* 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'
362 lines
12 KiB
Python
362 lines
12 KiB
Python
"""
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Canonical model catalogs and lightweight validation helpers.
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Add, remove, or reorder entries here — both `hermes setup` and
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`hermes` provider-selection will pick up the change automatically.
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"""
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from __future__ import annotations
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import json
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import urllib.request
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import urllib.error
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from difflib import get_close_matches
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from typing import Any, Optional
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# (model_id, display description shown in menus)
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OPENROUTER_MODELS: list[tuple[str, str]] = [
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("anthropic/claude-opus-4.6", "recommended"),
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("anthropic/claude-sonnet-4.5", ""),
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("openai/gpt-5.4-pro", ""),
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("openai/gpt-5.4", ""),
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("openai/gpt-5.3-codex", ""),
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("google/gemini-3-pro-preview", ""),
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("google/gemini-3-flash-preview", ""),
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("qwen/qwen3.5-plus-02-15", ""),
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("qwen/qwen3.5-35b-a3b", ""),
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("stepfun/step-3.5-flash", ""),
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("z-ai/glm-5", ""),
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("moonshotai/kimi-k2.5", ""),
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("minimax/minimax-m2.5", ""),
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]
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_PROVIDER_MODELS: dict[str, list[str]] = {
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"nous": [
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"claude-opus-4-6",
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"claude-sonnet-4-6",
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"gpt-5.4",
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"gemini-3-flash",
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"gemini-3.0-pro-preview",
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"deepseek-v3.2",
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],
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"openai-codex": [
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"gpt-5.2-codex",
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"gpt-5.1-codex-mini",
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"gpt-5.1-codex-max",
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],
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"zai": [
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"glm-5",
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"glm-4.7",
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"glm-4.5",
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"glm-4.5-flash",
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],
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"kimi-coding": [
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"kimi-for-coding",
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"kimi-k2.5",
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"kimi-k2-thinking",
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"kimi-k2-thinking-turbo",
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"kimi-k2-turbo-preview",
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"kimi-k2-0905-preview",
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],
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"minimax": [
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"MiniMax-M2.5",
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"MiniMax-M2.5-highspeed",
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"MiniMax-M2.1",
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],
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"minimax-cn": [
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"MiniMax-M2.5",
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"MiniMax-M2.5-highspeed",
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"MiniMax-M2.1",
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],
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}
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_PROVIDER_LABELS = {
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"openrouter": "OpenRouter",
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"openai-codex": "OpenAI Codex",
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"nous": "Nous Portal",
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"zai": "Z.AI / GLM",
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"kimi-coding": "Kimi / Moonshot",
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"minimax": "MiniMax",
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"minimax-cn": "MiniMax (China)",
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"custom": "Custom endpoint",
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}
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_PROVIDER_ALIASES = {
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"glm": "zai",
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"z-ai": "zai",
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"z.ai": "zai",
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"zhipu": "zai",
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"kimi": "kimi-coding",
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"moonshot": "kimi-coding",
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"minimax-china": "minimax-cn",
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"minimax_cn": "minimax-cn",
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}
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def model_ids() -> list[str]:
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"""Return just the OpenRouter model-id strings."""
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return [mid for mid, _ in OPENROUTER_MODELS]
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def menu_labels() -> list[str]:
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"""Return display labels like 'anthropic/claude-opus-4.6 (recommended)'."""
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labels = []
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for mid, desc in OPENROUTER_MODELS:
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labels.append(f"{mid} ({desc})" if desc else mid)
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return labels
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# All provider IDs and aliases that are valid for the provider:model syntax.
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_KNOWN_PROVIDER_NAMES: set[str] = (
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set(_PROVIDER_LABELS.keys())
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| set(_PROVIDER_ALIASES.keys())
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| {"openrouter", "custom"}
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)
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def list_available_providers() -> list[dict[str, str]]:
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"""Return info about all providers the user could use with ``provider:model``.
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Each dict has ``id``, ``label``, and ``aliases``.
