- 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>
Add MiniMax-M2.7 and M2.7-highspeed to _PROVIDER_MODELS for minimax
and minimax-cn providers in main.py so hermes model shows them.
Update opencode-go bare ID from m2.5 to m2.7 in models.py.
Salvaged from PR #4197 by octo-patch.
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.
* Add new Gemini 3.1 model entries to models.py
* fix: also add Gemini 3.1 models to nous provider list
---------
Co-authored-by: Andrei Ignat <andrei@ignat.se>
- Change default inference_base_url from dashscope-intl Anthropic-compat
endpoint to coding-intl OpenAI-compat /v1 endpoint. The old Anthropic
endpoint 404'd when used with the OpenAI SDK (which appends
/chat/completions to a /apps/anthropic base URL).
- Update curated model list: remove models unavailable on coding-intl
(qwen3-max, qwen-plus-latest, qwen3.5-flash, qwen-vl-max), add
third-party models available on the platform (glm-5, glm-4.7,
kimi-k2.5, MiniMax-M2.5).
- URL-based api_mode auto-detection still works: overriding
DASHSCOPE_BASE_URL to an /apps/anthropic endpoint automatically
switches to anthropic_messages mode.
- Update provider description and env var descriptions to reflect the
coding-intl multi-provider platform.
- Update tests to match new default URL and test the anthropic override
path instead.
Show only agentic models that map to OpenRouter defaults:
Qwen/Qwen3.5-397B-A17B ↔ qwen/qwen3.5-plus
Qwen/Qwen3.5-35B-A3B ↔ qwen/qwen3.5-35b-a3b
deepseek-ai/DeepSeek-V3.2 ↔ deepseek/deepseek-chat
moonshotai/Kimi-K2.5 ↔ moonshotai/kimi-k2.5
MiniMaxAI/MiniMax-M2.5 ↔ minimax/minimax-m2.5
zai-org/GLM-5 ↔ z-ai/glm-5
XiaomiMiMo/MiMo-V2-Flash ↔ xiaomi/mimo-v2-pro
moonshotai/Kimi-K2-Thinking ↔ moonshotai/kimi-k2-thinking
Users can still pick any HF model via Enter custom model name.
Salvage of PR #1747 (original PR #1171 by @davanstrien) onto current main.
Registers Hugging Face Inference Providers (router.huggingface.co/v1) as a named provider:
- hermes chat --provider huggingface (or --provider hf)
- 18 curated open models via hermes model picker
- HF_TOKEN in ~/.hermes/.env
- OpenAI-compatible endpoint with automatic failover (Groq, Together, SambaNova, etc.)
Files: auth.py, models.py, main.py, setup.py, config.py, model_metadata.py, .env.example, 5 docs pages, 17 new tests.
Co-authored-by: Daniel van Strien <davanstrien@gmail.com>
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
Cherry-picked from PR #2542 by ReqX. Adds glm-5-turbo to the direct
zai provider curated model list so /model zai:glm-5-turbo validates
correctly. The model was already in _OPENROUTER_UPSTREAM_MODELS but
missing from the direct provider list.
* feat(model): persist base_url on /model switch, auto-detect for bare /model custom
Phase 2+3 of the /model command overhaul:
Phase 2 — Persist base_url on model switch:
- CLI: save model.base_url when switching to a non-OpenRouter endpoint;
clear it when switching away from custom to prevent stale URLs
leaking into the new provider's resolution
- Gateway: same logic using direct YAML write
Phase 3 — Better feedback and edge cases:
- Bare '/model custom' now auto-detects the model from the endpoint
using _auto_detect_local_model() and saves all three config values
(model, provider, base_url) atomically
- Shows endpoint URL in success messages when switching to/from
custom providers (both CLI and gateway)
- Clear error messages when no custom endpoint is configured
- Updated test assertions for the additional save_config_value call
Fixes#2562 (Phase 2+3)
* feat(model): support custom:name:model triple syntax for named custom providers
Phase 5 of the /model command overhaul.
