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hermes-agent/hermes_cli/models.py

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Hermes Agent UX Improvements
2026-02-22 02:16:11 -08:00
"""
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
Canonical model catalogs and lightweight validation helpers.
Hermes Agent UX Improvements
2026-02-22 02:16:11 -08:00
Add, remove, or reorder entries here — both `hermes setup` and
`hermes` provider-selection will pick up the change automatically.
"""
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
from __future__ import annotations
feat: validate /model against live API instead of hardcoded lists 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.
2026-03-08 05:22:15 -07:00
import json
feat: add Vercel AI Gateway provider (#1628) * 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>
2026-03-17 00:12:16 -07:00
import os
feat: validate /model against live API instead of hardcoded lists 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.
2026-03-08 05:22:15 -07:00
import urllib.request
import urllib.error
feat: add Ollama Cloud as built-in provider Add ollama-cloud as a first-class provider with full parity to existing API-key providers (gemini, zai, minimax, etc.): - PROVIDER_REGISTRY entry with OLLAMA_API_KEY env var - Provider aliases: ollama -> custom (local), ollama_cloud -> ollama-cloud - models.dev integration for accurate context lengths - URL-to-provider mapping (ollama.com -> ollama-cloud) - Passthrough model normalization (preserves Ollama model:tag format) - Default auxiliary model (nemotron-3-nano:30b) - HermesOverlay in providers.py - CLI --provider choices, CANONICAL_PROVIDERS entry - Dynamic model discovery with disk caching (1hr TTL) - 37 provider-specific tests Cherry-picked from PR #6038 by kshitijk4poor. Closes #3926
2026-04-15 22:32:05 -07:00
import time
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
from difflib import get_close_matches
feat: add Ollama Cloud as built-in provider Add ollama-cloud as a first-class provider with full parity to existing API-key providers (gemini, zai, minimax, etc.): - PROVIDER_REGISTRY entry with OLLAMA_API_KEY env var - Provider aliases: ollama -> custom (local), ollama_cloud -> ollama-cloud - models.dev integration for accurate context lengths - URL-to-provider mapping (ollama.com -> ollama-cloud) - Passthrough model normalization (preserves Ollama model:tag format) - Default auxiliary model (nemotron-3-nano:30b) - HermesOverlay in providers.py - CLI --provider choices, CANONICAL_PROVIDERS entry - Dynamic model discovery with disk caching (1hr TTL) - 37 provider-specific tests Cherry-picked from PR #6038 by kshitijk4poor. Closes #3926
2026-04-15 22:32:05 -07:00
from pathlib import Path
fix: consolidate provider lists into single CANONICAL_PROVIDERS source of truth (#9237) 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
2026-04-13 14:59:50 -07:00
from typing import Any, NamedTuple, Optional
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
fix(cli): send User-Agent in /v1/models probe to pass Cloudflare 1010 Custom Claude proxies fronted by Cloudflare with Browser Integrity Check enabled (e.g. `packyapi.com`) reject requests with the default `Python-urllib/*` signature, returning HTTP 403 "error code: 1010". `probe_api_models` swallowed that in its blanket `except Exception: continue`, so `validate_requested_model` returned the misleading "Could not reach the <provider> API to validate `<model>`" error even though the endpoint is reachable and lists the requested model. Advertise the probe request as `hermes-cli/<version>` so Cloudflare treats it as a first-party client. This mirrors the pattern already used by `agent/gemini_native_adapter.py` and `agent/anthropic_adapter.py`, which set a descriptive UA for the same reason. Reproduction (pre-fix): python3 -c " import urllib.request req = urllib.request.Request( 'https://www.packyapi.com/v1/models', headers={'Authorization': 'Bearer sk-...'}) urllib.request.urlopen(req).read() " urllib.error.HTTPError: HTTP Error 403: Forbidden (body: b'error code: 1010') Any non-urllib UA (Mozilla, curl, reqwest) returns 200 with the OpenAI-compatible models listing. Tested on macOS (Python 3.11). No cross-platform concerns — the change is a single header addition to an existing `urllib.request.Request`.
2026-04-20 16:00:55 +08:00
from hermes_cli import __version__ as _HERMES_VERSION
# Identify ourselves so endpoints fronted by Cloudflare's Browser Integrity
# Check (error 1010) don't reject the default ``Python-urllib/*`` signature.
_HERMES_USER_AGENT = f"hermes-cli/{_HERMES_VERSION}"
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
COPILOT_BASE_URL = "https://api.githubcopilot.com"
COPILOT_MODELS_URL = f"{COPILOT_BASE_URL}/models"
COPILOT_EDITOR_VERSION = "vscode/1.104.1"
COPILOT_REASONING_EFFORTS_GPT5 = ["minimal", "low", "medium", "high"]
COPILOT_REASONING_EFFORTS_O_SERIES = ["low", "medium", "high"]
Refresh OpenRouter model catalog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-09 15:11:58 -05:00
# Fallback OpenRouter snapshot used when the live catalog is unavailable.
Hermes Agent UX Improvements
2026-02-22 02:16:11 -08:00
# (model_id, display description shown in menus)
OPENROUTER_MODELS: list[tuple[str, str]] = [
feat: replace kimi-k2.5 with kimi-k2.6 on OpenRouter and Nous Portal (#13148) * feat(security): URL query param + userinfo + form body redaction Port from nearai/ironclaw#2529. Hermes already has broad value-shape coverage in agent/redact.py (30+ vendor prefixes, JWTs, DB connstrs, etc.) but missed three key-name-based patterns that catch opaque tokens without recognizable prefixes: 1. URL query params - OAuth callback codes (?code=...), access_token, refresh_token, signature, etc. These are opaque and won't match any prefix regex. Now redacted by parameter NAME. 2. URL userinfo (https://user:pass@host) - for non-DB schemes. DB schemes were already handled by _DB_CONNSTR_RE. 3. Form-urlencoded body (k=v pairs joined by ampersands) - conservative, only triggers on clean pure-form inputs with no other text. Sensitive key allowlist matches ironclaw's (exact case-insensitive, NOT substring - so token_count and session_id pass through). Tests: +20 new test cases across 3 test classes. All 75 redact tests pass; gateway/test_pii_redaction and tools/test_browser_secret_exfil also green. Known pre-existing limitation: _ENV_ASSIGN_RE greedy match swallows whole all-caps ENV-style names + trailing text when followed by another assignment. Left untouched here (out of scope); URL query redaction handles the lowercase case. * feat: replace kimi-k2.5 with kimi-k2.6 on OpenRouter and Nous Portal Update model catalogs for OpenRouter (fallback snapshot), Nous Portal, and NVIDIA NIM to reference moonshotai/kimi-k2.6. Add kimi-k2.6 to the fixed-temperature frozenset in auxiliary_client.py so the 0.6 contract is enforced on aggregator routings. Native Moonshot provider lists (kimi-coding, kimi-coding-cn, moonshot, opencode-zen, opencode-go) are unchanged — those use Moonshot's own model IDs which are unaffected.
2026-04-20 11:49:54 -07:00
("moonshotai/kimi-k2.6", "recommended"),
feat: promote kimi-k2.5 to first position in all model suggestion lists (#11745) 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.
2026-04-17 12:05:22 -07:00
("anthropic/claude-opus-4.7", ""),
fix(agent): complete Claude Opus 4.7 API migration 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-guide Fixes NousResearch/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/.
2026-04-16 12:35:43 -05:00
("anthropic/claude-opus-4.6", ""),
chore: add claude-sonnet-4.6 to OpenRouter and Nous model lists (#4157)
2026-03-30 20:33:21 -07:00
("anthropic/claude-sonnet-4.6", ""),
Refresh OpenRouter model catalog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-09 15:11:58 -05:00
("qwen/qwen3.6-plus", ""),
Hermes Agent UX Improvements
2026-02-22 02:16:11 -08:00
("anthropic/claude-sonnet-4.5", ""),
feat: reorder OpenRouter catalog, add haiku-4.5, fix minimax slug - 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
2026-03-18 03:26:06 -07:00
("anthropic/claude-haiku-4.5", ""),
feat: add openrouter/elephant-alpha to curated model lists (#9378) * 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
2026-04-13 21:16:14 -07:00
("openrouter/elephant-alpha", "free"),
chore: update OpenRouter model list - Remove opus-4.5 and gpt-5.2 - Reorder GPT: 5.4-pro, 5.4, 5.3-codex - Add qwen/qwen3.5-plus-02-15 and qwen/qwen3.5-35b-a3b - Update z-ai/glm-4.7 → glm-5 - Update minimax/minimax-m2.1 → minimax-m2.5
2026-03-06 00:52:45 -08:00
("openai/gpt-5.4", ""),
feat: add gpt-5.4-mini, gpt-5.4-nano, healer-alpha to OpenRouter catalog
2026-03-18 03:23:20 -07:00
("openai/gpt-5.4-mini", ""),
docs: Gemini OAuth provider implementation plan (#2467) * 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)
2026-03-22 04:46:05 -07:00
("xiaomi/mimo-v2-pro", ""),
chore: update OpenRouter model list - Remove opus-4.5 and gpt-5.2 - Reorder GPT: 5.4-pro, 5.4, 5.3-codex - Add qwen/qwen3.5-plus-02-15 and qwen/qwen3.5-35b-a3b - Update z-ai/glm-4.7 → glm-5 - Update minimax/minimax-m2.1 → minimax-m2.5
2026-03-06 00:52:45 -08:00
("openai/gpt-5.3-codex", ""),
Refresh OpenRouter model catalog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-09 15:11:58 -05:00
("google/gemini-3-pro-image-preview", ""),
Hermes Agent UX Improvements
2026-02-22 02:16:11 -08:00
("google/gemini-3-flash-preview", ""),
feat: add Gemini 3.1 preview models to OpenRouter and Nous catalogs (#3803) * 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>
2026-03-29 15:44:07 -07:00
("google/gemini-3.1-pro-preview", ""),
("google/gemini-3.1-flash-lite-preview", ""),
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
("qwen/qwen3.5-plus-02-15", ""),
("qwen/qwen3.5-35b-a3b", ""),
chore: add openai/gpt-5.4-pro and stepfun/step-3.5-flash to OpenRouter models
2026-03-06 00:49:25 -08:00
("stepfun/step-3.5-flash", ""),
chore: add minimax-m2.7 to model catalogs (#2474) * 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>
2026-03-22 05:00:25 -07:00
("minimax/minimax-m2.7", ""),
chore: reorder OpenRouter catalog — glm-5-turbo under glm-5, minimax under stepfun
2026-03-18 03:31:04 -07:00
("minimax/minimax-m2.5", ""),
feat: replace z-ai/glm-5 with z-ai/glm-5.1 in OpenRouter and Nous model lists
2026-04-07 10:06:25 -07:00
("z-ai/glm-5.1", ""),
feat(zai): add GLM-5V-Turbo support for coding plan (#9907) - 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
2026-04-14 16:26:01 -07:00
("z-ai/glm-5v-turbo", ""),
chore: reorder OpenRouter catalog — glm-5-turbo under glm-5, minimax under stepfun
2026-03-18 03:31:04 -07:00
("z-ai/glm-5-turbo", ""),
Refresh OpenRouter model catalog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-09 15:11:58 -05:00
("x-ai/grok-4.20", ""),
docs: Gemini OAuth provider implementation plan (#2467) * 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)
2026-03-22 04:46:05 -07:00
("nvidia/nemotron-3-super-120b-a12b", ""),
feat: upgrade MiniMax default to M2.7 + add new OpenRouter models 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).
2026-03-18 02:42:58 -07:00
("nvidia/nemotron-3-super-120b-a12b:free", "free"),
("arcee-ai/trinity-large-preview:free", "free"),
feat: add arcee-ai/trinity-large-thinking to recommended models Added to OPENROUTER_MODELS and _PROVIDER_MODELS['nous'] lists. Also added 'trinity' family entry to DEFAULT_CONTEXT_LENGTHS (262K).
2026-04-03 13:45:16 -07:00
("arcee-ai/trinity-large-thinking", ""),
feat: reorder OpenRouter catalog, add haiku-4.5, fix minimax slug - 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
2026-03-18 03:26:06 -07:00
("openai/gpt-5.4-pro", ""),
("openai/gpt-5.4-nano", ""),
Hermes Agent UX Improvements
2026-02-22 02:16:11 -08:00
]
Refresh OpenRouter model catalog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-09 15:11:58 -05:00
_openrouter_catalog_cache: list[tuple[str, str]] | None = None
fix: unify openai-codex model list — derive from codex_models.py (#7844) 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.
2026-04-11 10:38:24 -07:00
feat: curated picker with live pricing for ai-gateway provider - Curated AI_GATEWAY_MODELS list in hermes_cli/models.py (OSS first, kimi-k2.5 as recommended default). - fetch_ai_gateway_models() filters the curated list against the live /v1/models catalog; falls back to the snapshot on network failure. - fetch_ai_gateway_pricing() translates Vercel's input/output field names to the prompt/completion shape the shared picker expects; carries input_cache_read / input_cache_write through unchanged. - get_pricing_for_provider() now handles ai-gateway. - _model_flow_ai_gateway() provides a guided URL prompt when no key is set and a pricing-column picker; routes ai-gateway to it instead of the generic api-key flow.
2026-04-19 23:05:14 -07:00
# Fallback Vercel AI Gateway snapshot used when the live catalog is unavailable.
# OSS / open-weight models prioritized first, then closed-source by family.
AI_GATEWAY_MODELS: list[tuple[str, str]] = [
("moonshotai/kimi-k2.5", "recommended"),
("qwen/qwen3.6-plus", ""),
("z-ai/glm-5.1", ""),
("minimax/minimax-m2.7", ""),
("anthropic/claude-sonnet-4.6", ""),
("anthropic/claude-opus-4.7", ""),
("anthropic/claude-opus-4.6", ""),
("anthropic/claude-haiku-4.5", ""),
("openai/gpt-5.4", ""),
("openai/gpt-5.4-mini", ""),
("openai/gpt-5.3-codex", ""),
("google/gemini-3.1-pro-preview", ""),
("google/gemini-3-flash-preview", ""),
("google/gemini-3.1-flash-lite-preview", ""),
("x-ai/grok-4.20", ""),
]
_ai_gateway_catalog_cache: list[tuple[str, str]] | None = None
fix: unify openai-codex model list — derive from codex_models.py (#7844) 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.
2026-04-11 10:38:24 -07:00
def _codex_curated_models() -> list[str]:
"""Derive the openai-codex curated list from codex_models.py.
Single source of truth: DEFAULT_CODEX_MODELS + forward-compat synthesis.
This keeps the gateway /model picker in sync with the CLI `hermes model`
flow without maintaining a separate static list.
"""
from hermes_cli.codex_models import DEFAULT_CODEX_MODELS, _add_forward_compat_models
return _add_forward_compat_models(list(DEFAULT_CODEX_MODELS))
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
_PROVIDER_MODELS: dict[str, list[str]] = {
feat: unified /model and /provider into single view 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.
2026-03-11 23:06:06 -07:00
"nous": [
feat: replace kimi-k2.5 with kimi-k2.6 on OpenRouter and Nous Portal (#13148) * feat(security): URL query param + userinfo + form body redaction Port from nearai/ironclaw#2529. Hermes already has broad value-shape coverage in agent/redact.py (30+ vendor prefixes, JWTs, DB connstrs, etc.) but missed three key-name-based patterns that catch opaque tokens without recognizable prefixes: 1. URL query params - OAuth callback codes (?code=...), access_token, refresh_token, signature, etc. These are opaque and won't match any prefix regex. Now redacted by parameter NAME. 2. URL userinfo (https://user:pass@host) - for non-DB schemes. DB schemes were already handled by _DB_CONNSTR_RE. 3. Form-urlencoded body (k=v pairs joined by ampersands) - conservative, only triggers on clean pure-form inputs with no other text. Sensitive key allowlist matches ironclaw's (exact case-insensitive, NOT substring - so token_count and session_id pass through). Tests: +20 new test cases across 3 test classes. All 75 redact tests pass; gateway/test_pii_redaction and tools/test_browser_secret_exfil also green. Known pre-existing limitation: _ENV_ASSIGN_RE greedy match swallows whole all-caps ENV-style names + trailing text when followed by another assignment. Left untouched here (out of scope); URL query redaction handles the lowercase case. * feat: replace kimi-k2.5 with kimi-k2.6 on OpenRouter and Nous Portal Update model catalogs for OpenRouter (fallback snapshot), Nous Portal, and NVIDIA NIM to reference moonshotai/kimi-k2.6. Add kimi-k2.6 to the fixed-temperature frozenset in auxiliary_client.py so the 0.6 contract is enforced on aggregator routings. Native Moonshot provider lists (kimi-coding, kimi-coding-cn, moonshot, opencode-zen, opencode-go) are unchanged — those use Moonshot's own model IDs which are unaffected.
2026-04-20 11:49:54 -07:00
"moonshotai/kimi-k2.6",
fix: make mimo-v2-pro the default model for Nous portal users 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.
2026-04-12 16:43:54 -07:00
"xiaomi/mimo-v2-pro",
feat: add claude-opus-4.7 to Nous Portal curated model list (#11398) 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.
2026-04-16 21:37:06 -07:00
"anthropic/claude-opus-4.7",
fix: align Nous Portal model slugs with OpenRouter naming (#3253) 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
2026-03-26 13:49:43 -07:00
"anthropic/claude-opus-4.6",
chore: add claude-sonnet-4.6 to OpenRouter and Nous model lists (#4157)
2026-03-30 20:33:21 -07:00
"anthropic/claude-sonnet-4.6",
fix: align Nous Portal model slugs with OpenRouter naming (#3253) 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
2026-03-26 13:49:43 -07:00
"anthropic/claude-sonnet-4.5",
"anthropic/claude-haiku-4.5",
"openai/gpt-5.4",
"openai/gpt-5.4-mini",
"openai/gpt-5.3-codex",
"google/gemini-3-pro-preview",
"google/gemini-3-flash-preview",
feat: add Gemini 3.1 preview models to OpenRouter and Nous catalogs (#3803) * 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>
2026-03-29 15:44:07 -07:00
"google/gemini-3.1-pro-preview",
"google/gemini-3.1-flash-lite-preview",
fix: align Nous Portal model slugs with OpenRouter naming (#3253) 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
2026-03-26 13:49:43 -07:00
"qwen/qwen3.5-plus-02-15",
"qwen/qwen3.5-35b-a3b",
"stepfun/step-3.5-flash",
"minimax/minimax-m2.7",
"minimax/minimax-m2.5",
feat: replace z-ai/glm-5 with z-ai/glm-5.1 in OpenRouter and Nous model lists
2026-04-07 10:06:25 -07:00
"z-ai/glm-5.1",
feat(zai): add GLM-5V-Turbo support for coding plan (#9907) - 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
2026-04-14 16:26:01 -07:00
"z-ai/glm-5v-turbo",
fix: align Nous Portal model slugs with OpenRouter naming (#3253) 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
2026-03-26 13:49:43 -07:00
"z-ai/glm-5-turbo",
"x-ai/grok-4.20-beta",
"nvidia/nemotron-3-super-120b-a12b",
"nvidia/nemotron-3-super-120b-a12b:free",
"arcee-ai/trinity-large-preview:free",
feat: add arcee-ai/trinity-large-thinking to recommended models Added to OPENROUTER_MODELS and _PROVIDER_MODELS['nous'] lists. Also added 'trinity' family entry to DEFAULT_CONTEXT_LENGTHS (262K).
2026-04-03 13:45:16 -07:00
"arcee-ai/trinity-large-thinking",
fix: align Nous Portal model slugs with OpenRouter naming (#3253) 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
2026-03-26 13:49:43 -07:00
"openai/gpt-5.4-pro",
"openai/gpt-5.4-nano",
feat: add openrouter/elephant-alpha to curated model lists (#9378) * 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
2026-04-13 21:16:14 -07:00
"openrouter/elephant-alpha",
feat: unified /model and /provider into single view 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.
2026-03-11 23:06:06 -07:00
],
fix: unify openai-codex model list — derive from codex_models.py (#7844) 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.
2026-04-11 10:38:24 -07:00
"openai-codex": _codex_curated_models(),
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
"copilot-acp": [
"copilot-acp",
],
"copilot": [
"gpt-5.4",
"gpt-5.4-mini",
"gpt-5-mini",
"gpt-5.3-codex",
"gpt-5.2-codex",
"gpt-4.1",
"gpt-4o",
"gpt-4o-mini",
"claude-opus-4.6",
"claude-sonnet-4.6",
"claude-sonnet-4.5",
"claude-haiku-4.5",
"gemini-2.5-pro",
"grok-code-fast-1",
],
feat(providers): add Google AI Studio (Gemini) as a first-class provider Cherry-picked from PR #5494 by kshitijk4poor. Adds native Gemini support via Google's OpenAI-compatible endpoint. Zero new dependencies.
2026-04-06 10:14:01 -07:00
"gemini": [
fix: update Gemini model catalog + wire models.dev as live model source Follow-up for salvaged PR #5494: - Update model catalog to Gemini 3.x + Gemma 4 (drop deprecated 2.0) - Add list_agentic_models() to models_dev.py with noise filter - Wire models.dev into _model_flow_api_key_provider as primary source (static curated list serves as offline fallback) - Add gemini -> google mapping in PROVIDER_TO_MODELS_DEV - Fix Gemma 4 context lengths to 256K (models.dev values) - Update auxiliary model to gemini-3-flash-preview - Expand tests: 3.x catalog, context lengths, models.dev integration
2026-04-06 10:19:19 -07:00
"gemini-3.1-pro-preview",
fix(gemini): list Gemini 3 preview models in google-gemini-cli/gemini pickers (#12776) The google-gemini-cli (Cloud Code Assist) and gemini (native API) model pickers only offered gemini-2.5-*, so users picking Gemini 3 had to type a custom model name — usually wrong (e.g. "gemini-3.1-pro"), producing a 404 from cloudcode-pa.googleapis.com. Replace the 2.5-* entries with the actual Code Assist / Gemini API preview IDs: gemini-3.1-pro-preview, gemini-3-pro-preview, gemini-3-flash-preview (and gemini-3.1-flash-lite-preview on native). Update the hardcoded fallback in hermes_cli/main.py to match. Copilot's menu retains gemini-2.5-pro — that catalog is Microsoft's.
2026-04-19 19:13:47 -07:00
"gemini-3-pro-preview",
fix: update Gemini model catalog + wire models.dev as live model source Follow-up for salvaged PR #5494: - Update model catalog to Gemini 3.x + Gemma 4 (drop deprecated 2.0) - Add list_agentic_models() to models_dev.py with noise filter - Wire models.dev into _model_flow_api_key_provider as primary source (static curated list serves as offline fallback) - Add gemini -> google mapping in PROVIDER_TO_MODELS_DEV - Fix Gemma 4 context lengths to 256K (models.dev values) - Update auxiliary model to gemini-3-flash-preview - Expand tests: 3.x catalog, context lengths, models.dev integration
2026-04-06 10:19:19 -07:00
"gemini-3-flash-preview",
"gemini-3.1-flash-lite-preview",
feat(providers): add Google AI Studio (Gemini) as a first-class provider Cherry-picked from PR #5494 by kshitijk4poor. Adds native Gemini support via Google's OpenAI-compatible endpoint. Zero new dependencies.
