fix: mini docstring stuff

.env-template

@@ -35,8 +35,5 @@ MICROSOFT_TENANT_ID=your-azure-ad-tenant-id
 #Alternatively, use "https://login.microsoftonline.com/common" for multi-tenant app.
 MICROSOFT_AUTHORITY=https://{tenantId}.ciamlogin.com/{tenantId}
 
-# User-data Postgres DB (Phase 0 of the MongoDB→Postgres migration).
-# Standard Postgres URI — `postgres://` and `postgresql://` both work.
-# Leave unset while the migration is still being rolled out; the app will
-# fall back to MongoDB for user data until POSTGRES_URI is configured.
+
 # POSTGRES_URI=postgresql://docsgpt:docsgpt@localhost:5432/docsgpt

application/core/model_configs.py

@@ -1,266 +0,0 @@
-"""
-Model configurations for all supported LLM providers.
-"""
-
-from application.core.model_settings import (
-    AvailableModel,
-    ModelCapabilities,
-    ModelProvider,
-)
-
-# Base image attachment types supported by most vision-capable LLMs
-IMAGE_ATTACHMENTS = [
-    "image/png",
-    "image/jpeg",
-    "image/jpg",
-    "image/webp",
-    "image/gif",
-]
-
-# PDF excluded: most OpenAI-compatible endpoints don't support native PDF uploads.
-# When excluded, PDFs are synthetically processed by converting pages to images.
-OPENAI_ATTACHMENTS = IMAGE_ATTACHMENTS
-
-GOOGLE_ATTACHMENTS = ["application/pdf"] + IMAGE_ATTACHMENTS
-
-ANTHROPIC_ATTACHMENTS = IMAGE_ATTACHMENTS
-
-OPENROUTER_ATTACHMENTS = IMAGE_ATTACHMENTS
-
-NOVITA_ATTACHMENTS = IMAGE_ATTACHMENTS
-
-
-OPENAI_MODELS = [
-    AvailableModel(
-        id="gpt-5.1",
-        provider=ModelProvider.OPENAI,
-        display_name="GPT-5.1",
-        description="Flagship model with enhanced reasoning, coding, and agentic capabilities",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            supports_structured_output=True,
-            supported_attachment_types=OPENAI_ATTACHMENTS,
-            context_window=200000,
-        ),
-    ),
-    AvailableModel(
-        id="gpt-5-mini",
-        provider=ModelProvider.OPENAI,
-        display_name="GPT-5 Mini",
-        description="Faster, cost-effective variant of GPT-5.1",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            supports_structured_output=True,
-            supported_attachment_types=OPENAI_ATTACHMENTS,
-            context_window=200000,
-        ),
-    )
-]
-
-
-ANTHROPIC_MODELS = [
-    AvailableModel(
-        id="claude-3-5-sonnet-20241022",
-        provider=ModelProvider.ANTHROPIC,
-        display_name="Claude 3.5 Sonnet (Latest)",
-        description="Latest Claude 3.5 Sonnet with enhanced capabilities",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            supported_attachment_types=ANTHROPIC_ATTACHMENTS,
-            context_window=200000,
-        ),
-    ),
-    AvailableModel(
-        id="claude-3-5-sonnet",
-        provider=ModelProvider.ANTHROPIC,
-        display_name="Claude 3.5 Sonnet",
-        description="Balanced performance and capability",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            supported_attachment_types=ANTHROPIC_ATTACHMENTS,
-            context_window=200000,
-        ),
-    ),
-    AvailableModel(
-        id="claude-3-opus",
-        provider=ModelProvider.ANTHROPIC,
-        display_name="Claude 3 Opus",
-        description="Most capable Claude model",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            supported_attachment_types=ANTHROPIC_ATTACHMENTS,
-            context_window=200000,
-        ),
-    ),
-    AvailableModel(
-        id="claude-3-haiku",
-        provider=ModelProvider.ANTHROPIC,
-        display_name="Claude 3 Haiku",
-        description="Fastest Claude model",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            supported_attachment_types=ANTHROPIC_ATTACHMENTS,
-            context_window=200000,
-        ),
-    ),
-]
-
-
-GOOGLE_MODELS = [
-    AvailableModel(
-        id="gemini-flash-latest",
-        provider=ModelProvider.GOOGLE,
-        display_name="Gemini Flash (Latest)",
-        description="Latest experimental Gemini model",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            supports_structured_output=True,
-            supported_attachment_types=GOOGLE_ATTACHMENTS,
-            context_window=int(1e6),
-        ),
-    ),
-    AvailableModel(
-        id="gemini-flash-lite-latest",
-        provider=ModelProvider.GOOGLE,
-        display_name="Gemini Flash Lite (Latest)",
