Two remaining gaps from the codex empty-output spec:
1. Normalize dict-shaped streamed items: output_item.done events may
yield dicts (raw/fallback paths) instead of SDK objects. The
extraction loop now uses _item_get() that handles both getattr
and dict .get() access.
2. Avoid plain-text synthesis when function_call events were streamed:
tracks has_function_calls during streaming and skips text-delta
synthesis when tool calls are present — prevents collapsing a
tool-call response into a fake text message.
The _CodexCompletionsAdapter (used for compression, vision, web_extract,
session_search, and memory flush when on the codex provider) streamed
responses but discarded all events with 'for _event in stream: pass'.
When get_final_response() returned empty output (the same chatgpt.com
backend-api shape change), auxiliary calls silently returned None content.
Now collects response.output_item.done and text deltas during streaming
and backfills empty output — same pattern as _run_codex_stream().
Tested live against chatgpt.com/backend-api/codex with OAuth.
Two fixes:
1. Replace all stale 'hermes login' references with 'hermes auth' across
auth.py, auxiliary_client.py, delegate_tool.py, config.py, run_agent.py,
and documentation. The 'hermes login' command was deprecated; 'hermes auth'
now handles OAuth credential management.
2. Fix credential removal not persisting for singleton-sourced credentials
(device_code for openai-codex/nous, hermes_pkce for anthropic).
auth_remove_command already cleared env vars for env-sourced credentials,
but singleton credentials stored in the auth store were re-seeded by
_seed_from_singletons() on the next load_pool() call. Now clears the
underlying auth store entry when removing singleton-sourced credentials.
When a user runs out of OpenRouter credits and switches to Codex (or any
other provider), auxiliary tasks (compression, vision, web_extract) would
still try OpenRouter first and fail with 402. Two fixes:
1. Payment fallback in call_llm(): When a resolved provider returns HTTP 402
or a credit-related error, automatically retry with the next available
provider in the auto-detection chain. Skips the depleted provider and
tries Nous → Custom → Codex → API-key providers.
2. Remove hardcoded OpenRouter fallback: The old code fell back specifically
to OpenRouter when auto/custom resolution returned no client. Now falls
back to the full auto-detection chain, which handles any available
provider — not just OpenRouter.
Also extracts _get_provider_chain() as a shared function (replaces inline
tuple in _resolve_auto and the new fallback), built at call time so test
patches on _try_* functions remain visible.
Adds 16 tests covering _is_payment_error(), _get_provider_chain(),
_try_payment_fallback(), and call_llm() integration with 402 retry.
Users on direct API-key providers (Alibaba, DeepSeek, ZAI, etc.) without
an OpenRouter or Nous key would get broken auxiliary tasks (compression,
vision, etc.) because _resolve_auto() only tried aggregator providers
first, then fell back to iterating PROVIDER_REGISTRY with wrong default
model names.
Now _resolve_auto() checks the user's main provider first. If it's not
an aggregator (OpenRouter/Nous), it uses their main model directly for
all auxiliary tasks. Aggregator users still get the cheap gemini-flash
model as before.
Adds _read_main_provider() to read model.provider from config.yaml,
mirroring the existing _read_main_model().
Reported by SkyLinx — Alibaba Coding Plan user getting 400 errors from
google/gemini-3-flash-preview being sent to DashScope.
Setup wizard now shows existing allowed_users when reconfiguring a
platform and preserves them if the user presses Enter. Previously the
wizard would display a misleading "No allowlist set" warning even when
the .env still held the original IDs.
Also downgrades the "provider X has no API key configured" log from
WARNING to DEBUG in resolve_provider_client — callers already handle
the None return with their own contextual messages. This eliminates
noisy startup warnings for providers in the fallback chain that the
user never configured (e.g. minimax).
* feat(auth): add same-provider credential pools and rotation UX
Add same-provider credential pooling so Hermes can rotate across
multiple credentials for a single provider, recover from exhausted
credentials without jumping providers immediately, and configure
that behavior directly in hermes setup.