2026-04-06 10:14:01 -07:00
],
feat(gemini): add Google Gemini CLI OAuth provider via Cloud Code Assist (free + paid tiers) (#11270) * feat(gemini): add Google Gemini CLI OAuth provider via Cloud Code Assist Adds 'google-gemini-cli' as a first-class inference provider with native OAuth authentication against Google, hitting the Cloud Code Assist backend (cloudcode-pa.googleapis.com) that powers Google's official gemini-cli. Supports both the free tier (generous daily quota, personal accounts) and paid tiers (Standard/Enterprise via GCP projects). Architecture ============ Three new modules under agent/: 1. google_oauth.py (625 lines) — PKCE Authorization Code flow - Google's public gemini-cli desktop OAuth client baked in (env-var overrides supported) - Cross-process file lock (fcntl POSIX / msvcrt Windows) with thread-local re-entrancy - Packed refresh format 'refresh_token|project_id|managed_project_id' on disk - In-flight refresh deduplication — concurrent requests don't double-refresh - invalid_grant → wipe credentials, prompt re-login - Headless detection (SSH/HERMES_HEADLESS) → paste-mode fallback - Refresh 60 s before expiry, atomic write with fsync+replace 2. google_code_assist.py (350 lines) — Code Assist control plane - load_code_assist(): POST /v1internal:loadCodeAssist (prod → sandbox fallback) - onboard_user(): POST /v1internal:onboardUser with LRO polling up to 60 s - retrieve_user_quota(): POST /v1internal:retrieveUserQuota → QuotaBucket list - VPC-SC detection (SECURITY_POLICY_VIOLATED → force standard-tier) - resolve_project_context(): env → config → discovered → onboarded priority - Matches Google's gemini-cli User-Agent / X-Goog-Api-Client / Client-Metadata 3. gemini_cloudcode_adapter.py (640 lines) — OpenAI↔Gemini translation - GeminiCloudCodeClient mimics openai.OpenAI interface (.chat.completions.create) - Full message translation: system→systemInstruction, tool_calls↔functionCall, tool results→functionResponse with sentinel thoughtSignature - Tools → tools[].functionDeclarations, tool_choice → toolConfig modes - GenerationConfig pass-through (temperature, max_tokens, top_p, stop) - Thinking config normalization (thinkingBudget, thinkingLevel, includeThoughts) - Request envelope {project, model, user_prompt_id, request} - Streaming: SSE (?alt=sse) with thought-part → reasoning stream separation - Response unwrapping (Code Assist wraps Gemini response in 'response' field) - finishReason mapping to OpenAI convention (STOP→stop, MAX_TOKENS→length, etc.) Provider registration — all 9 touchpoints ========================================== - hermes_cli/auth.py: PROVIDER_REGISTRY, aliases, resolver, status fn, dispatch - hermes_cli/models.py: _PROVIDER_MODELS, CANONICAL_PROVIDERS, aliases - hermes_cli/providers.py: HermesOverlay, ALIASES - hermes_cli/config.py: OPTIONAL_ENV_VARS (HERMES_GEMINI_CLIENT_ID/_SECRET/_PROJECT_ID) - hermes_cli/runtime_provider.py: dispatch branch + pool-entry branch - hermes_cli/main.py: _model_flow_google_gemini_cli with upfront policy warning - hermes_cli/auth_commands.py: pool handler, _OAUTH_CAPABLE_PROVIDERS - hermes_cli/doctor.py: 'Google Gemini OAuth' health check - run_agent.py: single dispatch branch in _create_openai_client /gquota slash command ====================== Shows Code Assist quota buckets with 20-char progress bars, per (model, tokenType). Registered in hermes_cli/commands.py, handler _handle_gquota_command in cli.py. Attribution =========== Derived with significant reference to: - jenslys/opencode-gemini-auth (MIT) — OAuth flow shape, request envelope, public client credentials, retry semantics. Attribution preserved in module docstrings. - clawdbot/extensions/google — VPC-SC handling, project discovery pattern. - PR #10176 (@sliverp) — PKCE module structure. - PR #10779 (@newarthur) — cross-process file locking pattern. Supersedes PRs #6745, #10176, #10779 (to be closed on merge with credit). Upfront policy warning ====================== Google considers using the gemini-cli OAuth client with third-party software a policy violation. The interactive flow shows a clear warning and requires explicit 'y' confirmation before OAuth begins. Documented prominently in website/docs/integrations/providers.md. Tests ===== 74 new tests in tests/agent/test_gemini_cloudcode.py covering: - PKCE S256 roundtrip - Packed refresh format parse/format/roundtrip - Credential I/O (0600 perms, atomic write, packed on disk) - Token lifecycle (fresh/expiring/force-refresh/invalid_grant/rotation preservation) - Project ID env resolution (3 env vars, priority order) - Headless detection - VPC-SC detection (JSON-nested + text match) - loadCodeAssist parsing + VPC-SC → standard-tier fallback - onboardUser: free-tier allows empty project, paid requires it, LRO polling - retrieveUserQuota parsing - resolve_project_context: 3 short-circuit paths + discovery + onboarding - build_gemini_request: messages → contents, system separation, tool_calls, tool_results, tools[], tool_choice (auto/required/specific), generationConfig, thinkingConfig normalization - Code Assist envelope wrap shape - Response translation: text, functionCall, thought → reasoning, unwrapped response, empty candidates, finish_reason mapping - GeminiCloudCodeClient end-to-end with mocked HTTP - Provider registration (9 tests: registry, 4 alias forms, no-regression on google-gemini alias, models catalog, determine_api_mode, _OAUTH_CAPABLE_PROVIDERS preservation, config env vars) - Auth status dispatch (logged-in + not) - /gquota command registration - run_gemini_oauth_login_pure pool-dict shape All 74 pass. 349 total tests pass across directly-touched areas (existing test_api_key_providers, test_auth_qwen_provider, test_gemini_provider, test_cli_init, test_cli_provider_resolution, test_registry all still green). Coexistence with existing 'gemini' (API-key) provider ===================================================== The existing gemini API-key provider is completely untouched. Its alias 'google-gemini' still resolves to 'gemini', not 'google-gemini-cli'. Users can have both configured simultaneously; 'hermes model' shows both as separate options. * feat(gemini): ship Google's public gemini-cli OAuth client as default Pivots from 'scrape-from-local-gemini-cli' (clawdbot pattern) to 'ship-creds-in-source' (opencode-gemini-auth pattern) for zero-setup UX. These are Google's PUBLIC gemini-cli desktop OAuth credentials, published openly in Google's own open-source gemini-cli repository. Desktop OAuth clients are not confidential — PKCE provides the security, not the client_secret. Shipping them here matches opencode-gemini-auth (MIT) and Google's own distribution model. Resolution order is now: 1. HERMES_GEMINI_CLIENT_ID / _SECRET env vars (power users, custom GCP clients) 2. Shipped public defaults (common case — works out of the box) 3. Scrape from locally installed gemini-cli (fallback for forks that deliberately wipe the shipped defaults) 4. Helpful error with install / env-var hints The credential strings are composed piecewise at import time to keep reviewer intent explicit (each constant is paired with a comment about why it's non-confidential) and to bypass naive secret scanners. UX impact: users no longer need 'npm install -g @google/gemini-cli' as a prerequisite. Just 'hermes model' -> 'Google Gemini (OAuth)' works out of the box. Scrape path is retained as a safety net. Tests cover all four resolution steps (env / shipped default / scrape fallback / hard failure). 79 new unit tests pass (was 76, +3 for the new resolution behaviors).
2026-04-16 16:49:00 -07:00
"google-gemini-cli": [
fix(gemini): list Gemini 3 preview models in google-gemini-cli/gemini pickers (#12776) The google-gemini-cli (Cloud Code Assist) and gemini (native API) model pickers only offered gemini-2.5-*, so users picking Gemini 3 had to type a custom model name — usually wrong (e.g. "gemini-3.1-pro"), producing a 404 from cloudcode-pa.googleapis.com. Replace the 2.5-* entries with the actual Code Assist / Gemini API preview IDs: gemini-3.1-pro-preview, gemini-3-pro-preview, gemini-3-flash-preview (and gemini-3.1-flash-lite-preview on native). Update the hardcoded fallback in hermes_cli/main.py to match. Copilot's menu retains gemini-2.5-pro — that catalog is Microsoft's.
2026-04-19 19:13:47 -07:00
"gemini-3.1-pro-preview",
"gemini-3-pro-preview",
"gemini-3-flash-preview",
feat(gemini): add Google Gemini CLI OAuth provider via Cloud Code Assist (free + paid tiers) (#11270) * feat(gemini): add Google Gemini CLI OAuth provider via Cloud Code Assist Adds 'google-gemini-cli' as a first-class inference provider with native OAuth authentication against Google, hitting the Cloud Code Assist backend (cloudcode-pa.googleapis.com) that powers Google's official gemini-cli. Supports both the free tier (generous daily quota, personal accounts) and paid tiers (Standard/Enterprise via GCP projects). Architecture ============ Three new modules under agent/: 1. google_oauth.py (625 lines) — PKCE Authorization Code flow - Google's public gemini-cli desktop OAuth client baked in (env-var overrides supported) - Cross-process file lock (fcntl POSIX / msvcrt Windows) with thread-local re-entrancy - Packed refresh format 'refresh_token|project_id|managed_project_id' on disk - In-flight refresh deduplication — concurrent requests don't double-refresh - invalid_grant → wipe credentials, prompt re-login - Headless detection (SSH/HERMES_HEADLESS) → paste-mode fallback - Refresh 60 s before expiry, atomic write with fsync+replace 2. google_code_assist.py (350 lines) — Code Assist control plane - load_code_assist(): POST /v1internal:loadCodeAssist (prod → sandbox fallback) - onboard_user(): POST /v1internal:onboardUser with LRO polling up to 60 s - retrieve_user_quota(): POST /v1internal:retrieveUserQuota → QuotaBucket list - VPC-SC detection (SECURITY_POLICY_VIOLATED → force standard-tier) - resolve_project_context(): env → config → discovered → onboarded priority - Matches Google's gemini-cli User-Agent / X-Goog-Api-Client / Client-Metadata 3. gemini_cloudcode_adapter.py (640 lines) — OpenAI↔Gemini translation - GeminiCloudCodeClient mimics openai.OpenAI interface (.chat.completions.create) - Full message translation: system→systemInstruction, tool_calls↔functionCall, tool results→functionResponse with sentinel thoughtSignature - Tools → tools[].functionDeclarations, tool_choice → toolConfig modes - GenerationConfig pass-through (temperature, max_tokens, top_p, stop) - Thinking config normalization (thinkingBudget, thinkingLevel, includeThoughts) - Request envelope {project, model, user_prompt_id, request} - Streaming: SSE (?alt=sse) with thought-part → reasoning stream separation - Response unwrapping (Code Assist wraps Gemini response in 'response' field) - finishReason mapping to OpenAI convention (STOP→stop, MAX_TOKENS→length, etc.) Provider registration — all 9 touchpoints ========================================== - hermes_cli/auth.py: PROVIDER_REGISTRY, aliases, resolver, status fn, dispatch - hermes_cli/models.py: _PROVIDER_MODELS, CANONICAL_PROVIDERS, aliases - hermes_cli/providers.py: HermesOverlay, ALIASES - hermes_cli/config.py: OPTIONAL_ENV_VARS (HERMES_GEMINI_CLIENT_ID/_SECRET/_PROJECT_ID) - hermes_cli/runtime_provider.py: dispatch branch + pool-entry branch - hermes_cli/main.py: _model_flow_google_gemini_cli with upfront policy warning - hermes_cli/auth_commands.py: pool handler, _OAUTH_CAPABLE_PROVIDERS - hermes_cli/doctor.py: 'Google Gemini OAuth' health check - run_agent.py: single dispatch branch in _create_openai_client /gquota slash command ====================== Shows Code Assist quota buckets with 20-char progress bars, per (model, tokenType). Registered in hermes_cli/commands.py, handler _handle_gquota_command in cli.py. Attribution =========== Derived with significant reference to: - jenslys/opencode-gemini-auth (MIT) — OAuth flow shape, request envelope, public client credentials, retry semantics. Attribution preserved in module docstrings. - clawdbot/extensions/google — VPC-SC handling, project discovery pattern. - PR #10176 (@sliverp) — PKCE module structure. - PR #10779 (@newarthur) — cross-process file locking pattern. Supersedes PRs #6745, #10176, #10779 (to be closed on merge with credit). Upfront policy warning ====================== Google considers using the gemini-cli OAuth client with third-party software a policy violation. The interactive flow shows a clear warning and requires explicit 'y' confirmation before OAuth begins. Documented prominently in website/docs/integrations/providers.md. Tests ===== 74 new tests in tests/agent/test_gemini_cloudcode.py covering: - PKCE S256 roundtrip - Packed refresh format parse/format/roundtrip - Credential I/O (0600 perms, atomic write, packed on disk) - Token lifecycle (fresh/expiring/force-refresh/invalid_grant/rotation preservation) - Project ID env resolution (3 env vars, priority order) - Headless detection - VPC-SC detection (JSON-nested + text match) - loadCodeAssist parsing + VPC-SC → standard-tier fallback - onboardUser: free-tier allows empty project, paid requires it, LRO polling - retrieveUserQuota parsing - resolve_project_context: 3 short-circuit paths + discovery + onboarding - build_gemini_request: messages → contents, system separation, tool_calls, tool_results, tools[], tool_choice (auto/required/specific), generationConfig, thinkingConfig normalization - Code Assist envelope wrap shape - Response translation: text, functionCall, thought → reasoning, unwrapped response, empty candidates, finish_reason mapping - GeminiCloudCodeClient end-to-end with mocked HTTP - Provider registration (9 tests: registry, 4 alias forms, no-regression on google-gemini alias, models catalog, determine_api_mode, _OAUTH_CAPABLE_PROVIDERS preservation, config env vars) - Auth status dispatch (logged-in + not) - /gquota command registration - run_gemini_oauth_login_pure pool-dict shape All 74 pass. 349 total tests pass across directly-touched areas (existing test_api_key_providers, test_auth_qwen_provider, test_gemini_provider, test_cli_init, test_cli_provider_resolution, test_registry all still green). Coexistence with existing 'gemini' (API-key) provider ===================================================== The existing gemini API-key provider is completely untouched. Its alias 'google-gemini' still resolves to 'gemini', not 'google-gemini-cli'. Users can have both configured simultaneously; 'hermes model' shows both as separate options. * feat(gemini): ship Google's public gemini-cli OAuth client as default Pivots from 'scrape-from-local-gemini-cli' (clawdbot pattern) to 'ship-creds-in-source' (opencode-gemini-auth pattern) for zero-setup UX. These are Google's PUBLIC gemini-cli desktop OAuth credentials, published openly in Google's own open-source gemini-cli repository. Desktop OAuth clients are not confidential — PKCE provides the security, not the client_secret. Shipping them here matches opencode-gemini-auth (MIT) and Google's own distribution model. Resolution order is now: 1. HERMES_GEMINI_CLIENT_ID / _SECRET env vars (power users, custom GCP clients) 2. Shipped public defaults (common case — works out of the box) 3. Scrape from locally installed gemini-cli (fallback for forks that deliberately wipe the shipped defaults) 4. Helpful error with install / env-var hints The credential strings are composed piecewise at import time to keep reviewer intent explicit (each constant is paired with a comment about why it's non-confidential) and to bypass naive secret scanners. UX impact: users no longer need 'npm install -g @google/gemini-cli' as a prerequisite. Just 'hermes model' -> 'Google Gemini (OAuth)' works out of the box. Scrape path is retained as a safety net. Tests cover all four resolution steps (env / shipped default / scrape fallback / hard failure). 79 new unit tests pass (was 76, +3 for the new resolution behaviors).
2026-04-16 16:49:00 -07:00
],
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
"zai": [
fix: preserve dots in model names for OpenCode Zen and ZAI providers (#8794) 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)
2026-04-12 21:22:59 -07:00
"glm-5.1",
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
"glm-5",
feat(zai): add GLM-5V-Turbo support for coding plan (#9907) - 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
2026-04-14 16:26:01 -07:00
"glm-5v-turbo",
feat(models): add glm-5-turbo to zai provider model list (#3095) 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.
2026-03-25 17:42:25 -07:00
"glm-5-turbo",
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
"glm-4.7",
"glm-4.5",
"glm-4.5-flash",
],
feat(providers): add native xAI provider 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
2026-04-10 12:51:30 +04:00
"xai": [
feat(xai): upgrade to Responses API, add TTS provider Cherry-picked and trimmed from PR #10600 by Jaaneek. - Switch xAI transport from openai_chat to codex_responses (Responses API) - Add codex_responses detection for xAI in all runtime_provider resolution paths - Add xAI api_mode detection in AIAgent.__init__ (provider name + URL auto-detect) - Add extra_headers passthrough for codex_responses requests - Add x-grok-conv-id session header for xAI prompt caching - Add xAI reasoning support (encrypted_content include, no effort param) - Move x-grok-conv-id from chat_completions path to codex_responses path - Add xAI TTS provider (dedicated /v1/tts endpoint with Opus conversion) - Add xAI provider aliases (grok, x-ai, x.ai) across auth, models, providers, auxiliary - Trim xAI model list to agentic models (grok-4.20-reasoning, grok-4-1-fast-reasoning) - Add XAI_API_KEY/XAI_BASE_URL to OPTIONAL_ENV_VARS - Add xAI TTS config section, setup wizard entry, tools_config provider option - Add shared xai_http.py helper for User-Agent string Co-authored-by: Jaaneek <Jaaneek@users.noreply.github.com>
2026-04-15 22:27:26 -07:00
"grok-4.20-reasoning",
feat(providers): add native xAI provider 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
2026-04-10 12:51:30 +04:00
"grok-4-1-fast-reasoning",
],
feat(providers): add native NVIDIA NIM provider 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.
2026-04-17 09:55:58 -07:00
"nvidia": [
fix(providers): complete NVIDIA NIM parity with other providers 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.
2026-04-17 13:09:14 -07:00
# NVIDIA flagship reasoning models
feat(providers): add native NVIDIA NIM provider 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.
2026-04-17 09:55:58 -07:00
"nvidia/nemotron-3-super-120b-a12b",
fix(providers): complete NVIDIA NIM parity with other providers 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.
2026-04-17 13:09:14 -07:00
"nvidia/nemotron-3-nano-30b-a3b",
"nvidia/llama-3.3-nemotron-super-49b-v1.5",
# Third-party agentic models hosted on build.nvidia.com
# (map to OpenRouter defaults — users get familiar picks on NIM)
"qwen/qwen3.5-397b-a17b",
"deepseek-ai/deepseek-v3.2",
feat: replace kimi-k2.5 with kimi-k2.6 on OpenRouter and Nous Portal (#13148) * feat(security): URL query param + userinfo + form body redaction Port from nearai/ironclaw#2529. Hermes already has broad value-shape coverage in agent/redact.py (30+ vendor prefixes, JWTs, DB connstrs, etc.) but missed three key-name-based patterns that catch opaque tokens without recognizable prefixes: 1. URL query params - OAuth callback codes (?code=...), access_token, refresh_token, signature, etc. These are opaque and won't match any prefix regex. Now redacted by parameter NAME. 2. URL userinfo (https://user:pass@host) - for non-DB schemes. DB schemes were already handled by _DB_CONNSTR_RE. 3. Form-urlencoded body (k=v pairs joined by ampersands) - conservative, only triggers on clean pure-form inputs with no other text. Sensitive key allowlist matches ironclaw's (exact case-insensitive, NOT substring - so token_count and session_id pass through). Tests: +20 new test cases across 3 test classes. All 75 redact tests pass; gateway/test_pii_redaction and tools/test_browser_secret_exfil also green. Known pre-existing limitation: _ENV_ASSIGN_RE greedy match swallows whole all-caps ENV-style names + trailing text when followed by another assignment. Left untouched here (out of scope); URL query redaction handles the lowercase case. * feat: replace kimi-k2.5 with kimi-k2.6 on OpenRouter and Nous Portal Update model catalogs for OpenRouter (fallback snapshot), Nous Portal, and NVIDIA NIM to reference moonshotai/kimi-k2.6. Add kimi-k2.6 to the fixed-temperature frozenset in auxiliary_client.py so the 0.6 contract is enforced on aggregator routings. Native Moonshot provider lists (kimi-coding, kimi-coding-cn, moonshot, opencode-zen, opencode-go) are unchanged — those use Moonshot's own model IDs which are unaffected.
2026-04-20 11:49:54 -07:00
"moonshotai/kimi-k2.6",
feat(providers): add native NVIDIA NIM provider 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.
2026-04-17 09:55:58 -07:00
"minimaxai/minimax-m2.5",
fix(providers): complete NVIDIA NIM parity with other providers 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.
2026-04-17 13:09:14 -07:00
"z-ai/glm5",
"openai/gpt-oss-120b",
feat(providers): add native NVIDIA NIM provider 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.
2026-04-17 09:55:58 -07:00
],
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
"kimi-coding": [
feat: add kimi-k2.6 to kimi-coding, kimi-coding-cn, and moonshot providers (#13152) Add kimi-k2.6 as the top model in kimi-coding, kimi-coding-cn, and moonshot static provider lists (models.py, setup.py, main.py). kimi-k2.5 retained alongside it.
2026-04-20 11:56:56 -07:00
"kimi-k2.6",
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
"kimi-k2.5",
feat: promote kimi-k2.5 to first position in all model suggestion lists (#11745) 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.
2026-04-17 12:05:22 -07:00
"kimi-for-coding",
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
"kimi-k2-thinking",
fix: improve Kimi model selection — auto-detect endpoint, add missing models (#1039) * 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).
2026-03-12 05:58:48 -07:00
"kimi-k2-thinking-turbo",
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
"kimi-k2-turbo-preview",
"kimi-k2-0905-preview",
],
feat(providers): add kimi-coding-cn provider for mainland China users 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.
2026-04-13 11:13:09 -07:00
"kimi-coding-cn": [
feat: add kimi-k2.6 to kimi-coding, kimi-coding-cn, and moonshot providers (#13152) Add kimi-k2.6 as the top model in kimi-coding, kimi-coding-cn, and moonshot static provider lists (models.py, setup.py, main.py). kimi-k2.5 retained alongside it.
2026-04-20 11:56:56 -07:00
"kimi-k2.6",
feat(providers): add kimi-coding-cn provider for mainland China users 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.
2026-04-13 11:13:09 -07:00
"kimi-k2.5",
"kimi-k2-thinking",
"kimi-k2-turbo-preview",
"kimi-k2-0905-preview",
],
fix: repair OpenCode model routing and selection (#4508) 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>
2026-04-02 09:36:24 -07:00
"moonshot": [
feat: add kimi-k2.6 to kimi-coding, kimi-coding-cn, and moonshot providers (#13152) Add kimi-k2.6 as the top model in kimi-coding, kimi-coding-cn, and moonshot static provider lists (models.py, setup.py, main.py). kimi-k2.5 retained alongside it.
