feat: add native Anthropic auxiliary vision

agent/anthropic_adapter.py

@@ -391,6 +391,68 @@ def _sanitize_tool_id(tool_id: str) -> str:
     return sanitized or "tool_0"
 
 
+def _convert_openai_image_part_to_anthropic(part: Dict[str, Any]) -> Optional[Dict[str, Any]]:
+    """Convert an OpenAI-style image block to Anthropic's image source format."""
+    image_data = part.get("image_url", {})
+    url = image_data.get("url", "") if isinstance(image_data, dict) else str(image_data)
+    if not isinstance(url, str) or not url.strip():
+        return None
+    url = url.strip()
+
+    if url.startswith("data:"):
+        header, sep, data = url.partition(",")
+        if sep and ";base64" in header:
+            media_type = header[5:].split(";", 1)[0] or "image/png"
+            return {
+                "type": "image",
+                "source": {
+                    "type": "base64",
+                    "media_type": media_type,
+                    "data": data,
+                },
+            }
+
+    if url.startswith("http://") or url.startswith("https://"):
+        return {
+            "type": "image",
+            "source": {
+                "type": "url",
+                "url": url,
+            },
+        }
+
+    return None
+
+
+def _convert_user_content_part_to_anthropic(part: Any) -> Optional[Dict[str, Any]]:
+    if isinstance(part, dict):
+        ptype = part.get("type")
+        if ptype == "text":
+            block = {"type": "text", "text": part.get("text", "")}
+            if isinstance(part.get("cache_control"), dict):
+                block["cache_control"] = dict(part["cache_control"])
+            return block
+        if ptype == "image_url":
+            return _convert_openai_image_part_to_anthropic(part)
+        if ptype == "image" and part.get("source"):
+            return dict(part)
+        if ptype == "image" and part.get("data"):
+            media_type = part.get("mimeType") or part.get("media_type") or "image/png"
+            return {
+                "type": "image",
+                "source": {
+                    "type": "base64",
+                    "media_type": media_type,
+                    "data": part.get("data", ""),
+                },
+            }
+        if ptype == "tool_result":
+            return dict(part)
+    elif part is not None:
+        return {"type": "text", "text": str(part)}
+    return None
+
+
 def convert_tools_to_anthropic(tools: List[Dict]) -> List[Dict]:
     """Convert OpenAI tool definitions to Anthropic format."""
     if not tools:
@@ -495,7 +557,15 @@ def convert_messages_to_anthropic(
             continue
 
         # Regular user message
-        result.append({"role": "user", "content": content})
+        if isinstance(content, list):
+            converted_blocks = []
+            for part in content:
+                converted = _convert_user_content_part_to_anthropic(part)
+                if converted is not None:
+                    converted_blocks.append(converted)
+            result.append({"role": "user", "content": converted_blocks or [{"type": "text", "text": ""}]})
+        else:
+            result.append({"role": "user", "content": content})
 
     # Strip orphaned tool_use blocks (no matching tool_result follows)
     tool_result_ids = set()

agent/auxiliary_client.py

@@ -1,4 +1,4 @@
-"""Shared auxiliary OpenAI client for cheap/fast side tasks.
+"""Shared auxiliary client router for side tasks.
 
 Provides a single resolution chain so every consumer (context compression,
 session search, web extraction, vision analysis, browser vision) picks up
@@ -10,21 +10,21 @@ Resolution order for text tasks (auto mode):
   3. Custom endpoint (OPENAI_BASE_URL + OPENAI_API_KEY)
   4. Codex OAuth (Responses API via chatgpt.com with gpt-5.3-codex,
      wrapped to look like a chat.completions client)
-  5. Direct API-key providers (z.ai/GLM, Kimi/Moonshot, MiniMax, MiniMax-CN)
-     — checked via PROVIDER_REGISTRY entries with auth_type='api_key'
-  6. None
+  5. Native Anthropic
+  6. Direct API-key providers (z.ai/GLM, Kimi/Moonshot, MiniMax, MiniMax-CN)
+  7. None
 
