xAI's grok-imagine-image API returns ephemeral imgen.x.ai/xai-tmp-* URLs
that 404 within minutes — long before downstream consumers (Telegram
send_photo, browser preview, multi-tier delivery fallback) get a chance
to fetch them. The xAI image_gen provider was passing those URLs
through unchanged on the elif url: branch; b64 responses were already
cached locally via save_b64_image. Result: every image_generate call
on a Telegram-routed xai-oauth profile delivered no image, falling
through to text-only.
Adds agent.image_gen_provider.save_url_image() — a sibling helper to
save_b64_image that downloads URL bytes to $HERMES_HOME/cache/images/.
Content-type-aware extension inference with URL-suffix fallback;
oversize cap (25MB default) with partial-write cleanup; empty-body
refusal. Mirrors the audio_cache pattern used by text_to_speech.
Wires save_url_image into both the xAI and OpenAI providers' URL
branches. When the download fails (network blip, 404 in-flight) we
log a warning and fall back to the bare URL rather than turning the
tool call into a hard error — the gateway's existing URL-send fallback
then gets a chance to surface the original error legibly.
Test plan:
- tests/agent/test_save_url_image.py — 8 direct tests against a real
in-process HTTP server: bytes round-trip, content-type → extension,
URL-suffix fallback, default-to-png, 404 propagation, empty-body
refusal, oversize cap + cleanup, filename uniqueness.
- tests/plugins/image_gen/test_xai_provider.py — flip
test_successful_url_response (was asserting the bug), add
test_url_response_falls_back_to_bare_url_when_download_fails.
- tests/plugins/image_gen/test_openai_provider.py — symmetric pair.
160/160 in the broader image_gen test surface.
Mirrors the architecture established by the web (#25182), browser
(#25214), and video_gen (#25126) plugin migrations:
* `tools/fal_common.py` — stateless atoms shared by both FAL-backed
plugins (image_gen + video_gen). Holds the lazy `fal_client` import
helper, `_ManagedFalSyncClient`, `_normalize_fal_queue_url_format`,
`_extract_http_status`. Stateful pieces (`fal_client` module global,
`_managed_fal_client*` cache, `_submit_fal_request`,
`_resolve_managed_fal_gateway`, `_get_managed_fal_client`)
intentionally stay on `tools.image_generation_tool` so the existing
`monkeypatch.setattr(image_tool, ...)` patch sites keep working
unchanged.
* `plugins/video_gen/fal/__init__.py` — drops its inline
`_load_fal_client` duplicate; consumes `tools.fal_common.import_fal_client`.
* `plugins/image_gen/fal/{plugin.yaml,__init__.py}` — new plugin.
`FalImageGenProvider` is a thin registration adapter that resolves
the legacy module via `import tools.image_generation_tool as _it`
and calls `_it.image_generate_tool` + `_it._resolve_fal_model` at
call time. The 18-model catalog, `_build_fal_payload`, managed-
gateway selection, and Clarity Upscaler chaining all remain in
`tools.image_generation_tool` as the single source of truth —
the plugin is a registration adapter, not a parallel implementation.
* `tools/image_generation_tool.py::_dispatch_to_plugin_provider` —
drops the `configured == "fal"` skip. Setting `image_gen.provider:
fal` now routes through the registry like any other provider; the
plugin re-enters this module's pipeline so behavior is identical.
Unset `image_gen.provider` still falls through to the in-tree
pipeline (preserves no-config-with-FAL_KEY UX from #15696).
* `hermes_cli/tools_config.py` — drops the hardcoded "FAL.ai" row from
`TOOL_CATEGORIES["image_gen"]["providers"]` (now injected by
`_plugin_image_gen_providers` like every other backend) and the
`getattr(provider, "name") == "fal"` skip that protected against
duplication with the hardcoded row. The "Nous Subscription" row
stays as a setup-flow entry — same shape browser kept "Nous
Subscription (Browser Use cloud)" after #25214.
* `tests/plugins/image_gen/test_fal_provider.py` — 14 cases covering
the ABC surface, call-time indirection (verifying
`monkeypatch.setattr(image_tool, "image_generate_tool", ...)` takes
effect through the plugin), response-shape stamping, exception
handling, and registry wiring.
* `tests/plugins/image_gen/check_parity_vs_main.py` — subprocess
harness mirroring `tests/plugins/browser/check_parity_vs_main.py`.
Pins one path to origin/main, one to the worktree; runs six
scenarios (unset, explicit-fal-no-creds, explicit-fal-with-creds,
explicit-fal-with-model, typo provider, managed-gateway-only) and
diffs the reduced shape `{dispatch_kind, provider_name, model}`
per scenario. The only acceptable diff is "legacy_fal → plugin
(fal)" for explicit-FAL paths — every other delta is flagged as
a regression.
* `tests/hermes_cli/test_image_gen_picker.py::test_fal_surfaced_alongside_other_plugins`
— flips the previous `test_fal_skipped_to_avoid_duplicate` to
match the new shape (FAL is a plugin now, no dedup needed).