2026-04-20 11:56:56 -07:00
"kimi-k2.6",
fix: repair OpenCode model routing and selection (#4508) 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>
2026-04-02 09:36:24 -07:00
"kimi-k2.5",
"kimi-k2-thinking",
"kimi-k2-turbo-preview",
"kimi-k2-0905-preview",
],
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
"minimax": [
fix(minimax): correct context lengths, model catalog, thinking guard, aux model, and config base_url Cherry-picked from PR #6046 by kshitijk4poor with dead code stripped. - Context lengths: 204800 → 1M (M1) / 1048576 (M2.5/M2.7) per official docs - Model catalog: add M1 family, remove deprecated M2.1 and highspeed variants - Thinking guard: skip extended thinking for MiniMax (Anthropic-compat endpoint) - Aux model: MiniMax-M2.7-highspeed → MiniMax-M2.7 (same model, half price) - Config base_url: honour model.base_url for API-key providers (fixes China users) - Stripped unused get_minimax_max_output() / _MINIMAX_MAX_OUTPUT (no consumer) Fixes #5777, #4082, #6039. Closes #3895.
2026-04-08 01:39:28 -07:00
"MiniMax-M2.7",
fix: align MiniMax provider with official API docs 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>
2026-04-10 03:53:18 -07:00
"MiniMax-M2.5",
"MiniMax-M2.1",
"MiniMax-M2",
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
],
"minimax-cn": [
fix(minimax): correct context lengths, model catalog, thinking guard, aux model, and config base_url Cherry-picked from PR #6046 by kshitijk4poor with dead code stripped. - Context lengths: 204800 → 1M (M1) / 1048576 (M2.5/M2.7) per official docs - Model catalog: add M1 family, remove deprecated M2.1 and highspeed variants - Thinking guard: skip extended thinking for MiniMax (Anthropic-compat endpoint) - Aux model: MiniMax-M2.7-highspeed → MiniMax-M2.7 (same model, half price) - Config base_url: honour model.base_url for API-key providers (fixes China users) - Stripped unused get_minimax_max_output() / _MINIMAX_MAX_OUTPUT (no consumer) Fixes #5777, #4082, #6039. Closes #3895.
2026-04-08 01:39:28 -07:00
"MiniMax-M2.7",
fix: align MiniMax provider with official API docs 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>
2026-04-10 03:53:18 -07:00
"MiniMax-M2.5",
"MiniMax-M2.1",
"MiniMax-M2",
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
],
feat: native Anthropic provider with Claude Code credential auto-discovery Add Anthropic as a first-class inference provider, bypassing OpenRouter for direct API access. Uses the native Anthropic SDK with a full format adapter (same pattern as the codex_responses api_mode). ## Auth (three methods, priority order) 1. ANTHROPIC_API_KEY env var (regular API key, sk-ant-api-*) 2. ANTHROPIC_TOKEN / CLAUDE_CODE_OAUTH_TOKEN env var (setup-token, sk-ant-oat-*) 3. Auto-discovery from ~/.claude/.credentials.json (Claude Code subscription) - Reads Claude Code's OAuth credentials - Checks token expiry with 60s buffer - Setup tokens use Bearer auth + anthropic-beta: oauth-2025-04-20 header - Regular API keys use standard x-api-key header ## Changes by file ### New files - agent/anthropic_adapter.py — Client builder, message/tool/response format conversion, Claude Code credential reader, token resolver. Handles system prompt extraction, tool_use/tool_result blocks, thinking/reasoning, orphaned tool_use cleanup, cache_control. - tests/test_anthropic_adapter.py — 36 tests covering all adapter logic ### Modified files - pyproject.toml — Add anthropic>=0.39.0 dependency - hermes_cli/auth.py — Add 'anthropic' to PROVIDER_REGISTRY with three env vars, plus 'claude'/'claude-code' aliases - hermes_cli/models.py — Add model catalog, labels, aliases, provider order - hermes_cli/main.py — Add 'anthropic' to --provider CLI choices - hermes_cli/runtime_provider.py — Add Anthropic branch returning api_mode='anthropic_messages' (before generic api_key fallthrough) - hermes_cli/setup.py — Add Anthropic setup wizard with Claude Code credential auto-discovery, model selection, OpenRouter tools prompt - agent/auxiliary_client.py — Add claude-haiku-4-5 as aux model - agent/model_metadata.py — Add bare Claude model context lengths - run_agent.py — Add anthropic_messages api_mode: * Client init (Anthropic SDK instead of OpenAI) * API call dispatch (_anthropic_client.messages.create) * Response validation (content blocks) * finish_reason mapping (stop_reason -> finish_reason) * Token usage (input_tokens/output_tokens) * Response normalization (normalize_anthropic_response) * Client interrupt/rebuild * Prompt caching auto-enabled for native Anthropic - tests/test_run_agent.py — Update test_anthropic_base_url_accepted to expect native routing, add test_prompt_caching_native_anthropic
2026-03-12 15:47:45 -07:00
"anthropic": [
fix(agent): complete Claude Opus 4.7 API migration 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-guide Fixes NousResearch/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/.
2026-04-16 12:35:43 -05:00
"claude-opus-4-7",
fix(anthropic): live model fetching + adaptive thinking for 4.5+ models - 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
2026-03-12 17:04:31 -07:00
"claude-opus-4-6",
"claude-sonnet-4-6",
"claude-opus-4-5-20251101",
"claude-sonnet-4-5-20250929",
feat: native Anthropic provider with Claude Code credential auto-discovery Add Anthropic as a first-class inference provider, bypassing OpenRouter for direct API access. Uses the native Anthropic SDK with a full format adapter (same pattern as the codex_responses api_mode). ## Auth (three methods, priority order) 1. ANTHROPIC_API_KEY env var (regular API key, sk-ant-api-*) 2. ANTHROPIC_TOKEN / CLAUDE_CODE_OAUTH_TOKEN env var (setup-token, sk-ant-oat-*) 3. Auto-discovery from ~/.claude/.credentials.json (Claude Code subscription) - Reads Claude Code's OAuth credentials - Checks token expiry with 60s buffer - Setup tokens use Bearer auth + anthropic-beta: oauth-2025-04-20 header - Regular API keys use standard x-api-key header ## Changes by file ### New files - agent/anthropic_adapter.py — Client builder, message/tool/response format conversion, Claude Code credential reader, token resolver. Handles system prompt extraction, tool_use/tool_result blocks, thinking/reasoning, orphaned tool_use cleanup, cache_control. - tests/test_anthropic_adapter.py — 36 tests covering all adapter logic ### Modified files - pyproject.toml — Add anthropic>=0.39.0 dependency - hermes_cli/auth.py — Add 'anthropic' to PROVIDER_REGISTRY with three env vars, plus 'claude'/'claude-code' aliases - hermes_cli/models.py — Add model catalog, labels, aliases, provider order - hermes_cli/main.py — Add 'anthropic' to --provider CLI choices - hermes_cli/runtime_provider.py — Add Anthropic branch returning api_mode='anthropic_messages' (before generic api_key fallthrough) - hermes_cli/setup.py — Add Anthropic setup wizard with Claude Code credential auto-discovery, model selection, OpenRouter tools prompt - agent/auxiliary_client.py — Add claude-haiku-4-5 as aux model - agent/model_metadata.py — Add bare Claude model context lengths - run_agent.py — Add anthropic_messages api_mode: * Client init (Anthropic SDK instead of OpenAI) * API call dispatch (_anthropic_client.messages.create) * Response validation (content blocks) * finish_reason mapping (stop_reason -> finish_reason) * Token usage (input_tokens/output_tokens) * Response normalization (normalize_anthropic_response) * Client interrupt/rebuild * Prompt caching auto-enabled for native Anthropic - tests/test_run_agent.py — Update test_anthropic_base_url_accepted to expect native routing, add test_prompt_caching_native_anthropic
2026-03-12 15:47:45 -07:00
"claude-opus-4-20250514",
fix(anthropic): live model fetching + adaptive thinking for 4.5+ models - 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
2026-03-12 17:04:31 -07:00
"claude-sonnet-4-20250514",
feat: native Anthropic provider with Claude Code credential auto-discovery Add Anthropic as a first-class inference provider, bypassing OpenRouter for direct API access. Uses the native Anthropic SDK with a full format adapter (same pattern as the codex_responses api_mode). ## Auth (three methods, priority order) 1. ANTHROPIC_API_KEY env var (regular API key, sk-ant-api-*) 2. ANTHROPIC_TOKEN / CLAUDE_CODE_OAUTH_TOKEN env var (setup-token, sk-ant-oat-*) 3. Auto-discovery from ~/.claude/.credentials.json (Claude Code subscription) - Reads Claude Code's OAuth credentials - Checks token expiry with 60s buffer - Setup tokens use Bearer auth + anthropic-beta: oauth-2025-04-20 header - Regular API keys use standard x-api-key header ## Changes by file ### New files - agent/anthropic_adapter.py — Client builder, message/tool/response format conversion, Claude Code credential reader, token resolver. Handles system prompt extraction, tool_use/tool_result blocks, thinking/reasoning, orphaned tool_use cleanup, cache_control. - tests/test_anthropic_adapter.py — 36 tests covering all adapter logic ### Modified files - pyproject.toml — Add anthropic>=0.39.0 dependency - hermes_cli/auth.py — Add 'anthropic' to PROVIDER_REGISTRY with three env vars, plus 'claude'/'claude-code' aliases - hermes_cli/models.py — Add model catalog, labels, aliases, provider order - hermes_cli/main.py — Add 'anthropic' to --provider CLI choices - hermes_cli/runtime_provider.py — Add Anthropic branch returning api_mode='anthropic_messages' (before generic api_key fallthrough) - hermes_cli/setup.py — Add Anthropic setup wizard with Claude Code credential auto-discovery, model selection, OpenRouter tools prompt - agent/auxiliary_client.py — Add claude-haiku-4-5 as aux model - agent/model_metadata.py — Add bare Claude model context lengths - run_agent.py — Add anthropic_messages api_mode: * Client init (Anthropic SDK instead of OpenAI) * API call dispatch (_anthropic_client.messages.create) * Response validation (content blocks) * finish_reason mapping (stop_reason -> finish_reason) * Token usage (input_tokens/output_tokens) * Response normalization (normalize_anthropic_response) * Client interrupt/rebuild * Prompt caching auto-enabled for native Anthropic - tests/test_run_agent.py — Update test_anthropic_base_url_accepted to expect native routing, add test_prompt_caching_native_anthropic
2026-03-12 15:47:45 -07:00
"claude-haiku-4-5-20251001",
],
feat: auto-detect provider when switching models via /model (#1506) 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>
2026-03-16 04:34:45 -07:00
"deepseek": [
"deepseek-chat",
"deepseek-reasoner",
],
feat(xiaomi): add Xiaomi MiMo as first-class provider 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.
2026-04-11 10:10:31 -07:00
"xiaomi": [
"mimo-v2-pro",
"mimo-v2-omni",
"mimo-v2-flash",
],
feat(providers): add Arcee AI as direct API provider 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.
2026-04-13 17:16:43 -07:00
"arcee": [
"trinity-large-thinking",
"trinity-large-preview",
"trinity-mini",
],
feat(provider): add OpenCode Zen and OpenCode Go providers 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>
2026-03-17 02:02:43 -07:00
"opencode-zen": [
feat: promote kimi-k2.5 to first position in all model suggestion lists (#11745) 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.
2026-04-17 12:05:22 -07:00
"kimi-k2.5",
feat(provider): add OpenCode Zen and OpenCode Go providers 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>
2026-03-17 02:02:43 -07:00
"gpt-5.4-pro",
"gpt-5.4",
"gpt-5.3-codex",
"gpt-5.2",
"gpt-5.2-codex",
"gpt-5.1",
"gpt-5.1-codex",
"gpt-5.1-codex-max",
"gpt-5.1-codex-mini",
"gpt-5",
"gpt-5-codex",
"gpt-5-nano",
"claude-opus-4-6",
"claude-opus-4-5",
"claude-opus-4-1",
"claude-sonnet-4-6",
"claude-sonnet-4-5",
"claude-sonnet-4",
"claude-haiku-4-5",
"claude-3-5-haiku",
"gemini-3.1-pro",
"gemini-3-pro",
"gemini-3-flash",
chore: add minimax-m2.7 to model catalogs (#2474) * 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>
2026-03-22 05:00:25 -07:00
"minimax-m2.7",
feat(provider): add OpenCode Zen and OpenCode Go providers 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>
2026-03-17 02:02:43 -07:00
"minimax-m2.5",
"minimax-m2.5-free",
"minimax-m2.1",
"glm-5",
"glm-4.7",
"glm-4.6",
"kimi-k2-thinking",
"kimi-k2",
"qwen3-coder",
"big-pickle",
],
"opencode-go": [
feat: promote kimi-k2.5 to first position in all model suggestion lists (#11745) 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.
2026-04-17 12:05:22 -07:00
"kimi-k2.5",
fix(models): add glm-5.1 to opencode-go catalogs
2026-04-16 17:19:28 -06:00
"glm-5.1",
feat(provider): add OpenCode Zen and OpenCode Go providers 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>
2026-03-17 02:02:43 -07:00
"glm-5",
fix(opencode-go): strip trailing /v1 from base URL for Anthropic models (#4918) 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
2026-04-03 18:47:51 -07:00
"mimo-v2-pro",
"mimo-v2-omni",
feat: add MiniMax M2.7 to hermes model picker and opencode-go (#4208) 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.
2026-03-31 01:54:13 -07:00
"minimax-m2.7",
fix(opencode-go): strip trailing /v1 from base URL for Anthropic models (#4918) 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
2026-04-03 18:47:51 -07:00
"minimax-m2.5",
feat(provider): add OpenCode Zen and OpenCode Go providers 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>
2026-03-17 02:02:43 -07:00
],
feat: add Vercel AI Gateway provider (#1628) * 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>
2026-03-17 00:12:16 -07:00
"ai-gateway": [
"anthropic/claude-opus-4.6",
"anthropic/claude-sonnet-4.6",
"anthropic/claude-sonnet-4.5",
"anthropic/claude-haiku-4.5",
"openai/gpt-5",
"openai/gpt-4.1",
"openai/gpt-4.1-mini",
"google/gemini-3-pro-preview",
"google/gemini-3-flash",
"google/gemini-2.5-pro",
"google/gemini-2.5-flash",
"deepseek/deepseek-v3.2",
],
feat: add Kilo Code (kilocode) as first-class inference provider (#1666) 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>
2026-03-17 02:40:34 -07:00
"kilocode": [
"anthropic/claude-opus-4.6",
"anthropic/claude-sonnet-4.6",
"openai/gpt-5.4",
"google/gemini-3-pro-preview",
"google/gemini-3-flash-preview",
],
fix: alibaba provider default endpoint and model list (#3484) - 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.
2026-03-27 22:10:10 -07:00
# Alibaba DashScope Coding platform (coding-intl) — default endpoint.
# Supports Qwen models + third-party providers (GLM, Kimi, MiniMax).
# Users with classic DashScope keys should override DASHSCOPE_BASE_URL
# to https://dashscope-intl.aliyuncs.com/compatible-mode/v1 (OpenAI-compat)
# or https://dashscope-intl.aliyuncs.com/apps/anthropic (Anthropic-compat).
feat: add Alibaba Cloud provider and Anthropic base_url override (#1673) 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
2026-03-17 02:49:22 -07:00
"alibaba": [
feat: promote kimi-k2.5 to first position in all model suggestion lists (#11745) 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.
2026-04-17 12:05:22 -07:00
"kimi-k2.5",
feat: add Alibaba Cloud provider and Anthropic base_url override (#1673) 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
2026-03-17 02:49:22 -07:00
"qwen3.5-plus",
"qwen3-coder-plus",
"qwen3-coder-next",
fix: alibaba provider default endpoint and model list (#3484) - 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.
2026-03-27 22:10:10 -07:00
# Third-party models available on coding-intl
"glm-5",
"glm-4.7",
"MiniMax-M2.5",
feat: add Alibaba Cloud provider and Anthropic base_url override (#1673) 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
2026-03-17 02:49:22 -07:00
],
feat: curate HF model picker with OpenRouter analogues (#3440) 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.
2026-03-27 13:54:46 -07:00
# Curated HF model list — only agentic models that map to OpenRouter defaults.
feat: add Hugging Face as a first-class inference provider (#3419) 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>
2026-03-27 12:41:59 -07:00
"huggingface": [
feat: promote kimi-k2.5 to first position in all model suggestion lists (#11745) 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.
2026-04-17 12:05:22 -07:00
"moonshotai/Kimi-K2.5",
feat: add Hugging Face as a first-class inference provider (#3419) 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>
2026-03-27 12:41:59 -07:00
"Qwen/Qwen3.5-397B-A17B",
feat: curate HF model picker with OpenRouter analogues (#3440) 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.
2026-03-27 13:54:46 -07:00
"Qwen/Qwen3.5-35B-A3B",
feat: add Hugging Face as a first-class inference provider (#3419) 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>
2026-03-27 12:41:59 -07:00
"deepseek-ai/DeepSeek-V3.2",
"MiniMaxAI/MiniMax-M2.5",
"zai-org/GLM-5",
feat: curate HF model picker with OpenRouter analogues (#3440) 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.
2026-03-27 13:54:46 -07:00
"XiaomiMiMo/MiMo-V2-Flash",
"moonshotai/Kimi-K2-Thinking",
feat: add moonshotai/Kimi-K2.6 to HuggingFace provider models (#13169)
2026-04-20 12:49:16 -07:00
"moonshotai/Kimi-K2.6",
feat: add Hugging Face as a first-class inference provider (#3419) 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>
2026-03-27 12:41:59 -07:00
],
feat: native AWS Bedrock provider via Converse API Salvaged from PR #7920 by JiaDe-Wu — cherry-picked Bedrock-specific additions onto current main, skipping stale-branch reverts (293 commits behind). Dual-path architecture: - Claude models → AnthropicBedrock SDK (prompt caching, thinking budgets) - Non-Claude models → Converse API via boto3 (Nova, DeepSeek, Llama, Mistral) Includes: - Core adapter (agent/bedrock_adapter.py, 1098 lines) - Full provider registration (auth, models, providers, config, runtime, main) - IAM credential chain + Bedrock API Key auth modes - Dynamic model discovery via ListFoundationModels + ListInferenceProfiles - Streaming with delta callbacks, error classification, guardrails - hermes doctor + hermes auth integration - /usage pricing for 7 Bedrock models - 130 automated tests (79 unit + 28 integration + follow-up fixes) - Documentation (website/docs/guides/aws-bedrock.md) - boto3 optional dependency (pip install hermes-agent[bedrock]) Co-authored-by: JiaDe WU <40445668+JiaDe-Wu@users.noreply.github.com>
2026-04-15 15:18:01 -07:00
# AWS Bedrock — static fallback list used when dynamic discovery is
# unavailable (no boto3, no credentials, or API error). The agent
# prefers live discovery via ListFoundationModels + ListInferenceProfiles.
# Use inference profile IDs (us.*) since most models require them.
"bedrock": [
"us.anthropic.claude-sonnet-4-6",
"us.anthropic.claude-opus-4-6-v1",
"us.anthropic.claude-haiku-4-5-20251001-v1:0",
"us.anthropic.claude-sonnet-4-5-20250929-v1:0",
"us.amazon.nova-pro-v1:0",
"us.amazon.nova-lite-v1:0",
"us.amazon.nova-micro-v1:0",
"deepseek.v3.2",
"us.meta.llama4-maverick-17b-instruct-v1:0",
"us.meta.llama4-scout-17b-instruct-v1:0",
],
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
}
feat(nous): free-tier model gating, pricing display, and vision fallback - 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
2026-04-07 02:17:14 -04:00
# ---------------------------------------------------------------------------
# Nous Portal free-model filtering
# ---------------------------------------------------------------------------
# Models that are ALLOWED to appear when priced as free on Nous Portal.
# Any other free model is hidden — prevents promotional/temporary free models
# from cluttering the selection when users are paying subscribers.
# Models in this list are ALSO filtered out if they are NOT free (i.e. they
# should only appear in the menu when they are genuinely free).
_NOUS_ALLOWED_FREE_MODELS: frozenset[str] = frozenset({
"xiaomi/mimo-v2-pro",
"xiaomi/mimo-v2-omni",
})
def _is_model_free(model_id: str, pricing: dict[str, dict[str, str]]) -> bool:
"""Return True if *model_id* has zero-cost prompt AND completion pricing."""
p = pricing.get(model_id)
if not p:
return False
try:
return float(p.get("prompt", "1")) == 0 and float(p.get("completion", "1")) == 0
except (TypeError, ValueError):
return False
def filter_nous_free_models(
model_ids: list[str],
pricing: dict[str, dict[str, str]],
) -> list[str]:
"""Filter the Nous Portal model list according to free-model policy.
Rules:
• Paid models that are NOT in the allowlist → keep (normal case).
• Free models that are NOT in the allowlist → drop.
• Allowlist models that ARE free → keep.
• Allowlist models that are NOT free → drop.
"""
if not pricing:
return model_ids # no pricing data — can't filter, show everything
result: list[str] = []
for mid in model_ids:
free = _is_model_free(mid, pricing)
if mid in _NOUS_ALLOWED_FREE_MODELS:
# Allowlist model: only show when it's actually free
if free:
result.append(mid)
else:
# Regular model: keep only when it's NOT free
if not free:
result.append(mid)
return result
# ---------------------------------------------------------------------------
# Nous Portal account tier detection
# ---------------------------------------------------------------------------
def fetch_nous_account_tier(access_token: str, portal_base_url: str = "") -> dict[str, Any]:
"""Fetch the user's Nous Portal account/subscription info.
Calls ``<portal>/api/oauth/account`` with the OAuth access token.
Returns the parsed JSON dict on success, e.g.::
{
"subscription": {
"plan": "Plus",
"tier": 2,
"monthly_charge": 20,
"credits_remaining": 1686.60,
...
},
...
}
Returns an empty dict on any failure (network, auth, parse).
"""
base = (portal_base_url or "https://portal.nousresearch.com").rstrip("/")
url = f"{base}/api/oauth/account"
headers = {
"Authorization": f"Bearer {access_token}",
"Accept": "application/json",
}
try:
req = urllib.request.Request(url, headers=headers)
with urllib.request.urlopen(req, timeout=8) as resp:
return json.loads(resp.read().decode())
except Exception:
return {}
def is_nous_free_tier(account_info: dict[str, Any]) -> bool:
"""Return True if the account info indicates a free (unpaid) tier.
Checks ``subscription.monthly_charge == 0``. Returns False when
the field is missing or unparseable (assumes paid — don't block users).
"""
sub = account_info.get("subscription")
if not isinstance(sub, dict):
return False
charge = sub.get("monthly_charge")
if charge is None:
return False
try:
return float(charge) == 0
except (TypeError, ValueError):
return False
def partition_nous_models_by_tier(
model_ids: list[str],
pricing: dict[str, dict[str, str]],
free_tier: bool,
) -> tuple[list[str], list[str]]:
"""Split Nous models into (selectable, unavailable) based on user tier.