 Resolution order for vision/multimodal tasks (auto mode):
-  1. OpenRouter
-  2. Nous Portal
-  3. Codex OAuth (gpt-5.3-codex supports vision via Responses API)
-  4. Custom endpoint (for local vision models: Qwen-VL, LLaVA, Pixtral, etc.)
-  5. None  (API-key providers like z.ai/Kimi/MiniMax are skipped —
-     they may not support multimodal)
+  1. Selected main provider, if it is one of the supported vision backends below
+  2. OpenRouter
+  3. Nous Portal
+  4. Codex OAuth (gpt-5.3-codex supports vision via Responses API)
+  5. Native Anthropic
+  6. Custom endpoint (for local vision models: Qwen-VL, LLaVA, Pixtral, etc.)
+  7. None
 
 Per-task provider overrides (e.g. AUXILIARY_VISION_PROVIDER,
-CONTEXT_COMPRESSION_PROVIDER) can force a specific provider for each task:
-"openrouter", "nous", "codex", or "main" (= steps 3-5).
+CONTEXT_COMPRESSION_PROVIDER) can force a specific provider for each task.
 Default "auto" follows the chains above.
 
 Per-task model overrides (e.g. AUXILIARY_VISION_MODEL,
@@ -74,6 +74,7 @@ auxiliary_is_nous: bool = False
 _OPENROUTER_MODEL = "google/gemini-3-flash-preview"
 _NOUS_MODEL = "gemini-3-flash"
 _NOUS_DEFAULT_BASE_URL = "https://inference-api.nousresearch.com/v1"
+_ANTHROPIC_DEFAULT_BASE_URL = "https://api.anthropic.com"
 _AUTH_JSON_PATH = get_hermes_home() / "auth.json"
 
 # Codex fallback: uses the Responses API (the only endpoint the Codex
@@ -309,6 +310,114 @@ class AsyncCodexAuxiliaryClient:
         self.base_url = sync_wrapper.base_url
 
 
+class _AnthropicCompletionsAdapter:
+    """OpenAI-client-compatible adapter for Anthropic Messages API."""
+
+    def __init__(self, real_client: Any, model: str):
+        self._client = real_client
+        self._model = model
+
+    def create(self, **kwargs) -> Any:
+        from agent.anthropic_adapter import build_anthropic_kwargs, normalize_anthropic_response
+
+        messages = kwargs.get("messages", [])
+        model = kwargs.get("model", self._model)
+        tools = kwargs.get("tools")
+        tool_choice = kwargs.get("tool_choice")
+        max_tokens = kwargs.get("max_tokens") or kwargs.get("max_completion_tokens") or 2000
+        temperature = kwargs.get("temperature")
+
+        normalized_tool_choice = None
+        if isinstance(tool_choice, str):
+            normalized_tool_choice = tool_choice
+        elif isinstance(tool_choice, dict):
+            choice_type = str(tool_choice.get("type", "")).lower()
+            if choice_type == "function":
+                normalized_tool_choice = tool_choice.get("function", {}).get("name")
+            elif choice_type in {"auto", "required", "none"}:
+                normalized_tool_choice = choice_type
+
+        anthropic_kwargs = build_anthropic_kwargs(
+            model=model,
+            messages=messages,
+            tools=tools,
+            max_tokens=max_tokens,
+            reasoning_config=None,
+            tool_choice=normalized_tool_choice,
+        )
+        if temperature is not None:
+            anthropic_kwargs["temperature"] = temperature
+
+        response = self._client.messages.create(**anthropic_kwargs)
+        assistant_message, finish_reason = normalize_anthropic_response(response)
+
+        usage = None
+        if hasattr(response, "usage") and response.usage:
+            prompt_tokens = getattr(response.usage, "input_tokens", 0) or 0
+            completion_tokens = getattr(response.usage, "output_tokens", 0) or 0
+            total_tokens = getattr(response.usage, "total_tokens", 0) or (prompt_tokens + completion_tokens)
+            usage = SimpleNamespace(
+                prompt_tokens=prompt_tokens,
+                completion_tokens=completion_tokens,
+                total_tokens=total_tokens,
+            )
+
+        choice = SimpleNamespace(
+            index=0,
+            message=assistant_message,
+            finish_reason=finish_reason,
+        )
+        return SimpleNamespace(
+            choices=[choice],
+            model=model,
+            usage=usage,
+        )
+
+
+class _AnthropicChatShim:
+    def __init__(self, adapter: _AnthropicCompletionsAdapter):
+        self.completions = adapter
+
+
+class AnthropicAuxiliaryClient:
+    """OpenAI-client-compatible wrapper over a native Anthropic client."""
+
+    def __init__(self, real_client: Any, model: str, api_key: str, base_url: str):
+        self._real_client = real_client
+        adapter = _AnthropicCompletionsAdapter(real_client, model)
+        self.chat = _AnthropicChatShim(adapter)
+        self.api_key = api_key
+        self.base_url = base_url
+
+    def close(self):
+        close_fn = getattr(self._real_client, "close", None)
+        if callable(close_fn):
+            close_fn()
+
+
+class _AsyncAnthropicCompletionsAdapter:
+    def __init__(self, sync_adapter: _AnthropicCompletionsAdapter):
+        self._sync = sync_adapter
+
+    async def create(self, **kwargs) -> Any:
+        import asyncio
+        return await asyncio.to_thread(self._sync.create, **kwargs)
+
+
+class _AsyncAnthropicChatShim:
+    def __init__(self, adapter: _AsyncAnthropicCompletionsAdapter):
+        self.completions = adapter
+
+
+class AsyncAnthropicAuxiliaryClient:
+    def __init__(self, sync_wrapper: "AnthropicAuxiliaryClient"):
+        sync_adapter = sync_wrapper.chat.completions
+        async_adapter = _AsyncAnthropicCompletionsAdapter(sync_adapter)
+        self.chat = _AsyncAnthropicChatShim(async_adapter)
+        self.api_key = sync_wrapper.api_key
+        self.base_url = sync_wrapper.base_url
+
+
 def _read_nous_auth() -> Optional[dict]:
     """Read and validate ~/.hermes/auth.json for an active Nous provider.
 