- agent/credential_pool.py: persisted per-provider credential pools
- hermes auth add/list/remove/reset CLI commands
- 429/402/401 recovery with pool rotation in run_agent.py
- Setup wizard integration for pool strategy configuration
- Auto-seeding from env vars and existing OAuth state
Co-authored-by: kshitijk4poor <82637225+kshitijk4poor@users.noreply.github.com>
Salvaged from PR #2647
* fix(tests): prevent pool auto-seeding from host env in credential pool tests
Tests for non-pool Anthropic paths and auth remove were failing when
host env vars (ANTHROPIC_API_KEY) or file-backed OAuth credentials
were present. The pool auto-seeding picked these up, causing unexpected
pool entries in tests.
- Mock _select_pool_entry in auxiliary_client OAuth flag tests
- Clear Anthropic env vars and mock _seed_from_singletons in auth remove test
* feat(auth): add thread safety, least_used strategy, and request counting
- Add threading.Lock to CredentialPool for gateway thread safety
(concurrent requests from multiple gateway sessions could race on
pool state mutations without this)
- Add 'least_used' rotation strategy that selects the credential
with the lowest request_count, distributing load more evenly
- Add request_count field to PooledCredential for usage tracking
- Add mark_used() method to increment per-credential request counts
- Wrap select(), mark_exhausted_and_rotate(), and try_refresh_current()
with lock acquisition
- Add tests: least_used selection, mark_used counting, concurrent
thread safety (4 threads × 20 selects with no corruption)
* feat(auth): add interactive mode for bare 'hermes auth' command
When 'hermes auth' is called without a subcommand, it now launches an
interactive wizard that:
1. Shows full credential pool status across all providers
2. Offers a menu: add, remove, reset cooldowns, set strategy
3. For OAuth-capable providers (anthropic, nous, openai-codex), the
add flow explicitly asks 'API key or OAuth login?' — making it
clear that both auth types are supported for the same provider
4. Strategy picker shows all 4 options (fill_first, round_robin,
least_used, random) with the current selection marked
5. Remove flow shows entries with indices for easy selection
The subcommand paths (hermes auth add/list/remove/reset) still work
exactly as before for scripted/non-interactive use.
* fix(tests): update runtime_provider tests for config.yaml source of truth (#4165)
Tests were using OPENAI_BASE_URL env var which is no longer consulted
after #4165. Updated to use model config (provider, base_url, api_key)
which is the new single source of truth for custom endpoint URLs.
* feat(auth): support custom endpoint credential pools keyed by provider name
Custom OpenAI-compatible endpoints all share provider='custom', making
the provider-keyed pool useless. Now pools for custom endpoints are
keyed by 'custom:<normalized_name>' where the name comes from the
custom_providers config list (auto-generated from URL hostname).
- Pool key format: 'custom:together.ai', 'custom:local-(localhost:8080)'
- load_pool('custom:name') seeds from custom_providers api_key AND
model.api_key when base_url matches
- hermes auth add/list now shows custom endpoints alongside registry
providers
- _resolve_openrouter_runtime and _resolve_named_custom_runtime check
pool before falling back to single config key
- 6 new tests covering custom pool keying, seeding, and listing
* docs: add Excalidraw diagram of full credential pool flow
Comprehensive architecture diagram showing:
- Credential sources (env vars, auth.json OAuth, config.yaml, CLI)
- Pool storage and auto-seeding
- Runtime resolution paths (registry, custom, OpenRouter)
- Error recovery (429 retry-then-rotate, 402 immediate, 401 refresh)
- CLI management commands and strategy configuration
Open at: https://excalidraw.com/#json=2Ycqhqpi6f12E_3ITyiwh,c7u9jSt5BwrmiVzHGbm87g
* fix(tests): update setup wizard pool tests for unified select_provider_and_model flow
The setup wizard now delegates to select_provider_and_model() instead
of using its own prompt_choice-based provider picker. Tests needed:
- Mock select_provider_and_model as no-op (provider pre-written to config)
- Call _stub_tts BEFORE custom prompt_choice mock (it overwrites it)
- Pre-write model.provider to config so the pool step is reached
* docs: add comprehensive credential pool documentation
- New page: website/docs/user-guide/features/credential-pools.md
Full guide covering quick start, CLI commands, rotation strategies,
error recovery, custom endpoint pools, auto-discovery, thread safety,
architecture, and storage format.