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Checks which providers have valid credentials configured.
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"""
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# Canonical providers in display order
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_PROVIDER_ORDER = [
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"openrouter", "nous", "openai-codex",
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"zai", "kimi-coding", "minimax", "minimax-cn",
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]
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# Build reverse alias map
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aliases_for: dict[str, list[str]] = {}
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for alias, canonical in _PROVIDER_ALIASES.items():
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aliases_for.setdefault(canonical, []).append(alias)
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result = []
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for pid in _PROVIDER_ORDER:
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label = _PROVIDER_LABELS.get(pid, pid)
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alias_list = aliases_for.get(pid, [])
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# Check if this provider has credentials available
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has_creds = False
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try:
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from hermes_cli.runtime_provider import resolve_runtime_provider
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runtime = resolve_runtime_provider(requested=pid)
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has_creds = bool(runtime.get("api_key"))
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except Exception:
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pass
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result.append({
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"id": pid,
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"label": label,
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"aliases": alias_list,
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"authenticated": has_creds,
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})
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return result
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def parse_model_input(raw: str, current_provider: str) -> tuple[str, str]:
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"""Parse ``/model`` input into ``(provider, model)``.
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Supports ``provider:model`` syntax to switch providers at runtime::
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openrouter:anthropic/claude-sonnet-4.5 → ("openrouter", "anthropic/claude-sonnet-4.5")
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nous:hermes-3 → ("nous", "hermes-3")
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anthropic/claude-sonnet-4.5 → (current_provider, "anthropic/claude-sonnet-4.5")
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gpt-5.4 → (current_provider, "gpt-5.4")
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The colon is only treated as a provider delimiter if the left side is a
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recognized provider name or alias. This avoids misinterpreting model names
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that happen to contain colons (e.g. ``anthropic/claude-3.5-sonnet:beta``).
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Returns ``(provider, model)`` where *provider* is either the explicit
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provider from the input or *current_provider* if none was specified.
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"""
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stripped = raw.strip()
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colon = stripped.find(":")
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if colon > 0:
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provider_part = stripped[:colon].strip().lower()
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model_part = stripped[colon + 1:].strip()
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if provider_part and model_part and provider_part in _KNOWN_PROVIDER_NAMES:
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return (normalize_provider(provider_part), model_part)
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return (current_provider, stripped)
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def curated_models_for_provider(provider: Optional[str]) -> list[tuple[str, str]]:
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"""Return ``(model_id, description)`` tuples for a provider's model list.
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Tries to fetch the live model list from the provider's API first,
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falling back to the static ``_PROVIDER_MODELS`` catalog if the API
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is unreachable.
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"""
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normalized = normalize_provider(provider)
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if normalized == "openrouter":
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return list(OPENROUTER_MODELS)
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# Try live API first (Codex, Nous, etc. all support /models)
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live = provider_model_ids(normalized)
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if live:
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return [(m, "") for m in live]
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# Fallback to static catalog
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models = _PROVIDER_MODELS.get(normalized, [])
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return [(m, "") for m in models]
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def normalize_provider(provider: Optional[str]) -> str:
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"""Normalize provider aliases to Hermes' canonical provider ids.
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Note: ``"auto"`` passes through unchanged — use
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``hermes_cli.auth.resolve_provider()`` to resolve it to a concrete
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provider based on credentials and environment.
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"""
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normalized = (provider or "openrouter").strip().lower()
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return _PROVIDER_ALIASES.get(normalized, normalized)
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def provider_model_ids(provider: Optional[str]) -> list[str]:
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"""Return the best known model catalog for a provider.
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Tries live API endpoints for providers that support them (Codex, Nous),
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falling back to static lists.