@@ -380,6 +489,9 @@ def _resolve_api_key_provider() -> Tuple[Optional[OpenAI], Optional[str]]:
                 break
         if not api_key:
             continue
+        if provider_id == "anthropic":
+            return _try_anthropic()
+
         # Resolve base URL (with optional env-var override)
         # Kimi Code keys (sk-kimi-) need api.kimi.com/coding/v1
         env_url = ""
@@ -484,6 +596,22 @@ def _try_codex() -> Tuple[Optional[Any], Optional[str]]:
     return CodexAuxiliaryClient(real_client, _CODEX_AUX_MODEL), _CODEX_AUX_MODEL
 
 
+def _try_anthropic() -> Tuple[Optional[Any], Optional[str]]:
+    try:
+        from agent.anthropic_adapter import build_anthropic_client, resolve_anthropic_token
+    except ImportError:
+        return None, None
+
+    token = resolve_anthropic_token()
+    if not token:
+        return None, None
+
+    model = _API_KEY_PROVIDER_AUX_MODELS.get("anthropic", "claude-haiku-4-5-20251001")
+    logger.debug("Auxiliary client: Anthropic native (%s)", model)
+    real_client = build_anthropic_client(token, _ANTHROPIC_DEFAULT_BASE_URL)
+    return AnthropicAuxiliaryClient(real_client, model, token, _ANTHROPIC_DEFAULT_BASE_URL), model
+
+
 def _resolve_forced_provider(forced: str) -> Tuple[Optional[OpenAI], Optional[str]]:
     """Resolve a specific forced provider.  Returns (None, None) if creds missing."""
     if forced == "openrouter":
@@ -546,6 +674,8 @@ def _to_async_client(sync_client, model: str):
 
     if isinstance(sync_client, CodexAuxiliaryClient):
         return AsyncCodexAuxiliaryClient(sync_client), model
+    if isinstance(sync_client, AnthropicAuxiliaryClient):
+        return AsyncAnthropicAuxiliaryClient(sync_client), model
 
     async_kwargs = {
         "api_key": sync_client.api_key,
@@ -686,6 +816,14 @@ def resolve_provider_client(
         return None, None
 
     if pconfig.auth_type == "api_key":
+        if provider == "anthropic":
+            client, default_model = _try_anthropic()
+            if client is None:
+                logger.warning("resolve_provider_client: anthropic requested but no Anthropic credentials found")
+                return None, None
+            final_model = model or default_model
+            return (_to_async_client(client, final_model) if async_mode else (client, final_model))
+
         # Find the first configured API key
         api_key = ""
         for env_var in pconfig.api_key_env_vars:
@@ -772,6 +910,7 @@ _VISION_AUTO_PROVIDER_ORDER = (
     "openrouter",
     "nous",
     "openai-codex",
+    "anthropic",
     "custom",
 )
 