Extends parse_model_input() to handle the triple syntax:
/model custom:local-server:qwen → provider='custom:local-server', model='qwen'
/model custom:my-model → provider='custom', model='my-model' (unchanged)
The 'custom:local-server' provider string is already supported by
_get_named_custom_provider() in runtime_provider.py, which matches
it against the custom_providers list in config.yaml. This just wires
the parsing so users can do it from the /model slash command.
Added 4 tests covering single, triple, whitespace, and empty model cases.
* fix: respect DashScope v1 runtime mode for alibaba
Remove the hardcoded Alibaba branch from resolve_runtime_provider()
that forced api_mode='anthropic_messages' regardless of the base URL.
Alibaba now goes through the generic API-key provider path, which
auto-detects the protocol from the URL:
- /apps/anthropic → anthropic_messages (via endswith check)
- /v1 → chat_completions (default)
This fixes Alibaba setup with OpenAI-compatible DashScope endpoints
(e.g. coding-intl.dashscope.aliyuncs.com/v1) that were broken because
runtime always forced Anthropic mode even when setup saved a /v1 URL.
Based on PR #2024 by @kshitijk4poor.
* docs(skill): add split, merge, search examples to ocr-and-documents skill
Adds pymupdf examples for PDF splitting, merging, and text search
to the existing ocr-and-documents skill. No new dependencies — pymupdf
already covers all three operations natively.
* fix: replace all production print() calls with logger in rl_training_tool
Replace all bare print() calls in production code paths with proper logger calls.
- Add `import logging` and module-level `logger = logging.getLogger(__name__)`
- Replace print() in _start_training_run() with logger.info()
- Replace print() in _stop_training_run() with logger.info()
- Replace print(Warning/Note) calls with logger.warning() and logger.info()
Using the logging framework allows log level filtering, proper formatting,
and log routing instead of always printing to stdout.
* fix(gateway): process /queue'd messages after agent completion
/queue stored messages in adapter._pending_messages but never consumed
them after normal (non-interrupted) completion. The consumption path
at line 5219 only checked pending messages when result.get('interrupted')
was True — since /queue deliberately doesn't interrupt, queued messages
were silently dropped.
Now checks adapter._pending_messages after both interrupted AND normal
completion. For queued messages (non-interrupt), the first response is
delivered before recursing to process the queued follow-up. Skips the
direct send when streaming already delivered the response.
Reported by GhostMode on Discord.
* chore: add minimax/minimax-m2.7 to OpenRouter and MiniMax model catalogs
---------
Co-authored-by: kshitijk4poor <kshitijk4poor@users.noreply.github.com>
Co-authored-by: memosr.eth <96793918+memosr@users.noreply.github.com>
* docs: add Gemini OAuth provider implementation plan
Planning doc for a standard-route Gemini provider using Google OAuth
(Authorization Code + PKCE) with the OpenAI-compatible endpoint at
generativelanguage.googleapis.com. Covers OAuth flow, token lifecycle,
file list, and estimated scope (~700 lines).
Replaces the Node.js bridge approach from PR #2042.
* chore: update OpenRouter model list
- Add xiaomi/mimo-v2-pro
- Add nvidia/nemotron-3-super-120b-a12b (paid, higher rate limits)
- Remove openrouter/hunter-alpha and openrouter/healer-alpha (discontinued)
Add has_usable_secret() to reject empty, short (<4 char), and common
placeholder API key values (changeme, your_api_key, placeholder, etc.)
throughout the auth/runtime resolution chain.
Update list_available_providers() to use provider-specific auth status
via get_auth_status() instead of resolve_runtime_provider(), preventing
cross-provider key fallback from making providers appear available when
they aren't actually configured.
Preserve keyless custom endpoint support by checking via base URL.
Cherry-picked from PR #2121 by aashizpoudel.
