config.ini.example

# OwnSona CLI configuration template.
#
# Copy this file to the OS-specific default location:
#
#   Linux / BSD     ~/.config/ownsona/config.ini
#   macOS           ~/Library/Application Support/ownsona/config.ini
#   Windows         %LOCALAPPDATA%\ownsona\config.ini
#
# Or point $OWNSONA_CONFIG at it.  --server / --token also work as
# per-invocation flags.
#
# After copying, set `server_url` below and then run:
#
#   ownsona auth login
#
# That command performs an OAuth 2.1 auth code flow against the AS
# that protects your server.  It opens a browser, you sign in, and the
# resulting OAuth state gets written back into this file under the
# auto-managed `oauth_*` keys at the bottom.  Refresh happens
# automatically before each subsequent CLI call.

server_url = https://your.host/mcp

# Legacy / external-IdP path: a static bearer token used verbatim with
# no refresh.  Leave commented out unless you're talking to a server
# that issues long-lived tokens out of band.
# token = REPLACE_ME

# Shared secret that authorizes changing a memory's `keep` protection
# flag (the `enumerate` k/r actions).  Must match the server's
# OwnsonaAdminSecret.  Only the CLI sends it, and only on set_keep
# calls; leave it unset if you never manage the keep flag.
# Env override: OWNSONA_ADMIN_SECRET
# admin_secret = REPLACE_ME

# ---------------------------------------------------------------------
# Settings below are used only by the `teach` subcommand (LLM-driven
# fact extraction from prose).  Other subcommands ignore them.
# ---------------------------------------------------------------------

# OpenAI-compatible chat-completion endpoint.  Defaults to OpenAI's;
# point at any service that exposes the same /chat/completions shape
# (OpenRouter, a local Ollama server with the OpenAI compat layer, etc.).
# Env override: OWNSONA_LLM_BASE_URL
# llm_base_url = https://api.openai.com/v1

# Model used by `teach` to extract facts from prose.  gpt-4o is the
# recommended default; gpt-4o-mini works at ~10x lower cost with
# noticeably lower quality.  Override per-invocation with --model.
# Env override: OWNSONA_LLM_MODEL
# llm_model = gpt-4o

# API key for the LLM endpoint.  Can be the same OpenAI key the server
# uses for embeddings, or a separate one if you want isolated billing.
# Required only if you run `teach`.
# Env override: OWNSONA_LLM_API_KEY
# llm_api_key = sk-...

# How `teach` should refer to the subject in extracted facts.
# Defaults to "the user"; set to your own name (e.g. "Blake") so the
# extracted memories match the style of your existing ones.
# Env override: OWNSONA_SUBJECT
# subject_name = Blake

# ---------------------------------------------------------------------
# Below this point: managed by `ownsona auth login` and the per-request
# refresh path.  You normally do not edit these by hand; if they look
# stale or broken, run `ownsona auth login` again.
# ---------------------------------------------------------------------
# oauth_client_id                 = (set by `auth login`)
# oauth_refresh_token             = (set by `auth login` and rotated on each refresh)
# oauth_access_token              = (rotated on each refresh; ~1h TTL)
# oauth_access_token_expires_at   = (Unix epoch seconds)
# oauth_authorization_server      = (auto-discovered via RFC 9728 if unset)
# oauth_resource                  = (defaults to server_url)