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
Display live per-million-token pricing from /v1/models when listing
models for OpenRouter or Nous Portal. Prices are shown in a
column-aligned table with decimal points vertically aligned for
easy comparison.
Pricing appears in three places:
- /provider slash command (table with In/Out headers)
- hermes model picker (aligned columns in both TerminalMenu and
numbered fallback)
Implementation:
- Add fetch_models_with_pricing() in models.py with per-base_url
module-level cache (one network call per endpoint per session)
- Add _format_price_per_mtok() with fixed 2-decimal formatting
- Add format_model_pricing_table() for terminal table display
- Add get_pricing_for_provider() convenience wrapper
- Update _prompt_model_selection() to accept optional pricing dict
- Wire pricing through _model_flow_openrouter/nous in main.py
- Update test mocks for new pricing parameter
The Anthropic SDK appends /v1/messages to the base_url, so OpenCode's
base URL https://opencode.ai/zen/go/v1 produced a double /v1 path
(https://opencode.ai/zen/go/v1/v1/messages), causing 404s for MiniMax
models. Strip trailing /v1 when api_mode is anthropic_messages.
Also adds MiMo-V2-Pro, MiMo-V2-Omni, and MiniMax-M2.5 to the OpenCode
Go model lists per their updated docs.
Fixes#4890
OpenCode Zen and Go are mixed-API-surface providers — different models
behind them use different API surfaces (GPT on Zen uses codex_responses,
Claude on Zen uses anthropic_messages, MiniMax on Go uses
anthropic_messages, GLM/Kimi on Go use chat_completions).
Changes:
- Add normalize_opencode_model_id() and opencode_model_api_mode() to
models.py for model ID normalization and API surface routing
- Add _provider_supports_explicit_api_mode() to runtime_provider.py
to prevent stale api_mode from leaking across provider switches
- Wire opencode routing into all three api_mode resolution paths:
pool entry, api_key provider, and explicit runtime
- Add api_mode field to ModelSwitchResult for propagation through the
switch pipeline
- Consolidate _PROVIDER_MODELS from main.py into models.py (single
source of truth, eliminates duplicate dict)
- Add opencode normalization to setup wizard and model picker flows
- Add opencode block to _normalize_model_for_provider in CLI
- Add opencode-zen/go fallback model lists to setup.py
Tests: 160 targeted tests pass (26 new tests covering normalization,
api_mode routing per provider/model, persistence, and setup wizard
normalization).
Based on PR #3017 by SaM13997.
Co-authored-by: SaM13997 <139419381+SaM13997@users.noreply.github.com>