- Updated fallback-providers.md to reference credential pools as the
first layer of resilience (same-provider rotation before cross-provider)
- Added hermes auth to CLI commands reference with usage examples
- Added credential_pool_strategies to configuration guide
* chore: remove excalidraw diagram from repo (external link only)
* refactor: simplify credential pool code — extract helpers, collapse extras, dedup patterns
- _load_config_safe(): replace 4 identical try/except/import blocks
- _iter_custom_providers(): shared generator for custom provider iteration
- PooledCredential.extra dict: collapse 11 round-trip-only fields
(token_type, scope, client_id, portal_base_url, obtained_at,
expires_in, agent_key_id, agent_key_expires_in, agent_key_reused,
agent_key_obtained_at, tls) into a single extra dict with
__getattr__ for backward-compatible access
- _available_entries(): shared exhaustion-check between select and peek
- Dedup anthropic OAuth seeding (hermes_pkce + claude_code identical)
- SimpleNamespace replaces class _Args boilerplate in auth_commands
- _try_resolve_from_custom_pool(): shared pool-check in runtime_provider
Net -17 lines. All 383 targeted tests pass.
---------
Co-authored-by: kshitijk4poor <82637225+kshitijk4poor@users.noreply.github.com>
OPENAI_BASE_URL was written to .env AND config.yaml, creating a dual-source
confusion. Users (especially Docker) would see the URL in .env and assume
that's where all config lives, then wonder why LLM_MODEL in .env didn't work.
Changes:
- Remove all 27 save_env_value("OPENAI_BASE_URL", ...) calls across main.py,
setup.py, and tools_config.py
- Remove OPENAI_BASE_URL env var reading from runtime_provider.py, cli.py,
models.py, and gateway/run.py
- Remove LLM_MODEL/HERMES_MODEL env var reading from gateway/run.py and
auxiliary_client.py — config.yaml model.default is authoritative
- Vision base URL now saved to config.yaml auxiliary.vision.base_url
(both setup wizard and tools_config paths)
- Tests updated to set config values instead of env vars
Convention enforced: .env is for SECRETS only (API keys). All other
configuration (model names, base URLs, provider selection) lives
exclusively in config.yaml.
The auxiliary client's auto-detection chain was a black box — when
compression, summarization, or memory flush failed, the only clue was
a generic 'Request timed out' with no indication of which provider was
tried or why it was skipped.
Now logs at INFO level:
- 'Auxiliary auto-detect: using local/custom (qwen3.5-9b) — skipped:
openrouter, nous' when auto-detection picks a provider
- 'Auxiliary compression: using auto (qwen3.5-9b) at http://localhost:11434/v1'
before each auxiliary call
- 'Auxiliary compression: provider custom unavailable, falling back to
openrouter' on fallback
- Clear warning with actionable guidance when NO provider is available:
'Set OPENROUTER_API_KEY or configure a local model in config.yaml'
Local inference servers (Ollama, llama.cpp, vLLM, LM Studio) don't
require API keys, but the auxiliary client's _resolve_custom_runtime()
rejected endpoints with empty keys — causing the auto-detection chain
to skip the user's local server entirely. This broke compression,
summarization, and memory flush for users running local models without
an OpenRouter/cloud API key.
The main CLI already had this fix (PR #2556, 'no-key-required'
placeholder), but the auxiliary client's resolution path was missed.
Two fixes:
- _resolve_custom_runtime(): use 'no-key-required' placeholder instead
of returning None when base_url is present but key is empty
- resolve_provider_client() custom branch: same placeholder fallback
for explicit_base_url without explicit_api_key
Updates 2 tests that expected the old (broken) behavior.