Verified: 195/195 tests across
`tests/{tools/test_image_generation*,tools/test_managed_media_gateways,plugins/image_gen,plugins/video_gen,hermes_cli/test_image_gen_picker}.py`
pass on this branch with no test patches modified outside the picker
test that asserted the old skip behaviour.
Fixes#26241
Adds a new authentication provider that lets SuperGrok subscribers sign
in to Hermes with their xAI account via the standard OAuth 2.0 PKCE
loopback flow, instead of pasting a raw API key from console.x.ai.
Highlights
----------
* OAuth 2.0 PKCE loopback login against accounts.x.ai with discovery,
state/nonce, and a strict CORS-origin allowlist on the callback.
* Authorize URL carries `plan=generic` (required for non-allowlisted
loopback clients) and `referrer=hermes-agent` for best-effort
attribution in xAI's OAuth server logs.
* Token storage in `auth.json` with file-locked atomic writes; JWT
`exp`-based expiry detection with skew; refresh-token rotation
synced both ways between the singleton store and the credential
pool so multi-process / multi-profile setups don't tear each other's
refresh tokens.
* Reactive 401 retry: on a 401 from the xAI Responses API, the agent
refreshes the token, swaps it back into `self.api_key`, and retries
the call once. Guarded against silent account swaps when the active
key was sourced from a different (manual) pool entry.
* Auxiliary tasks (curator, vision, embeddings, etc.) route through a
dedicated xAI Responses-mode auxiliary client instead of falling back
to OpenRouter billing.
* Direct HTTP tools (`tools/xai_http.py`, transcription, TTS, image-gen
plugin) resolve credentials through a unified runtime → singleton →
env-var fallback chain so xai-oauth users get them for free.
* `hermes auth add xai-oauth` and `hermes auth remove xai-oauth N` are
wired through the standard auth-commands surface; remove cleans up
the singleton loopback_pkce entry so it doesn't silently reinstate.
* `hermes model` provider picker shows
"xAI Grok OAuth (SuperGrok Subscription)" and the model-flow falls
back to pool credentials when the singleton is missing.
Hardening
---------
* Discovery and refresh responses validate the returned
`token_endpoint` host against the same `*.x.ai` allowlist as the
authorization endpoint, blocking MITM persistence of a hostile
endpoint.
* Discovery / refresh / token-exchange `response.json()` calls are
wrapped to raise typed `AuthError` on malformed bodies (captive
portals, proxy error pages) instead of leaking JSONDecodeError
tracebacks.
* `prompt_cache_key` is routed through `extra_body` on the codex
transport (sending it as a top-level kwarg trips xAI's SDK with a
TypeError).
* Credential-pool sync-back preserves `active_provider` so refreshing
an OAuth entry doesn't silently flip the active provider out from
under the running agent.
Testing
-------
* New `tests/hermes_cli/test_auth_xai_oauth_provider.py` (~63 tests)
covers JWT expiry, OAuth URL params (plan + referrer), CORS origins,
redirect URI validation, singleton↔pool sync, concurrency races,
refresh error paths, runtime resolution, and malformed-JSON guards.
* Extended `test_credential_pool.py`, `test_codex_transport.py`, and
`test_run_agent_codex_responses.py` cover the pool sync-back,
`extra_body` routing, and 401 reactive refresh paths.
* 165 tests passing on this branch via `scripts/run_tests.sh`.
The xAI /v1/images/generations endpoint expects resolution as a
literal string ('1k' or '2k'), not the numeric value ('1024').
- Change _XAI_RESOLUTIONS from a dict mapping to a validation set
- Use the resolution key directly instead of the mapped value
- Fall back to DEFAULT_RESOLUTION on invalid config values
Fixes 422 Unprocessable Entity errors when resolution was sent.
The agent-facing image_generate tool only passes prompt + aspect_ratio to
provider.generate() (see tools/image_generation_tool.py:953). The editing
block (reference_images / edit_image kwargs) could never fire from the
tool surface, and the xAI edits endpoint is /images/edits with a
different payload shape anyway — not /images/generations as submitted.
- Remove reference_images / edit_image kwargs handling from generate()
- Remove matching test_with_reference_images case
- Update docstring + plugin.yaml description to text-to-image only
- Surface resolution in the success extras
Follow-up to PR #14547. Tests: 18/18 pass.
New built-in image_gen backend at plugins/image_gen/openai-codex/ that
exposes the same gpt-image-2 low/medium/high tier catalog as the
existing 'openai' plugin, but routes generation through the ChatGPT/
Codex Responses image_generation tool path. Available whenever the user
has Codex OAuth signed in; no OPENAI_API_KEY required.
The two plugins are independent — users select between them via
'hermes tools' → Image Generation, and image_gen.provider in
config.yaml. The existing 'openai' (API-key) plugin is unchanged.
Reuses _read_codex_access_token() and _codex_cloudflare_headers() from
agent.auxiliary_client so token expiry / cred-pool / Cloudflare
originator handling stays in one place.
Inspired by #14047 by @Hygaard, but re-implemented as a separate
plugin instead of an in-place fork of the openai plugin.