For paid-tier users: all models are selectable, none unavailable
(free-model filtering is handled separately by ``filter_nous_free_models``).
For free-tier users: only free models are selectable; paid models
are returned as unavailable (shown grayed out in the menu).
"""
if not free_tier:
return (model_ids, [])
if not pricing:
return (model_ids, []) # can't determine, show everything
selectable: list[str] = []
unavailable: list[str] = []
for mid in model_ids:
if _is_model_free(mid, pricing):
selectable.append(mid)
else:
unavailable.append(mid)
return (selectable, unavailable)
fix(nous): add 3-minute TTL cache to free-tier detection 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.
2026-04-07 09:30:26 -07:00
# ---------------------------------------------------------------------------
# TTL cache for free-tier detection — avoids repeated API calls within a
# session while still picking up upgrades quickly.
# ---------------------------------------------------------------------------
_FREE_TIER_CACHE_TTL: int = 180 # seconds (3 minutes)
_free_tier_cache: tuple[bool, float] | None = None # (result, timestamp)
feat(nous): free-tier model gating, pricing display, and vision fallback - 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
2026-04-07 02:17:14 -04:00
def check_nous_free_tier() -> bool:
"""Check if the current Nous Portal user is on a free (unpaid) tier.
fix(nous): add 3-minute TTL cache to free-tier detection 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.
2026-04-07 09:30:26 -07:00
Results are cached for ``_FREE_TIER_CACHE_TTL`` seconds to avoid
hitting the Portal API on every call. The cache is short-lived so
that an account upgrade is reflected within a few minutes.
Returns False (assume paid) on any error — never blocks paying users.
feat(nous): free-tier model gating, pricing display, and vision fallback - 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
2026-04-07 02:17:14 -04:00
"""
fix(nous): add 3-minute TTL cache to free-tier detection 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.
2026-04-07 09:30:26 -07:00
global _free_tier_cache
import time
now = time.monotonic()
if _free_tier_cache is not None:
cached_result, cached_at = _free_tier_cache
if now - cached_at < _FREE_TIER_CACHE_TTL:
return cached_result
feat(nous): free-tier model gating, pricing display, and vision fallback - 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
2026-04-07 02:17:14 -04:00
try:
from hermes_cli.auth import get_provider_auth_state, resolve_nous_runtime_credentials
# Ensure we have a fresh token (triggers refresh if needed)
resolve_nous_runtime_credentials(min_key_ttl_seconds=60)
state = get_provider_auth_state("nous")
if not state:
fix(nous): add 3-minute TTL cache to free-tier detection 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.
2026-04-07 09:30:26 -07:00
_free_tier_cache = (False, now)
feat(nous): free-tier model gating, pricing display, and vision fallback - 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
2026-04-07 02:17:14 -04:00
return False
access_token = state.get("access_token", "")
portal_url = state.get("portal_base_url", "")
if not access_token:
fix(nous): add 3-minute TTL cache to free-tier detection 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.
2026-04-07 09:30:26 -07:00
_free_tier_cache = (False, now)
feat(nous): free-tier model gating, pricing display, and vision fallback - 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
2026-04-07 02:17:14 -04:00
return False
account_info = fetch_nous_account_tier(access_token, portal_url)
fix(nous): add 3-minute TTL cache to free-tier detection 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.
2026-04-07 09:30:26 -07:00
result = is_nous_free_tier(account_info)
_free_tier_cache = (result, now)
return result
feat(nous): free-tier model gating, pricing display, and vision fallback - 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
2026-04-07 02:17:14 -04:00
except Exception:
fix(nous): add 3-minute TTL cache to free-tier detection 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.
2026-04-07 09:30:26 -07:00
_free_tier_cache = (False, now)
feat(nous): free-tier model gating, pricing display, and vision fallback - 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
2026-04-07 02:17:14 -04:00
return False # default to paid on error — don't block users
fix: consolidate provider lists into single CANONICAL_PROVIDERS source of truth (#9237) 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
2026-04-13 14:59:50 -07:00
# ---------------------------------------------------------------------------
# Canonical provider list — single source of truth for provider identity.
# Every code path that lists, displays, or iterates providers derives from
# this list: hermes model, /model, /provider, list_authenticated_providers.
#
# Fields:
# slug — internal provider ID (used in config.yaml, --provider flag)
# label — short display name
# tui_desc — longer description for the `hermes model` interactive picker
# ---------------------------------------------------------------------------
class ProviderEntry(NamedTuple):
slug: str
label: str
tui_desc: str # detailed description for `hermes model` TUI
CANONICAL_PROVIDERS: list[ProviderEntry] = [
refactor: remove provider tier system — flat picker in hermes model (#9303) 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
2026-04-13 18:51:13 -07:00
ProviderEntry("nous", "Nous Portal", "Nous Portal (Nous Research subscription)"),
ProviderEntry("openrouter", "OpenRouter", "OpenRouter (100+ models, pay-per-use)"),
feat: use Vercel's deep-link for ai-gateway API key creation prompt Vercel provides a d?to= redirect URL that routes users through their team picker to the AI Gateway API keys management page. Using this specific URL lands users directly on the "Create key" page instead of the generic AI Gateway dashboard.
2026-04-20 10:43:35 -07:00
ProviderEntry("ai-gateway", "Vercel AI Gateway", "Vercel AI Gateway (200+ models, $5 free credit, no markup)"),
refactor: remove provider tier system — flat picker in hermes model (#9303) 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
2026-04-13 18:51:13 -07:00
ProviderEntry("anthropic", "Anthropic", "Anthropic (Claude models — API key or Claude Code)"),
ProviderEntry("openai-codex", "OpenAI Codex", "OpenAI Codex"),
chore: rename AI Gateway → Vercel AI Gateway, move Xiaomi to #5 (#9326) - Rename 'AI Gateway' to 'Vercel AI Gateway' across auth, models, doctor, setup, and tests. - Move Xiaomi MiMo to position #5 in the provider picker.
2026-04-13 19:51:54 -07:00
ProviderEntry("xiaomi", "Xiaomi MiMo", "Xiaomi MiMo (MiMo-V2 models — pro, omni, flash)"),
fix(providers): complete NVIDIA NIM parity with other providers 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.
2026-04-17 13:09:14 -07:00
ProviderEntry("nvidia", "NVIDIA NIM", "NVIDIA NIM (Nemotron models — build.nvidia.com or local NIM)"),
refactor: remove provider tier system — flat picker in hermes model (#9303) 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
2026-04-13 18:51:13 -07:00
ProviderEntry("qwen-oauth", "Qwen OAuth (Portal)", "Qwen OAuth (reuses local Qwen CLI login)"),
ProviderEntry("copilot", "GitHub Copilot", "GitHub Copilot (uses GITHUB_TOKEN or gh auth token)"),
ProviderEntry("copilot-acp", "GitHub Copilot ACP", "GitHub Copilot ACP (spawns `copilot --acp --stdio`)"),
ProviderEntry("huggingface", "Hugging Face", "Hugging Face Inference Providers (20+ open models)"),
feat(providers): route gemini through the native AI Studio API - add a native Gemini adapter over generateContent/streamGenerateContent - switch the built-in gemini provider off the OpenAI-compatible endpoint - preserve thought signatures and native functionResponse replay - route auxiliary Gemini clients through the same adapter - add focused unit coverage plus native-provider integration checks
2026-04-20 00:00:50 +05:30
ProviderEntry("gemini", "Google AI Studio", "Google AI Studio (Gemini models — native Gemini API)"),
feat(gemini): add Google Gemini CLI OAuth provider via Cloud Code Assist (free + paid tiers) (#11270) * feat(gemini): add Google Gemini CLI OAuth provider via Cloud Code Assist Adds 'google-gemini-cli' as a first-class inference provider with native OAuth authentication against Google, hitting the Cloud Code Assist backend (cloudcode-pa.googleapis.com) that powers Google's official gemini-cli. Supports both the free tier (generous daily quota, personal accounts) and paid tiers (Standard/Enterprise via GCP projects). Architecture ============ Three new modules under agent/: 1. google_oauth.py (625 lines) — PKCE Authorization Code flow - Google's public gemini-cli desktop OAuth client baked in (env-var overrides supported) - Cross-process file lock (fcntl POSIX / msvcrt Windows) with thread-local re-entrancy - Packed refresh format 'refresh_token|project_id|managed_project_id' on disk - In-flight refresh deduplication — concurrent requests don't double-refresh - invalid_grant → wipe credentials, prompt re-login - Headless detection (SSH/HERMES_HEADLESS) → paste-mode fallback - Refresh 60 s before expiry, atomic write with fsync+replace 2. google_code_assist.py (350 lines) — Code Assist control plane - load_code_assist(): POST /v1internal:loadCodeAssist (prod → sandbox fallback) - onboard_user(): POST /v1internal:onboardUser with LRO polling up to 60 s - retrieve_user_quota(): POST /v1internal:retrieveUserQuota → QuotaBucket list - VPC-SC detection (SECURITY_POLICY_VIOLATED → force standard-tier) - resolve_project_context(): env → config → discovered → onboarded priority - Matches Google's gemini-cli User-Agent / X-Goog-Api-Client / Client-Metadata 3. gemini_cloudcode_adapter.py (640 lines) — OpenAI↔Gemini translation - GeminiCloudCodeClient mimics openai.OpenAI interface (.chat.completions.create) - Full message translation: system→systemInstruction, tool_calls↔functionCall, tool results→functionResponse with sentinel thoughtSignature - Tools → tools[].functionDeclarations, tool_choice → toolConfig modes - GenerationConfig pass-through (temperature, max_tokens, top_p, stop) - Thinking config normalization (thinkingBudget, thinkingLevel, includeThoughts) - Request envelope {project, model, user_prompt_id, request} - Streaming: SSE (?alt=sse) with thought-part → reasoning stream separation - Response unwrapping (Code Assist wraps Gemini response in 'response' field) - finishReason mapping to OpenAI convention (STOP→stop, MAX_TOKENS→length, etc.) Provider registration — all 9 touchpoints ========================================== - hermes_cli/auth.py: PROVIDER_REGISTRY, aliases, resolver, status fn, dispatch - hermes_cli/models.py: _PROVIDER_MODELS, CANONICAL_PROVIDERS, aliases - hermes_cli/providers.py: HermesOverlay, ALIASES - hermes_cli/config.py: OPTIONAL_ENV_VARS (HERMES_GEMINI_CLIENT_ID/_SECRET/_PROJECT_ID) - hermes_cli/runtime_provider.py: dispatch branch + pool-entry branch - hermes_cli/main.py: _model_flow_google_gemini_cli with upfront policy warning - hermes_cli/auth_commands.py: pool handler, _OAUTH_CAPABLE_PROVIDERS - hermes_cli/doctor.py: 'Google Gemini OAuth' health check - run_agent.py: single dispatch branch in _create_openai_client /gquota slash command ====================== Shows Code Assist quota buckets with 20-char progress bars, per (model, tokenType). Registered in hermes_cli/commands.py, handler _handle_gquota_command in cli.py. Attribution =========== Derived with significant reference to: - jenslys/opencode-gemini-auth (MIT) — OAuth flow shape, request envelope, public client credentials, retry semantics. Attribution preserved in module docstrings. - clawdbot/extensions/google — VPC-SC handling, project discovery pattern. - PR #10176 (@sliverp) — PKCE module structure. - PR #10779 (@newarthur) — cross-process file locking pattern. Supersedes PRs #6745, #10176, #10779 (to be closed on merge with credit). Upfront policy warning ====================== Google considers using the gemini-cli OAuth client with third-party software a policy violation. The interactive flow shows a clear warning and requires explicit 'y' confirmation before OAuth begins. Documented prominently in website/docs/integrations/providers.md. Tests ===== 74 new tests in tests/agent/test_gemini_cloudcode.py covering: - PKCE S256 roundtrip - Packed refresh format parse/format/roundtrip - Credential I/O (0600 perms, atomic write, packed on disk) - Token lifecycle (fresh/expiring/force-refresh/invalid_grant/rotation preservation) - Project ID env resolution (3 env vars, priority order) - Headless detection - VPC-SC detection (JSON-nested + text match) - loadCodeAssist parsing + VPC-SC → standard-tier fallback - onboardUser: free-tier allows empty project, paid requires it, LRO polling - retrieveUserQuota parsing - resolve_project_context: 3 short-circuit paths + discovery + onboarding - build_gemini_request: messages → contents, system separation, tool_calls, tool_results, tools[], tool_choice (auto/required/specific), generationConfig, thinkingConfig normalization - Code Assist envelope wrap shape - Response translation: text, functionCall, thought → reasoning, unwrapped response, empty candidates, finish_reason mapping - GeminiCloudCodeClient end-to-end with mocked HTTP - Provider registration (9 tests: registry, 4 alias forms, no-regression on google-gemini alias, models catalog, determine_api_mode, _OAUTH_CAPABLE_PROVIDERS preservation, config env vars) - Auth status dispatch (logged-in + not) - /gquota command registration - run_gemini_oauth_login_pure pool-dict shape All 74 pass. 349 total tests pass across directly-touched areas (existing test_api_key_providers, test_auth_qwen_provider, test_gemini_provider, test_cli_init, test_cli_provider_resolution, test_registry all still green). Coexistence with existing 'gemini' (API-key) provider ===================================================== The existing gemini API-key provider is completely untouched. Its alias 'google-gemini' still resolves to 'gemini', not 'google-gemini-cli'. Users can have both configured simultaneously; 'hermes model' shows both as separate options. * feat(gemini): ship Google's public gemini-cli OAuth client as default Pivots from 'scrape-from-local-gemini-cli' (clawdbot pattern) to 'ship-creds-in-source' (opencode-gemini-auth pattern) for zero-setup UX. These are Google's PUBLIC gemini-cli desktop OAuth credentials, published openly in Google's own open-source gemini-cli repository. Desktop OAuth clients are not confidential — PKCE provides the security, not the client_secret. Shipping them here matches opencode-gemini-auth (MIT) and Google's own distribution model. Resolution order is now: 1. HERMES_GEMINI_CLIENT_ID / _SECRET env vars (power users, custom GCP clients) 2. Shipped public defaults (common case — works out of the box) 3. Scrape from locally installed gemini-cli (fallback for forks that deliberately wipe the shipped defaults) 4. Helpful error with install / env-var hints The credential strings are composed piecewise at import time to keep reviewer intent explicit (each constant is paired with a comment about why it's non-confidential) and to bypass naive secret scanners. UX impact: users no longer need 'npm install -g @google/gemini-cli' as a prerequisite. Just 'hermes model' -> 'Google Gemini (OAuth)' works out of the box. Scrape path is retained as a safety net. Tests cover all four resolution steps (env / shipped default / scrape fallback / hard failure). 79 new unit tests pass (was 76, +3 for the new resolution behaviors).
2026-04-16 16:49:00 -07:00
ProviderEntry("google-gemini-cli", "Google Gemini (OAuth)", "Google Gemini via OAuth + Code Assist (free tier supported; no API key needed)"),
refactor: remove provider tier system — flat picker in hermes model (#9303) 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
2026-04-13 18:51:13 -07:00
ProviderEntry("deepseek", "DeepSeek", "DeepSeek (DeepSeek-V3, R1, coder — direct API)"),
ProviderEntry("xai", "xAI", "xAI (Grok models — direct API)"),
ProviderEntry("zai", "Z.AI / GLM", "Z.AI / GLM (Zhipu AI direct API)"),
fix(kimi): include kimi-coding-cn in Kimi base URL resolution (#10534) 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.
2026-04-15 14:54:30 -07:00
ProviderEntry("kimi-coding", "Kimi / Kimi Coding Plan", "Kimi Coding Plan (api.kimi.com) & Moonshot API"),
refactor: remove provider tier system — flat picker in hermes model (#9303) 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
2026-04-13 18:51:13 -07:00
ProviderEntry("kimi-coding-cn", "Kimi / Moonshot (China)", "Kimi / Moonshot China (Moonshot CN direct API)"),
ProviderEntry("minimax", "MiniMax", "MiniMax (global direct API)"),
ProviderEntry("minimax-cn", "MiniMax (China)", "MiniMax China (domestic direct API)"),
ProviderEntry("alibaba", "Alibaba Cloud (DashScope)","Alibaba Cloud / DashScope Coding (Qwen + multi-provider)"),
feat: add Ollama Cloud as built-in provider Add ollama-cloud as a first-class provider with full parity to existing API-key providers (gemini, zai, minimax, etc.): - PROVIDER_REGISTRY entry with OLLAMA_API_KEY env var - Provider aliases: ollama -> custom (local), ollama_cloud -> ollama-cloud - models.dev integration for accurate context lengths - URL-to-provider mapping (ollama.com -> ollama-cloud) - Passthrough model normalization (preserves Ollama model:tag format) - Default auxiliary model (nemotron-3-nano:30b) - HermesOverlay in providers.py - CLI --provider choices, CANONICAL_PROVIDERS entry - Dynamic model discovery with disk caching (1hr TTL) - 37 provider-specific tests Cherry-picked from PR #6038 by kshitijk4poor. Closes #3926
2026-04-15 22:32:05 -07:00
ProviderEntry("ollama-cloud", "Ollama Cloud", "Ollama Cloud (cloud-hosted open models — ollama.com)"),
refactor: remove provider tier system — flat picker in hermes model (#9303) 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
2026-04-13 18:51:13 -07:00
ProviderEntry("arcee", "Arcee AI", "Arcee AI (Trinity models — direct API)"),
ProviderEntry("kilocode", "Kilo Code", "Kilo Code (Kilo Gateway API)"),
ProviderEntry("opencode-zen", "OpenCode Zen", "OpenCode Zen (35+ curated models, pay-as-you-go)"),
ProviderEntry("opencode-go", "OpenCode Go", "OpenCode Go (open models, $10/month subscription)"),
feat: native AWS Bedrock provider via Converse API Salvaged from PR #7920 by JiaDe-Wu — cherry-picked Bedrock-specific additions onto current main, skipping stale-branch reverts (293 commits behind). Dual-path architecture: - Claude models → AnthropicBedrock SDK (prompt caching, thinking budgets) - Non-Claude models → Converse API via boto3 (Nova, DeepSeek, Llama, Mistral) Includes: - Core adapter (agent/bedrock_adapter.py, 1098 lines) - Full provider registration (auth, models, providers, config, runtime, main) - IAM credential chain + Bedrock API Key auth modes - Dynamic model discovery via ListFoundationModels + ListInferenceProfiles - Streaming with delta callbacks, error classification, guardrails - hermes doctor + hermes auth integration - /usage pricing for 7 Bedrock models - 130 automated tests (79 unit + 28 integration + follow-up fixes) - Documentation (website/docs/guides/aws-bedrock.md) - boto3 optional dependency (pip install hermes-agent[bedrock]) Co-authored-by: JiaDe WU <40445668+JiaDe-Wu@users.noreply.github.com>
2026-04-15 15:18:01 -07:00
ProviderEntry("bedrock", "AWS Bedrock", "AWS Bedrock (Claude, Nova, Llama, DeepSeek — IAM or API key)"),
fix: consolidate provider lists into single CANONICAL_PROVIDERS source of truth (#9237) 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
2026-04-13 14:59:50 -07:00
]
# Derived dicts — used throughout the codebase
_PROVIDER_LABELS = {p.slug: p.label for p in CANONICAL_PROVIDERS}
_PROVIDER_LABELS["custom"] = "Custom endpoint" # special case: not a named provider
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
feat: add Ollama Cloud as built-in provider Add ollama-cloud as a first-class provider with full parity to existing API-key providers (gemini, zai, minimax, etc.): - PROVIDER_REGISTRY entry with OLLAMA_API_KEY env var - Provider aliases: ollama -> custom (local), ollama_cloud -> ollama-cloud - models.dev integration for accurate context lengths - URL-to-provider mapping (ollama.com -> ollama-cloud) - Passthrough model normalization (preserves Ollama model:tag format) - Default auxiliary model (nemotron-3-nano:30b) - HermesOverlay in providers.py - CLI --provider choices, CANONICAL_PROVIDERS entry - Dynamic model discovery with disk caching (1hr TTL) - 37 provider-specific tests Cherry-picked from PR #6038 by kshitijk4poor. Closes #3926
2026-04-15 22:32:05 -07:00
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
_PROVIDER_ALIASES = {
"glm": "zai",
"z-ai": "zai",
"z.ai": "zai",
"zhipu": "zai",
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
"github": "copilot",
"github-copilot": "copilot",
"github-models": "copilot",
"github-model": "copilot",
"github-copilot-acp": "copilot-acp",
"copilot-acp-agent": "copilot-acp",
feat(providers): add Google AI Studio (Gemini) as a first-class provider Cherry-picked from PR #5494 by kshitijk4poor. Adds native Gemini support via Google's OpenAI-compatible endpoint. Zero new dependencies.
2026-04-06 10:14:01 -07:00
"google": "gemini",
"google-gemini": "gemini",
"google-ai-studio": "gemini",
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
"kimi": "kimi-coding",
"moonshot": "kimi-coding",
feat(providers): add kimi-coding-cn provider for mainland China users 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.
2026-04-13 11:13:09 -07:00
"kimi-cn": "kimi-coding-cn",
"moonshot-cn": "kimi-coding-cn",
feat(providers): add Arcee AI as direct API provider 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.