Two issues with /model preventing proper provider switching:
1. Bare provider names not detected: typing '/model nous' treated 'nous'
as a model name instead of triggering a provider switch. Fixed by adding
step 0 in detect_provider_for_model() that checks if the input matches
a known provider name/alias (excluding 'custom'/'openrouter' which need
explicit model names) and returns that provider's default model.
2. Custom endpoint details hidden: /model (no args) showed '[custom]' with
just a usage hint but no endpoint URL or model name. Now displays the
configured base_url for custom providers in both CLI and gateway.
Note: config base_url and OPENAI_BASE_URL are intentionally NOT cleared on
provider switch — dedicated provider paths (nous, anthropic, codex) have
their own credential resolution that ignores these, and clearing them would
destroy the user's custom endpoint config, preventing switching back.
Co-authored-by: Test <test@test.com>
The previous copilot_model_api_mode() checked the catalog's
supported_endpoints first and picked /chat/completions when a model
supported both endpoints. This is wrong — GPT-5+ models should use
the Responses API even when the catalog lists both.
Replicate opencode's shouldUseCopilotResponsesApi() logic:
- GPT-5+ models (gpt-5.4, gpt-5.3-codex, etc.) → Responses API
- gpt-5-mini → Chat Completions (explicit exception)
- Everything else (gpt-4o, claude, gemini, etc.) → Chat Completions
- Model ID pattern is the primary signal, catalog is secondary
The catalog fallback now only matters for non-GPT-5 models that might
exclusively support /v1/messages (e.g. Claude via Copilot).
Models are auto-detected from the live catalog at
api.githubcopilot.com/models — no hardcoded list required for
supported models, only a static fallback for when the API is
unreachable.
- Add anthropic/claude-haiku-4.5
- Move gpt-5.4-pro and gpt-5.4-nano to bottom
- Fix minimax/minimax-m2.7 → minimax-m2.5 (m2.7 not on OpenRouter)
- Tag hunter-alpha and healer-alpha as free
- Place hunter/healer-alpha right below gpt-5.4-mini
Builds on PR #1879's Copilot integration with critical auth improvements
modeled after opencode's implementation:
- Add hermes_cli/copilot_auth.py with:
- OAuth device code flow (copilot_device_code_login) using the same
client_id (Ov23li8tweQw6odWQebz) as opencode and Copilot CLI
- Token type validation: reject classic PATs (ghp_*) with a clear
error message explaining supported token types
- Proper env var priority: COPILOT_GITHUB_TOKEN > GH_TOKEN > GITHUB_TOKEN
(matching Copilot CLI documentation)
- copilot_request_headers() with Openai-Intent, x-initiator, and
Copilot-Vision-Request headers (matching opencode)
- Update auth.py:
- PROVIDER_REGISTRY copilot entry uses correct env var order
- _resolve_api_key_provider_secret delegates to copilot_auth for
the copilot provider with proper token validation
- Update models.py:
- copilot_default_headers() now includes Openai-Intent and x-initiator
- Update main.py:
- _model_flow_copilot offers OAuth device code login when no token
is found, with manual token entry as fallback
- Shows supported vs unsupported token types
- 22 new tests covering token validation, env var priority, header
generation, and integration with existing auth infrastructure
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>
fetch_nous_models() uses keyword-only parameters (the * separator in
its signature), but models.py called it with positional args and in
the wrong order (api_key first, base_url second). This always raised
TypeError, silently caught by except Exception: pass.
Result: Nous provider model list was completely broken — /model
autocomplete and provider_model_ids('nous') always fell back to the
static model catalog instead of fetching live models.
Add Alibaba Cloud (DashScope) as a first-class inference provider
using the Anthropic-compatible endpoint. This gives access to Qwen
models (qwen3.5-plus, qwen3-max, qwen3-coder-plus, etc.) through
the same api_mode as native Anthropic.
Also add ANTHROPIC_BASE_URL env var support so users can point the
Anthropic provider at any compatible endpoint.
