* fix(model-picker): serve cached custom-provider catalog on no-probe opens
#58183 stopped GUI picker opens from live-probing saved custom
OpenAI-compatible endpoints so a stopped local server could not stall the
picker. It gated the whole discovery block, not just the network call, so
`cached_fetch_api_models()` was skipped too — and with it the catalog an
earlier probe had already written to `provider_models_cache.json`.
A custom endpoint that is not the current provider therefore renders only
the models named in its config entry. A local server with 8 models loaded
shows the 1 model that was saved when the provider was first added, on
every picker open, while an explicit Refresh shows all 8.
Add `cache_only` to `cached_fetch_api_models()`: answer from disk within
the existing stale-serve window, never fetch, never revalidate off-thread,
return None on a miss. Split the three call sites in
`list_authenticated_providers()` into what the user's config permits
(`discover_models`, an explicit `models:` allowlist) and how we may obtain
it, so suppressing the probe now downgrades to a cached read instead of
skipping discovery outright. `discover_models: false` still pins, and a
cache hit no longer writes back to config since the probe that populated
it already did.
The latency win stands: a cold cache is a miss, so picker opens against
offline endpoints still make zero network calls.
* test(model-picker): pin the cached-catalog contract for no-probe opens
Cover both halves of the invariant, since fixing either one alone
reintroduces a bug the other guards against.
`cache_only` on `cached_fetch_api_models()`: a fresh entry and an entry
past its TTL but inside the stale-serve window both serve; an entry beyond
that window, an empty cache, rotated credentials, `force_refresh`, and a
missing base_url are all misses — and none of them fetch or spawn a
background revalidation.
`list_authenticated_providers()` on the GUI path: a non-current endpoint
with a warm cache reports its full catalog across all three provider
shapes (`custom_providers`, `providers:`, bare `provider: custom`) with no
live fetch attempted. A cold cache keeps the configured list and still
makes no network call, which is the #58183 guarantee. `discover_models:
false` keeps pinning, and a cache hit does not write back to config.
* fix: persist discovered custom-provider models in the hermes model flow
The `hermes model` named-custom-provider flow (_model_flow_named_custom)
probes the endpoint and shows the full catalog, but never persists it to the
entry's `models:` list. No-probe surfaces (dashboard, desktop, ACP) call
build_models_payload(..., probe_custom_providers=False) and only render the
configured `models:` list, so a provider added via `hermes model` collapses
to the single `model:` default everywhere except the CLI. OpenAI-compatible
providers added via a probing picker already benefit from
_save_discovered_models_to_config; the CLI flow did not.
Persist the live catalog after a successful probe, mirroring the picker path
in model_switch.py. A failed save is non-fatal.
* fix(model-picker): stop an auto-saved catalog pinning a keyless endpoint
The cached-catalog read added for no-probe picker opens still sat behind
the no-key discovery gate, so it never reached the shape that motivated
it: a keyless local model server.
`bool(api_key) or not has_explicit_models` is a network-cost gate. It
exists so Hermes does not probe an endpoint it cannot authenticate to
when that endpoint already declares its catalog (5f00f36ba, 1039e90b5).
Reading a catalog an earlier probe already paid for costs nothing, so
the gate belongs on the probe, not on discovery as a whole.
Left on the discovery side it re-pins the endpoint it was meant to
spare. A successful probe calls `_save_discovered_models_to_config()`,
which writes a plain list into `models:` — exactly the shape
`_models_config_is_allowlist()` reads back as an explicit user
allowlist. A keyless server therefore froze on the catalog of its first
probe and could never widen again, which is the "lineup changes after
config was written" case. f66319097 already carved the dict shape out of
this trap for the same reason; the list shape is the other door into it.
Move the clause to `_probe_live` at both custom-endpoint sites. Probe
suppression is unchanged — verified byte-identical to main across the
keyed/keyless x declared/undeclared matrix — and `discover_models: false`
remains the documented way to pin a catalog.
