Follow-up on the native NVIDIA NIM provider salvage. The original PR wired
PROVIDER_REGISTRY + HERMES_OVERLAYS correctly but missed several touchpoints
required for full parity with other OpenAI-compatible providers (xai,
huggingface, deepseek, zai).
Gaps closed:
- hermes_cli/main.py:
- Add 'nvidia' to the _model_flow_api_key_provider dispatch tuple so
selecting 'NVIDIA NIM' in `hermes model` actually runs the api-key
provider flow (previously fell through silently).
- Add 'nvidia' to `hermes chat --provider` argparse choices so the
documented test command (`hermes chat --provider nvidia --model ...`)
parses successfully.
- hermes_cli/config.py: Register NVIDIA_API_KEY and NVIDIA_BASE_URL in
OPTIONAL_ENV_VARS so setup wizard can prompt for them and they're
auto-added to the subprocess env blocklist.
- hermes_cli/doctor.py: Add NVIDIA NIM row to `_apikey_providers` so
`hermes doctor` probes https://integrate.api.nvidia.com/v1/models.
- hermes_cli/dump.py: Add NVIDIA_API_KEY → 'nvidia' mapping for
`hermes dump` credential masking.
- tests/tools/test_local_env_blocklist.py: Extend registry_vars fixture
with NVIDIA_API_KEY to verify it's blocked from leaking into subprocesses.
- agent/model_metadata.py: Add 'nemotron' → 131072 context-length entry
so all Nemotron variants get 128K context via substring match (rather
than falling back to MINIMUM_CONTEXT_LENGTH).
- hermes_cli/models.py: Fix hallucinated model ID
'nvidia/nemotron-3-nano-8b-a4b' → 'nvidia/nemotron-3-nano-30b-a3b'
(verified against live integrate.api.nvidia.com/v1/models catalog).
Expand curated list from 5 to 9 agentic models mapping to OpenRouter
defaults per provider-guide convention: add qwen3.5-397b-a17b,
deepseek-v3.2, llama-3.3-nemotron-super-49b-v1.5, gpt-oss-120b.
- cli-config.yaml.example: Document 'nvidia' provider option.
- scripts/release.py: Map asurla@nvidia.com → anniesurla in AUTHOR_MAP
for CI attribution.
E2E verified: `hermes chat --provider nvidia ...` now reaches NVIDIA's
endpoint (returns 401 with bogus key instead of argparse error);
`hermes doctor` detects NVIDIA NIM when NVIDIA_API_KEY is set.
Adds NVIDIA NIM as a first-class provider: ProviderConfig in
auth.py, HermesOverlay in providers.py, curated models
(Nemotron plus other open source models hosted on
build.nvidia.com), URL mapping in model_metadata.py, aliases
(nim, nvidia-nim, build-nvidia, nemotron), and env var tests.
Docs updated: providers page, quickstart table, fallback
providers table, and README provider list.
Move moonshotai/kimi-k2.5 to position #1 in every model picker list:
- OPENROUTER_MODELS (with 'recommended' tag)
- _PROVIDER_MODELS: nous, kimi-coding, opencode-zen, opencode-go, alibaba, huggingface
- _model_flow_kimi() Coding Plan model list in main.py
kimi-coding-cn and moonshot lists already had kimi-k2.5 first.
The Copilot API returns HTTP 400 "model_not_supported" when it receives a
model ID it doesn't recognize (vendor-prefixed like
`anthropic/claude-sonnet-4.6` or dash-notation like `claude-sonnet-4-6`).
Two bugs combined to leave both formats unhandled:
1. `_COPILOT_MODEL_ALIASES` in hermes_cli/models.py only covered bare
dot-notation and vendor-prefixed dot-notation. Hermes' default Claude
IDs elsewhere use hyphens (anthropic native format), and users with an
aggregator-style config who switch `model.provider` to `copilot`
inherit `anthropic/claude-X-4.6` — neither case was in the table.
2. The Copilot branch of `normalize_model_for_provider()` only stripped
the vendor prefix when it matched the target provider (`copilot/`) or
was the special-cased `openai/` for openai-codex. Every other vendor
prefix survived to the Copilot request unchanged.
Fix:
- Add dash-notation aliases (`claude-{opus,sonnet,haiku}-4-{5,6}` and the
`anthropic/`-prefixed variants) to the alias table.