Add per-task timeout settings under auxiliary.{task}.timeout in config.yaml
instead of hardcoded values. Users with slow local models (Ollama, llama.cpp)
can now increase timeouts for compression, vision, session search, etc.
Defaults:
- auxiliary.compression.timeout: 120s (was hardcoded 45s)
- auxiliary.vision.timeout: 30s (unchanged)
- all other aux tasks: 30s (was hardcoded 30s)
- title_generator: 30s (was hardcoded 15s)
call_llm/async_call_llm now auto-resolve timeout from config when not
explicitly passed. Callers can still override with an explicit timeout arg.
Based on PR #3406 by alanfwilliams. Converted from env vars to config.yaml
per project conventions.
Co-authored-by: alanfwilliams <alanfwilliams@users.noreply.github.com>
Salvage of #3389 by @binhnt92 with reasoning fallback and retry logic added on top.
All 7 auxiliary LLM call sites now use extract_content_or_reasoning() which mirrors the main agent loop's behavior: extract content, strip think blocks, fall back to structured reasoning fields, retry on empty.
Closes#3389.
The OpenAI SDK's AsyncHttpxClientWrapper.__del__ schedules aclose() via
asyncio.get_running_loop().create_task(). When an AsyncOpenAI client is
garbage-collected while prompt_toolkit's event loop is running (the common
CLI idle state), the aclose() task runs on prompt_toolkit's loop but the
underlying TCP transport is bound to a different (dead) worker loop.
The transport's self._loop.call_soon() then raises RuntimeError('Event
loop is closed'), which prompt_toolkit surfaces as the disruptive
'Unhandled exception in event loop ... Press ENTER to continue...' error.
Three-layer fix:
1. neuter_async_httpx_del(): Monkey-patches __del__ to a no-op at CLI
startup before any AsyncOpenAI clients are created. Safe because
cached clients are explicitly cleaned via _force_close_async_httpx,
and uncached clients' TCP connections are cleaned by the OS on exit.
2. Custom asyncio exception handler: Installed on prompt_toolkit's event
loop to silently suppress 'Event loop is closed' RuntimeError.
Defense-in-depth for SDK upgrades that might change the class name.
3. cleanup_stale_async_clients(): Called after each agent turn (when the
agent thread joins) to proactively evict cache entries whose event
loop is closed, preventing stale clients from accumulating.
_try_anthropic() caught ImportError on the module import (line 667-669)
but not on the build_anthropic_client() call (line 696). When the
anthropic_adapter module imports fine but the anthropic SDK is missing,
build_anthropic_client() raises ImportError at call time. This escaped
_try_anthropic() entirely, killing get_available_vision_backends() and
cascading to 7 test failures:
- 4 setup wizard tests hit unexpected 'Configure vision:' prompt
- 3 codex-auth-as-vision tests failed check_vision_requirements()
The fix wraps the build_anthropic_client call in try/except ImportError,
returning (None, None) when the SDK is unavailable — consistent with the
existing guard at the top of the function.
Nous Portal now passes through OpenRouter model names and routes from
there. Update the static fallback model list and auxiliary client default
to use OpenRouter-format slugs (provider/model) instead of bare names.
- _PROVIDER_MODELS['nous']: full OpenRouter catalog
- _NOUS_MODEL: google/gemini-3-flash-preview (was gemini-3-flash)
- Updated 4 test assertions for the new default model name
In gateway mode, async tools (vision_analyze, web_extract, session_search)
deadlock because _run_async() spawns a thread with asyncio.run(), creating
a new event loop, but _get_cached_client() returns an AsyncOpenAI client
bound to a different loop. httpx.AsyncClient cannot work across event loop
boundaries, causing await client.chat.completions.create() to hang forever.
Fix: include the event loop identity in the async client cache key so each
loop gets its own AsyncOpenAI instance. Also fix session_search_tool.py
which had its own broken asyncio.run()-in-thread pattern — now uses the
centralized _run_async() bridge.