2026-04-13 17:16:43 -07:00
"arcee-ai": "arcee",
"arceeai": "arcee",
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
"minimax-china": "minimax-cn",
"minimax_cn": "minimax-cn",
feat: native Anthropic provider with Claude Code credential auto-discovery Add Anthropic as a first-class inference provider, bypassing OpenRouter for direct API access. Uses the native Anthropic SDK with a full format adapter (same pattern as the codex_responses api_mode). ## Auth (three methods, priority order) 1. ANTHROPIC_API_KEY env var (regular API key, sk-ant-api-*) 2. ANTHROPIC_TOKEN / CLAUDE_CODE_OAUTH_TOKEN env var (setup-token, sk-ant-oat-*) 3. Auto-discovery from ~/.claude/.credentials.json (Claude Code subscription) - Reads Claude Code's OAuth credentials - Checks token expiry with 60s buffer - Setup tokens use Bearer auth + anthropic-beta: oauth-2025-04-20 header - Regular API keys use standard x-api-key header ## Changes by file ### New files - agent/anthropic_adapter.py — Client builder, message/tool/response format conversion, Claude Code credential reader, token resolver. Handles system prompt extraction, tool_use/tool_result blocks, thinking/reasoning, orphaned tool_use cleanup, cache_control. - tests/test_anthropic_adapter.py — 36 tests covering all adapter logic ### Modified files - pyproject.toml — Add anthropic>=0.39.0 dependency - hermes_cli/auth.py — Add 'anthropic' to PROVIDER_REGISTRY with three env vars, plus 'claude'/'claude-code' aliases - hermes_cli/models.py — Add model catalog, labels, aliases, provider order - hermes_cli/main.py — Add 'anthropic' to --provider CLI choices - hermes_cli/runtime_provider.py — Add Anthropic branch returning api_mode='anthropic_messages' (before generic api_key fallthrough) - hermes_cli/setup.py — Add Anthropic setup wizard with Claude Code credential auto-discovery, model selection, OpenRouter tools prompt - agent/auxiliary_client.py — Add claude-haiku-4-5 as aux model - agent/model_metadata.py — Add bare Claude model context lengths - run_agent.py — Add anthropic_messages api_mode: * Client init (Anthropic SDK instead of OpenAI) * API call dispatch (_anthropic_client.messages.create) * Response validation (content blocks) * finish_reason mapping (stop_reason -> finish_reason) * Token usage (input_tokens/output_tokens) * Response normalization (normalize_anthropic_response) * Client interrupt/rebuild * Prompt caching auto-enabled for native Anthropic - tests/test_run_agent.py — Update test_anthropic_base_url_accepted to expect native routing, add test_prompt_caching_native_anthropic
2026-03-12 15:47:45 -07:00
"claude": "anthropic",
"claude-code": "anthropic",
feat: auto-detect provider when switching models via /model (#1506) 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>
2026-03-16 04:34:45 -07:00
"deep-seek": "deepseek",
feat(provider): add OpenCode Zen and OpenCode Go providers 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>
2026-03-17 02:02:43 -07:00
"opencode": "opencode-zen",
"zen": "opencode-zen",
"go": "opencode-go",
"opencode-go-sub": "opencode-go",
feat: add Vercel AI Gateway provider (#1628) * 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>
2026-03-17 00:12:16 -07:00
"aigateway": "ai-gateway",
"vercel": "ai-gateway",
"vercel-ai-gateway": "ai-gateway",
feat: add Kilo Code (kilocode) as first-class inference provider (#1666) 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>
2026-03-17 02:40:34 -07:00
"kilo": "kilocode",
"kilo-code": "kilocode",
"kilo-gateway": "kilocode",
feat: add Alibaba Cloud provider and Anthropic base_url override (#1673) 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
2026-03-17 02:49:22 -07:00
"dashscope": "alibaba",
"aliyun": "alibaba",
"qwen": "alibaba",
"alibaba-cloud": "alibaba",
feat(qwen): add Qwen OAuth provider with portal request support 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)
2026-04-08 20:48:21 +05:30
"qwen-portal": "qwen-oauth",
feat(gemini): add Google Gemini CLI OAuth provider via Cloud Code Assist (free + paid tiers) (#11270) * feat(gemini): add Google Gemini CLI OAuth provider via Cloud Code Assist Adds 'google-gemini-cli' as a first-class inference provider with native OAuth authentication against Google, hitting the Cloud Code Assist backend (cloudcode-pa.googleapis.com) that powers Google's official gemini-cli. Supports both the free tier (generous daily quota, personal accounts) and paid tiers (Standard/Enterprise via GCP projects). Architecture ============ Three new modules under agent/: 1. google_oauth.py (625 lines) — PKCE Authorization Code flow - Google's public gemini-cli desktop OAuth client baked in (env-var overrides supported) - Cross-process file lock (fcntl POSIX / msvcrt Windows) with thread-local re-entrancy - Packed refresh format 'refresh_token|project_id|managed_project_id' on disk - In-flight refresh deduplication — concurrent requests don't double-refresh - invalid_grant → wipe credentials, prompt re-login - Headless detection (SSH/HERMES_HEADLESS) → paste-mode fallback - Refresh 60 s before expiry, atomic write with fsync+replace 2. google_code_assist.py (350 lines) — Code Assist control plane - load_code_assist(): POST /v1internal:loadCodeAssist (prod → sandbox fallback) - onboard_user(): POST /v1internal:onboardUser with LRO polling up to 60 s - retrieve_user_quota(): POST /v1internal:retrieveUserQuota → QuotaBucket list - VPC-SC detection (SECURITY_POLICY_VIOLATED → force standard-tier) - resolve_project_context(): env → config → discovered → onboarded priority - Matches Google's gemini-cli User-Agent / X-Goog-Api-Client / Client-Metadata 3. gemini_cloudcode_adapter.py (640 lines) — OpenAI↔Gemini translation - GeminiCloudCodeClient mimics openai.OpenAI interface (.chat.completions.create) - Full message translation: system→systemInstruction, tool_calls↔functionCall, tool results→functionResponse with sentinel thoughtSignature - Tools → tools[].functionDeclarations, tool_choice → toolConfig modes - GenerationConfig pass-through (temperature, max_tokens, top_p, stop) - Thinking config normalization (thinkingBudget, thinkingLevel, includeThoughts) - Request envelope {project, model, user_prompt_id, request} - Streaming: SSE (?alt=sse) with thought-part → reasoning stream separation - Response unwrapping (Code Assist wraps Gemini response in 'response' field) - finishReason mapping to OpenAI convention (STOP→stop, MAX_TOKENS→length, etc.) Provider registration — all 9 touchpoints ========================================== - hermes_cli/auth.py: PROVIDER_REGISTRY, aliases, resolver, status fn, dispatch - hermes_cli/models.py: _PROVIDER_MODELS, CANONICAL_PROVIDERS, aliases - hermes_cli/providers.py: HermesOverlay, ALIASES - hermes_cli/config.py: OPTIONAL_ENV_VARS (HERMES_GEMINI_CLIENT_ID/_SECRET/_PROJECT_ID) - hermes_cli/runtime_provider.py: dispatch branch + pool-entry branch - hermes_cli/main.py: _model_flow_google_gemini_cli with upfront policy warning - hermes_cli/auth_commands.py: pool handler, _OAUTH_CAPABLE_PROVIDERS - hermes_cli/doctor.py: 'Google Gemini OAuth' health check - run_agent.py: single dispatch branch in _create_openai_client /gquota slash command ====================== Shows Code Assist quota buckets with 20-char progress bars, per (model, tokenType). Registered in hermes_cli/commands.py, handler _handle_gquota_command in cli.py. Attribution =========== Derived with significant reference to: - jenslys/opencode-gemini-auth (MIT) — OAuth flow shape, request envelope, public client credentials, retry semantics. Attribution preserved in module docstrings. - clawdbot/extensions/google — VPC-SC handling, project discovery pattern. - PR #10176 (@sliverp) — PKCE module structure. - PR #10779 (@newarthur) — cross-process file locking pattern. Supersedes PRs #6745, #10176, #10779 (to be closed on merge with credit). Upfront policy warning ====================== Google considers using the gemini-cli OAuth client with third-party software a policy violation. The interactive flow shows a clear warning and requires explicit 'y' confirmation before OAuth begins. Documented prominently in website/docs/integrations/providers.md. Tests ===== 74 new tests in tests/agent/test_gemini_cloudcode.py covering: - PKCE S256 roundtrip - Packed refresh format parse/format/roundtrip - Credential I/O (0600 perms, atomic write, packed on disk) - Token lifecycle (fresh/expiring/force-refresh/invalid_grant/rotation preservation) - Project ID env resolution (3 env vars, priority order) - Headless detection - VPC-SC detection (JSON-nested + text match) - loadCodeAssist parsing + VPC-SC → standard-tier fallback - onboardUser: free-tier allows empty project, paid requires it, LRO polling - retrieveUserQuota parsing - resolve_project_context: 3 short-circuit paths + discovery + onboarding - build_gemini_request: messages → contents, system separation, tool_calls, tool_results, tools[], tool_choice (auto/required/specific), generationConfig, thinkingConfig normalization - Code Assist envelope wrap shape - Response translation: text, functionCall, thought → reasoning, unwrapped response, empty candidates, finish_reason mapping - GeminiCloudCodeClient end-to-end with mocked HTTP - Provider registration (9 tests: registry, 4 alias forms, no-regression on google-gemini alias, models catalog, determine_api_mode, _OAUTH_CAPABLE_PROVIDERS preservation, config env vars) - Auth status dispatch (logged-in + not) - /gquota command registration - run_gemini_oauth_login_pure pool-dict shape All 74 pass. 349 total tests pass across directly-touched areas (existing test_api_key_providers, test_auth_qwen_provider, test_gemini_provider, test_cli_init, test_cli_provider_resolution, test_registry all still green). Coexistence with existing 'gemini' (API-key) provider ===================================================== The existing gemini API-key provider is completely untouched. Its alias 'google-gemini' still resolves to 'gemini', not 'google-gemini-cli'. Users can have both configured simultaneously; 'hermes model' shows both as separate options. * feat(gemini): ship Google's public gemini-cli OAuth client as default Pivots from 'scrape-from-local-gemini-cli' (clawdbot pattern) to 'ship-creds-in-source' (opencode-gemini-auth pattern) for zero-setup UX. These are Google's PUBLIC gemini-cli desktop OAuth credentials, published openly in Google's own open-source gemini-cli repository. Desktop OAuth clients are not confidential — PKCE provides the security, not the client_secret. Shipping them here matches opencode-gemini-auth (MIT) and Google's own distribution model. Resolution order is now: 1. HERMES_GEMINI_CLIENT_ID / _SECRET env vars (power users, custom GCP clients) 2. Shipped public defaults (common case — works out of the box) 3. Scrape from locally installed gemini-cli (fallback for forks that deliberately wipe the shipped defaults) 4. Helpful error with install / env-var hints The credential strings are composed piecewise at import time to keep reviewer intent explicit (each constant is paired with a comment about why it's non-confidential) and to bypass naive secret scanners. UX impact: users no longer need 'npm install -g @google/gemini-cli' as a prerequisite. Just 'hermes model' -> 'Google Gemini (OAuth)' works out of the box. Scrape path is retained as a safety net. Tests cover all four resolution steps (env / shipped default / scrape fallback / hard failure). 79 new unit tests pass (was 76, +3 for the new resolution behaviors).
2026-04-16 16:49:00 -07:00
"gemini-cli": "google-gemini-cli",
"gemini-oauth": "google-gemini-cli",
feat: add Hugging Face as a first-class inference provider (#3419) 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>
2026-03-27 12:41:59 -07:00
"hf": "huggingface",
"hugging-face": "huggingface",
"huggingface-hub": "huggingface",
feat(xiaomi): add Xiaomi MiMo as first-class provider 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.
2026-04-11 10:10:31 -07:00
"mimo": "xiaomi",
"xiaomi-mimo": "xiaomi",
feat: native AWS Bedrock provider via Converse API Salvaged from PR #7920 by JiaDe-Wu — cherry-picked Bedrock-specific additions onto current main, skipping stale-branch reverts (293 commits behind). Dual-path architecture: - Claude models → AnthropicBedrock SDK (prompt caching, thinking budgets) - Non-Claude models → Converse API via boto3 (Nova, DeepSeek, Llama, Mistral) Includes: - Core adapter (agent/bedrock_adapter.py, 1098 lines) - Full provider registration (auth, models, providers, config, runtime, main) - IAM credential chain + Bedrock API Key auth modes - Dynamic model discovery via ListFoundationModels + ListInferenceProfiles - Streaming with delta callbacks, error classification, guardrails - hermes doctor + hermes auth integration - /usage pricing for 7 Bedrock models - 130 automated tests (79 unit + 28 integration + follow-up fixes) - Documentation (website/docs/guides/aws-bedrock.md) - boto3 optional dependency (pip install hermes-agent[bedrock]) Co-authored-by: JiaDe WU <40445668+JiaDe-Wu@users.noreply.github.com>
2026-04-15 15:18:01 -07:00
"aws": "bedrock",
"aws-bedrock": "bedrock",
"amazon-bedrock": "bedrock",
"amazon": "bedrock",
fix: consolidate provider lists into single CANONICAL_PROVIDERS source of truth (#9237) 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
2026-04-13 14:59:50 -07:00
"grok": "xai",
"x-ai": "xai",
"x.ai": "xai",
feat(providers): add native NVIDIA NIM provider 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.
2026-04-17 09:55:58 -07:00
"nim": "nvidia",
"nvidia-nim": "nvidia",
"build-nvidia": "nvidia",
"nemotron": "nvidia",
feat: add Ollama Cloud as built-in provider Add ollama-cloud as a first-class provider with full parity to existing API-key providers (gemini, zai, minimax, etc.): - PROVIDER_REGISTRY entry with OLLAMA_API_KEY env var - Provider aliases: ollama -> custom (local), ollama_cloud -> ollama-cloud - models.dev integration for accurate context lengths - URL-to-provider mapping (ollama.com -> ollama-cloud) - Passthrough model normalization (preserves Ollama model:tag format) - Default auxiliary model (nemotron-3-nano:30b) - HermesOverlay in providers.py - CLI --provider choices, CANONICAL_PROVIDERS entry - Dynamic model discovery with disk caching (1hr TTL) - 37 provider-specific tests Cherry-picked from PR #6038 by kshitijk4poor. Closes #3926
2026-04-15 22:32:05 -07:00
"ollama": "custom", # bare "ollama" = local; use "ollama-cloud" for cloud
"ollama_cloud": "ollama-cloud",
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
}
Hermes Agent UX Improvements
2026-02-22 02:16:11 -08:00
fix: fall back to provider's default model when model config is empty (#8303) 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.
2026-04-12 03:53:30 -07:00
def get_default_model_for_provider(provider: str) -> str:
"""Return the default model for a provider, or empty string if unknown.
Uses the first entry in _PROVIDER_MODELS as the default. This is the
model a user would be offered first in the ``hermes model`` picker.
Used as a fallback when the user has configured a provider but never
selected a model (e.g. ``hermes auth add openai-codex`` without
``hermes model``).
"""
models = _PROVIDER_MODELS.get(provider, [])
return models[0] if models else ""
Refresh OpenRouter model catalog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-09 15:11:58 -05:00
def _openrouter_model_is_free(pricing: Any) -> bool:
"""Return True when both prompt and completion pricing are zero."""
if not isinstance(pricing, dict):
return False
try:
return float(pricing.get("prompt", "0")) == 0 and float(pricing.get("completion", "0")) == 0
except (TypeError, ValueError):
return False
def fetch_openrouter_models(
timeout: float = 8.0,
*,
force_refresh: bool = False,
) -> list[tuple[str, str]]:
"""Return the curated OpenRouter picker list, refreshed from the live catalog when possible."""
global _openrouter_catalog_cache
if _openrouter_catalog_cache is not None and not force_refresh:
return list(_openrouter_catalog_cache)
fallback = list(OPENROUTER_MODELS)
preferred_ids = [mid for mid, _ in fallback]
try:
req = urllib.request.Request(
"https://openrouter.ai/api/v1/models",
headers={"Accept": "application/json"},
)
with urllib.request.urlopen(req, timeout=timeout) as resp:
payload = json.loads(resp.read().decode())
except Exception:
return list(_openrouter_catalog_cache or fallback)
live_items = payload.get("data", [])
if not isinstance(live_items, list):
return list(_openrouter_catalog_cache or fallback)
live_by_id: dict[str, dict[str, Any]] = {}
for item in live_items:
if not isinstance(item, dict):
continue
mid = str(item.get("id") or "").strip()
if not mid:
continue
live_by_id[mid] = item
curated: list[tuple[str, str]] = []
for preferred_id in preferred_ids:
live_item = live_by_id.get(preferred_id)
if live_item is None:
continue
desc = "free" if _openrouter_model_is_free(live_item.get("pricing")) else ""
curated.append((preferred_id, desc))
if not curated:
return list(_openrouter_catalog_cache or fallback)
first_id, _ = curated[0]
curated[0] = (first_id, "recommended")
_openrouter_catalog_cache = curated
return list(curated)
def model_ids(*, force_refresh: bool = False) -> list[str]:
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
"""Return just the OpenRouter model-id strings."""
Refresh OpenRouter model catalog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-09 15:11:58 -05:00
return [mid for mid, _ in fetch_openrouter_models(force_refresh=force_refresh)]
Hermes Agent UX Improvements
2026-02-22 02:16:11 -08:00
feat: curated picker with live pricing for ai-gateway provider - Curated AI_GATEWAY_MODELS list in hermes_cli/models.py (OSS first, kimi-k2.5 as recommended default). - fetch_ai_gateway_models() filters the curated list against the live /v1/models catalog; falls back to the snapshot on network failure. - fetch_ai_gateway_pricing() translates Vercel's input/output field names to the prompt/completion shape the shared picker expects; carries input_cache_read / input_cache_write through unchanged. - get_pricing_for_provider() now handles ai-gateway. - _model_flow_ai_gateway() provides a guided URL prompt when no key is set and a pricing-column picker; routes ai-gateway to it instead of the generic api-key flow.
2026-04-19 23:05:14 -07:00
def _ai_gateway_model_is_free(pricing: Any) -> bool:
"""Return True if an AI Gateway model has $0 input AND output pricing."""
if not isinstance(pricing, dict):
return False
try:
return float(pricing.get("input", "0")) == 0 and float(pricing.get("output", "0")) == 0
except (TypeError, ValueError):
return False
def fetch_ai_gateway_models(
timeout: float = 8.0,
*,
force_refresh: bool = False,
) -> list[tuple[str, str]]:
"""Return the curated AI Gateway picker list, refreshed from the live catalog when possible."""
global _ai_gateway_catalog_cache
if _ai_gateway_catalog_cache is not None and not force_refresh:
return list(_ai_gateway_catalog_cache)
from hermes_constants import AI_GATEWAY_BASE_URL
fallback = list(AI_GATEWAY_MODELS)
preferred_ids = [mid for mid, _ in fallback]
try:
req = urllib.request.Request(
f"{AI_GATEWAY_BASE_URL.rstrip('/')}/models",
headers={"Accept": "application/json"},
)
with urllib.request.urlopen(req, timeout=timeout) as resp:
payload = json.loads(resp.read().decode())
except Exception:
return list(_ai_gateway_catalog_cache or fallback)
live_items = payload.get("data", [])
if not isinstance(live_items, list):
return list(_ai_gateway_catalog_cache or fallback)
live_by_id: dict[str, dict[str, Any]] = {}
for item in live_items:
if not isinstance(item, dict):
continue
mid = str(item.get("id") or "").strip()
if not mid:
continue
live_by_id[mid] = item
curated: list[tuple[str, str]] = []
for preferred_id in preferred_ids:
live_item = live_by_id.get(preferred_id)
if live_item is None:
continue
desc = "free" if _ai_gateway_model_is_free(live_item.get("pricing")) else ""
curated.append((preferred_id, desc))
if not curated:
return list(_ai_gateway_catalog_cache or fallback)
feat: auto-promote free Moonshot models to top of ai-gateway picker When the live Vercel AI Gateway catalog exposes a Moonshot model with zero input AND output pricing, it's promoted to position #1 as the recommended default — even if the exact ID isn't in the curated AI_GATEWAY_MODELS list. This enables dynamic discovery of new free Moonshot variants without requiring a PR to update curation. Paid Moonshot models are unaffected; falls back to the normal curated recommended tag when no free Moonshot is live.
2026-04-20 00:18:51 -07:00
# If the live catalog offers a free Moonshot model, auto-promote it to
# position #1 as "recommended" — dynamic discovery without a PR.
free_moonshot = next(
(
mid
for mid, item in live_by_id.items()
if mid.startswith("moonshotai/")
and _ai_gateway_model_is_free(item.get("pricing"))
),
None,
)
if free_moonshot:
curated = [(mid, desc) for mid, desc in curated if mid != free_moonshot]
curated.insert(0, (free_moonshot, "recommended"))
else:
first_id, _ = curated[0]
curated[0] = (first_id, "recommended")
feat: curated picker with live pricing for ai-gateway provider - Curated AI_GATEWAY_MODELS list in hermes_cli/models.py (OSS first, kimi-k2.5 as recommended default). - fetch_ai_gateway_models() filters the curated list against the live /v1/models catalog; falls back to the snapshot on network failure. - fetch_ai_gateway_pricing() translates Vercel's input/output field names to the prompt/completion shape the shared picker expects; carries input_cache_read / input_cache_write through unchanged. - get_pricing_for_provider() now handles ai-gateway. - _model_flow_ai_gateway() provides a guided URL prompt when no key is set and a pricing-column picker; routes ai-gateway to it instead of the generic api-key flow.
2026-04-19 23:05:14 -07:00
_ai_gateway_catalog_cache = curated
return list(curated)
def ai_gateway_model_ids(*, force_refresh: bool = False) -> list[str]:
"""Return just the AI Gateway model-id strings."""
return [mid for mid, _ in fetch_ai_gateway_models(force_refresh=force_refresh)]
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
fix: remove 115 verified dead code symbols across 46 production files 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>
2026-04-10 03:03:30 -07:00
feat: show model pricing for OpenRouter and Nous Portal providers 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
2026-04-03 18:46:45 -04:00
# ---------------------------------------------------------------------------
# Pricing helpers — fetch live pricing from OpenRouter-compatible /v1/models
# ---------------------------------------------------------------------------
# Cache: maps model_id → {"prompt": str, "completion": str} per endpoint
_pricing_cache: dict[str, dict[str, dict[str, str]]] = {}
def _format_price_per_mtok(per_token_str: str) -> str:
"""Convert a per-token price string to a human-friendly $/Mtok string.
Always uses 2 decimal places so that prices align vertically when
right-justified in a column (the decimal point stays in the same position).
Examples:
"0.000003" → "$3.00" (per million tokens)
"0.00003" → "$30.00"
"0.00000015" → "$0.15"
"0.0000001" → "$0.10"
"0.00018" → "$180.00"
"0" → "free"
"""
try:
val = float(per_token_str)
except (TypeError, ValueError):
return "?"
if val == 0:
return "free"
per_m = val * 1_000_000
return f"${per_m:.2f}"
def format_model_pricing_table(
models: list[tuple[str, str]],
pricing_map: dict[str, dict[str, str]],
current_model: str = "",
indent: str = " ",
) -> list[str]:
"""Build a column-aligned model+pricing table for terminal display.
Returns a list of pre-formatted lines ready to print.
*models* is ``[(model_id, description), ...]``.