- Rewire the Copilot / Copilot-ACP branch of
`normalize_model_for_provider()` to delegate to the existing
`normalize_copilot_model_id()`. That function already does alias
lookups, catalog-aware resolution, and vendor-prefix fallback — it was
being bypassed for the generic normalisation entry point.
Because `switch_model()` already calls `normalize_model_for_provider()`
for every `/model` switch (line 685 in model_switch.py), this single fix
covers the CLI startup path (cli.py), the `/model` slash command path,
and the gateway load-from-config path.
Closes#6879
Credits dsr-restyn (#6743) who independently diagnosed the dash-notation
case; their aliases are folded into this consolidated fix alongside the
vendor-prefix stripping repair.
Mirrors OpenRouter which already lists anthropic/claude-opus-4.7 as
recommended. Surfaces the model in the `hermes model` picker and the
gateway /model flow for Nous Portal users.
Context length (1M) is already covered by the existing claude-opus-4.7
entry in agent/model_metadata.py DEFAULT_CONTEXT_LENGTHS.
Claude Opus 4.7 introduced several breaking API changes that the current
codebase partially handled but not completely. This patch finishes the
migration per the official migration guide at
https://platform.claude.com/docs/en/about-claude/models/migration-guideFixesNousResearch/hermes-agent#11137
Breaking-change coverage:
1. Adaptive thinking + output_config.effort — 4.7 is now recognized by
_supports_adaptive_thinking() (extends previous 4.6-only gate).
2. Sampling parameter stripping — 4.7 returns 400 for any non-default
temperature / top_p / top_k. build_anthropic_kwargs drops them as a
safety net; the OpenAI-protocol auxiliary path (_build_call_kwargs)
and AnthropicCompletionsAdapter.create() both early-exit before
setting temperature for 4.7+ models. This keeps flush_memories and
structured-JSON aux paths that hardcode temperature from 400ing
when the aux model is flipped to 4.7.
3. thinking.display = "summarized" — 4.7 defaults display to "omitted",
which silently hides reasoning text from Hermes's CLI activity feed
during long tool runs. Restoring "summarized" preserves 4.6 UX.
4. Effort level mapping — xhigh now maps to xhigh (was xhigh→max, which
silently over-efforted every coding/agentic request). max is now a
distinct ceiling per Anthropic's 5-level effort model.
5. New stop_reason values — refusal and model_context_window_exceeded
were silently collapsed to "stop" (end_turn) by the adapter's
stop_reason_map. Now mapped to "content_filter" and "length"
respectively, matching upstream finish-reason handling already in
bedrock_adapter.
6. Model catalogs — claude-opus-4-7 added to the Anthropic provider
list, anthropic/claude-opus-4.7 added at top of OpenRouter fallback
catalog (recommended), claude-opus-4-7 added to model_metadata
DEFAULT_CONTEXT_LENGTHS (1M, matching 4.6 per migration guide).
7. Prefill docstrings — run_agent.AIAgent and BatchRunner now document
that Anthropic Sonnet/Opus 4.6+ reject a trailing assistant-role
prefill (400).
8. Tests — 4 new tests in test_anthropic_adapter covering display
default, xhigh preservation, max on 4.7, refusal / context-overflow
stop_reason mapping, plus the sampling-param predicate. test_model_metadata
accepts 4.7 at 1M context.
Tested on macOS 15.5 (darwin). 119 tests pass in
tests/agent/test_anthropic_adapter.py, 1320 pass in tests/agent/.
provider_model_ids() and list_authenticated_providers() had no case for
"ollama-cloud", so the /model slash command showed 0 models despite
fetch_ollama_cloud_models() being fully implemented. The CLI subcommand
worked because it called fetch_ollama_cloud_models() directly.
- Add ollama-cloud case to provider_model_ids() in models.py
- Populate curated dict for ollama-cloud in list_authenticated_providers()
- Add tests for both code paths
Group A (3 tests): 'No LLM provider configured' RuntimeError
- test_user_message_surrogates_sanitized, test_counters_initialized_in_init,
test_openai_prompt_tokens_unchanged
- Root cause: AIAgent.__init__ now requires base_url alongside api_key to
skip resolve_provider_client() (which returns None when API keys are
blanked in CI). Added base_url='http://localhost:1234/v1' to test
agent construction.