When AsyncOpenAI clients are garbage-collected after the event loop
closes, their AsyncHttpxClientWrapper.__del__ tries to schedule
aclose() on the dead loop, causing RuntimeError: Event loop is closed.
prompt_toolkit catches this as an unhandled exception and shows
'Press ENTER to continue...' which blocks CLI exit.
Fix: Add shutdown_cached_clients() to auxiliary_client.py that marks
all cached async clients' underlying httpx transport as CLOSED before
GC runs. This prevents __del__ from attempting the aclose() call.
- _force_close_async_httpx(): sets httpx AsyncClient._state to CLOSED
- shutdown_cached_clients(): iterates _client_cache, closes sync clients
normally and marks async clients as closed
- Also fix stale client eviction in _get_cached_client to mark evicted
async clients as closed (was just del-ing them, triggering __del__)
- Call shutdown_cached_clients() from _run_cleanup() in cli.py
When a non-OpenRouter provider (e.g. minimax, anthropic) is set in
config.yaml but its API key is missing, Hermes silently fell back to
OpenRouter, causing confusing 404 errors.
Now checks if the user explicitly configured a provider before falling
back. Explicit providers raise RuntimeError with a clear message naming
the missing env var. Auto/openrouter/custom providers still fall through
to OpenRouter as before.
Three code paths fixed:
- run_agent.py AIAgent.__init__ — main client initialization
- auxiliary_client.py call_llm — sync auxiliary calls
- auxiliary_client.py call_llm_streaming — async auxiliary calls
Based on PR #2272 by @StefanIsMe. Applied manually to fix a
pconfig NameError in the original and extend to call_llm_streaming.
Co-authored-by: StefanIsMe <StefanIsMe@users.noreply.github.com>
Two bugs in the auxiliary provider auto-detection chain:
1. Expired Codex JWT blocks the auto chain: _read_codex_access_token()
returned any stored token without checking expiry, preventing fallback
to working providers. Now decodes JWT exp claim and returns None for
expired tokens.
2. Auxiliary Anthropic client missing OAuth identity transforms:
_AnthropicCompletionsAdapter always called build_anthropic_kwargs with
is_oauth=False, causing 400 errors for OAuth tokens. Now detects OAuth
tokens via _is_oauth_token() and propagates the flag through the
adapter chain.
Cherry-picked from PR #2378 by 0xbyt4. Fixed test_api_key_no_oauth_flag
to mock resolve_anthropic_token directly (env var alone was insufficient).
Only honor config.model.base_url for Anthropic resolution when
config.model.provider is actually "anthropic". This prevents a Codex
(or other provider) base_url from leaking into Anthropic runtime and
auxiliary client paths, which would send requests to the wrong
endpoint.
Closes#2384
Cherry-picked from PR #2146 by @crazywriter1. Fixes#2104.
asyncio.run() creates and closes a fresh event loop each call. Cached
httpx/AsyncOpenAI clients bound to the dead loop crash on GC with
'Event loop is closed'. This hit vision_analyze on first use in CLI.
Two-layer fix:
- model_tools._run_async(): replace asyncio.run() with persistent
loop via _get_tool_loop() + run_until_complete()
- auxiliary_client._get_cached_client(): track which loop created
each async client, discard stale entries if loop is closed
6 regression tests covering loop lifecycle, reuse, and full vision
dispatch chain.
Co-authored-by: Test <test@test.com>
After #1675 removed ANTHROPIC_BASE_URL env var support, the Anthropic
provider base URL was hardcoded to https://api.anthropic.com. Now reads
model.base_url from config.yaml as an override, falling back to the
default when not set. Also applies to the auxiliary client.
Cherry-picked from PR #1949 by @rivercrab26.
Co-authored-by: rivercrab26 <rivercrab26@users.noreply.github.com>
MiniMax: Add M2.7 and M2.7-highspeed as new defaults across provider
model lists, auxiliary client, metadata, setup wizard, RL training tool,
fallback tests, and docs. Retain M2.5/M2.1 as alternatives.