@@ -793,6 +932,8 @@ def _resolve_strict_vision_backend(provider: str) -> Tuple[Optional[Any], Option
         return _try_nous()
     if provider == "openai-codex":
         return _try_codex()
+    if provider == "anthropic":
+        return _try_anthropic()
     if provider == "custom":
         return _try_custom_endpoint()
     return None, None
@@ -802,19 +943,36 @@ def _strict_vision_backend_available(provider: str) -> bool:
     return _resolve_strict_vision_backend(provider)[0] is not None
 
 
+def _preferred_main_vision_provider() -> Optional[str]:
+    """Return the selected main provider when it is also a supported vision backend."""
+    try:
+        from hermes_cli.config import load_config
+
+        config = load_config()
+        model_cfg = config.get("model", {})
+        if isinstance(model_cfg, dict):
+            provider = _normalize_vision_provider(model_cfg.get("provider", ""))
+            if provider in _VISION_AUTO_PROVIDER_ORDER:
+                return provider
+    except Exception:
+        pass
+    return None
+
+
 def get_available_vision_backends() -> List[str]:
     """Return the currently available vision backends in auto-selection order.
 
     This is the single source of truth for setup, tool gating, and runtime
-    auto-routing of vision tasks. Phase 1 keeps the auto list conservative:
-    OpenRouter, Nous Portal, Codex OAuth, then custom OpenAI-compatible
-    endpoints. Explicit provider overrides can still route elsewhere.
+    auto-routing of vision tasks. The selected main provider is preferred when
+    it is also a known-good vision backend; otherwise Hermes falls back through
+    the standard conservative order.
     """
-    return [
-        provider
-        for provider in _VISION_AUTO_PROVIDER_ORDER
-        if _strict_vision_backend_available(provider)
-    ]
+    ordered = list(_VISION_AUTO_PROVIDER_ORDER)
+    preferred = _preferred_main_vision_provider()
+    if preferred in ordered:
+        ordered.remove(preferred)
+        ordered.insert(0, preferred)
+    return [provider for provider in ordered if _strict_vision_backend_available(provider)]
 
 
 def resolve_vision_provider_client(

hermes_cli/setup.py

@@ -1268,11 +1268,9 @@ def setup_model_provider(config: dict):
 
     _vision_needs_setup = not bool(_vision_backends)
 
-    if selected_provider in {"openrouter", "nous", "openai-codex"}:
-        # If the user just selected one of our known-good vision backends during
-        # setup, treat vision as covered. Auth/setup failure returns earlier.
-        _vision_needs_setup = False
-    elif selected_provider == "custom" and "custom" in _vision_backends:
+    if selected_provider in _vision_backends:
+        # If the user just selected a backend Hermes can already use for
+        # vision, treat it as covered. Auth/setup failure returns earlier.
         _vision_needs_setup = False
 
     if _vision_needs_setup:

tests/agent/test_auxiliary_client.py

@@ -10,6 +10,8 @@ import pytest
 from agent.auxiliary_client import (
     get_text_auxiliary_client,
     get_vision_auxiliary_client,
+    get_available_vision_backends,
+    resolve_provider_client,
     auxiliary_max_tokens_param,
     _read_codex_access_token,
     _get_auxiliary_provider,
@@ -24,6 +26,7 @@ def _clean_env(monkeypatch):
     for key in (
         "OPENROUTER_API_KEY", "OPENAI_BASE_URL", "OPENAI_API_KEY",
         "OPENAI_MODEL", "LLM_MODEL", "NOUS_INFERENCE_BASE_URL",
+        "ANTHROPIC_API_KEY", "ANTHROPIC_TOKEN", "CLAUDE_CODE_OAUTH_TOKEN",
         # Per-task provider/model overrides
         "AUXILIARY_VISION_PROVIDER", "AUXILIARY_VISION_MODEL",
         "AUXILIARY_WEB_EXTRACT_PROVIDER", "AUXILIARY_WEB_EXTRACT_MODEL",
@@ -164,14 +167,74 @@ class TestGetTextAuxiliaryClient:
 
 
 class TestVisionClientFallback:
-    """Vision client auto mode only tries OpenRouter + Nous (multimodal-capable)."""
+    """Vision client auto mode resolves known-good multimodal backends."""
 