Group B (5 tests): Discord slash command auto-registration
- test_auto_registers_missing_gateway_commands, test_auto_registered_command_*,
test_register_skill_group_*
- Root cause: xdist workers that loaded a discord mock WITHOUT
app_commands.Command/Group caused _register_slash_commands() to fail
silently. Added comprehensive shared discord mock in
tests/gateway/conftest.py (same pattern as existing telegram mock).
Group C (5 errors): Discord reply mode 'NoneType has no DMChannel'
- All TestReplyToText tests
- Root cause: FakeDMChannel was not a subclass of real discord.DMChannel,
so isinstance() checks in _handle_message failed when running in full
suite (real discord installed). Made FakeDMChannel inherit from
discord.DMChannel when available. Removed fragile monkeypatch approach.
Group D (2 tests): detect_provider_for_model wrong provider
- test_openrouter_slug_match (got 'ai-gateway'), test_bare_name_gets_
openrouter_slug (got 'copilot')
- Root cause: ai-gateway, copilot, and kilocode are multi-vendor
aggregators that list other providers' models (OpenRouter-style slugs).
They were being matched in Step 1 before OpenRouter. Added all three
to _AGGREGATORS set so they're skipped like nous/openrouter.
Group E (1 test): model_flow_custom StopIteration
- test_model_flow_custom_saves_verified_v1_base_url
- Root cause: 'Display name' prompt was added after the test was written.
The input iterator had 5 answers but the flow now asks 6 questions.
Added 6th empty string answer.
Group F (1 test): Telegram proxy env assertion
- test_uses_proxy_env_for_primary_and_fallback_transports
- Root cause: _resolve_proxy_url() now checks TELEGRAM_PROXY first
(via resolve_proxy_url('TELEGRAM_PROXY')). Test didn't clear this
env var, allowing potential leakage from other tests in xdist workers.
Added TELEGRAM_PROXY to the cleanup list.
copilot_model_api_mode() called normalize_copilot_model_id() which
fetched the GitHub model catalog via HTTP, then the secondary endpoint
check fetched it again because the catalog was never passed through.
Fix: fetch the catalog once at the top of copilot_model_api_mode()
and pass it to normalize_copilot_model_id(). The secondary check
then sees a non-None catalog and skips the redundant fetch.
For a Claude model switch on Copilot this eliminates one 5-second-
timeout HTTP call from the interactive /model path.
Surfaced during review of PR #10533.
Co-authored-by: kshitijk4poor <kshitijk4poor@users.noreply.github.com>
detect_provider_for_model() silently remapped models to OpenRouter when
the direct provider's credentials weren't found via env vars. Three bugs:
1. Credential check only looked at env vars from PROVIDER_REGISTRY,
missing credential pool entries, auth store, and OAuth tokens
2. When env var check failed, silently returned ('openrouter', slug)
instead of the direct provider the model actually belongs to
3. Users with valid credentials via non-env-var mechanisms (pool,
OAuth, Claude Code tokens) got silently rerouted
Fix:
- Expand credential check to also query credential pool and auth store
- Always return the direct provider match regardless of credential
status -- let client init handle missing creds with a clear error
rather than silently routing through the wrong provider
Same philosophy as the provider-required fix: don't guess, don't
silently reroute, error clearly when something is missing.
Closes#10300
Route kimi-coding-cn through _resolve_kimi_base_url() in both
get_api_key_provider_status() and resolve_api_key_provider_credentials()
so CN users with sk-kimi- prefixed keys get auto-detected to the Kimi
Coding Plan endpoint, matching the existing behavior for kimi-coding.
Also update the kimi-coding display label to accurately reflect the
dual-endpoint setup (Kimi Coding Plan + Moonshot API).
Salvaged from PR #10525 by kkikione999.
- Add glm-5v-turbo to OpenRouter, Nous, and native Z.AI model lists
- Add glm-5v context length entry (200K tokens) to model metadata
- Update Z.AI endpoint probe to try multiple candidate models per
endpoint (glm-5.1, glm-5v-turbo, glm-4.7) — fixes detection for
newer coding plan accounts that lack older models
- Add zai to _PROVIDER_VISION_MODELS so auxiliary vision tasks
(vision_analyze, browser screenshots) route through 5v
Fixes#9888
* feat(skills): add fitness-nutrition skill to optional-skills
Cherry-picked from PR #9177 by @haileymarshall.