OpenRouter: Add grok-4.20-beta, nemotron-3-super-120b-a12b:free,
trinity-large-preview:free, glm-5-turbo, and hunter-alpha to the
model catalog.
MiniMax changes based on PR #1882 by @octo-patch (applied manually
due to stale conflicts in refactored pricing module).
Add first-class GitHub Copilot and Copilot ACP provider support across
model selection, runtime provider resolution, CLI sessions, delegated
subagents, cron jobs, and the Telegram gateway.
This also normalizes Copilot model catalogs and API modes, introduces a
Copilot ACP OpenAI-compatible shim, and fixes service-mode auth by
resolving Homebrew-installed gh binaries under launchd.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
- Add summary_base_url config option to compression block for custom
OpenAI-compatible endpoints (e.g. zai, DeepSeek, Ollama)
- Remove compression env var bridges from cli.py and gateway/run.py
(CONTEXT_COMPRESSION_* env vars no longer set from config)
- Switch run_agent.py to read compression config directly from
config.yaml instead of env vars
- Fix backwards-compat block in _resolve_task_provider_model to also
fire when auxiliary.compression.provider is 'auto' (DEFAULT_CONFIG
sets this, which was silently preventing the compression section's
summary_* keys from being read)
- Add test for summary_base_url config-to-client flow
- Update docs to show compression as config.yaml-only
Closes#1591
Based on PR #1702 by @uzaylisak
The module-level auxiliary_is_nous was set to True by _try_nous() and
never reset. In long-running gateway processes, once Nous was resolved
as auxiliary provider, the flag stayed True forever — even if
subsequent resolutions chose a different provider (e.g. OpenRouter).
This caused Nous product tags to be sent to non-Nous providers.
Reset the flag at the start of _resolve_auto() so only the winning
provider's flag persists.
* fix: thread safety for concurrent subagent delegation
Four thread-safety fixes that prevent crashes and data races when
running multiple subagents concurrently via delegate_task:
1. Remove redirect_stdout/stderr from delegate_tool — mutating global
sys.stdout races with the spinner thread when multiple children start
concurrently, causing segfaults. Children already run with
quiet_mode=True so the redirect was redundant.
2. Split _run_single_child into _build_child_agent (main thread) +
_run_single_child (worker thread). AIAgent construction creates
httpx/SSL clients which are not thread-safe to initialize
concurrently.
3. Add threading.Lock to SessionDB — subagents share the parent's
SessionDB and call create_session/append_message from worker threads
with no synchronization.
4. Add _active_children_lock to AIAgent — interrupt() iterates
_active_children while worker threads append/remove children.
5. Add _client_cache_lock to auxiliary_client — multiple subagent
threads may resolve clients concurrently via call_llm().
Based on PR #1471 by peteromallet.
* feat: Honcho base_url override via config.yaml + quick command alias type
Two features salvaged from PR #1576:
1. Honcho base_url override: allows pointing Hermes at a remote
self-hosted Honcho deployment via config.yaml:
honcho:
base_url: "http://192.168.x.x:8000"
When set, this overrides the Honcho SDK's environment mapping
(production/local), enabling LAN/VPN Honcho deployments without
requiring the server to live on localhost. Uses config.yaml instead
of env var (HONCHO_URL) per project convention.
2. Quick command alias type: adds a new 'alias' quick command type
that rewrites to another slash command before normal dispatch:
quick_commands:
sc:
type: alias
target: /context
Supports both CLI and gateway. Arguments are forwarded to the
target command.
Based on PR #1576 by redhelix.
---------
Co-authored-by: peteromallet <peteromallet@users.noreply.github.com>
Co-authored-by: redhelix <redhelix@users.noreply.github.com>
Add Kilo Gateway (kilo.ai) as an API-key provider with OpenAI-compatible
endpoint at https://api.kilo.ai/api/gateway. Supports 500+ models from
Anthropic, OpenAI, Google, xAI, Mistral, MiniMax via a single API key.