"""
if not models:
return []
show cache pricing as well (if supported)
2026-04-05 22:39:02 -04:00
# Build rows: (model_id, input_price, output_price, cache_price, is_current)
rows: list[tuple[str, str, str, str, bool]] = []
has_cache = False
feat: show model pricing for OpenRouter and Nous Portal providers 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
2026-04-03 18:46:45 -04:00
for mid, _desc in models:
is_cur = mid == current_model
p = pricing_map.get(mid)
if p:
inp = _format_price_per_mtok(p.get("prompt", ""))
out = _format_price_per_mtok(p.get("completion", ""))
show cache pricing as well (if supported)
2026-04-05 22:39:02 -04:00
cache_read = p.get("input_cache_read", "")
cache = _format_price_per_mtok(cache_read) if cache_read else ""
if cache:
has_cache = True
feat: show model pricing for OpenRouter and Nous Portal providers 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
2026-04-03 18:46:45 -04:00
else:
show cache pricing as well (if supported)
2026-04-05 22:39:02 -04:00
inp, out, cache = "", "", ""
rows.append((mid, inp, out, cache, is_cur))
feat: show model pricing for OpenRouter and Nous Portal providers 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
2026-04-03 18:46:45 -04:00
name_col = max(len(r[0]) for r in rows) + 2
# Compute price column widths from the actual data so decimals align
price_col = max(
max((len(r[1]) for r in rows if r[1]), default=4),
max((len(r[2]) for r in rows if r[2]), default=4),
3, # minimum: "In" / "Out" header
)
show cache pricing as well (if supported)
2026-04-05 22:39:02 -04:00
cache_col = max(
max((len(r[3]) for r in rows if r[3]), default=4),
5, # minimum: "Cache" header
) if has_cache else 0
feat: show model pricing for OpenRouter and Nous Portal providers 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
2026-04-03 18:46:45 -04:00
lines: list[str] = []
# Header
show cache pricing as well (if supported)
2026-04-05 22:39:02 -04:00
if has_cache:
lines.append(f"{indent}{'Model':<{name_col}} {'In':>{price_col}} {'Out':>{price_col}} {'Cache':>{cache_col}} /Mtok")
lines.append(f"{indent}{'-' * name_col} {'-' * price_col} {'-' * price_col} {'-' * cache_col}")
else:
lines.append(f"{indent}{'Model':<{name_col}} {'In':>{price_col}} {'Out':>{price_col}} /Mtok")
lines.append(f"{indent}{'-' * name_col} {'-' * price_col} {'-' * price_col}")
for mid, inp, out, cache, is_cur in rows:
feat: show model pricing for OpenRouter and Nous Portal providers 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
2026-04-03 18:46:45 -04:00
marker = " ← current" if is_cur else ""
show cache pricing as well (if supported)
2026-04-05 22:39:02 -04:00
if has_cache:
lines.append(f"{indent}{mid:<{name_col}} {inp:>{price_col}} {out:>{price_col}} {cache:>{cache_col}}{marker}")
else:
lines.append(f"{indent}{mid:<{name_col}} {inp:>{price_col}} {out:>{price_col}}{marker}")
feat: show model pricing for OpenRouter and Nous Portal providers 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
2026-04-03 18:46:45 -04:00
return lines
def fetch_models_with_pricing(
api_key: str | None = None,
base_url: str = "https://openrouter.ai/api",
timeout: float = 8.0,
*,
force_refresh: bool = False,
) -> dict[str, dict[str, str]]:
"""Fetch ``/v1/models`` and return ``{model_id: {prompt, completion}}`` pricing.
Results are cached per *base_url* so repeated calls are free.
Works with any OpenRouter-compatible endpoint (OpenRouter, Nous Portal).
"""
cache_key = (base_url or "").rstrip("/")
if not force_refresh and cache_key in _pricing_cache:
return _pricing_cache[cache_key]
url = cache_key.rstrip("/") + "/v1/models"
headers: dict[str, str] = {"Accept": "application/json"}
if api_key:
headers["Authorization"] = f"Bearer {api_key}"
try:
req = urllib.request.Request(url, headers=headers)
with urllib.request.urlopen(req, timeout=timeout) as resp:
payload = json.loads(resp.read().decode())
except Exception:
_pricing_cache[cache_key] = {}
return {}
result: dict[str, dict[str, str]] = {}
for item in payload.get("data", []):
mid = item.get("id")
pricing = item.get("pricing")
if mid and isinstance(pricing, dict):
show cache pricing as well (if supported)
2026-04-05 22:39:02 -04:00
entry: dict[str, str] = {
feat: show model pricing for OpenRouter and Nous Portal providers 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
2026-04-03 18:46:45 -04:00
"prompt": str(pricing.get("prompt", "")),
"completion": str(pricing.get("completion", "")),
}
show cache pricing as well (if supported)
2026-04-05 22:39:02 -04:00
if pricing.get("input_cache_read"):
entry["input_cache_read"] = str(pricing["input_cache_read"])
if pricing.get("input_cache_write"):
entry["input_cache_write"] = str(pricing["input_cache_write"])
result[mid] = entry
feat: show model pricing for OpenRouter and Nous Portal providers 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
2026-04-03 18:46:45 -04:00
_pricing_cache[cache_key] = result
return result
feat: curated picker with live pricing for ai-gateway provider - Curated AI_GATEWAY_MODELS list in hermes_cli/models.py (OSS first, kimi-k2.5 as recommended default). - fetch_ai_gateway_models() filters the curated list against the live /v1/models catalog; falls back to the snapshot on network failure. - fetch_ai_gateway_pricing() translates Vercel's input/output field names to the prompt/completion shape the shared picker expects; carries input_cache_read / input_cache_write through unchanged. - get_pricing_for_provider() now handles ai-gateway. - _model_flow_ai_gateway() provides a guided URL prompt when no key is set and a pricing-column picker; routes ai-gateway to it instead of the generic api-key flow.
2026-04-19 23:05:14 -07:00
def fetch_ai_gateway_pricing(
timeout: float = 8.0,
*,
force_refresh: bool = False,
) -> dict[str, dict[str, str]]:
"""Fetch Vercel AI Gateway /v1/models and return hermes-shaped pricing.
Vercel uses ``input`` / ``output`` field names; hermes's picker expects
``prompt`` / ``completion``. This translates. Cache read/write field names
already match.
"""
from hermes_constants import AI_GATEWAY_BASE_URL
cache_key = AI_GATEWAY_BASE_URL.rstrip("/")
if not force_refresh and cache_key in _pricing_cache:
return _pricing_cache[cache_key]
try:
req = urllib.request.Request(
f"{cache_key}/models",
headers={"Accept": "application/json"},
)
with urllib.request.urlopen(req, timeout=timeout) as resp:
payload = json.loads(resp.read().decode())
except Exception:
_pricing_cache[cache_key] = {}
return {}
result: dict[str, dict[str, str]] = {}
for item in payload.get("data", []):
if not isinstance(item, dict):
continue
mid = item.get("id")
pricing = item.get("pricing")
if not (mid and isinstance(pricing, dict)):
continue
entry: dict[str, str] = {
"prompt": str(pricing.get("input", "")),
"completion": str(pricing.get("output", "")),
}
if pricing.get("input_cache_read"):
entry["input_cache_read"] = str(pricing["input_cache_read"])
if pricing.get("input_cache_write"):
entry["input_cache_write"] = str(pricing["input_cache_write"])
result[mid] = entry
_pricing_cache[cache_key] = result
return result
feat: show model pricing for OpenRouter and Nous Portal providers 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
2026-04-03 18:46:45 -04:00
def _resolve_openrouter_api_key() -> str:
"""Best-effort OpenRouter API key for pricing fetch."""
return os.getenv("OPENROUTER_API_KEY", "").strip()
def _resolve_nous_pricing_credentials() -> tuple[str, str]:
"""Return ``(api_key, base_url)`` for Nous Portal pricing, or empty strings."""
try:
from hermes_cli.auth import resolve_nous_runtime_credentials
creds = resolve_nous_runtime_credentials()
if creds:
return (creds.get("api_key", ""), creds.get("base_url", ""))
except Exception:
pass
return ("", "")
Refresh OpenRouter model catalog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-09 15:11:58 -05:00
def get_pricing_for_provider(provider: str, *, force_refresh: bool = False) -> dict[str, dict[str, str]]:
feat: curated picker with live pricing for ai-gateway provider - Curated AI_GATEWAY_MODELS list in hermes_cli/models.py (OSS first, kimi-k2.5 as recommended default). - fetch_ai_gateway_models() filters the curated list against the live /v1/models catalog; falls back to the snapshot on network failure. - fetch_ai_gateway_pricing() translates Vercel's input/output field names to the prompt/completion shape the shared picker expects; carries input_cache_read / input_cache_write through unchanged. - get_pricing_for_provider() now handles ai-gateway. - _model_flow_ai_gateway() provides a guided URL prompt when no key is set and a pricing-column picker; routes ai-gateway to it instead of the generic api-key flow.
2026-04-19 23:05:14 -07:00
"""Return live pricing for providers that support it (openrouter, nous, ai-gateway)."""
feat: show model pricing for OpenRouter and Nous Portal providers 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
2026-04-03 18:46:45 -04:00
normalized = normalize_provider(provider)
if normalized == "openrouter":
return fetch_models_with_pricing(
api_key=_resolve_openrouter_api_key(),
base_url="https://openrouter.ai/api",
Refresh OpenRouter model catalog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-09 15:11:58 -05:00
force_refresh=force_refresh,
feat: show model pricing for OpenRouter and Nous Portal providers 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
2026-04-03 18:46:45 -04:00
)
feat: curated picker with live pricing for ai-gateway provider - Curated AI_GATEWAY_MODELS list in hermes_cli/models.py (OSS first, kimi-k2.5 as recommended default). - fetch_ai_gateway_models() filters the curated list against the live /v1/models catalog; falls back to the snapshot on network failure. - fetch_ai_gateway_pricing() translates Vercel's input/output field names to the prompt/completion shape the shared picker expects; carries input_cache_read / input_cache_write through unchanged. - get_pricing_for_provider() now handles ai-gateway. - _model_flow_ai_gateway() provides a guided URL prompt when no key is set and a pricing-column picker; routes ai-gateway to it instead of the generic api-key flow.
2026-04-19 23:05:14 -07:00
if normalized == "ai-gateway":
return fetch_ai_gateway_pricing(force_refresh=force_refresh)
feat: show model pricing for OpenRouter and Nous Portal providers 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
2026-04-03 18:46:45 -04:00
if normalized == "nous":
api_key, base_url = _resolve_nous_pricing_credentials()
if base_url:
# Nous base_url typically looks like https://inference-api.nousresearch.com/v1
# We need the part before /v1 for our fetch function
stripped = base_url.rstrip("/")
if stripped.endswith("/v1"):
stripped = stripped[:-3]
return fetch_models_with_pricing(
api_key=api_key,
base_url=stripped,
Refresh OpenRouter model catalog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-09 15:11:58 -05:00
force_refresh=force_refresh,
feat: show model pricing for OpenRouter and Nous Portal providers 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
2026-04-03 18:46:45 -04:00
)
return {}
feat: /provider command + fix gateway bugs + harden parse_model_input /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.
2026-03-08 06:09:36 -07:00
# All provider IDs and aliases that are valid for the provider:model syntax.
_KNOWN_PROVIDER_NAMES: set[str] = (
set(_PROVIDER_LABELS.keys())
| set(_PROVIDER_ALIASES.keys())
| {"openrouter", "custom"}
)
def list_available_providers() -> list[dict[str, str]]:
"""Return info about all providers the user could use with ``provider:model``.
Each dict has ``id``, ``label``, and ``aliases``.
Checks which providers have valid credentials configured.
fix: consolidate provider lists into single CANONICAL_PROVIDERS source of truth (#9237) 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
2026-04-13 14:59:50 -07:00
Derives the provider list from :data:`CANONICAL_PROVIDERS` (single
source of truth shared with ``hermes model``, ``/model``, etc.).
feat: /provider command + fix gateway bugs + harden parse_model_input /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.
2026-03-08 06:09:36 -07:00
"""
fix: consolidate provider lists into single CANONICAL_PROVIDERS source of truth (#9237) 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
2026-04-13 14:59:50 -07:00
# Derive display order from canonical list + custom
provider_order = [p.slug for p in CANONICAL_PROVIDERS] + ["custom"]
feat: /provider command + fix gateway bugs + harden parse_model_input /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.
2026-03-08 06:09:36 -07:00
# Build reverse alias map
aliases_for: dict[str, list[str]] = {}
for alias, canonical in _PROVIDER_ALIASES.items():
aliases_for.setdefault(canonical, []).append(alias)
result = []
fix: consolidate provider lists into single CANONICAL_PROVIDERS source of truth (#9237) 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
2026-04-13 14:59:50 -07:00
for pid in provider_order:
feat: /provider command + fix gateway bugs + harden parse_model_input /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.
2026-03-08 06:09:36 -07:00
label = _PROVIDER_LABELS.get(pid, pid)
alias_list = aliases_for.get(pid, [])
# Check if this provider has credentials available
has_creds = False
try:
fix: ignore placeholder provider keys in provider activation checks 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.
2026-03-21 12:55:42 -07:00
from hermes_cli.auth import get_auth_status, has_usable_secret
fix: show custom endpoint models in /model via live API probe (#1645) 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>
2026-03-17 01:52:46 -07:00
if pid == "custom":
refactor: make config.yaml the single source of truth for endpoint URLs (#4165) 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.
2026-03-30 22:02:53 -07:00
custom_base_url = _get_custom_base_url() or ""
fix: ignore placeholder provider keys in provider activation checks 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.
2026-03-21 12:55:42 -07:00
has_creds = bool(custom_base_url.strip())
elif pid == "openrouter":
has_creds = has_usable_secret(os.getenv("OPENROUTER_API_KEY", ""))
fix: show custom endpoint models in /model via live API probe (#1645) 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>
2026-03-17 01:52:46 -07:00
else:
fix: ignore placeholder provider keys in provider activation checks 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.
2026-03-21 12:55:42 -07:00
status = get_auth_status(pid)
has_creds = bool(status.get("logged_in") or status.get("configured"))
feat: /provider command + fix gateway bugs + harden parse_model_input /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.
2026-03-08 06:09:36 -07:00
except Exception:
pass
result.append({
"id": pid,
"label": label,
"aliases": alias_list,
"authenticated": has_creds,
})
return result
feat: provider switching via /model + enhanced model 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.
2026-03-08 05:45:55 -07:00
def parse_model_input(raw: str, current_provider: str) -> tuple[str, str]:
"""Parse ``/model`` input into ``(provider, model)``.
Supports ``provider:model`` syntax to switch providers at runtime::
openrouter:anthropic/claude-sonnet-4.5 → ("openrouter", "anthropic/claude-sonnet-4.5")
nous:hermes-3 → ("nous", "hermes-3")
anthropic/claude-sonnet-4.5 → (current_provider, "anthropic/claude-sonnet-4.5")
gpt-5.4 → (current_provider, "gpt-5.4")
feat: /provider command + fix gateway bugs + harden parse_model_input /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.
2026-03-08 06:09:36 -07:00
The colon is only treated as a provider delimiter if the left side is a
recognized provider name or alias. This avoids misinterpreting model names
that happen to contain colons (e.g. ``anthropic/claude-3.5-sonnet:beta``).
feat: provider switching via /model + enhanced model 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.
2026-03-08 05:45:55 -07:00
Returns ``(provider, model)`` where *provider* is either the explicit
provider from the input or *current_provider* if none was specified.
"""
stripped = raw.strip()
colon = stripped.find(":")
if colon > 0:
provider_part = stripped[:colon].strip().lower()
model_part = stripped[colon + 1:].strip()
feat: /provider command + fix gateway bugs + harden parse_model_input /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.
2026-03-08 06:09:36 -07:00
if provider_part and model_part and provider_part in _KNOWN_PROVIDER_NAMES:
feat(model): /model command overhaul — Phases 2, 3, 5 * 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.
2026-03-24 06:58:04 -07:00
# Support custom:name:model triple syntax for named custom
# providers. ``custom:local:qwen`` → ("custom:local", "qwen").
# Single colon ``custom:qwen`` → ("custom", "qwen") as before.
if provider_part == "custom" and ":" in model_part:
second_colon = model_part.find(":")
custom_name = model_part[:second_colon].strip()
actual_model = model_part[second_colon + 1:].strip()
if custom_name and actual_model:
return (f"custom:{custom_name}", actual_model)
feat: provider switching via /model + enhanced model 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.
2026-03-08 05:45:55 -07:00
return (normalize_provider(provider_part), model_part)
return (current_provider, stripped)
fix: show custom endpoint models in /model via live API probe (#1645) 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>
2026-03-17 01:52:46 -07:00
def _get_custom_base_url() -> str:
"""Get the custom endpoint base_url from config.yaml."""
try:
from hermes_cli.config import load_config
config = load_config()
model_cfg = config.get("model", {})
if isinstance(model_cfg, dict):
return str(model_cfg.get("base_url", "")).strip()
except Exception:
pass
return ""
Refresh OpenRouter model catalog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-09 15:11:58 -05:00
def curated_models_for_provider(
provider: Optional[str],
*,
force_refresh: bool = False,
) -> list[tuple[str, str]]:
fix: fetch live model lists from provider APIs instead of static lists 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.
2026-03-12 02:46:33 -07:00
"""Return ``(model_id, description)`` tuples for a provider's model list.
Tries to fetch the live model list from the provider's API first,
falling back to the static ``_PROVIDER_MODELS`` catalog if the API
is unreachable.
"""
feat: provider switching via /model + enhanced model 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.
2026-03-08 05:45:55 -07:00
normalized = normalize_provider(provider)
if normalized == "openrouter":
Refresh OpenRouter model catalog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-09 15:11:58 -05:00
return fetch_openrouter_models(force_refresh=force_refresh)
fix: fetch live model lists from provider APIs instead of static lists 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.
2026-03-12 02:46:33 -07:00
# Try live API first (Codex, Nous, etc. all support /models)
live = provider_model_ids(normalized)
if live:
return [(m, "") for m in live]
# Fallback to static catalog
feat: provider switching via /model + enhanced model 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.
2026-03-08 05:45:55 -07:00
models = _PROVIDER_MODELS.get(normalized, [])
return [(m, "") for m in models]
feat: auto-detect provider when switching models via /model (#1506) 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>
2026-03-16 04:34:45 -07:00
def detect_provider_for_model(
model_name: str,
current_provider: str,
) -> Optional[tuple[str, str]]:
"""Auto-detect the best provider for a model name.
Returns ``(provider_id, model_name)`` — the model name may be remapped
(e.g. bare ``deepseek-chat`` → ``deepseek/deepseek-chat`` for OpenRouter).
Returns ``None`` when no confident match is found.
Priority:
fix: /model command — bare provider names, custom endpoint display 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>
2026-03-19 12:06:48 -07:00
0. Bare provider name → switch to that provider's default model
feat: auto-detect provider when switching models via /model (#1506) 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>
2026-03-16 04:34:45 -07:00
1. Direct provider with credentials (highest)
2. Direct provider without credentials → remap to OpenRouter slug
3. OpenRouter catalog match
"""
name = (model_name or "").strip()
if not name:
return None
name_lower = name.lower()
fix: /model command — bare provider names, custom endpoint display 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>
2026-03-19 12:06:48 -07:00
# --- Step 0: bare provider name typed as model ---
# If someone types `/model nous` or `/model anthropic`, treat it as a
# provider switch and pick the first model from that provider's catalog.
# Skip "custom" and "openrouter" — custom has no model catalog, and
# openrouter requires an explicit model name to be useful.
resolved_provider = _PROVIDER_ALIASES.get(name_lower, name_lower)
if resolved_provider not in {"custom", "openrouter"}:
default_models = _PROVIDER_MODELS.get(resolved_provider, [])
if (
resolved_provider in _PROVIDER_LABELS
and default_models
and resolved_provider != normalize_provider(current_provider)
):
return (resolved_provider, default_models[0])
feat: auto-detect provider when switching models via /model (#1506) 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>
2026-03-16 04:34:45 -07:00
# Aggregators list other providers' models — never auto-switch TO them
fix(tests): resolve 12 CI failures + 10 errors across 6 root causes (#11040) 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.
2026-04-16 06:49:36 -07:00
_AGGREGATORS = {"nous", "openrouter", "ai-gateway", "copilot", "kilocode"}
feat: auto-detect provider when switching models via /model (#1506) 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>
2026-03-16 04:34:45 -07:00
# If the model belongs to the current provider's catalog, don't suggest switching
current_models = _PROVIDER_MODELS.get(current_provider, [])
if any(name_lower == m.lower() for m in current_models):
return None
# --- Step 1: check static provider catalogs for a direct match ---
direct_match: Optional[str] = None
for pid, models in _PROVIDER_MODELS.items():
if pid == current_provider or pid in _AGGREGATORS:
continue
if any(name_lower == m.lower() for m in models):
direct_match = pid
break
if direct_match:
fix: stop /model from silently rerouting direct providers to OpenRouter (#10300) (#10780) 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
2026-04-16 02:27:20 -07:00
# Check if we have credentials for this provider — env vars,
# credential pool, or auth store entries.
feat: auto-detect provider when switching models via /model (#1506) 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>
2026-03-16 04:34:45 -07:00
has_creds = False
try:
from hermes_cli.auth import PROVIDER_REGISTRY
pconfig = PROVIDER_REGISTRY.get(direct_match)
if pconfig:
import os
for env_var in pconfig.api_key_env_vars:
if os.getenv(env_var, "").strip():
has_creds = True
break
except Exception:
pass
fix: stop /model from silently rerouting direct providers to OpenRouter (#10300) (#10780) 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
2026-04-16 02:27:20 -07:00
# Also check credential pool and auth store — covers OAuth,
# Claude Code tokens, and other non-env-var credentials (#10300).
if not has_creds:
try:
from agent.credential_pool import load_pool
pool = load_pool(direct_match)
if pool.has_credentials():
has_creds = True
except Exception:
pass
if not has_creds:
try:
from hermes_cli.auth import _load_auth_store
store = _load_auth_store()
if direct_match in store.get("providers", {}) or direct_match in store.get("credential_pool", {}):
has_creds = True
except Exception:
pass
# Always return the direct provider match. If credentials are
# missing, the client init will give a clear error rather than
# silently routing through the wrong provider (#10300).
feat: auto-detect provider when switching models via /model (#1506) 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>
2026-03-16 04:34:45 -07:00
return (direct_match, name)
# --- Step 2: check OpenRouter catalog ---
# First try exact match (handles provider/model format)
or_slug = _find_openrouter_slug(name)
if or_slug:
if current_provider != "openrouter":
return ("openrouter", or_slug)
# Already on openrouter, just return the resolved slug
if or_slug != name:
return ("openrouter", or_slug)
return None # already on openrouter with matching name
return None
def _find_openrouter_slug(model_name: str) -> Optional[str]:
"""Find the full OpenRouter model slug for a bare or partial model name.
Handles:
- Exact match: ``anthropic/claude-opus-4.6`` → as-is
- Bare name: ``deepseek-chat`` → ``deepseek/deepseek-chat``
- Bare name: ``claude-opus-4.6`` → ``anthropic/claude-opus-4.6``
"""
name_lower = model_name.strip().lower()
if not name_lower:
return None
# Exact match (already has provider/ prefix)
Refresh OpenRouter model catalog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-09 15:11:58 -05:00
for mid in model_ids():
feat: auto-detect provider when switching models via /model (#1506) 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>
2026-03-16 04:34:45 -07:00
if name_lower == mid.lower():
return mid
# Try matching just the model part (after the /)
Refresh OpenRouter model catalog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-09 15:11:58 -05:00
for mid in model_ids():
feat: auto-detect provider when switching models via /model (#1506) 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>
2026-03-16 04:34:45 -07:00
if "/" in mid:
_, model_part = mid.split("/", 1)
if name_lower == model_part.lower():
return mid
return None
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
def normalize_provider(provider: Optional[str]) -> str:
fix: resolve 'auto' provider properly via credential detection '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.
2026-03-08 05:58:45 -07:00
"""Normalize provider aliases to Hermes' canonical provider ids.
Note: ``"auto"`` passes through unchanged — use
``hermes_cli.auth.resolve_provider()`` to resolve it to a concrete
provider based on credentials and environment.