Adds a fitness and nutrition skill for gym-goers and health-conscious users:
- Exercise search via wger API (690+ exercises, free, no auth)
- Nutrition lookup via USDA FoodData Central (380K+ foods, DEMO_KEY fallback)
- Offline body composition calculators (BMI, TDEE, 1RM, macros, body fat %)
- Pure stdlib Python, no pip dependencies
Changes from original PR:
- Moved from skills/ to optional-skills/health/ (correct location)
- Fixed BMR formula in FORMULAS.md (removed confusing -5+10, now just +5)
- Fixed author attribution to match PR submitter
- Marked USDA_API_KEY as optional (DEMO_KEY works without signup)
Also adds optional env var support to the skill readiness checker:
- New 'optional: true' field in required_environment_variables entries
- Optional vars are preserved in metadata but don't block skill readiness
- Optional vars skip the CLI capture prompt flow
- Skills with only optional missing vars show as 'available' not 'setup_needed'
* fix: auto-correct close model name matches in /model validation
When a user types a model name with a minor typo (e.g. gpt5.3-codex instead
of gpt-5.3-codex), the validation now auto-corrects to the closest match
instead of accepting the wrong name with a warning.
Uses difflib get_close_matches with cutoff=0.9 to avoid false corrections
(e.g. gpt-5.3 should not silently become gpt-5.4). Applied consistently
across all three validation paths: codex provider, custom endpoints, and
generic API-probed providers.
The validate_requested_model() return dict gains an optional corrected_model
key that switch_model() applies before building the result.
Reported by Discord user — /model gpt5.3-codex was accepted with a warning
but would fail at the API level.
---------
Co-authored-by: haileymarshall <haileymarshall@users.noreply.github.com>
* Add hermes debug share instructions to all issue templates
- bug_report.yml: Add required Debug Report section with hermes debug share
and /debug instructions, make OS/Python/Hermes version optional (covered
by debug report), demote old logs field to optional supplementary
- setup_help.yml: Replace hermes doctor reference with hermes debug share,
add Debug Report section with fallback chain (debug share -> --local -> doctor)
- feature_request.yml: Add optional Debug Report section for environment context
All templates now guide users to run hermes debug share (or /debug in chat)
and paste the resulting paste.rs links, giving maintainers system info,
config, and recent logs in one step.
* feat: add openrouter/elephant-alpha to curated model lists
- Add to OPENROUTER_MODELS (free, positioned above GPT models)
- Add to _PROVIDER_MODELS["nous"] mirror list
- Add 256K context window fallback in model_metadata.py
Remove the two-tier (top/extended) provider picker that hid most
providers behind a 'More providers...' submenu. All providers now
appear in a single flat list.
- Remove tier field from ProviderEntry namedtuple
- Remove tier values from all CANONICAL_PROVIDERS entries
- Flatten the hermes model picker (no more 'More...' submenu)
- Move 'Custom endpoint' to the bottom of the main list
Adds Arcee AI as a standard direct provider (ARCEEAI_API_KEY) with
Trinity models: trinity-large-thinking, trinity-large-preview, trinity-mini.
Standard OpenAI-compatible provider checklist: auth.py, config.py,
models.py, main.py, providers.py, doctor.py, model_normalize.py,
model_metadata.py, setup.py, trajectory_compressor.py.
Based on PR #9274 by arthurbr11, simplified to a standard direct
provider without dual-endpoint OpenRouter routing.
Three separate hardcoded provider lists (/model, /provider, hermes model)
diverged over time, causing providers to be missing from some commands.
- Create CANONICAL_PROVIDERS in hermes_cli/models.py as the single source
of truth for all provider identity, labels, and TUI ordering
- Derive _PROVIDER_LABELS and list_available_providers() from canonical list
- Add step 2b in list_authenticated_providers() to cross-check canonical
list — catches providers with credentials that weren't found via
PROVIDER_TO_MODELS_DEV or HERMES_OVERLAYS mappings
- Derive hermes model TUI provider menus from canonical list
- Add deepseek and xai as first-class providers (were missing from TUI)
- Add grok/x-ai/x.ai aliases for xai provider
Fixes: /model command not showing all providers that hermes model shows
Cherry-picked from PR #7637 by hcshen0111.