     def test_vision_returns_none_without_any_credentials(self):
-        with patch("agent.auxiliary_client._read_nous_auth", return_value=None):
+        with (
+            patch("agent.auxiliary_client._read_nous_auth", return_value=None),
+            patch("agent.auxiliary_client._try_anthropic", return_value=(None, None)),
+        ):
             client, model = get_vision_auxiliary_client()
         assert client is None
         assert model is None
 
+    def test_vision_auto_includes_anthropic_when_configured(self, monkeypatch):
+        monkeypatch.setenv("ANTHROPIC_API_KEY", "sk-ant-api03-key")
+        with (
+            patch("agent.auxiliary_client._read_nous_auth", return_value=None),
+            patch("agent.anthropic_adapter.build_anthropic_client", return_value=MagicMock()),
+            patch("agent.anthropic_adapter.resolve_anthropic_token", return_value="sk-ant-api03-key"),
+        ):
+            backends = get_available_vision_backends()
+
+        assert "anthropic" in backends
+
+    def test_resolve_provider_client_returns_native_anthropic_wrapper(self, monkeypatch):
+        monkeypatch.setenv("ANTHROPIC_API_KEY", "sk-ant-api03-key")
+        with (
+            patch("agent.auxiliary_client._read_nous_auth", return_value=None),
+            patch("agent.anthropic_adapter.build_anthropic_client", return_value=MagicMock()),
+            patch("agent.anthropic_adapter.resolve_anthropic_token", return_value="sk-ant-api03-key"),
+        ):
+            client, model = resolve_provider_client("anthropic")
+
+        assert client is not None
+        assert client.__class__.__name__ == "AnthropicAuxiliaryClient"
+        assert model == "claude-haiku-4-5-20251001"
+
+    def test_vision_auto_uses_anthropic_when_no_higher_priority_backend(self, monkeypatch):
+        monkeypatch.setenv("ANTHROPIC_API_KEY", "sk-ant-api03-key")
+        with (
+            patch("agent.auxiliary_client._read_nous_auth", return_value=None),
+            patch("agent.anthropic_adapter.build_anthropic_client", return_value=MagicMock()),
+            patch("agent.anthropic_adapter.resolve_anthropic_token", return_value="sk-ant-api03-key"),
+        ):
+            client, model = get_vision_auxiliary_client()
+
+        assert client is not None
+        assert client.__class__.__name__ == "AnthropicAuxiliaryClient"
+        assert model == "claude-haiku-4-5-20251001"
+
+    def test_selected_anthropic_provider_is_preferred_for_vision_auto(self, monkeypatch):
+        monkeypatch.setenv("OPENROUTER_API_KEY", "or-key")
+        monkeypatch.setenv("ANTHROPIC_API_KEY", "sk-ant-api03-key")
+
+        def fake_load_config():
+            return {"model": {"provider": "anthropic", "default": "claude-sonnet-4-6"}}
+
+        with (
+            patch("agent.auxiliary_client._read_nous_auth", return_value=None),
+            patch("agent.anthropic_adapter.build_anthropic_client", return_value=MagicMock()),
+            patch("agent.anthropic_adapter.resolve_anthropic_token", return_value="sk-ant-api03-key"),
+            patch("agent.auxiliary_client.OpenAI") as mock_openai,
+            patch("hermes_cli.config.load_config", fake_load_config),
+        ):
+            client, model = get_vision_auxiliary_client()
+
+        assert client is not None
+        assert client.__class__.__name__ == "AnthropicAuxiliaryClient"
+        assert model == "claude-haiku-4-5-20251001"
+
     def test_vision_auto_includes_codex(self, codex_auth_dir):
         """Codex supports vision (gpt-5.3-codex), so auto mode should use it."""
         with patch("agent.auxiliary_client._read_nous_auth", return_value=None), \

tests/hermes_cli/test_setup_model_provider.py

@@ -111,6 +111,7 @@ def test_setup_keep_current_config_provider_uses_provider_specific_model_menu(tm
     monkeypatch.setattr("hermes_cli.auth.get_active_provider", lambda: None)
     monkeypatch.setattr("hermes_cli.auth.detect_external_credentials", lambda: [])
     monkeypatch.setattr("hermes_cli.models.provider_model_ids", lambda provider: [])
+    monkeypatch.setattr("agent.auxiliary_client.get_available_vision_backends", lambda: [])
 