Closes#11195
* feat(plugins): pluggable image_gen backends + OpenAI provider
Adds a ImageGenProvider ABC so image generation backends register as
bundled plugins under `plugins/image_gen/<name>/`. The plugin scanner
gains three primitives to make this work generically:
- `kind:` manifest field (`standalone` | `backend` | `exclusive`).
Bundled `kind: backend` plugins auto-load — no `plugins.enabled`
incantation. User-installed backends stay opt-in.
- Path-derived keys: `plugins/image_gen/openai/` gets key
`image_gen/openai`, so a future `tts/openai` cannot collide.
- Depth-2 recursion into category namespaces (parent dirs without a
`plugin.yaml` of their own).
Includes `OpenAIImageGenProvider` as the first consumer (gpt-image-1.5
default, plus gpt-image-1, gpt-image-1-mini, DALL-E 3/2). Base64
responses save to `$HERMES_HOME/cache/images/`; URL responses pass
through.
FAL stays in-tree for this PR — a follow-up ports it into
`plugins/image_gen/fal/` so the in-tree `image_generation_tool.py`
slims down. The dispatch shim in `_handle_image_generate` only fires
when `image_gen.provider` is explicitly set to a non-FAL value, so
existing FAL setups are untouched.
- 41 unit tests (scanner recursion, kind parsing, gate logic,
registry, OpenAI payload shapes)
- E2E smoke verified: bundled plugin autoloads, registers, and
`_handle_image_generate` routes to OpenAI when configured
* fix(image_gen/openai): don't send response_format to gpt-image-*
The live API rejects it: 'Unknown parameter: response_format'
(verified 2026-04-21 with gpt-image-1.5). gpt-image-* models return
b64_json unconditionally, so the parameter was both unnecessary and
actively broken.
* feat(image_gen/openai): gpt-image-2 only, drop legacy catalog
gpt-image-2 is the latest/best OpenAI image model (released 2026-04-21)
and there's no reason to expose the older gpt-image-1.5 / gpt-image-1 /
dall-e-3 / dall-e-2 alongside it — slower, lower quality, or awkward
(dall-e-2 squares only). Trim the catalog down to a single model.
Live-verified end-to-end: landscape 1536x1024 render of a Moog-style
synth matches prompt exactly, 2.4MB PNG saved to cache.
* feat(image_gen/openai): expose gpt-image-2 as three quality tiers
Users pick speed/fidelity via the normal model picker instead of a
hidden quality knob. All three tier IDs resolve to the single underlying
gpt-image-2 API model with a different quality parameter:
gpt-image-2-low ~15s fast iteration
gpt-image-2-medium ~40s default
gpt-image-2-high ~2min highest fidelity
Live-measured on OpenAI's API today: 15.4s / 40.8s / 116.9s for the
same 1024x1024 prompt.
Config:
image_gen.openai.model: gpt-image-2-high
# or
image_gen.model: gpt-image-2-low
# or env var for scripts/tests
OPENAI_IMAGE_MODEL=gpt-image-2-medium
Live-verified end-to-end with the low tier: 18.8s landscape render of a
golden retriever in wildflowers, vision-confirmed exact match.
* feat(tools_config): plugin image_gen providers inject themselves into picker
'hermes tools' → Image Generation now shows plugin-registered backends
alongside Nous Subscription and FAL.ai without tools_config.py needing
to know about them. OpenAI appears as a third option today; future
backends appear automatically as they're added.
Mechanism:
- ImageGenProvider gains an optional get_setup_schema() hook
(name, badge, tag, env_vars). Default derived from display_name.
- tools_config._plugin_image_gen_providers() pulls the schemas from
every registered non-FAL plugin provider.
- _visible_providers() appends those rows when rendering the Image
Generation category.
- _configure_provider() handles the new image_gen_plugin_name marker:
writes image_gen.provider and routes to the plugin's list_models()
catalog for the model picker.
- _toolset_needs_configuration_prompt('image_gen') stops demanding a
FAL key when any plugin provider reports is_available().
FAL is skipped in the plugin path because it already has hardcoded
TOOL_CATEGORIES rows — when it gets ported to a plugin in a follow-up
PR the hardcoded rows go away and it surfaces through the same path
as OpenAI.
Verified live: picker shows Nous Subscription / FAL.ai / OpenAI.
Picking OpenAI prompts for OPENAI_API_KEY, then shows the
gpt-image-2-low/medium/high model picker sourced from the plugin.
397 tests pass across plugins/, tools_config, registry, and picker.
* fix(image_gen): close final gaps for plugin-backend parity with FAL
Two small places that still hardcoded FAL:
- hermes_cli/setup.py status line: an OpenAI-only setup showed
'Image Generation: missing FAL_KEY'. Now probes plugin providers
and reports '(OpenAI)' when one is_available() — or falls back to
'missing FAL_KEY or OPENAI_API_KEY' if nothing is configured.
- image_generate tool schema description: said 'using FAL.ai, default
FLUX 2 Klein 9B'. Rewrote provider-neutral — 'backend and model are
user-configured' — and notes the 'image' field can be a URL or an
absolute path, which the gateway delivers either way via
extract_local_files().