Adds kimi-coding-cn provider with dedicated KIMI_CN_API_KEY env var
and api.moonshot.cn/v1 endpoint for China-region Moonshot users.
OpenCode Zen was in _DOT_TO_HYPHEN_PROVIDERS, causing all dotted model
names (minimax-m2.5-free, gpt-5.4, glm-5.1) to be mangled. The fix:
Layer 1 (model_normalize.py): Remove opencode-zen from the blanket
dot-to-hyphen set. Add an explicit block that preserves dots for
non-Claude models while keeping Claude hyphenated (Zen's Claude
endpoint uses anthropic_messages mode which expects hyphens).
Layer 2 (run_agent.py _anthropic_preserve_dots): Add opencode-zen and
zai to the provider allowlist. Broaden URL check from opencode.ai/zen/go
to opencode.ai/zen/ to cover both Go and Zen endpoints. Add bigmodel.cn
for ZAI URL detection.
Also adds glm-5.1 to ZAI model lists in models.py and setup.py.
Closes#7710
Salvaged from contributions by:
- konsisumer (PR #7739, #7719)
- DomGrieco (PR #8708)
- Esashiero (PR #7296)
- sharziki (PR #7497)
- XiaoYingGee (PR #8750)
- APTX4869-maker (PR #8752)
- kagura-agent (PR #7157)
Users who set up Nous auth without explicitly selecting a model via
`hermes model` were silently falling back to anthropic/claude-opus-4.6
(the first entry in _PROVIDER_MODELS['nous']), causing unexpected
charges on their Nous plan. Move xiaomi/mimo-v2-pro to the first
position so unconfigured users default to a free model instead.
When a user configures a provider (e.g. `hermes auth add openai-codex`)
but never selects a model via `hermes model`, the gateway and CLI would
pass an empty model string to the API, causing:
'Codex Responses request model must be a non-empty string'
Now both gateway (_resolve_session_agent_runtime) and CLI
(_ensure_runtime_credentials) detect an empty model and fill it from
the provider's first catalog entry in _PROVIDER_MODELS. This covers
all providers that have a static model list (openai-codex, anthropic,
gemini, copilot, etc.).
The fix is conservative: it only triggers when model is truly empty
and a known provider was resolved. Explicit model choices are never
overridden.
When /model is called with no arguments in the interactive CLI, open a
two-step prompt_toolkit modal instead of the previous text-only listing:
1. Provider selection — curses_single_select with all authenticated providers
2. Model selection — live API fetch with curated fallback
Also fixes:
- OpenAI Codex model normalization (openai/gpt-5.4 → gpt-5.4)
- Dedicated Codex validation path using provider_model_ids()
Preserves curses_radiolist (used by setup, tools, plugins) alongside the
new curses_single_select. Retains tool elapsed timer in spinner.
Cherry-picked from PR #7438 by MestreY0d4-Uninter.
Cherry-picked from PR #7702 by kshitijk4poor.
Adds Xiaomi MiMo as a direct provider (XIAOMI_API_KEY) with models:
- mimo-v2-pro (1M context), mimo-v2-omni (256K, multimodal), mimo-v2-flash (256K, cheapest)
Standard OpenAI-compatible provider checklist: auth.py, config.py, models.py,
main.py, providers.py, doctor.py, model_normalize.py, model_metadata.py,
models_dev.py, auxiliary_client.py, .env.example, cli-config.yaml.example.
Follow-up: vision tasks use mimo-v2-omni (multimodal) instead of the user's
main model. Non-vision aux uses the user's selected model. Added
_PROVIDER_VISION_MODELS dict for provider-specific vision model overrides.
On failure, falls back to aggregators (gemini flash) via existing fallback chain.
Corrects pre-existing context lengths: mimo-v2-pro 1048576→1000000,
mimo-v2-omni 1048576→256000, adds mimo-v2-flash 256000.
36 tests covering registry, aliases, auto-detect, credentials, models.dev,
normalization, URL mapping, providers module, doctor, aux client, vision
model override, and agent init.
The _PROVIDER_MODELS['openai-codex'] static list was a manually maintained
duplicate of DEFAULT_CODEX_MODELS in codex_models.py. They drifted — the
static list was missing gpt-5.3-codex-spark (and previously gpt-5.4).
Replace the hardcoded list with _codex_curated_models() which calls
DEFAULT_CODEX_MODELS + _add_forward_compat_models() from codex_models.py.