* test(model-picker): cover the keyless auto-save pinning trap
Three tests around the gate move, each failing on the code before it:
- a keyless endpoint carrying an auto-saved `models:` list still reads
its full cached catalog
- the same row, cold cache and probing enabled, still makes zero live
fetches — the network-cost gate the clause exists for
- an end-to-end round trip: persist a probe result via
`_save_discovered_models_to_config()`, reload it, and assert the shape
we wrote does not read back as a user pin
The round-trip test guards the whole chain rather than one branch, so a
future change that makes the saved shape look like an intentional
allowlist fails here even if the gate logic is refactored.
* fix(model-picker): key the custom-endpoint model cache by api_mode
`cached_fetch_api_models()` fingerprints entries with `api_mode`, but no
call site in `list_authenticated_providers()` passed it, so every custom
row resolved to the `api_mode=None` fingerprint. Two rows sharing a
base_url and credential but differing by `api_mode` are deliberately
distinct picker rows — it is part of `group_key` at both sites — yet they
collapsed onto one cache entry.
That was latent while probing was the only way to fill a row: a mismatched
entry was overwritten by the row's own live fetch. Serving that entry
without a probe makes it visible, so an `anthropic_messages` row could
render the catalog an OpenAI-mode row cached against the same URL. The
wire protocols differ (`x-api-key` + `anthropic-version` vs
`Authorization: Bearer`), so those catalogs are not interchangeable.
Persist `api_mode` on the group at both grouping sites — it is already
part of `group_key`, so it is constant across the group — and pass it
into the cache read. Section 3b (bare `provider: custom`) has no
`api_mode` in scope and already reads with the empty-credential
fingerprint, so it is unchanged.
Reported by Copilot review on #81973.
---------
Co-authored-by: xxxigm <tuancanhnguyen706@gmail.com>
Co-authored-by: Navlem <114683850+Navlem@users.noreply.github.com>
Use providers keys as the canonical custom-provider identity while accepting legacy bare keys, display-name slugs, bare custom fallback, and doubled custom prefixes across resolution, pickers, doctor, and runtime reverse lookup.
Co-authored-by: Bakhtier Sizhaev <bakhtiersizhaev@users.noreply.github.com>
Sibling fix for #65977 — _model_flow_bedrock_api_key used only
get_env_value for AWS_BEARER_TOKEN_BEDROCK, missing pool-backed
keys. Now uses _resolve_api_key_provider_secret like the other
flows.
hermes model's custom-endpoint flow is the other write path that produced a
plaintext key, on both the model block and the custom_providers entry. Route
it through the same .env indirection as the Desktop panel, and swap an
existing entry's inline key for the reference when the URL is re-saved.
Co-authored-by: liuhao1024 <sunsky.lau@gmail.com>
- Refresh _OFFICIAL_DOCS_PRICING fireworks entries against current
docs.fireworks.ai/serverless/pricing: qwen3p6-plus is gone (replaced
by qwen3p7-plus); add glm-5p2/5p1, kimi-k2p7-code, deepseek-v4-flash,
minimax-m3/m2p7, gpt-oss-120b/20b, and the routers/*-fast tiers with
their distinct higher rates.
- Picker pricing via get_pricing_for_provider('fireworks'): pure dict
transform over the shared models.dev in-memory/disk cache (1h TTL) +
_pricing_cache memoization — no new network call on the picker path.
- Wire pricing display into the generic api-key-provider setup flow so
Fireworks model pickers show $/M columns like OpenRouter/Nous do.
- Invariant tests: plugin fallback_models all priced, fast tiers price
higher than standard, every row carries cache_read < input.
Bug 2 of #28156: the picker offered us./global. inference profiles to
EU-region endpoints (unroutable — AWS rejects them regardless of
credentials) and _RECOMMENDED hardcoded us.anthropic.* ids, so non-US
pickers pinned profiles their endpoint can't invoke.
- bedrock_model_routable_from_region(): geo-prefixed profiles are only
offered in their own geography (full AWS prefix set incl. apac./jp./
ca./sa./me./af.); bare ids and global.* pass everywhere; unknown
region shapes hide nothing.
- Recommendations match geo-agnostically on the base model id, so an EU
picker pins eu.anthropic.claude-sonnet-4-6; in-region geo profiles
sort above global.* for the same model (addresses the global.*-first
ordering complaint from the issue thread).