Changes:
- auth.py: Add alibaba ProviderConfig + ANTHROPIC_BASE_URL on anthropic
- models.py: Add alibaba to catalog, labels, aliases (dashscope/aliyun/qwen), provider order
- runtime_provider.py: Add alibaba resolution (anthropic_messages api_mode) + ANTHROPIC_BASE_URL
- model_metadata.py: Add Qwen model context lengths (128K)
- config.py: Add DASHSCOPE_API_KEY, DASHSCOPE_BASE_URL, ANTHROPIC_BASE_URL env vars
Usage:
hermes --provider alibaba --model qwen3.5-plus
# or via aliases:
hermes --provider qwen --model qwen3-max
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>
Add 'custom' to the provider order so custom OpenAI-compatible
endpoints appear in /model list. Probes the endpoint's /models API
to dynamically discover available models.
Changes:
- Add 'custom' to _PROVIDER_ORDER in list_available_providers()
- Add _get_custom_base_url() helper to read model.base_url from config
- Add custom branch in provider_model_ids() using fetch_api_models()
- Custom endpoint detection via base_url presence for has_creds check
Based on PR #1612 by @aashizpoudel.
Co-authored-by: Aashish Poudel <aashizpoudel@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>
When typing /model deepseek-chat while on a different provider, the
model name now auto-resolves to the correct provider instead of
silently staying on the wrong one and causing API errors.
Detection priority:
1. Direct provider with credentials (e.g. DEEPSEEK_API_KEY set)
2. OpenRouter catalog match with proper slug remapping
3. Direct provider without creds (clear error beats silent failure)
Also adds DeepSeek as a first-class API-key provider — just set
DEEPSEEK_API_KEY and /model deepseek-chat routes directly.
Bare model names get remapped to proper OpenRouter slugs:
/model gpt-5.4 → openai/gpt-5.4
/model claude-opus-4.6 → anthropic/claude-opus-4.6
Salvages the concept from PR #1177 by @virtaava with credential
awareness and OpenRouter slug mapping added.
Co-authored-by: virtaava <virtaava@users.noreply.github.com>
Fixes Anthropic OAuth/subscription authentication end-to-end:
Auth failures (401 errors):
- Add missing 'claude-code-20250219' beta header for OAuth tokens. Both
clawdbot and OpenCode include this alongside 'oauth-2025-04-20' — without
it, Anthropic's API rejects OAuth tokens with 401 authentication errors.
- Fix _fetch_anthropic_models() to use canonical beta headers from
_COMMON_BETAS + _OAUTH_ONLY_BETAS instead of hardcoding.
Token refresh:
- Add _refresh_oauth_token() — when Claude Code credentials from
~/.claude/.credentials.json are expired but have a refresh token,
automatically POST to console.anthropic.com/v1/oauth/token to get
a new access token. Uses the same client_id as Claude Code / OpenCode.
- Add _write_claude_code_credentials() — writes refreshed tokens back
to ~/.claude/.credentials.json, preserving other fields.
- resolve_anthropic_token() now auto-refreshes expired tokens before
returning None.
Config contamination:
- Anthropic's _model_flow_anthropic() no longer saves base_url to config.
Since resolve_runtime_provider() always hardcodes Anthropic's URL, the
stale base_url was contaminating other providers when users switched
without re-running 'hermes model' (e.g., Codex hitting api.anthropic.com).
- _update_config_for_provider() now pops base_url when passed empty string.
- Same fix in setup.py.