     setup_model_provider(config)
     save_config(config)
@@ -149,6 +150,7 @@ def test_setup_keep_current_anthropic_can_configure_openai_vision_default(tmp_pa
     monkeypatch.setattr("hermes_cli.auth.get_active_provider", lambda: None)
     monkeypatch.setattr("hermes_cli.auth.detect_external_credentials", lambda: [])
     monkeypatch.setattr("hermes_cli.models.provider_model_ids", lambda provider: [])
+    monkeypatch.setattr("agent.auxiliary_client.get_available_vision_backends", lambda: [])
 
     setup_model_provider(config)
     env = _read_env(tmp_path)
@@ -224,3 +226,17 @@ def test_setup_summary_marks_codex_auth_as_vision_available(tmp_path, monkeypatc
     assert "missing run 'hermes setup' to configure" not in output
     assert "Mixture of Agents" in output
     assert "missing OPENROUTER_API_KEY" in output
+
+
+def test_setup_summary_marks_anthropic_auth_as_vision_available(tmp_path, monkeypatch, capsys):
+    monkeypatch.setenv("HERMES_HOME", str(tmp_path))
+    _clear_provider_env(monkeypatch)
+    monkeypatch.setenv("ANTHROPIC_API_KEY", "sk-ant-api03-key")
+    monkeypatch.setattr("shutil.which", lambda _name: None)
+    monkeypatch.setattr("agent.auxiliary_client.get_available_vision_backends", lambda: ["anthropic"])
+
+    _print_setup_summary(load_config(), tmp_path)
+    output = capsys.readouterr().out
+
+    assert "Vision (image analysis)" in output
+    assert "missing run 'hermes setup' to configure" not in output

tests/test_anthropic_adapter.py

@@ -567,6 +567,56 @@ class TestConvertMessages:
         assert tool_block["content"] == "result"
         assert tool_block["cache_control"] == {"type": "ephemeral"}
 
+    def test_converts_data_url_image_to_anthropic_image_block(self):
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": "Describe this image"},
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": "data:image/png;base64,ZmFrZQ=="},
+                    },
+                ],
+            }
+        ]
+
+        _, result = convert_messages_to_anthropic(messages)
+        blocks = result[0]["content"]
+        assert blocks[0] == {"type": "text", "text": "Describe this image"}
+        assert blocks[1] == {
+            "type": "image",
+            "source": {
+                "type": "base64",
+                "media_type": "image/png",
+                "data": "ZmFrZQ==",
+            },
+        }
+
+    def test_converts_remote_image_url_to_anthropic_image_block(self):
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": "Describe this image"},
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": "https://example.com/cat.png"},
+                    },
+                ],
+            }
+        ]
+
+        _, result = convert_messages_to_anthropic(messages)
+        blocks = result[0]["content"]
+        assert blocks[1] == {
+            "type": "image",
+            "source": {
+                "type": "url",
+                "url": "https://example.com/cat.png",
+            },
+        }
+
     def test_empty_cached_assistant_tool_turn_converts_without_empty_text_block(self):
         messages = apply_anthropic_cache_control([
             {"role": "system", "content": "System prompt"},

tools/vision_tools.py

@@ -3,7 +3,8 @@
 Vision Tools Module
 
 This module provides vision analysis tools that work with image URLs.
-Uses Gemini 3 Flash Preview via OpenRouter API for intelligent image understanding.
+Uses the centralized auxiliary vision router, which can select OpenRouter,
+Nous, Codex, native Anthropic, or a custom OpenAI-compatible endpoint.
 
 Available tools:
 - vision_analyze_tool: Analyze images from URLs with custom prompts
@@ -409,7 +410,7 @@ if __name__ == "__main__":
     
     if not api_available:
         print("❌ No auxiliary vision model available")
-        print("Set OPENROUTER_API_KEY or configure Nous Portal to enable vision tools.")
+        print("Configure a supported multimodal backend (OpenRouter, Nous, Codex, Anthropic, or a custom OpenAI-compatible endpoint).")
         exit(1)
     else:
         print("✅ Vision model available")