- Dedup generalized from (us., global.) to all profile prefixes.
ruff check --fix --select F541 . on current main. Pure prefix removals;
adjacent-string concatenations keep the f only on interpolating fragments.
No string content or live placeholder altered.
Replace the loopback/PKCE-callback server and manual-paste fallback with
the RFC 8628 device-code flow as the only xAI Grok OAuth login path. The
flow works in headless/SSH/container sessions with no 127.0.0.1 listener,
shrinking the local attack surface.
- Poll the token endpoint with server-provided interval, honoring
slow_down and expires_in; store tokens with auth_mode
oauth_device_code.
- Adaptive proactive refresh skew for short-lived device-code JWTs;
rotated tokens sync back to auth.json, the global root store, and the
credential pool (no refresh-token replay).
- Clear source suppression on successful re-login (CLI + dashboard) and
drop the duplicate dashboard pool entry so exactly one seeded
device_code entry exists.
- Use the shared device_code source name for consistency with the
nous/codex device-code providers.
- Desktop: remove the loopback OAuth flow states and dead type variants;
pkce providers' sign-in URL selection is unchanged.
- Docs (EN + zh-Hans) rewritten for device-code login; drop the deleted
--manual-paste flag from documented commands.
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.
Selecting 'Mixture of Agents' in the `hermes model` provider picker fell
through silently — select_provider_and_model had no moa branch, so it just
reprinted the current model/provider summary and exited. And the CLI session
banner rendered the bare preset name (e.g. 'opus-gpt · Nous Research'),
which is meaningless out of context.
- Add _model_flow_moa: always lists the available presets (even one), then
prints the full reference-models + aggregator breakdown for the selection
and persists model.provider=moa / model.default=<preset> (dropping stale
base_url + endpoint creds, since moa is a virtual local provider).
- Wire the branch into select_provider_and_model.
- build_welcome_banner takes provider; when 'moa' it renders
'MoA: <preset> · agg <aggregator>' instead of a bare slug. Both CLI call
sites pass self.provider.
Tests: 2 new banner tests (moa + non-moa unchanged); E2E verified the picker
persists the preset and clears stale base_url/api_key.
- Remove dead `chosen_base or effective_base` fallback; _select_zai_endpoint
always returns a non-empty base URL (returns current_base on cancel).
- Add .rstrip("/") to official-endpoint return for symmetry with custom-proxy
path (both now return normalized URLs).
- Replace magic index 4 with len(ZAI_ENDPOINTS) in custom-proxy tests so they
don't break if a 5th endpoint is added to ZAI_ENDPOINTS.
When provider_id == 'zai', replace the plain text Base URL input with
_select_zai_endpoint, which presents a curses picker offering Global,
China, Coding Plan Global, Coding Plan China, and custom proxy options.
Other API-key providers (MiniMax, DeepSeek, etc.) keep the text input.
Presents a curses-based picker (via _prompt_provider_choice) offering the
four official Z.AI endpoints — Global, China, Coding Plan Global, Coding
Plan China — plus a custom-proxy option. Sourced from ZAI_ENDPOINTS in
auth.py so it stays in sync with the probe list.
Not yet wired into the setup flow; that comes in the next commit.
* feat(providers): remove google-gemini-cli + google-antigravity OAuth providers
Google now actively bans accounts for third-party tools that piggyback on
Gemini CLI / Antigravity / Code Assist OAuth, and because abuse prevention
sits at a backend layer the ban can extend to the entire Google account
(Gmail/Drive), with a second violation being permanent.
Ref: https://github.com/google-gemini/gemini-cli/discussions/20632
Removes both OAuth inference providers entirely (modules, provider profiles,
auth/runtime/config/models wiring, the /gquota Code Assist quota command,
the antigravity-cli optional skill, desktop + docs surface in en + zh-Hans).
The API-key 'gemini' provider (GOOGLE_API_KEY/GEMINI_API_KEY against
generativelanguage.googleapis.com) is unaffected and stays fully supported.