-        description="Fast with huge context window",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            supports_structured_output=True,
-            supported_attachment_types=GOOGLE_ATTACHMENTS,
-            context_window=int(1e6),
-        ),
-    ),
-    AvailableModel(
-        id="gemini-3-pro-preview",
-        provider=ModelProvider.GOOGLE,
-        display_name="Gemini 3 Pro",
-        description="Most capable Gemini model",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            supports_structured_output=True,
-            supported_attachment_types=GOOGLE_ATTACHMENTS,
-            context_window=2000000,
-        ),
-    ),
-]
-
-
-GROQ_MODELS = [
-    AvailableModel(
-        id="llama-3.3-70b-versatile",
-        provider=ModelProvider.GROQ,
-        display_name="Llama 3.3 70B",
-        description="Latest Llama model with high-speed inference",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            context_window=128000,
-        ),
-    ),
-    AvailableModel(
-        id="openai/gpt-oss-120b",
-        provider=ModelProvider.GROQ,
-        display_name="GPT-OSS 120B",
-        description="Open-source GPT model optimized for speed",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            context_window=128000,
-        ),
-    ),
-]
-
-
-OPENROUTER_MODELS = [
-    AvailableModel(
-        id="qwen/qwen3-coder:free",
-        provider=ModelProvider.OPENROUTER,
-        display_name="Qwen 3 Coder",
-        description="Latest Qwen model with high-speed inference",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            context_window=128000,
-            supported_attachment_types=OPENROUTER_ATTACHMENTS
-        ),
-    ),
-    AvailableModel(
-        id="google/gemma-3-27b-it:free",
-        provider=ModelProvider.OPENROUTER,
-        display_name="Gemma 3 27B",
-        description="Latest Gemma model with high-speed inference",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            context_window=128000,
-            supported_attachment_types=OPENROUTER_ATTACHMENTS
-        ),
-    ),
-]
-
-NOVITA_MODELS = [
-    AvailableModel(
-        id="moonshotai/kimi-k2.5",
-        provider=ModelProvider.NOVITA,
-        display_name="Kimi K2.5",
-        description="MoE model with function calling, structured output, reasoning, and vision",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            supports_structured_output=True,
-            supported_attachment_types=NOVITA_ATTACHMENTS,
-            context_window=262144,
-        ),
-    ),
-    AvailableModel(
-        id="zai-org/glm-5",
-        provider=ModelProvider.NOVITA,
-        display_name="GLM-5",
-        description="MoE model with function calling, structured output, and reasoning",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            supports_structured_output=True,
-            supported_attachment_types=[],
-            context_window=202800,
-        ),
-    ),
-    AvailableModel(
-        id="minimax/minimax-m2.5",
-        provider=ModelProvider.NOVITA,
-        display_name="MiniMax M2.5",
-        description="MoE model with function calling, structured output, and reasoning",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            supports_structured_output=True,
-            supported_attachment_types=[],
-            context_window=204800,
-        ),
-    ),
-]
-
-
-AZURE_OPENAI_MODELS = [
-    AvailableModel(
-        id="azure-gpt-4",
-        provider=ModelProvider.AZURE_OPENAI,
-        display_name="Azure OpenAI GPT-4",
-        description="Azure-hosted GPT model",
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            supports_structured_output=True,
-            supported_attachment_types=OPENAI_ATTACHMENTS,
-            context_window=8192,
-        ),
-    ),
-]
-
-
-def create_custom_openai_model(model_name: str, base_url: str) -> AvailableModel:
-    """Create a custom OpenAI-compatible model (e.g., LM Studio, Ollama)."""
-    return AvailableModel(
-        id=model_name,
-        provider=ModelProvider.OPENAI,
-        display_name=model_name,
-        description=f"Custom OpenAI-compatible model at {base_url}",
-        base_url=base_url,
-        capabilities=ModelCapabilities(
-            supports_tools=True,
-            supported_attachment_types=OPENAI_ATTACHMENTS,
-        ),
-    )