Flow/UX (hermes model command):
- CLAUDE_CODE_OAUTH_TOKEN env var now checked in credential detection
- Reauthentication option when existing credentials found
- run_oauth_setup_token() runs 'claude setup-token' as interactive
subprocess, then auto-detects saved credentials
- Clean has_creds/needs_auth flow in both main.py and setup.py
Tests (14 new):
- Beta header assertions for claude-code-20250219
- Token refresh: successful refresh with credential writeback, failed
refresh returns None, no refresh token returns None
- Credential writeback: new file creation, preserving existing fields
- Auto-refresh integration in resolve_anthropic_token()
- CLAUDE_CODE_OAUTH_TOKEN fallback, credential file auto-discovery
- run_oauth_setup_token() (5 scenarios)
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
- Add _fetch_anthropic_models() to hermes_cli/models.py — hits the
Anthropic /v1/models endpoint to get the live model catalog. Handles
both API key and OAuth token auth headers.
- Wire it into provider_model_ids() so both 'hermes model' and
'hermes setup model' show the live list instead of a stale static one.
- Update static _PROVIDER_MODELS fallback with full current catalog:
opus-4-6, sonnet-4-6, opus-4-5, sonnet-4-5, opus-4, sonnet-4, haiku-4-5
- Update model_metadata.py with context lengths for all current models.
- Fix thinking parameter for 4.5+ models: use type='adaptive' instead
of type='enabled' (Anthropic deprecated 'enabled' for newer models,
warns at runtime). Detects model version from the model name string.
Verified live:
hermes model → Anthropic → auto-detected creds → shows 7 live models
hermes chat --provider anthropic --model claude-opus-4-6 → works
* fix: use session_key instead of chat_id for adapter interrupt lookups
monitor_for_interrupt() in _run_agent was using source.chat_id to query
the adapter's has_pending_interrupt() and get_pending_message() methods.
But the adapter stores interrupt events under build_session_key(source),
which produces a different string (e.g. 'agent:main:telegram:dm' vs '123456').
This key mismatch meant the interrupt was never detected through the
adapter path, which is the only active interrupt path for all adapter-based
platforms (Telegram, Discord, Slack, etc.). The gateway-level interrupt
path (in dispatch_message) is unreachable because the adapter intercepts
the 2nd message in handle_message() before it reaches dispatch_message().
Result: sending a new message while subagents were running had no effect —
the interrupt was silently lost.
Fix: replace all source.chat_id references in the interrupt-related code
within _run_agent() with the session_key parameter, which matches the
adapter's storage keys.
Also adds regression tests verifying session_key vs chat_id consistency.
* debug: add file-based logging to CLI interrupt path
Temporary instrumentation to diagnose why message-based interrupts
don't seem to work during subagent execution. Logs to
~/.hermes/interrupt_debug.log (immune to redirect_stdout).
Two log points:
1. When Enter handler puts message into _interrupt_queue
2. When chat() reads it and calls agent.interrupt()
This will reveal whether the message reaches the queue and
whether the interrupt is actually fired.
* fix: accept unlisted models with warning instead of rejecting
validate_requested_model() previously hard-rejected any model not found
in the provider's API listing. This was too aggressive — users on higher
plan tiers (e.g. Z.AI Pro/Max) may have access to models not shown in
the public listing (like glm-5 on coding endpoints).
Changes:
- validate_requested_model: accept unlisted models with a warning note
instead of blocking. The model is saved to config and used immediately.
- Z.AI setup: always offer glm-5 in the model list regardless of whether
a coding endpoint was detected. Pro/Max plans support it.
- Z.AI setup detection message: softened from 'GLM-5 is not available'
to 'GLM-5 may still be available depending on your plan tier'
* fix: /reasoning command output ordering, display, and inline think extraction
Three issues with the /reasoning command:
1. Output interleaving: The command echo used print() while feedback
used _cprint(), causing them to render out-of-order under
prompt_toolkit's patch_stdout. Changed echo to use _cprint() so
all output renders through the same path in correct order.
2. Reasoning display not working: /reasoning show toggled a flag
but reasoning never appeared for models that embed thinking in
inline <think> blocks rather than structured API fields. Added
fallback extraction in _build_assistant_message to capture
<think> block content as reasoning when no structured reasoning
fields (reasoning, reasoning_content, reasoning_details) are
present. This feeds into both the reasoning callback (during
tool loops) and the post-response reasoning box display.