Now both the CLI 'hermes model' flow and the gateway /model picker derive
from the same source of truth. New models added to DEFAULT_CODEX_MODELS
or _FORWARD_COMPAT_TEMPLATE_MODELS automatically appear everywhere.
The _PROVIDER_MODELS['openai-codex'] list was missing gpt-5.4 and gpt-5.4-mini,
causing them to not appear in the /model picker for ChatGPT OAuth users.
codex_models.py already had these models in DEFAULT_CODEX_MODELS, but the
curated list that feeds the Telegram/Discord /model picker was never updated.
Reported by @chongdashu
Aligns MiniMax provider with official API documentation. Fixes 6 bugs:
transport mismatch (openai_chat -> anthropic_messages), credential leak
in switch_model(), prompt caching sent to non-Anthropic endpoints,
dot-to-hyphen model name corruption, trajectory compressor URL routing,
and stale doctor health check.
Also corrects context window (204,800), thinking support (manual mode),
max output (131,072), and model catalog (M2 family only on /anthropic).
Source: https://platform.minimax.io/docs/api-reference/text-anthropic-api
Co-authored-by: kshitijk4poor <kshitijk4poor@users.noreply.github.com>
Adds xAI as a first-class provider: ProviderConfig in auth.py,
HermesOverlay in providers.py, 11 curated Grok models, URL mapping
in model_metadata.py, aliases (x-ai, x.ai), and env var tests.
Uses standard OpenAI-compatible chat completions.
Closes#7050
Automated dead code audit using vulture + coverage.py + ast-grep intersection,
confirmed by Opus deep verification pass. Every symbol verified to have zero
production callers (test imports excluded from reachability analysis).
Removes ~1,534 lines of dead production code across 46 files and ~1,382 lines
of stale test code. 3 entire files deleted (agent/builtin_memory_provider.py,
hermes_cli/checklist.py, tests/hermes_cli/test_setup_model_selection.py).
Co-authored-by: alt-glitch <balyan.sid@gmail.com>
Extends the /fast command to support Anthropic's Fast Mode beta in addition
to OpenAI Priority Processing. When enabled on Claude Opus 4.6, adds
speed:"fast" and the fast-mode-2026-02-01 beta header to API requests for
~2.5x faster output token throughput.
Changes:
- hermes_cli/models.py: Add _ANTHROPIC_FAST_MODE_MODELS registry,
model_supports_fast_mode() now recognizes Claude Opus 4.6,
resolve_fast_mode_overrides() returns {speed: fast} for Anthropic
vs {service_tier: priority} for OpenAI
- agent/anthropic_adapter.py: Add _FAST_MODE_BETA constant,
build_anthropic_kwargs() accepts fast_mode=True which injects
speed:fast + beta header via extra_headers (skipped for third-party
Anthropic-compatible endpoints like MiniMax)
- run_agent.py: Pass fast_mode to build_anthropic_kwargs in the
anthropic_messages path of _build_api_kwargs()
- cli.py: Update _handle_fast_command with provider-aware messaging
(shows 'Anthropic Fast Mode' vs 'Priority Processing')
- hermes_cli/commands.py: Update /fast description to mention both
providers
- tests: 13 new tests covering Anthropic model detection, override
resolution, CLI availability, routing, adapter kwargs, and
third-party endpoint safety
Previously /fast only supported gpt-5.4 and forced a provider switch to
openai-codex. Now supports all 13 models from OpenAI's Priority Processing
pricing table (gpt-5.4, gpt-5.4-mini, gpt-5.2, gpt-5.1, gpt-5, gpt-5-mini,
gpt-4.1, gpt-4.1-mini, gpt-4.1-nano, gpt-4o, gpt-4o-mini, o3, o4-mini).
Key changes:
- Replaced _FAST_MODE_BACKEND_CONFIG with _PRIORITY_PROCESSING_MODELS frozenset
- Removed provider-forcing logic — service_tier is now injected into whatever
API path the user is already on (Codex Responses, Chat Completions, or
OpenRouter passthrough)
- Added request_overrides support to chat_completions path in run_agent.py
- Updated messaging from 'Codex inference tier' to 'Priority Processing'
- Expanded test coverage for all supported models
Add /fast slash command to toggle OpenAI Codex service_tier between
normal and priority ('fast') inference. Only exposed for models
registered in _FAST_MODE_BACKEND_CONFIG (currently gpt-5.4).
