agent/vertex_adapter.py resolved VERTEX_CREDENTIALS_PATH,
GOOGLE_APPLICATION_CREDENTIALS, VERTEX_PROJECT_ID, and VERTEX_REGION via raw
os.environ.get() instead of the profile-scoped get_secret() every other
credential lookup in hermes_cli/runtime_provider.py uses. In a multiplex
gateway serving several profiles from one process, os.environ still holds
whichever profile's .env python-dotenv loaded at boot — so a raw read here
let one profile's turn silently mint a Vertex OAuth2 token from, and get
billed against, a different profile's GCP service account. No error, no
fail-closed guard: the multiplex UnscopedSecretError protection was bypassed
entirely because these reads never went through get_secret().
- _resolve_credentials_path/_resolve_project_override/_resolve_region now
call agent.secret_scope.get_secret(), matching the _getenv() pattern
already used for every other provider's credentials.
- get_vertex_credentials()'s ADC fallback (google.auth.default()) reads
GOOGLE_APPLICATION_CREDENTIALS from os.environ internally, bypassing
get_secret() entirely — closed with a narrow guard: when multiplexing is
active and this profile's scope has no Vertex credentials of its own, but
os.environ still carries a value (left by a different profile's boot-time
dotenv load), refuse ADC rather than silently authenticate as a stranger.
- Zero behavior change for single-profile installs: get_secret() falls
through to os.environ transparently whenever multiplexing is off.
Same bug class as the already-fixed _HERMES_OAUTH_FILE/_AUTH_JSON_PATH/
HOOKS_DIR cross-profile leaks, now closed for Vertex's OAuth2 credential
path.
Adds Vertex AI as a first-class provider for Gemini models via Vertex's
OpenAI-compatible endpoint. Vertex authenticates with short-lived OAuth2
access tokens (service-account JSON or ADC), not a static API key — the
missing piece behind the recurring requests (#13484, #12639, #56259).
- agent/vertex_adapter.py: OAuth2 token minting + refresh-on-expiry
(5-min margin), ADC->service-account fallback, global vs regional
endpoint URLs. Config precedence: env var > config.yaml > default.
- plugins/model-providers/vertex/: provider profile (auth_type=vertex),
reuses Gemini's extra_body.google.thinking_config translation.
- runtime_provider: vertex short-circuit BEFORE the credential pool so a
credentials-file path is never mistaken for a static API key; mints a
fresh token + computes base_url per resolve.
- run_agent + conversation_loop: _try_refresh_vertex_client_credentials()
re-mints the token and rebuilds the client on a mid-session 401, so a
long-lived gateway agent survives token expiry (~1h).
- auxiliary_client: vertex auth_type branch for side-LLM tasks.
- config.yaml: vertex.project_id / vertex.region (non-secret, bridged to
env); credential path stays in .env (VERTEX_CREDENTIALS_PATH).
- setup wizard + model picker: dedicated _model_flow_vertex; curated
google/gemini-* model list; --provider choices.
- pricing/metadata: Vertex prices off the gemini docs snapshot; endpoint
host auto-maps to the vertex provider (no probe spam).
- lazy_deps + pyproject [vertex] extra: google-auth, opt-in only.
- docs: guides/google-vertex.md + providers page; tests for adapter +
runtime resolution.
Salvages and modernizes #8427 by @slawt onto current main: rewired from
the legacy PROVIDER_REGISTRY path to the provider-profile architecture,
moved non-secret config out of .env into config.yaml, and added the
per-turn 401 token-refresh the original lacked.