* fix(skills): keep the antigravity-cli skill — only the OAuth provider is removed
The antigravity-cli optional skill orchestrates the external `agy` binary as
a coding-agent tool via the terminal tool — it does NOT wrap Hermes inference
through the banned google-antigravity OAuth provider, so it carries none of
the account-ban risk that motivated removing that provider. Restore the skill,
its docs page, the sidebar entry, and the optional-skills catalog row. The
google-antigravity / google-gemini-cli inference providers stay fully removed.
CI on the salvage caught two issues the stale PR base masked:
1. The model-setup flows were extracted from main.py into
hermes_cli/model_setup_flows.py after @pmos69 forked. The cherry-pick
re-introduced a stale _model_flow_custom into main.py (duplicating the
one main.py now imports) and put _model_flow_google_antigravity there too.
Move the antigravity flow into model_setup_flows.py alongside its siblings
and drop the stale _model_flow_custom dup. Fixes the getpass/stdin OSError
in tests/cli/test_cli_provider_resolution.py.
2. google-antigravity re-exposes Claude/Gemini/GPT-OSS models, so its catalog
was hijacking bare short aliases (`sonnet` -> google-antigravity instead of
anthropic) in detect_static_provider_for_model via dict insertion order.
Add _BORROWED_MODEL_PROVIDERS and defer those providers to a last-resort
pass so a model's native vendor always wins alias/direct-catalog detection.
Fixes tests/hermes_cli/test_models.py::test_short_alias_resolves_to_static_model.
Switch the default model for the xAI/Grok provider and the xAI web
search backend from grok-4.3 to grok-build-0.1. grok-build-0.1 is
already recognized by the model metadata, so no new model definition
is required; grok-4.3 remains selectable.
Rebased onto current main and re-ported across the restructured
surfaces: model flows now thread confirm_provider/base_url/api_key
through hermes_cli/model_setup_flows.py, the Discord picker lives in
plugins/platforms/discord/adapter.py, and the web dashboard picker
applies chat-mode switches via config.set so the expensive-model
confirmation can ride the response.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
xAI's consent page renders the authorization code in-page instead of
redirecting to the loopback callback, so the listener just hangs and the
manual-paste flow demands a callback URL that never contains the token.
- auth.py: poll stdin non-blockingly while waiting for the xAI loopback
callback; accept a pasted bare Grok Build code and substitute the locally
generated state (PKCE code_verifier still binds the exchange). No need to
wait for timeout or re-run with --manual-paste.
- computer_use: parse PNG/JPEG dimensions from base64 and fall back to the
text/AX/SOM payload when the screenshot is below the provider minimum
(8x8), which xAI rejects with HTTP 400.
- model_setup_flows.py: xAI credential reuse prompt uses the standard radio
picker via a shared _prompt_auth_credentials_choice helper.
- main.py: thread a title through _prompt_provider_choice; re-home the helper
import (flows live in model_setup_flows.py post-decomposition).
Salvaged from #36781 onto current main (contributor's main.py edits re-homed
to model_setup_flows.py, where the flows were extracted since the PR opened).
Lift the 18 _model_flow_* provider-setup wizard functions out of hermes_cli/main.py
into hermes_cli/model_setup_flows.py. Behavior-neutral; main.py 14050 -> 11479 LOC.
select_provider_and_model (the dispatcher) STAYS in main.py and re-imports the
flows via an explicit 'from hermes_cli.model_setup_flows import (...)' block, so
both its bare-name calls and existing test monkeypatches targeting
hermes_cli.main._model_flow_* keep resolving against main's namespace unchanged.
Imports: 3 neutral deps (argparse, os, subprocess) at the module top; the 14
main.py-internal helpers the flows call (_prompt_api_key, _save_custom_provider,
the reasoning-effort/stepfun/qwen helpers, _run_anthropic_oauth_flow, ...) are
lazy-imported per-flow (from hermes_cli.main import ...) so the new module never
imports main at module scope -> no import cycle.
Repointed one source-inspection change-detector (test_setup_ollama_cloud_force_refresh)
to read the module the ollama-cloud branch moved to.
Validation: 6563/6563 hermes_cli tests pass; live flow-dispatch probe confirms the
lazy main-internal imports resolve at runtime.
Austin Pickett
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