- Register kilocode in PROVIDER_REGISTRY with aliases (kilo, kilo-code,
kilo-gateway) and KILOCODE_API_KEY / KILOCODE_BASE_URL env vars
- Add to model catalog, CLI provider menu, setup wizard, doctor checks
- Add google/gemini-3-flash-preview as default aux model
- 12 new tests covering registration, aliases, credential resolution,
runtime config
- Documentation updates (env vars, config, fallback providers)
- Fix setup test index shift from provider insertion
Inspired by PR #1473 by @amanning3390.
Co-authored-by: amanning3390 <amanning3390@users.noreply.github.com>
Add support for OpenCode Zen (pay-as-you-go, 35+ curated models) and
OpenCode Go ($10/month subscription, open models) as first-class providers.
Both are OpenAI-compatible endpoints resolved via the generic api_key
provider flow — no custom adapter needed.
Files changed:
- hermes_cli/auth.py — ProviderConfig entries + aliases
- hermes_cli/config.py — OPENCODE_ZEN/GO API key env vars
- hermes_cli/models.py — model catalogs, labels, aliases, provider order
- hermes_cli/main.py — provider labels, menu entries, model flow dispatch
- hermes_cli/setup.py — setup wizard branches (idx 10, 11)
- agent/model_metadata.py — context lengths for all OpenCode models
- agent/auxiliary_client.py — default aux models
- .env.example — documentation
Co-authored-by: DevAgarwal2 <DevAgarwal2@users.noreply.github.com>
* feat: add Vercel AI Gateway as a first-class provider
Adds AI Gateway (ai-gateway.vercel.sh) as a new inference provider
with AI_GATEWAY_API_KEY authentication, live model discovery, and
reasoning support via extra_body.reasoning.
Based on PR #1492 by jerilynzheng.
* feat: add AI Gateway to setup wizard, doctor, and fallback providers
* test: add AI Gateway to api_key_providers test suite
* feat: add AI Gateway to hermes model CLI and model metadata
Wire AI Gateway into the interactive model selection menu and add
context lengths for AI Gateway model IDs in model_metadata.py.
* feat: use claude-haiku-4.5 as AI Gateway auxiliary model
* revert: use gemini-3-flash as AI Gateway auxiliary model
* fix: move AI Gateway below established providers in selection order
---------
Co-authored-by: jerilynzheng <jerilynzheng@users.noreply.github.com>
Co-authored-by: jerilynzheng <zheng.jerilyn@gmail.com>
Add base_url/api_key overrides for auxiliary tasks and delegation so users can
route those flows straight to a custom OpenAI-compatible endpoint without
having to rely on provider=main or named custom providers.
Also clear gateway session env vars in test isolation so the full suite stays
deterministic when run from a messaging-backed agent session.
* fix: prevent model/provider mismatch when switching providers during active gateway
When _update_config_for_provider() writes the new provider and base_url
to config.yaml, the gateway (which re-reads config per-message) can pick
up the change before model selection completes. This causes the old model
name (e.g. 'anthropic/claude-opus-4.6') to be sent to the new provider's
API (e.g. MiniMax), which fails.
Changes:
- _update_config_for_provider() now accepts an optional default_model
parameter. When provided and the current model.default is empty or
uses OpenRouter format (contains '/'), it sets a safe default model
for the new provider.
- All setup.py callers for direct-API providers (zai, kimi, minimax,
minimax-cn, anthropic) now pass a provider-appropriate default model.
- _setup_provider_model_selection() now validates the 'Keep current'
choice: if the current model uses OpenRouter format and wouldn't work
with the new provider, it warns and switches to the provider's first
default model instead of silently keeping the incompatible name.
Reported by a user on Home Assistant whose gateway started sending
'anthropic/claude-opus-4.6' to MiniMax's API after running hermes setup.
