Files
hermes-agent/hermes_cli/models.py
Teknium 4a8cd6f856 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

362 lines
12 KiB
Python

"""
Canonical model catalogs and lightweight validation helpers.
Add, remove, or reorder entries here — both `hermes setup` and
`hermes` provider-selection will pick up the change automatically.
"""
from __future__ import annotations
import json
import urllib.request
import urllib.error
from difflib import get_close_matches
from typing import Any, Optional
# (model_id, display description shown in menus)
OPENROUTER_MODELS: list[tuple[str, str]] = [
("anthropic/claude-opus-4.6", "recommended"),
("anthropic/claude-sonnet-4.5", ""),
("openai/gpt-5.4-pro", ""),
("openai/gpt-5.4", ""),
("openai/gpt-5.3-codex", ""),
("google/gemini-3-pro-preview", ""),
("google/gemini-3-flash-preview", ""),
("qwen/qwen3.5-plus-02-15", ""),
("qwen/qwen3.5-35b-a3b", ""),
("stepfun/step-3.5-flash", ""),
("z-ai/glm-5", ""),
("moonshotai/kimi-k2.5", ""),
("minimax/minimax-m2.5", ""),
]
_PROVIDER_MODELS: dict[str, list[str]] = {
"nous": [
"claude-opus-4-6",
"claude-sonnet-4-6",
"gpt-5.4",
"gemini-3-flash",
"gemini-3.0-pro-preview",
"deepseek-v3.2",
],
"openai-codex": [
"gpt-5.2-codex",
"gpt-5.1-codex-mini",
"gpt-5.1-codex-max",
],
"zai": [
"glm-5",
"glm-4.7",
"glm-4.5",
"glm-4.5-flash",
],
"kimi-coding": [
"kimi-for-coding",
"kimi-k2.5",
"kimi-k2-thinking",
"kimi-k2-thinking-turbo",
"kimi-k2-turbo-preview",
"kimi-k2-0905-preview",
],
"minimax": [
"MiniMax-M2.5",
"MiniMax-M2.5-highspeed",
"MiniMax-M2.1",
],
"minimax-cn": [
"MiniMax-M2.5",
"MiniMax-M2.5-highspeed",
"MiniMax-M2.1",
],
}
_PROVIDER_LABELS = {
"openrouter": "OpenRouter",
"openai-codex": "OpenAI Codex",
"nous": "Nous Portal",
"zai": "Z.AI / GLM",
"kimi-coding": "Kimi / Moonshot",
"minimax": "MiniMax",
"minimax-cn": "MiniMax (China)",
"custom": "Custom endpoint",
}
_PROVIDER_ALIASES = {
"glm": "zai",
"z-ai": "zai",
"z.ai": "zai",
"zhipu": "zai",
"kimi": "kimi-coding",
"moonshot": "kimi-coding",
"minimax-china": "minimax-cn",
"minimax_cn": "minimax-cn",
}
def model_ids() -> list[str]:
"""Return just the OpenRouter model-id strings."""
return [mid for mid, _ in OPENROUTER_MODELS]
def menu_labels() -> list[str]:
"""Return display labels like 'anthropic/claude-opus-4.6 (recommended)'."""
labels = []
for mid, desc in OPENROUTER_MODELS:
labels.append(f"{mid} ({desc})" if desc else mid)
return labels
# 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.
"""
# Canonical providers in display order
_PROVIDER_ORDER = [
"openrouter", "nous", "openai-codex",
"zai", "kimi-coding", "minimax", "minimax-cn",
]
# Build reverse alias map
aliases_for: dict[str, list[str]] = {}
for alias, canonical in _PROVIDER_ALIASES.items():
aliases_for.setdefault(canonical, []).append(alias)
result = []
for pid in _PROVIDER_ORDER:
label = _PROVIDER_LABELS.get(pid, pid)
alias_list = aliases_for.get(pid, [])
# Check if this provider has credentials available
has_creds = False
try:
from hermes_cli.runtime_provider import resolve_runtime_provider
runtime = resolve_runtime_provider(requested=pid)
has_creds = bool(runtime.get("api_key"))
except Exception:
pass
result.append({
"id": pid,
"label": label,
"aliases": alias_list,
"authenticated": has_creds,
})
return result
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")
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``).
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()
if provider_part and model_part and provider_part in _KNOWN_PROVIDER_NAMES:
return (normalize_provider(provider_part), model_part)
return (current_provider, stripped)
def curated_models_for_provider(provider: Optional[str]) -> list[tuple[str, str]]:
"""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.
"""
normalized = normalize_provider(provider)
if normalized == "openrouter":
return list(OPENROUTER_MODELS)
# 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
models = _PROVIDER_MODELS.get(normalized, [])
return [(m, "") for m in models]
def normalize_provider(provider: Optional[str]) -> str:
"""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.
"""
normalized = (provider or "openrouter").strip().lower()
return _PROVIDER_ALIASES.get(normalized, normalized)
def provider_model_ids(provider: Optional[str]) -> list[str]:
"""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.
"""
normalized = normalize_provider(provider)
if normalized == "openrouter":
return model_ids()
if normalized == "openai-codex":
from hermes_cli.codex_models import get_codex_model_ids
return get_codex_model_ids()
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:
live = fetch_nous_models(creds.get("api_key", ""), creds.get("base_url", ""))
if live:
return live
except Exception:
pass
return list(_PROVIDER_MODELS.get(normalized, []))
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.).
"""
if not base_url:
return None
url = base_url.rstrip("/") + "/models"
headers: dict[str, str] = {}
if api_key:
headers["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())
# Standard OpenAI format: {"data": [{"id": "model-name", ...}, ...]}
return [m.get("id", "") for m in data.get("data", [])]
except Exception:
return None
def validate_requested_model(
model_name: str,
provider: Optional[str],
*,
api_key: Optional[str] = None,
base_url: Optional[str] = None,
) -> dict[str, Any]:
"""
Validate a ``/model`` value for the active provider.
Performs format checks first, then probes the live API to confirm
the model actually exists.
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"
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.",
}
# Custom endpoints can serve any model — skip validation
if normalized == "custom":
return {
"accepted": True,
"persist": True,
"recognized": False,
"message": None,
}
# 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:
if requested in set(api_models):
# API confirmed the model exists
return {
"accepted": True,
"persist": True,
"recognized": True,
"message": None,
}
else:
# 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.
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)
return {
"accepted": True,
"persist": True,
"recognized": False,
"message": (
f"Note: `{requested}` was not found in this provider's model listing. "
f"It may still work if your plan supports it."
f"{suggestion_text}"
),
}
# api_models is None — couldn't reach API. Accept and persist,
# but warn so typos don't silently break things.
provider_label = _PROVIDER_LABELS.get(normalized, normalized)
return {
"accepted": True,
"persist": True,
"recognized": False,
"message": (
f"Could not reach the {provider_label} API to validate `{requested}`. "
f"If the service isn't down, this model may not be valid."
),
}