"""
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
normalized = (provider or "openrouter").strip().lower()
return _PROVIDER_ALIASES.get(normalized, normalized)
Show configured model and provider in status output Made-with: Cursor
2026-03-11 19:37:42 +03:00
def provider_label(provider: Optional[str]) -> str:
"""Return a human-friendly label for a provider id or alias."""
original = (provider or "openrouter").strip()
normalized = original.lower()
if normalized == "auto":
return "Auto"
normalized = normalize_provider(normalized)
return _PROVIDER_LABELS.get(normalized, original or "OpenRouter")
feat: expand /fast to all OpenAI Priority Processing models (#6960) 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
2026-04-09 22:06:30 -07:00
# Models that support OpenAI Priority Processing (service_tier="priority").
# See https://openai.com/api-priority-processing/ for the canonical list.
# Only the bare model slug is stored (no vendor prefix).
_PRIORITY_PROCESSING_MODELS: frozenset[str] = frozenset({
"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",
})
feat: add Codex fast mode toggle (/fast command) 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>
2026-04-09 18:10:57 -07:00
feat: add Anthropic Fast Mode support to /fast command (#7037) 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
2026-04-10 02:32:15 -07:00
# Models that support Anthropic Fast Mode (speed="fast").
# See https://platform.claude.com/docs/en/build-with-claude/fast-mode
# Currently only Claude Opus 4.6. Both hyphen and dot variants are stored
# to handle native Anthropic (claude-opus-4-6) and OpenRouter (claude-opus-4.6).
_ANTHROPIC_FAST_MODE_MODELS: frozenset[str] = frozenset({
"claude-opus-4-6",
"claude-opus-4.6",
})
feat: add Codex fast mode toggle (/fast command) 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>
2026-04-09 18:10:57 -07:00
feat: add Anthropic Fast Mode support to /fast command (#7037) 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
2026-04-10 02:32:15 -07:00
def _strip_vendor_prefix(model_id: str) -> str:
"""Strip vendor/ prefix from a model ID (e.g. 'anthropic/claude-opus-4-6' -> 'claude-opus-4-6')."""
feat: add Codex fast mode toggle (/fast command) 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>
2026-04-09 18:10:57 -07:00
raw = str(model_id or "").strip().lower()
if "/" in raw:
raw = raw.split("/", 1)[1]
feat: add Anthropic Fast Mode support to /fast command (#7037) 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
2026-04-10 02:32:15 -07:00
return raw
def model_supports_fast_mode(model_id: Optional[str]) -> bool:
"""Return whether Hermes should expose the /fast toggle for this model."""
raw = _strip_vendor_prefix(str(model_id or ""))
if raw in _PRIORITY_PROCESSING_MODELS:
return True
# Anthropic fast mode — strip date suffixes (e.g. claude-opus-4-6-20260401)
# and OpenRouter variant tags (:fast, :beta) for matching.
base = raw.split(":")[0]
return base in _ANTHROPIC_FAST_MODE_MODELS
def _is_anthropic_fast_model(model_id: Optional[str]) -> bool:
"""Return True if the model supports Anthropic's fast mode (speed='fast')."""
raw = _strip_vendor_prefix(str(model_id or ""))
base = raw.split(":")[0]
return base in _ANTHROPIC_FAST_MODE_MODELS
feat: add Codex fast mode toggle (/fast command) 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>
2026-04-09 18:10:57 -07:00
feat: expand /fast to all OpenAI Priority Processing models (#6960) 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
2026-04-09 22:06:30 -07:00
def resolve_fast_mode_overrides(model_id: Optional[str]) -> dict[str, Any] | None:
feat: add Anthropic Fast Mode support to /fast command (#7037) 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
2026-04-10 02:32:15 -07:00
"""Return request_overrides for fast/priority mode, or None if unsupported.
Returns provider-appropriate overrides:
- OpenAI models: ``{"service_tier": "priority"}`` (Priority Processing)
- Anthropic models: ``{"speed": "fast"}`` (Anthropic Fast Mode beta)
feat: add Codex fast mode toggle (/fast command) 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>
2026-04-09 18:10:57 -07:00
feat: add Anthropic Fast Mode support to /fast command (#7037) 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
2026-04-10 02:32:15 -07:00
The overrides are injected into the API request kwargs by
``_build_api_kwargs`` in run_agent.py — each API path handles its own
keys (service_tier for OpenAI/Codex, speed for Anthropic Messages).
feat: expand /fast to all OpenAI Priority Processing models (#6960) 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
2026-04-09 22:06:30 -07:00
"""
if not model_supports_fast_mode(model_id):
feat: add Codex fast mode toggle (/fast command) 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>
2026-04-09 18:10:57 -07:00
return None
feat: add Anthropic Fast Mode support to /fast command (#7037) 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
2026-04-10 02:32:15 -07:00
if _is_anthropic_fast_model(model_id):
return {"speed": "fast"}
feat: expand /fast to all OpenAI Priority Processing models (#6960) 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
2026-04-09 22:06:30 -07:00
return {"service_tier": "priority"}
feat: add Codex fast mode toggle (/fast command) 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>
2026-04-09 18:10:57 -07:00
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
def _resolve_copilot_catalog_api_key() -> str:
"""Best-effort GitHub token for fetching the Copilot model catalog."""
try:
from hermes_cli.auth import resolve_api_key_provider_credentials
creds = resolve_api_key_provider_credentials("copilot")
return str(creds.get("api_key") or "").strip()
except Exception:
return ""
Refresh OpenRouter model catalog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-09 15:11:58 -05:00
def provider_model_ids(provider: Optional[str], *, force_refresh: bool = False) -> list[str]:
fix: fetch live model lists from provider APIs instead of static lists 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.
2026-03-12 02:46:33 -07:00
"""Return the best known model catalog for a provider.
Tries live API endpoints for providers that support them (Codex, Nous),
falling back to static lists.
"""
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
normalized = normalize_provider(provider)
if normalized == "openrouter":
Refresh OpenRouter model catalog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-09 15:11:58 -05:00
return model_ids(force_refresh=force_refresh)
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
if normalized == "openai-codex":
from hermes_cli.codex_models import get_codex_model_ids
return get_codex_model_ids()
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
if normalized in {"copilot", "copilot-acp"}:
try:
live = _fetch_github_models(_resolve_copilot_catalog_api_key())
if live:
return live
except Exception:
pass
if normalized == "copilot-acp":
return list(_PROVIDER_MODELS.get("copilot", []))
fix: fetch live model lists from provider APIs instead of static lists 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.
2026-03-12 02:46:33 -07:00
if normalized == "nous":
# Try live Nous Portal /models endpoint
try:
from hermes_cli.auth import fetch_nous_models, resolve_nous_runtime_credentials
creds = resolve_nous_runtime_credentials()
if creds:
fix(cli): use keyword args for fetch_nous_models (always TypeError) 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.
2026-03-17 03:42:46 -07:00
live = fetch_nous_models(api_key=creds.get("api_key", ""), inference_base_url=creds.get("base_url", ""))
fix: fetch live model lists from provider APIs instead of static lists 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.
2026-03-12 02:46:33 -07:00
if live:
return live
except Exception:
pass
fix(anthropic): live model fetching + adaptive thinking for 4.5+ models - 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
2026-03-12 17:04:31 -07:00
if normalized == "anthropic":
live = _fetch_anthropic_models()
if live:
return live
feat: add Vercel AI Gateway provider (#1628) * 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>
2026-03-17 00:12:16 -07:00
if normalized == "ai-gateway":
live = _fetch_ai_gateway_models()
if live:
return live
fix: wire up Ollama Cloud dynamic model discovery in /model TUI picker 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
2026-04-16 20:03:31 +09:30
if normalized == "ollama-cloud":
live = fetch_ollama_cloud_models(force_refresh=force_refresh)
if live:
return live
fix: show custom endpoint models in /model via live API probe (#1645) 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>
2026-03-17 01:52:46 -07:00
if normalized == "custom":
base_url = _get_custom_base_url()
if base_url:
# Try common API key env vars for custom endpoints
api_key = (
os.getenv("CUSTOM_API_KEY", "")
or os.getenv("OPENAI_API_KEY", "")
or os.getenv("OPENROUTER_API_KEY", "")
)
live = fetch_api_models(api_key, base_url)
if live:
return live
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
return list(_PROVIDER_MODELS.get(normalized, []))
fix(anthropic): live model fetching + adaptive thinking for 4.5+ models - 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
2026-03-12 17:04:31 -07:00
def _fetch_anthropic_models(timeout: float = 5.0) -> Optional[list[str]]:
"""Fetch available models from the Anthropic /v1/models endpoint.
Uses resolve_anthropic_token() to find credentials (env vars or
Claude Code auto-discovery). Returns sorted model IDs or None.
"""
try:
from agent.anthropic_adapter import resolve_anthropic_token, _is_oauth_token
except ImportError:
return None
token = resolve_anthropic_token()
if not token:
return None
headers: dict[str, str] = {"anthropic-version": "2023-06-01"}
if _is_oauth_token(token):
headers["Authorization"] = f"Bearer {token}"
fix: Anthropic OAuth — beta header, token refresh, config contamination, reauthentication (#1132) 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)
2026-03-12 20:45:50 -07:00
from agent.anthropic_adapter import _COMMON_BETAS, _OAUTH_ONLY_BETAS
headers["anthropic-beta"] = ",".join(_COMMON_BETAS + _OAUTH_ONLY_BETAS)
fix(anthropic): live model fetching + adaptive thinking for 4.5+ models - 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
2026-03-12 17:04:31 -07:00
else:
headers["x-api-key"] = token
req = urllib.request.Request(
"https://api.anthropic.com/v1/models",
headers=headers,
)
try:
with urllib.request.urlopen(req, timeout=timeout) as resp:
data = json.loads(resp.read().decode())
models = [m["id"] for m in data.get("data", []) if m.get("id")]
# Sort: latest/largest first (opus > sonnet > haiku, higher version first)
return sorted(models, key=lambda m: (
"opus" not in m, # opus first
"sonnet" not in m, # then sonnet
"haiku" not in m, # then haiku
m, # alphabetical within tier
))
fix(anthropic): deep scan fixes — auth, retries, edge cases 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
2026-03-12 17:14:22 -07:00
except Exception as e:
import logging
logging.getLogger(__name__).debug("Failed to fetch Anthropic models: %s", e)
fix(anthropic): live model fetching + adaptive thinking for 4.5+ models - 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
2026-03-12 17:04:31 -07:00
return None
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
def _payload_items(payload: Any) -> list[dict[str, Any]]:
if isinstance(payload, list):
return [item for item in payload if isinstance(item, dict)]
if isinstance(payload, dict):
data = payload.get("data", [])
if isinstance(data, list):
return [item for item in data if isinstance(item, dict)]
return []
def copilot_default_headers() -> dict[str, str]:
feat: proper Copilot auth with OAuth device code flow and token validation 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
2026-03-18 03:25:58 -07:00
"""Standard headers for Copilot API requests.
Includes Openai-Intent and x-initiator headers that opencode and the
Copilot CLI send on every request.
"""
try:
from hermes_cli.copilot_auth import copilot_request_headers
return copilot_request_headers(is_agent_turn=True)
except ImportError:
return {
"Editor-Version": COPILOT_EDITOR_VERSION,
"User-Agent": "HermesAgent/1.0",
"Openai-Intent": "conversation-edits",
"x-initiator": "agent",
}
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
def _copilot_catalog_item_is_text_model(item: dict[str, Any]) -> bool:
model_id = str(item.get("id") or "").strip()
if not model_id:
return False
if item.get("model_picker_enabled") is False:
return False
capabilities = item.get("capabilities")
if isinstance(capabilities, dict):
model_type = str(capabilities.get("type") or "").strip().lower()
if model_type and model_type != "chat":
return False
supported_endpoints = item.get("supported_endpoints")
if isinstance(supported_endpoints, list):
normalized_endpoints = {
str(endpoint).strip()
for endpoint in supported_endpoints
if str(endpoint).strip()
}
if normalized_endpoints and not normalized_endpoints.intersection(
{"/chat/completions", "/responses", "/v1/messages"}
):
return False
return True
def fetch_github_model_catalog(
api_key: Optional[str] = None, timeout: float = 5.0
) -> Optional[list[dict[str, Any]]]:
"""Fetch the live GitHub Copilot model catalog for this account."""
attempts: list[dict[str, str]] = []
if api_key:
attempts.append({
**copilot_default_headers(),
"Authorization": f"Bearer {api_key}",
})
attempts.append(copilot_default_headers())
for headers in attempts:
req = urllib.request.Request(COPILOT_MODELS_URL, headers=headers)
try:
with urllib.request.urlopen(req, timeout=timeout) as resp:
data = json.loads(resp.read().decode())
items = _payload_items(data)
models: list[dict[str, Any]] = []
seen_ids: set[str] = set()
for item in items:
if not _copilot_catalog_item_is_text_model(item):
continue
model_id = str(item.get("id") or "").strip()
if not model_id or model_id in seen_ids:
continue
seen_ids.add(model_id)
models.append(item)
if models:
return models
except Exception:
continue
return None
def _is_github_models_base_url(base_url: Optional[str]) -> bool:
normalized = (base_url or "").strip().rstrip("/").lower()
return (
normalized.startswith(COPILOT_BASE_URL)
or normalized.startswith("https://models.github.ai/inference")
)
def _fetch_github_models(api_key: Optional[str] = None, timeout: float = 5.0) -> Optional[list[str]]:
catalog = fetch_github_model_catalog(api_key=api_key, timeout=timeout)
if not catalog:
return None
return [item.get("id", "") for item in catalog if item.get("id")]
_COPILOT_MODEL_ALIASES = {
"openai/gpt-5": "gpt-5-mini",
"openai/gpt-5-chat": "gpt-5-mini",
"openai/gpt-5-mini": "gpt-5-mini",
"openai/gpt-5-nano": "gpt-5-mini",
"openai/gpt-4.1": "gpt-4.1",
"openai/gpt-4.1-mini": "gpt-4.1",
"openai/gpt-4.1-nano": "gpt-4.1",
"openai/gpt-4o": "gpt-4o",
"openai/gpt-4o-mini": "gpt-4o-mini",
"openai/o1": "gpt-5.2",
"openai/o1-mini": "gpt-5-mini",
"openai/o1-preview": "gpt-5.2",
"openai/o3": "gpt-5.3-codex",
"openai/o3-mini": "gpt-5-mini",
"openai/o4-mini": "gpt-5-mini",
"anthropic/claude-opus-4.6": "claude-opus-4.6",
"anthropic/claude-sonnet-4.6": "claude-sonnet-4.6",
"anthropic/claude-sonnet-4.5": "claude-sonnet-4.5",
"anthropic/claude-haiku-4.5": "claude-haiku-4.5",
fix(copilot): normalize vendor-prefixed and dash-notation model IDs (#6879) (#11561) 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.
2026-04-17 04:19:36 -07:00
# Dash-notation fallbacks: Hermes' default Claude IDs elsewhere use
# hyphens (anthropic native format), but Copilot's API only accepts
# dot-notation. Accept both so users who configure copilot + a
# default hyphenated Claude model don't hit HTTP 400
# "model_not_supported". See issue #6879.
"claude-opus-4-6": "claude-opus-4.6",
"claude-sonnet-4-6": "claude-sonnet-4.6",
"claude-sonnet-4-5": "claude-sonnet-4.5",
"claude-haiku-4-5": "claude-haiku-4.5",
"anthropic/claude-opus-4-6": "claude-opus-4.6",
"anthropic/claude-sonnet-4-6": "claude-sonnet-4.6",
"anthropic/claude-sonnet-4-5": "claude-sonnet-4.5",
"anthropic/claude-haiku-4-5": "claude-haiku-4.5",
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
}
def _copilot_catalog_ids(
catalog: Optional[list[dict[str, Any]]] = None,
api_key: Optional[str] = None,
) -> set[str]:
if catalog is None and api_key:
catalog = fetch_github_model_catalog(api_key=api_key)
if not catalog:
return set()
return {
str(item.get("id") or "").strip()
for item in catalog
if str(item.get("id") or "").strip()
}
def normalize_copilot_model_id(
model_id: Optional[str],
*,
catalog: Optional[list[dict[str, Any]]] = None,
api_key: Optional[str] = None,
) -> str:
raw = str(model_id or "").strip()
if not raw:
return ""
catalog_ids = _copilot_catalog_ids(catalog=catalog, api_key=api_key)
alias = _COPILOT_MODEL_ALIASES.get(raw)
if alias:
return alias
candidates = [raw]
if "/" in raw:
candidates.append(raw.split("/", 1)[1].strip())
if raw.endswith("-mini"):
candidates.append(raw[:-5])
if raw.endswith("-nano"):
candidates.append(raw[:-5])
if raw.endswith("-chat"):
candidates.append(raw[:-5])
seen: set[str] = set()
for candidate in candidates:
if not candidate or candidate in seen:
continue
seen.add(candidate)
if candidate in _COPILOT_MODEL_ALIASES:
return _COPILOT_MODEL_ALIASES[candidate]
if candidate in catalog_ids:
return candidate
if "/" in raw:
return raw.split("/", 1)[1].strip()
return raw
def _github_reasoning_efforts_for_model_id(model_id: str) -> list[str]:
raw = (model_id or "").strip().lower()
if raw.startswith(("openai/o1", "openai/o3", "openai/o4", "o1", "o3", "o4")):
return list(COPILOT_REASONING_EFFORTS_O_SERIES)
normalized = normalize_copilot_model_id(model_id).lower()
if normalized.startswith("gpt-5"):
return list(COPILOT_REASONING_EFFORTS_GPT5)
return []
fix: correct Copilot API mode selection to match opencode 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.
2026-03-18 03:54:50 -07:00
def _should_use_copilot_responses_api(model_id: str) -> bool:
"""Decide whether a Copilot model should use the Responses API.
Replicates opencode's ``shouldUseCopilotResponsesApi`` logic:
GPT-5+ models use Responses API, except ``gpt-5-mini`` which uses
Chat Completions. All non-GPT models (Claude, Gemini, etc.) use
Chat Completions.
"""
import re
match = re.match(r"^gpt-(\d+)", model_id)
if not match:
return False
major = int(match.group(1))
return major >= 5 and not model_id.startswith("gpt-5-mini")
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
def copilot_model_api_mode(
model_id: Optional[str],
*,
catalog: Optional[list[dict[str, Any]]] = None,
api_key: Optional[str] = None,
) -> str:
fix: correct Copilot API mode selection to match opencode 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.
2026-03-18 03:54:50 -07:00
"""Determine the API mode for a Copilot model.
Uses the model ID pattern (matching opencode's approach) as the
primary signal. Falls back to the catalog's ``supported_endpoints``
only for models not covered by the pattern check.
"""
fix(copilot): eliminate redundant catalog fetch in api_mode resolution (#11008) 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>
2026-04-16 05:18:34 -07:00
# Fetch the catalog once so normalize + endpoint check share it
# (avoids two redundant network calls for non-GPT-5 models).
if catalog is None and api_key:
catalog = fetch_github_model_catalog(api_key=api_key)
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
normalized = normalize_copilot_model_id(model_id, catalog=catalog, api_key=api_key)
if not normalized:
return "chat_completions"
fix: correct Copilot API mode selection to match opencode 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.
2026-03-18 03:54:50 -07:00
# Primary: model ID pattern (matches opencode's shouldUseCopilotResponsesApi)
if _should_use_copilot_responses_api(normalized):
return "codex_responses"
# Secondary: check catalog for non-GPT-5 models (Claude via /v1/messages, etc.)
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
if catalog:
catalog_entry = next((item for item in catalog if item.get("id") == normalized), None)
fix: correct Copilot API mode selection to match opencode 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.
2026-03-18 03:54:50 -07:00
if isinstance(catalog_entry, dict):
supported_endpoints = {
str(endpoint).strip()
for endpoint in (catalog_entry.get("supported_endpoints") or [])
if str(endpoint).strip()
}
# For non-GPT-5 models, check if they only support messages API
if "/v1/messages" in supported_endpoints and "/chat/completions" not in supported_endpoints:
return "anthropic_messages"
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
return "chat_completions"
fix: repair OpenCode model routing and selection (#4508) 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>
2026-04-02 09:36:24 -07:00
def normalize_opencode_model_id(provider_id: Optional[str], model_id: Optional[str]) -> str:
"""Normalize OpenCode config IDs to the bare model slug used in API requests."""
provider = normalize_provider(provider_id)
current = str(model_id or "").strip()
if not current or provider not in {"opencode-zen", "opencode-go"}:
return current
prefix = f"{provider}/"
if current.lower().startswith(prefix):
return current[len(prefix):]
return current
def opencode_model_api_mode(provider_id: Optional[str], model_id: Optional[str]) -> str:
"""Determine the API mode for an OpenCode Zen / Go model.
OpenCode routes different models behind different API surfaces:
- GPT-5 / Codex models on Zen use ``/v1/responses``
- Claude models on Zen use ``/v1/messages``
- MiniMax models on Go use ``/v1/messages``
- GLM / Kimi on Go use ``/v1/chat/completions``
- Other Zen models (Gemini, GLM, Kimi, MiniMax, Qwen, etc.) use
``/v1/chat/completions``
This follows the published OpenCode docs for Zen and Go endpoints.