* fix: auxiliary client uses main model for custom/local endpoints instead of gpt-4o-mini
When a user runs a local server (e.g. Qwen3.5-9B via OPENAI_BASE_URL),
the auxiliary client (context compression, vision, session search) would
send requests for 'gpt-4o-mini' or 'google/gemini-3-flash-preview' to
the local server, which only serves one model — causing 404 errors
mid-task.
Changes:
- _try_custom_endpoint() now reads the user's configured main model via
_read_main_model() (checks OPENAI_MODEL → HERMES_MODEL → LLM_MODEL →
config.yaml model.default) instead of hardcoding 'gpt-4o-mini'.
- resolve_provider_client() auto mode now detects when an OpenRouter-
formatted model override (containing '/') would be sent to a non-
OpenRouter provider (like a local server) and drops it in favor of
the provider's default model.
- Test isolation fixes: properly clear env vars in 'nothing available'
tests to prevent host environment leakage.
Fixes from comprehensive code review and cross-referencing with
clawdbot/OpenCode implementations:
CRITICAL:
- Add one-shot guard (anthropic_auth_retry_attempted) to prevent
infinite 401 retry loops when credentials keep changing
- Fix _is_oauth_token(): managed keys from ~/.claude.json are NOT
regular API keys (don't start with sk-ant-api). Inverted the logic:
only sk-ant-api* is treated as API key auth, everything else uses
Bearer auth + oauth beta headers
HIGH:
- Wrap json.loads(args) in try/except in message conversion — malformed
tool_call arguments no longer crash the entire conversation
- Raise AuthError in runtime_provider when no Anthropic token found
(was silently passing empty string, causing confusing API errors)
- Remove broken _try_anthropic() from auxiliary vision chain — the
centralized router creates an OpenAI client for api_key providers
which doesn't work with Anthropic's Messages API
MEDIUM:
- Handle empty assistant message content — Anthropic rejects empty
content blocks, now inserts '(empty)' placeholder
- Fix setup.py existing_key logic — set to 'KEEP' sentinel instead
of None to prevent falling through to the auth choice prompt
- Add debug logging to _fetch_anthropic_models on failure
Tests: 43 adapter tests (2 new for token detection), 3197 total passed
* fix: stop rejecting unlisted models + auto-detect from /models endpoint
validate_requested_model() now accepts models not in the provider's API
listing with a warning instead of blocking. Removes hardcoded catalog
fallback for validation — if API is unreachable, accepts with a warning.
Model selection flows (setup + /model command) now probe the provider's
/models endpoint to get the real available models. Falls back to
hardcoded defaults with a clear warning when auto-detection fails:
'Could not auto-detect models — use Custom model if yours isn't listed.'
Z.AI setup no longer excludes GLM-5 on coding plans.
* fix: use hermes-agent.nousresearch.com as HTTP-Referer for OpenRouter
OpenRouter scrapes the favicon/logo from the HTTP-Referer URL for app
rankings. We were sending the GitHub repo URL, which gives us a generic
GitHub logo. Changed to the proper website URL so our actual branding
shows up in rankings.
Changed in run_agent.py (main agent client) and auxiliary_client.py
(vision/summarization clients).
Feedback fixes:
1. Revert _convert_vision_content — vision is handled by the vision_analyze
tool, not by converting image blocks inline in conversation messages.
Removed the function and its tests.
2. Add Anthropic to 'hermes model' (cmd_model in main.py):
- Added to provider_labels dict
- Added to providers selection list
- Added _model_flow_anthropic() with Claude Code credential auto-detection,
API key prompting, and model selection from catalog.
3. Wire up Anthropic as a vision-capable auxiliary provider:
- Added _try_anthropic() to auxiliary_client.py using claude-sonnet-4
as the vision model (Claude natively supports multimodal)
- Added to the get_vision_auxiliary_client() auto-detection chain
(after OpenRouter/Nous, before Codex/custom)
Cache tracking note: the Anthropic cache metrics branch in run_agent.py
(cache_read_input_tokens / cache_creation_input_tokens) is in the correct
place — it's response-level parsing, same location as the existing
OpenRouter cache tracking. auxiliary_client.py has no cache tracking.
