
  # (Future: an automatic pass triggered by the model's own context window rather
  # than by a hand-tuned token count.)
  #
  # `strength` controls which LLM is picked for summary generation via the AUTO
  # selector (same strength levels used for agent assignment). Compaction is a
  # simple writing task — `low` or `average` is usually sufficient.
  # Omit `strength` to use whatever AUTO picks.
  # NOTE: the Settings page has an instance-wide "Compaction model" picker
  # (registry config key `compaction_model`) — when set, it wins over this
  # `strength` fallback and needs no restart.
  #
  # When the LLM provider does not report token usage (e.g. some LM Studio
  # setups), a rough estimate (total chars / 4) is used as a fallback.
  #
  # compaction:
  #   threshold_tokens: 30000   # arms the automatic pass, above this many input tokens
  #   keep_recent: 6            # raw messages kept outside the summary
  #   strength: low             # LLM strength for summary generation
  # ───────────────────────────────────────────────────────────────────────────

  # ── Date/time injection ─────────────────────────────────────────────────────
  # Configured above as `datetime`. The only setting is `enabled`.
  # The injected time is always truncated to the hour: not for the prompt cache
  # (the block is the LAST system message, so the cached prefix never changes
  # whatever the timestamp says) but because a second-precision stamp reads as
  # exact to the model long after it stopped being true. The block states the
  # granularity and tells the agent to run `date` when it needs the minute.
  #   enabled: true          # set to false to disable injection entirely
  # ───────────────────────────────────────────────────────────────────────────

  # ── LLM request/response log ────────────────────────────────────────────────
  # Logs every chat_with_tools call to the `llm_requests` table.
  # Captures the full HTTP request body, response body, headers (api-key redacted),
  # token counts, and round-trip duration.
  #
  # WARNING: disabling `enabled` also disables the home-page LLM statistics.
  #
  # What to save (all default to true):
  #   request_payload_save  — full request JSON (can be hundreds of KB per call)
  #   response_payload_save — full response JSON
  #   request_header_save   — HTTP request headers (api-key always redacted)
  #   response_header_save  — HTTP response headers
  #
  # Cleanup policy (all optional — omit to keep data forever):
  #   cleanup_request_payload_after  — set request_json = '' after N days
  #   cleanup_response_payload_after — set response_json = NULL after N days
  #   cleanup_headers_after          — null out both header columns after N days
  #   cleanup_rows_after             — physically delete rows after N days
  #
  # The cleaner runs 1 minute after startup, then every 12 hours.
  #
  requests_log:
    enabled: true
    request_payload_save: false
    response_payload_save: true
    request_header_save: true
    response_header_save: true
    cleanup_request_payload_after: 7
    cleanup_response_payload_after: 14
    cleanup_headers_after: 30
    cleanup_rows_after: 90
  # ───────────────────────────────────────────────────────────────────────────

# ── Event triage (background event processor) ──────────────────────────────────
# Runs periodically to process pending MCP events (email, calendar, WhatsApp) and
# decide whether to surface a notification to the user.
#
# NOTE: top-level, NOT under `llm:` — nesting it there parses fine and is then
# silently ignored.
#
# interval_secs  — how often it runs (default: 900 = 15 minutes)
# batch_size     — max events processed per pass (default: 50)
#
# event_triage:
#   interval_secs: 900
#   batch_size: 50
# ───────────────────────────────────────────────────────────────────────────────