"""
provider = normalize_provider(provider_id)
normalized = normalize_opencode_model_id(provider_id, model_id).lower()
if not normalized:
return "chat_completions"
if provider == "opencode-go":
if normalized.startswith("minimax-"):
return "anthropic_messages"
return "chat_completions"
if provider == "opencode-zen":
if normalized.startswith("claude-"):
return "anthropic_messages"
if normalized.startswith("gpt-"):
return "codex_responses"
return "chat_completions"
return "chat_completions"
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
def github_model_reasoning_efforts(
model_id: Optional[str],
*,
catalog: Optional[list[dict[str, Any]]] = None,
api_key: Optional[str] = None,
) -> list[str]:
"""Return supported reasoning-effort levels for a Copilot-visible model."""
normalized = normalize_copilot_model_id(model_id, catalog=catalog, api_key=api_key)
if not normalized:
return []
catalog_entry = None
if catalog is not None:
catalog_entry = next((item for item in catalog if item.get("id") == normalized), None)
elif api_key:
fetched_catalog = fetch_github_model_catalog(api_key=api_key)
if fetched_catalog:
catalog_entry = next((item for item in fetched_catalog if item.get("id") == normalized), None)
if catalog_entry is not None:
capabilities = catalog_entry.get("capabilities")
if isinstance(capabilities, dict):
supports = capabilities.get("supports")
if isinstance(supports, dict):
efforts = supports.get("reasoning_effort")
if isinstance(efforts, list):
normalized_efforts = [
str(effort).strip().lower()
for effort in efforts
if str(effort).strip()
]
return list(dict.fromkeys(normalized_efforts))
return []
legacy_capabilities = {
str(capability).strip().lower()
for capability in catalog_entry.get("capabilities", [])
if str(capability).strip()
}
if "reasoning" not in legacy_capabilities:
return []
return _github_reasoning_efforts_for_model_id(str(model_id or normalized))
fix(custom-endpoint): verify /models and suggest working /v1 base URL (#1480)
2026-03-15 20:09:50 -07:00
def probe_api_models(
api_key: Optional[str],
base_url: Optional[str],
timeout: float = 5.0,
) -> dict[str, Any]:
"""Probe an OpenAI-compatible ``/models`` endpoint with light URL heuristics."""
normalized = (base_url or "").strip().rstrip("/")
if not normalized:
return {
"models": None,
"probed_url": None,
"resolved_base_url": "",
"suggested_base_url": None,
"used_fallback": False,
}
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
if _is_github_models_base_url(normalized):
models = _fetch_github_models(api_key=api_key, timeout=timeout)
return {
"models": models,
"probed_url": COPILOT_MODELS_URL,
"resolved_base_url": COPILOT_BASE_URL,
"suggested_base_url": None,
"used_fallback": False,
}
fix(custom-endpoint): verify /models and suggest working /v1 base URL (#1480)
2026-03-15 20:09:50 -07:00
if normalized.endswith("/v1"):
alternate_base = normalized[:-3].rstrip("/")
else:
alternate_base = normalized + "/v1"
candidates: list[tuple[str, bool]] = [(normalized, False)]
if alternate_base and alternate_base != normalized:
candidates.append((alternate_base, True))
tried: list[str] = []
fix(cli): send User-Agent in /v1/models probe to pass Cloudflare 1010 Custom Claude proxies fronted by Cloudflare with Browser Integrity Check enabled (e.g. `packyapi.com`) reject requests with the default `Python-urllib/*` signature, returning HTTP 403 "error code: 1010". `probe_api_models` swallowed that in its blanket `except Exception: continue`, so `validate_requested_model` returned the misleading "Could not reach the <provider> API to validate `<model>`" error even though the endpoint is reachable and lists the requested model. Advertise the probe request as `hermes-cli/<version>` so Cloudflare treats it as a first-party client. This mirrors the pattern already used by `agent/gemini_native_adapter.py` and `agent/anthropic_adapter.py`, which set a descriptive UA for the same reason. Reproduction (pre-fix): python3 -c " import urllib.request req = urllib.request.Request( 'https://www.packyapi.com/v1/models', headers={'Authorization': 'Bearer sk-...'}) urllib.request.urlopen(req).read() " urllib.error.HTTPError: HTTP Error 403: Forbidden (body: b'error code: 1010') Any non-urllib UA (Mozilla, curl, reqwest) returns 200 with the OpenAI-compatible models listing. Tested on macOS (Python 3.11). No cross-platform concerns — the change is a single header addition to an existing `urllib.request.Request`.
2026-04-20 16:00:55 +08:00
headers: dict[str, str] = {"User-Agent": _HERMES_USER_AGENT}
fix(custom-endpoint): verify /models and suggest working /v1 base URL (#1480)
2026-03-15 20:09:50 -07:00
if api_key:
headers["Authorization"] = f"Bearer {api_key}"
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
if normalized.startswith(COPILOT_BASE_URL):
headers.update(copilot_default_headers())
fix(custom-endpoint): verify /models and suggest working /v1 base URL (#1480)
2026-03-15 20:09:50 -07:00
for candidate_base, is_fallback in candidates:
url = candidate_base.rstrip("/") + "/models"
tried.append(url)
req = urllib.request.Request(url, headers=headers)
try:
with urllib.request.urlopen(req, timeout=timeout) as resp:
data = json.loads(resp.read().decode())
return {
"models": [m.get("id", "") for m in data.get("data", [])],
"probed_url": url,
"resolved_base_url": candidate_base.rstrip("/"),
"suggested_base_url": alternate_base if alternate_base != candidate_base else normalized,
"used_fallback": is_fallback,
}
except Exception:
continue
return {
"models": None,
fix(models): correct probed_url selection logic 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.
2026-04-09 16:15:37 +09:00
"probed_url": tried[0] if tried else normalized.rstrip("/") + "/models",
fix(custom-endpoint): verify /models and suggest working /v1 base URL (#1480)
2026-03-15 20:09:50 -07:00
"resolved_base_url": normalized,
"suggested_base_url": alternate_base if alternate_base != normalized else None,
"used_fallback": False,
}
feat: add Vercel AI Gateway provider (#1628) * 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>
2026-03-17 00:12:16 -07:00
def _fetch_ai_gateway_models(timeout: float = 5.0) -> Optional[list[str]]:
"""Fetch available language models with tool-use from AI Gateway."""
api_key = os.getenv("AI_GATEWAY_API_KEY", "").strip()
if not api_key:
return None
base_url = os.getenv("AI_GATEWAY_BASE_URL", "").strip()
if not base_url:
from hermes_constants import AI_GATEWAY_BASE_URL
base_url = AI_GATEWAY_BASE_URL
url = base_url.rstrip("/") + "/models"
headers: dict[str, str] = {"Authorization": f"Bearer {api_key}"}
req = urllib.request.Request(url, headers=headers)
try:
with urllib.request.urlopen(req, timeout=timeout) as resp:
data = json.loads(resp.read().decode())
return [
m["id"]
for m in data.get("data", [])
if m.get("id")
and m.get("type") == "language"
and "tool-use" in (m.get("tags") or [])
]
except Exception:
return None
feat: validate /model against live API instead of hardcoded lists 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.
2026-03-08 05:22:15 -07:00
def fetch_api_models(
api_key: Optional[str],
base_url: Optional[str],
timeout: float = 5.0,
) -> Optional[list[str]]:
"""Fetch the list of available model IDs from the provider's ``/models`` endpoint.
Returns a list of model ID strings, or ``None`` if the endpoint could not
be reached (network error, timeout, auth failure, etc.).
"""
fix(custom-endpoint): verify /models and suggest working /v1 base URL (#1480)
2026-03-15 20:09:50 -07:00
return probe_api_models(api_key, base_url, timeout=timeout).get("models")
feat: validate /model against live API instead of hardcoded lists 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.
2026-03-08 05:22:15 -07:00
feat: add Ollama Cloud as built-in provider Add ollama-cloud as a first-class provider with full parity to existing API-key providers (gemini, zai, minimax, etc.): - PROVIDER_REGISTRY entry with OLLAMA_API_KEY env var - Provider aliases: ollama -> custom (local), ollama_cloud -> ollama-cloud - models.dev integration for accurate context lengths - URL-to-provider mapping (ollama.com -> ollama-cloud) - Passthrough model normalization (preserves Ollama model:tag format) - Default auxiliary model (nemotron-3-nano:30b) - HermesOverlay in providers.py - CLI --provider choices, CANONICAL_PROVIDERS entry - Dynamic model discovery with disk caching (1hr TTL) - 37 provider-specific tests Cherry-picked from PR #6038 by kshitijk4poor. Closes #3926
2026-04-15 22:32:05 -07:00
# ---------------------------------------------------------------------------
# Ollama Cloud — merged model discovery with disk cache
# ---------------------------------------------------------------------------
_OLLAMA_CLOUD_CACHE_TTL = 3600 # 1 hour
def _ollama_cloud_cache_path() -> Path:
"""Return the path for the Ollama Cloud model cache."""
from hermes_constants import get_hermes_home
return get_hermes_home() / "ollama_cloud_models_cache.json"
def _load_ollama_cloud_cache(*, ignore_ttl: bool = False) -> Optional[dict]:
"""Load cached Ollama Cloud models from disk.
Args:
ignore_ttl: If True, return data even if the TTL has expired (stale fallback).
"""
try:
cache_path = _ollama_cloud_cache_path()
if not cache_path.exists():
return None
with open(cache_path, encoding="utf-8") as f:
data = json.load(f)
if not isinstance(data, dict):
return None
models = data.get("models")
if not (isinstance(models, list) and models):
return None
if not ignore_ttl:
cached_at = data.get("cached_at", 0)
if (time.time() - cached_at) > _OLLAMA_CLOUD_CACHE_TTL:
return None # stale
return data
except Exception:
pass
return None
def _save_ollama_cloud_cache(models: list[str]) -> None:
"""Persist the merged Ollama Cloud model list to disk."""
try:
from utils import atomic_json_write
cache_path = _ollama_cloud_cache_path()
cache_path.parent.mkdir(parents=True, exist_ok=True)
atomic_json_write(cache_path, {"models": models, "cached_at": time.time()}, indent=None)
except Exception:
pass
def fetch_ollama_cloud_models(
api_key: Optional[str] = None,
base_url: Optional[str] = None,
*,
force_refresh: bool = False,
) -> list[str]:
"""Fetch Ollama Cloud models by merging live API + models.dev, with disk cache.
Resolution order:
1. Disk cache (if fresh, < 1 hour, and not force_refresh)
2. Live ``/v1/models`` endpoint (primary — freshest source)
3. models.dev registry (secondary — fills gaps for unlisted models)
4. Merge: live models first, then models.dev additions (deduped)
Returns a list of model IDs (never None — empty list on total failure).
"""
# 1. Check disk cache
if not force_refresh:
cached = _load_ollama_cloud_cache()
if cached is not None:
return cached["models"]
# 2. Live API probe
if not api_key:
api_key = os.getenv("OLLAMA_API_KEY", "")
if not base_url:
base_url = os.getenv("OLLAMA_BASE_URL", "") or "https://ollama.com/v1"
live_models: list[str] = []
if api_key:
result = fetch_api_models(api_key, base_url, timeout=8.0)
if result:
live_models = result
# 3. models.dev registry
mdev_models: list[str] = []
try:
from agent.models_dev import list_agentic_models
mdev_models = list_agentic_models("ollama-cloud")
except Exception:
pass
# 4. Merge: live first, then models.dev additions (deduped, order-preserving)
if live_models or mdev_models:
seen: set[str] = set()
merged: list[str] = []
for m in live_models:
if m and m not in seen:
seen.add(m)
merged.append(m)
for m in mdev_models:
if m and m not in seen:
seen.add(m)
merged.append(m)
if merged:
_save_ollama_cloud_cache(merged)
return merged
# Total failure — return stale cache if available (ignore TTL)
stale = _load_ollama_cloud_cache(ignore_ttl=True)
if stale is not None:
return stale["models"]
return []
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
def validate_requested_model(
model_name: str,
provider: Optional[str],
*,
feat: validate /model against live API instead of hardcoded lists 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.
2026-03-08 05:22:15 -07:00
api_key: Optional[str] = None,
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
base_url: Optional[str] = None,
) -> dict[str, Any]:
"""
feat: validate /model against live API instead of hardcoded lists 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.
2026-03-08 05:22:15 -07:00
Validate a ``/model`` value for the active provider.
Performs format checks first, then probes the live API to confirm
the model actually exists.
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
Returns a dict with:
- accepted: whether the CLI should switch to the requested model now
- persist: whether it is safe to save to config
- recognized: whether it matched a known provider catalog
- message: optional warning / guidance for the user
"""
requested = (model_name or "").strip()
normalized = normalize_provider(provider)
if normalized == "openrouter" and base_url and "openrouter.ai" not in base_url:
normalized = "custom"
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
requested_for_lookup = requested
if normalized == "copilot":
requested_for_lookup = normalize_copilot_model_id(
requested,
api_key=api_key,
) or requested
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
if not requested:
return {
"accepted": False,
"persist": False,
"recognized": False,
"message": "Model name cannot be empty.",
}
if any(ch.isspace() for ch in requested):
return {
"accepted": False,
"persist": False,
"recognized": False,
"message": "Model names cannot contain spaces.",
}
fix: custom endpoint model validation + better /model error messages - 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.
2026-03-11 23:29:26 -07:00
if normalized == "custom":
fix(custom-endpoint): verify /models and suggest working /v1 base URL (#1480)
2026-03-15 20:09:50 -07:00
probe = probe_api_models(api_key, base_url)
api_models = probe.get("models")
if api_models is not None:
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
if requested_for_lookup in set(api_models):
fix(custom-endpoint): verify /models and suggest working /v1 base URL (#1480)
2026-03-15 20:09:50 -07:00
return {
"accepted": True,
"persist": True,
"recognized": True,
"message": None,
}
fix: auto-correct close model name matches in /model validation (#9424) * 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>
2026-04-13 23:09:39 -07:00
# Auto-correct if the top match is very similar (e.g. typo)
auto = get_close_matches(requested_for_lookup, api_models, n=1, cutoff=0.9)
if auto:
return {
"accepted": True,
"persist": True,
"recognized": True,
"corrected_model": auto[0],
"message": f"Auto-corrected `{requested}` → `{auto[0]}`",
}
fix(custom-endpoint): verify /models and suggest working /v1 base URL (#1480)
2026-03-15 20:09:50 -07:00
suggestions = get_close_matches(requested, api_models, n=3, cutoff=0.5)
suggestion_text = ""
if suggestions:
suggestion_text = "\n Similar models: " + ", ".join(f"`{s}`" for s in suggestions)
message = (
f"Note: `{requested}` was not found in this custom endpoint's model listing "
f"({probe.get('probed_url')}). It may still work if the server supports hidden or aliased models."
f"{suggestion_text}"
)
if probe.get("used_fallback"):
message += (
f"\n Endpoint verification succeeded after trying `{probe.get('resolved_base_url')}`. "
f"Consider saving that as your base URL."
)
return {
fix(ui-tui): harden TUI error handling, model validation, command UX parity, and gateway lifecycle
2026-04-13 18:29:24 -05:00
"accepted": False,
"persist": False,
fix(custom-endpoint): verify /models and suggest working /v1 base URL (#1480)
2026-03-15 20:09:50 -07:00
"recognized": False,
"message": message,
}
message = (
f"Note: could not reach this custom endpoint's model listing at `{probe.get('probed_url')}`. "
f"Hermes will still save `{requested}`, but the endpoint should expose `/models` for verification."
)
if probe.get("suggested_base_url"):
message += f"\n If this server expects `/v1`, try base URL: `{probe.get('suggested_base_url')}`"
fix: custom endpoint model validation + better /model error messages - 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.
2026-03-11 23:29:26 -07:00
return {
fix(ui-tui): harden TUI error handling, model validation, command UX parity, and gateway lifecycle
2026-04-13 18:29:24 -05:00
"accepted": False,
"persist": False,
fix: custom endpoint model validation + better /model error messages - 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.
2026-03-11 23:29:26 -07:00
"recognized": False,
fix(custom-endpoint): verify /models and suggest working /v1 base URL (#1480)
2026-03-15 20:09:50 -07:00
"message": message,
fix: custom endpoint model validation + better /model error messages - 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.
2026-03-11 23:29:26 -07:00
}
feat(cli): add native /model picker modal for provider → model selection 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.
2026-04-11 16:59:41 -07:00
# OpenAI Codex has its own catalog path; /v1/models probing is not the right validation path.
if normalized == "openai-codex":
try:
codex_models = provider_model_ids("openai-codex")
except Exception:
codex_models = []
if codex_models:
if requested_for_lookup in set(codex_models):
return {
"accepted": True,
"persist": True,
"recognized": True,
"message": None,
}
fix: auto-correct close model name matches in /model validation (#9424) * 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>
2026-04-13 23:09:39 -07:00
# Auto-correct if the top match is very similar (e.g. typo)
auto = get_close_matches(requested_for_lookup, codex_models, n=1, cutoff=0.9)
if auto:
return {
"accepted": True,
"persist": True,
"recognized": True,
"corrected_model": auto[0],
"message": f"Auto-corrected `{requested}` → `{auto[0]}`",
}
feat(cli): add native /model picker modal for provider → model selection 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.
2026-04-11 16:59:41 -07:00
suggestions = get_close_matches(requested_for_lookup, codex_models, n=3, cutoff=0.5)
suggestion_text = ""
if suggestions:
suggestion_text = "\n Similar models: " + ", ".join(f"`{s}`" for s in suggestions)
return {
fix: fake models
2026-04-13 14:57:42 -05:00
"accepted": False,
"persist": False,
feat(cli): add native /model picker modal for provider → model selection 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.
2026-04-11 16:59:41 -07:00
"recognized": False,
"message": (
fix: fake models
2026-04-13 14:57:42 -05:00
f"Model `{requested}` was not found in the OpenAI Codex model listing."
feat(cli): add native /model picker modal for provider → model selection 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.
2026-04-11 16:59:41 -07:00
f"{suggestion_text}"
),
}
fix(models): validate MiniMax models against static catalog (#12611, #12460, #12399, #12547)
2026-04-20 02:03:31 +00:00
# MiniMax providers don't expose a /models endpoint — validate against
# the static catalog instead, similar to openai-codex.
if normalized in ("minimax", "minimax-cn"):
try:
catalog_models = provider_model_ids(normalized)
except Exception:
catalog_models = []
if catalog_models:
# Case-insensitive lookup (catalog uses mixed case like MiniMax-M2.7)
catalog_lower = {m.lower(): m for m in catalog_models}
if requested_for_lookup.lower() in catalog_lower:
return {
"accepted": True,
"persist": True,
"recognized": True,
"message": None,
}
# Auto-correct close matches (case-insensitive)
catalog_lower_list = list(catalog_lower.keys())
auto = get_close_matches(requested_for_lookup.lower(), catalog_lower_list, n=1, cutoff=0.9)
if auto:
corrected = catalog_lower[auto[0]]
return {
"accepted": True,
"persist": True,
"recognized": True,
"corrected_model": corrected,
"message": f"Auto-corrected `{requested}` → `{corrected}`",
}
suggestions = get_close_matches(requested_for_lookup.lower(), catalog_lower_list, n=3, cutoff=0.5)
suggestion_text = ""
if suggestions:
suggestion_text = "\n Similar models: " + ", ".join(f"`{catalog_lower[s]}`" for s in suggestions)
return {
"accepted": True,
"persist": True,
"recognized": False,
"message": (
f"Note: `{requested}` was not found in the MiniMax catalog."
f"{suggestion_text}"
"\n MiniMax does not expose a /models endpoint, so Hermes cannot verify the model name."
"\n The model may still work if it exists on the server."
),
}
feat: validate /model against live API instead of hardcoded lists 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.
2026-03-08 05:22:15 -07:00
# Probe the live API to check if the model actually exists
api_models = fetch_api_models(api_key, base_url)
if api_models is not None:
feat: integrate GitHub Copilot providers across Hermes 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>
2026-03-17 23:40:22 -07:00
if requested_for_lookup in set(api_models):
feat: validate /model against live API instead of hardcoded lists 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.
2026-03-08 05:22:15 -07:00
# API confirmed the model exists
return {
"accepted": True,
"persist": True,
"recognized": True,
"message": None,
}
else:
fix: stop rejecting unlisted models, accept with warning instead * 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'
2026-03-12 16:02:35 -07:00
# API responded but model is not listed. Accept anyway —
# the user may have access to models not shown in the public
# listing (e.g. Z.AI Pro/Max plans can use glm-5 on coding
# endpoints even though it's not in /models). Warn but allow.
fix: auto-correct close model name matches in /model validation (#9424) * 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>
2026-04-13 23:09:39 -07:00
# Auto-correct if the top match is very similar (e.g. typo)
auto = get_close_matches(requested_for_lookup, api_models, n=1, cutoff=0.9)
if auto:
return {
"accepted": True,
"persist": True,
"recognized": True,
"corrected_model": auto[0],
"message": f"Auto-corrected `{requested}` → `{auto[0]}`",
}
feat: validate /model against live API instead of hardcoded lists 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.
2026-03-08 05:22:15 -07:00
suggestions = get_close_matches(requested, api_models, n=3, cutoff=0.5)
suggestion_text = ""
if suggestions:
fix: stop rejecting unlisted models, accept with warning instead * 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'
2026-03-12 16:02:35 -07:00
suggestion_text = "\n Similar models: " + ", ".join(f"`{s}`" for s in suggestions)
feat: validate /model against live API instead of hardcoded lists 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.
2026-03-08 05:22:15 -07:00
fix: fake models
2026-04-13 14:57:42 -05:00
return {
"accepted": False,
"persist": False,
"recognized": False,
"message": (
f"Model `{requested}` was not found in this provider's model listing."
f"{suggestion_text}"
),
}
fix: validate /model values before saving
2026-03-07 19:56:48 -08:00
fix: stop rejecting unlisted models, accept with warning instead * 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'
2026-03-12 16:02:35 -07:00
# api_models is None — couldn't reach API. Accept and persist,
# but warn so typos don't silently break things.
feat: native AWS Bedrock provider via Converse API Salvaged from PR #7920 by JiaDe-Wu — cherry-picked Bedrock-specific additions onto current main, skipping stale-branch reverts (293 commits behind). Dual-path architecture: - Claude models → AnthropicBedrock SDK (prompt caching, thinking budgets) - Non-Claude models → Converse API via boto3 (Nova, DeepSeek, Llama, Mistral) Includes: - Core adapter (agent/bedrock_adapter.py, 1098 lines) - Full provider registration (auth, models, providers, config, runtime, main) - IAM credential chain + Bedrock API Key auth modes - Dynamic model discovery via ListFoundationModels + ListInferenceProfiles - Streaming with delta callbacks, error classification, guardrails - hermes doctor + hermes auth integration - /usage pricing for 7 Bedrock models - 130 automated tests (79 unit + 28 integration + follow-up fixes) - Documentation (website/docs/guides/aws-bedrock.md) - boto3 optional dependency (pip install hermes-agent[bedrock]) Co-authored-by: JiaDe WU <40445668+JiaDe-Wu@users.noreply.github.com>
2026-04-15 15:18:01 -07:00
# Bedrock: use our own discovery instead of HTTP /models endpoint.
# Bedrock's bedrock-runtime URL doesn't support /models — it uses the
# AWS SDK control plane (ListFoundationModels + ListInferenceProfiles).
if normalized == "bedrock":
try:
from agent.bedrock_adapter import discover_bedrock_models, resolve_bedrock_region
region = resolve_bedrock_region()
discovered = discover_bedrock_models(region)
discovered_ids = {m["id"] for m in discovered}
if requested in discovered_ids:
return {
"accepted": True,
"persist": True,
"recognized": True,
"message": None,
}
# Not in discovered list — still accept (user may have custom
# inference profiles or cross-account access), but warn.
suggestions = get_close_matches(requested, list(discovered_ids), n=3, cutoff=0.4)
suggestion_text = ""
if suggestions:
suggestion_text = "\n Similar models: " + ", ".join(f"`{s}`" for s in suggestions)
return {
"accepted": True,
"persist": True,
"recognized": False,
"message": (
f"Note: `{requested}` was not found in Bedrock model discovery for {region}. "
f"It may still work with custom inference profiles or cross-account access."
f"{suggestion_text}"
),
}
except Exception:
pass # Fall through to generic warning
feat: validate /model against live API instead of hardcoded lists 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.
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provider_label = _PROVIDER_LABELS.get(normalized, normalized)
fix: validate /model values before saving
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return {
fix(ui-tui): harden TUI error handling, model validation, command UX parity, and gateway lifecycle
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"accepted": False,
"persist": False,
fix: validate /model values before saving
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"recognized": False,
"message": (
fix: stop rejecting unlisted models, accept with warning instead * 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'
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f"Could not reach the {provider_label} API to validate `{requested}`. "
f"If the service isn't down, this model may not be valid."
fix: validate /model values before saving
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),
}
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