3. Feedback clarity: Added checkmarks to confirm actions, persisted
show/hide to config (was session-only before), and aligned the
status display for readability.
Tests: 7 new tests for inline think block extraction (41 total).
* feat: add /reasoning command to gateway (Telegram/Discord/etc)
The /reasoning command only existed in the CLI — messaging platforms
had no way to view or change reasoning settings. This adds:
1. /reasoning command handler in the gateway:
- No args: shows current effort level and display state
- /reasoning <level>: sets reasoning effort (none/low/medium/high/xhigh)
- /reasoning show|hide: toggles reasoning display in responses
- All changes saved to config.yaml immediately
2. Reasoning display in gateway responses:
- When show_reasoning is enabled, prepends a 'Reasoning' block
with the model's last_reasoning content before the response
- Collapses long reasoning (>15 lines) to keep messages readable
- Uses last_reasoning from run_conversation result dict
3. Plumbing:
- Added _show_reasoning attribute loaded from config at startup
- Propagated last_reasoning through _run_agent return dict
- Added /reasoning to help text and known_commands set
- Uses getattr for _show_reasoning to handle test stubs
* fix: improve Kimi model selection — auto-detect endpoint, add missing models
Kimi Coding Plan setup:
- New dedicated _model_flow_kimi() replaces the generic API-key flow
for kimi-coding. Removes the confusing 'Base URL' prompt entirely —
the endpoint is auto-detected from the API key prefix:
sk-kimi-* → api.kimi.com/coding/v1 (Kimi Coding Plan)
other → api.moonshot.ai/v1 (legacy Moonshot)
- Shows appropriate models for each endpoint:
Coding Plan: kimi-for-coding, kimi-k2.5, kimi-k2-thinking, kimi-k2-thinking-turbo
Moonshot: full model catalog
- Clears any stale KIMI_BASE_URL override so runtime auto-detection
via _resolve_kimi_base_url() works correctly.
Model catalog updates:
- Added kimi-for-coding (primary Coding Plan model) and kimi-k2-thinking-turbo
to models.py, main.py _PROVIDER_MODELS, and model_metadata.py context windows.
- Updated User-Agent from KimiCLI/1.0 to KimiCLI/1.3 (Kimi's coding
endpoint whitelists known coding agents via User-Agent sniffing).
curated_models_for_provider() now tries the live API first (via
provider_model_ids) before falling back to static _PROVIDER_MODELS.
This means /model and /provider slash commands show the actual
available models, not a stale hardcoded list.
Also added live Nous Portal model fetching via fetch_nous_models()
in provider_model_ids(), alongside the existing Codex live fetch.
- Custom endpoints can serve any model, so skip validation for
provider='custom' in validate_requested_model(). Previously it
would reject any model name since there's no static catalog or
live API to check against.
- Show clear setup instructions when switching to custom endpoint
without OPENAI_BASE_URL/OPENAI_API_KEY configured.
- Added curated model lists for Nous Portal and OpenAI Codex to
_PROVIDER_MODELS so /model shows their available models.
Both /model and /provider now show the same unified display:
Current: anthropic/claude-opus-4.6 via OpenRouter
Authenticated providers & models:
[openrouter] ← active
anthropic/claude-opus-4.6 ← current
anthropic/claude-sonnet-4.5
...
[nous]
claude-opus-4-6
gemini-3-flash
...
[openai-codex]
gpt-5.2-codex
gpt-5.1-codex-mini
...
Not configured: Z.AI / GLM, Kimi / Moonshot, ...
Switch model: /model <model-name>
Switch provider: /model <provider>:<model-name>
Example: /model nous:claude-opus-4-6
Users can see all authenticated providers and their models at a glance,
making it easy to switch mid-conversation.
Also added curated model lists for Nous Portal and OpenAI Codex to
hermes_cli/models.py.