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"""
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normalized = normalize_provider(provider)
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if normalized == "openrouter":
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return model_ids()
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if normalized == "openai-codex":
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from hermes_cli.codex_models import get_codex_model_ids
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return get_codex_model_ids()
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if normalized == "nous":
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# Try live Nous Portal /models endpoint
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try:
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from hermes_cli.auth import fetch_nous_models, resolve_nous_runtime_credentials
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creds = resolve_nous_runtime_credentials()
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if creds:
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live = fetch_nous_models(creds.get("api_key", ""), creds.get("base_url", ""))
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if live:
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return live
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except Exception:
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pass
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return list(_PROVIDER_MODELS.get(normalized, []))
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def fetch_api_models(
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api_key: Optional[str],
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base_url: Optional[str],
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timeout: float = 5.0,
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) -> Optional[list[str]]:
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"""Fetch the list of available model IDs from the provider's ``/models`` endpoint.
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Returns a list of model ID strings, or ``None`` if the endpoint could not
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be reached (network error, timeout, auth failure, etc.).
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"""
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if not base_url:
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return None
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url = base_url.rstrip("/") + "/models"
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headers: dict[str, str] = {}
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if api_key:
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headers["Authorization"] = f"Bearer {api_key}"
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req = urllib.request.Request(url, headers=headers)
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try:
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with urllib.request.urlopen(req, timeout=timeout) as resp:
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data = json.loads(resp.read().decode())
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# Standard OpenAI format: {"data": [{"id": "model-name", ...}, ...]}
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return [m.get("id", "") for m in data.get("data", [])]
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except Exception:
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return None
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def validate_requested_model(
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model_name: str,
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provider: Optional[str],
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*,
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api_key: Optional[str] = None,
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base_url: Optional[str] = None,
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) -> dict[str, Any]:
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"""
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Validate a ``/model`` value for the active provider.
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Performs format checks first, then probes the live API to confirm
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the model actually exists.
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Returns a dict with:
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- accepted: whether the CLI should switch to the requested model now
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- persist: whether it is safe to save to config
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- recognized: whether it matched a known provider catalog
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- message: optional warning / guidance for the user
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"""
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requested = (model_name or "").strip()
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normalized = normalize_provider(provider)
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if normalized == "openrouter" and base_url and "openrouter.ai" not in base_url:
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normalized = "custom"
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if not requested:
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return {
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"accepted": False,
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"persist": False,
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"recognized": False,
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"message": "Model name cannot be empty.",
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}
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if any(ch.isspace() for ch in requested):
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return {
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"accepted": False,
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"persist": False,
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"recognized": False,
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"message": "Model names cannot contain spaces.",
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}
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# Custom endpoints can serve any model — skip validation
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if normalized == "custom":
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return {
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"accepted": True,
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"persist": True,
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"recognized": False,
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"message": None,
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}
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# Probe the live API to check if the model actually exists
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api_models = fetch_api_models(api_key, base_url)
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if api_models is not None:
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if requested in set(api_models):
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# API confirmed the model exists
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return {
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"accepted": True,
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"persist": True,
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"recognized": True,
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"message": None,
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}
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else:
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# API responded but model is not listed. Accept anyway —
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# the user may have access to models not shown in the public
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# listing (e.g. Z.AI Pro/Max plans can use glm-5 on coding
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# endpoints even though it's not in /models). Warn but allow.
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suggestions = get_close_matches(requested, api_models, n=3, cutoff=0.5)
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suggestion_text = ""
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if suggestions:
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suggestion_text = "\n Similar models: " + ", ".join(f"`{s}`" for s in suggestions)
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return {
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"accepted": True,
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"persist": True,
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"recognized": False,
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"message": (
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f"Note: `{requested}` was not found in this provider's model listing. "
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f"It may still work if your plan supports it."
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f"{suggestion_text}"
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),
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}
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# api_models is None — couldn't reach API. Accept and persist,
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# but warn so typos don't silently break things.
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provider_label = _PROVIDER_LABELS.get(normalized, normalized)
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return {
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"accepted": True,
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"persist": True,
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"recognized": False,
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"message": (
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f"Could not reach the {provider_label} API to validate `{requested}`. "
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f"If the service isn't down, this model may not be valid."
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),
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}
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