- Registry-based backend config for extensibility
- Dynamic command visibility (hidden from help/autocomplete for
non-supported models) via command_filter on SlashCommandCompleter
- service_tier flows through request_overrides from route resolution
- Omit max_output_tokens for Codex backend (rejects it)
- Persists to config.yaml under agent.service_tier
Salvage cleanup: removed simple_term_menu/input() menu (banned),
bare /fast now shows status like /reasoning. Removed redundant
override resolution in _build_api_kwargs — single source of truth
via request_overrides from route.
Co-authored-by: Hermes Agent <hermes@nousresearch.com>
Updated the logic for determining the probed_url in the probe_api_models function to use the first tried URL instead of the last. This change ensures that the most relevant URL is returned when probing for models. Additionally, improved the output message in the _model_flow_custom function to provide clearer guidance based on the suggested_base_url.
Based on #6079 by @tunamitom with critical fixes and comprehensive tests.
Changes from #6079:
- Fix: sanitization overwrite bug — Qwen message prep now runs AFTER codex
field sanitization, not before (was silently discarding Qwen transforms)
- Fix: missing try/except AuthError in runtime_provider.py — stale Qwen
credentials now fall through to next provider on auto-detect
- Fix: 'qwen' alias conflict — bare 'qwen' stays mapped to 'alibaba'
(DashScope); use 'qwen-portal' or 'qwen-cli' for the OAuth provider
- Fix: hardcoded ['coder-model'] replaced with live API fetch + curated
fallback list (qwen3-coder-plus, qwen3-coder)
- Fix: extract _is_qwen_portal() helper + _qwen_portal_headers() to replace
5 inline 'portal.qwen.ai' string checks and share headers between init
and credential swap
- Fix: add Qwen branch to _apply_client_headers_for_base_url for mid-session
credential swaps
- Fix: remove suspicious TypeError catch blocks around _prompt_provider_choice
- Fix: handle bare string items in content lists (were silently dropped)
- Fix: remove redundant dict() copies after deepcopy in message prep
- Revert: unrelated ai-gateway test mock removal and model_switch.py comment deletion
New tests (30 test functions):
- _qwen_cli_auth_path, _read_qwen_cli_tokens (success + 3 error paths)
- _save_qwen_cli_tokens (roundtrip, parent creation, permissions)
- _qwen_access_token_is_expiring (5 edge cases: fresh, expired, within skew,
None, non-numeric)
- _refresh_qwen_cli_tokens (success, preserve old refresh, 4 error paths,
default expires_in, disk persistence)
- resolve_qwen_runtime_credentials (fresh, auto-refresh, force-refresh,
missing token, env override)
- get_qwen_auth_status (logged in, not logged in)
- Runtime provider resolution (direct, pool entry, alias)
- _build_api_kwargs (metadata, vl_high_resolution_images, message formatting,
max_tokens suppression)
check_nous_free_tier() now caches its result for 180 seconds to avoid
redundant Portal API calls during a session (auxiliary client init,
model selection, login flow all call it independently).
The TTL is short enough that an account upgrade from free to paid is
reflected within 3 minutes. clear_nous_free_tier_cache() is exposed
for explicit invalidation on login/logout.
Adds 4 tests for cache hit, TTL expiry, explicit clear, and TTL bound.
- Show pricing during initial Nous Portal login (was missing from
_login_nous, only shown in the already-logged-in hermes model path)
- Filter free models for paid subscribers: non-allowlisted free models
are hidden; allowlisted models (xiaomi/mimo-v2-pro, xiaomi/mimo-v2-omni)
only appear when actually priced as free
- Detect free-tier accounts via portal api/oauth/account endpoint
(monthly_charge == 0); free-tier users see only free models as
selectable, with paid models shown dimmed and unselectable
- Use xiaomi/mimo-v2-omni as the auxiliary vision model for free-tier
Nous users so vision_analyze and browser_vision work without paid
model access (replaces the default google/gemini-3-flash-preview)
- Unavailable models rendered via print() before TerminalMenu to avoid
simple_term_menu line-width padding artifacts; upgrade URL resolved
from auth state portal_base_url (supports staging/custom portals)
- Add 21 tests covering filter_nous_free_models, is_nous_free_tier,
and partition_nous_models_by_tier