Three issues caused the gateway to display 'openrouter' instead of
'Custom endpoint' when users configured a custom OAI-compatible endpoint:
1. hermes setup: custom endpoint path saved OPENAI_BASE_URL and
OPENAI_API_KEY to .env but never wrote model.provider to config.yaml.
All other providers (Codex, z.ai, Kimi, etc.) call
_update_config_for_provider() which sets this — custom was the only
path that skipped it. Now writes model.provider='custom' and
model.base_url to config.yaml.
2. hermes model: custom endpoint set model.provider='auto' in config.yaml.
The CLI display had a hack to detect OPENAI_BASE_URL and override to
'custom', but the gateway didn't. Now sets model.provider='custom'
directly.
3. gateway /model and /provider commands: defaulted to 'openrouter' and
read config.yaml — which had no provider set. Added OPENAI_BASE_URL
detection fallback (same pattern the CLI uses) as a defensive catch
for existing users who set up before this fix.
/provider command (CLI + gateway):
Shows all providers with auth status (✓/✗), aliases, and active marker.
Users can now discover what provider names work with provider:model syntax.
Gateway bugs fixed:
- Config was saved even when validation.persist=False (told user 'session
only' but actually persisted the unvalidated model)
- HERMES_INFERENCE_PROVIDER env var not set on provider switch, causing
the switch to be silently overridden if that env var was already set
parse_model_input hardened:
- Colon only treated as provider delimiter if left side is a recognized
provider name or alias. 'anthropic/claude-3.5-sonnet:beta' now passes
through as a model name instead of trying provider='anthropic/claude-3.5-sonnet'.
- HTTP URLs, random colons no longer misinterpreted.
56 tests passing across model validation, CLI commands, and integration.
'auto' doesn't always mean openrouter — it could be nous, zai,
kimi-coding, etc. depending on configured credentials. Reverted the
hardcoded mapping and now both CLI and gateway call
resolve_provider() to detect the actual active provider when 'auto'
is set. Falls back to openrouter only if resolution fails.
- normalize_provider('auto') now returns 'openrouter' (the default)
so /model shows the curated model list instead of nothing
- CLI /model display uses normalize_provider before looking up labels
- Gateway /model handler now uses the same validation logic as CLI:
live API probe, provider:model syntax, curated model list display
Add provider:model syntax to /model command for runtime provider switching:
/model zai:glm-5 → switch to Z.AI provider with glm-5
/model nous:hermes-3 → switch to Nous Portal with hermes-3
/model openrouter:anthropic/claude-sonnet-4.5 → explicit OpenRouter
When switching providers, credentials are resolved via resolve_runtime_provider
and validated before committing. Both model and provider are saved to config.
Provider aliases work (glm: → zai, kimi: → kimi-coding, etc.).
Enhanced /model (no args) display now shows:
- Current model and provider
- Curated model list for the current provider with ← marker
- Usage examples including provider:model syntax
39 tests covering parse_model_input, curated_models_for_provider,
provider switching (success + credential failure), and display output.
Not all providers require 'provider/model' format. Removing the rigid
format check lets the live API probe handle all validation uniformly.
If someone types 'gpt-5.4' on OpenRouter, the probe won't find it and
will suggest 'openai/gpt-5.4' — better UX than a format rejection.
Replace the static catalog-based model validation with a live API probe.
The /model command now hits the provider's /models endpoint to check if
the requested model actually exists:
- Model found in API → accepted + saved to config
- Model NOT found in API → rejected with 'Error: not a valid model'
and fuzzy-match suggestions from the live model list
- API unreachable → graceful fallback to hardcoded catalog (session-only
for unrecognized models)
- Format errors (empty, spaces, missing '/') still caught instantly
without a network call
The API probe takes ~0.2s for OpenRouter (346 models) and works with any
OpenAI-compatible endpoint (Ollama, vLLM, custom, etc.).
32 tests covering all paths: format checks, API found, API not found,
API unreachable fallback, CLI integration.