application/core/model_registry.py

@@ -0,0 +1,164 @@
+"""Layered model registry.
+
+Loads model catalogs from YAML files (built-in + operator-supplied),
+groups them by provider name, then for each registered provider plugin
+calls ``get_models`` to produce the final per-provider model list.
+
+The ``user_id`` parameter on lookup methods is reserved for the future
+end-user BYOM (per-user model records in Postgres). It is currently
+ignored — defaulted to ``None`` everywhere — so call sites can be
+threaded through without a wide refactor when BYOM lands.
+"""
+
+from __future__ import annotations
+
+import logging
+from collections import defaultdict
+from typing import Dict, List, Optional
+
+from application.core.model_settings import AvailableModel
+from application.core.model_yaml import (
+    BUILTIN_MODELS_DIR,
+    ProviderCatalog,
+    load_model_yamls,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class ModelRegistry:
+    """Singleton registry of available models."""
+
+    _instance: Optional["ModelRegistry"] = None
+    _initialized: bool = False
+
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super().__new__(cls)
+        return cls._instance
+
+    def __init__(self):
+        if not ModelRegistry._initialized:
+            self.models: Dict[str, AvailableModel] = {}
+            self.default_model_id: Optional[str] = None
+            self._load_models()
+            ModelRegistry._initialized = True
+
+    @classmethod
+    def get_instance(cls) -> "ModelRegistry":
+        return cls()
+
+    @classmethod
+    def reset(cls) -> None:
+        """Clear the singleton. Intended for test fixtures."""
+        cls._instance = None
+        cls._initialized = False
+
+    def _load_models(self) -> None:
+        from pathlib import Path
+
+        from application.core.settings import settings
+        from application.llm.providers import ALL_PROVIDERS
+
+        directories = [BUILTIN_MODELS_DIR]
+        operator_dir = getattr(settings, "MODELS_CONFIG_DIR", None)
+        if operator_dir:
+            op_path = Path(operator_dir)
+            if not op_path.exists():
+                logger.warning(
+                    "MODELS_CONFIG_DIR=%s does not exist; no operator "
+                    "model YAMLs will be loaded.",
+                    operator_dir,
+                )
+            elif not op_path.is_dir():
+                logger.warning(
+                    "MODELS_CONFIG_DIR=%s is not a directory; no operator "
+                    "model YAMLs will be loaded.",
+                    operator_dir,
+                )
+            else:
+                directories.append(op_path)
+
+        catalogs = load_model_yamls(directories)
+
+        # Validate every catalog targets a known plugin before doing any
+        # registry work, so an unknown provider name in YAML aborts boot
+        # with a clear error.
+        plugin_names = {p.name for p in ALL_PROVIDERS}
+        for c in catalogs:
+            if c.provider not in plugin_names:
+                raise ValueError(
+                    f"{c.source_path}: YAML declares unknown provider "
+                    f"{c.provider!r}; no Provider plugin is registered "
+                    f"under that name. Known: {sorted(plugin_names)}"
+                )
+
+        catalogs_by_provider: Dict[str, List[ProviderCatalog]] = defaultdict(list)
+        for c in catalogs:
+            catalogs_by_provider[c.provider].append(c)
+
+        self.models.clear()
+        for provider in ALL_PROVIDERS:
+            if not provider.is_enabled(settings):
+                continue
+            for model in provider.get_models(
+                settings, catalogs_by_provider.get(provider.name, [])
+            ):
+                self.models[model.id] = model
+
+        self.default_model_id = self._resolve_default(settings)
+
+        logger.info(
+            "ModelRegistry loaded %d models, default: %s",
+            len(self.models),
+            self.default_model_id,
+        )
+
+    def _resolve_default(self, settings) -> Optional[str]:
+        if settings.LLM_NAME:
+            for name in self._parse_model_names(settings.LLM_NAME):
+                if name in self.models:
+                    return name
+            if settings.LLM_NAME in self.models:
+                return settings.LLM_NAME
+
+        if settings.LLM_PROVIDER and settings.API_KEY:
+            for model_id, model in self.models.items():
+                if model.provider.value == settings.LLM_PROVIDER:
+                    return model_id
+
+        if self.models:
+            return next(iter(self.models.keys()))
+        return None
+
+    @staticmethod
+    def _parse_model_names(llm_name: str) -> List[str]:
+        if not llm_name:
+            return []
+        return [name.strip() for name in llm_name.split(",") if name.strip()]
+
+    # ------------------------------------------------------------------
+    # Lookup API. ``user_id`` is reserved for the future BYOM and
+    # is ignored today — but threading it through every call site now
+    # means BYOM doesn't require a wide refactor when we build it.
+    # ------------------------------------------------------------------
+
+    def get_model(
+        self, model_id: str, user_id: Optional[str] = None
+    ) -> Optional[AvailableModel]:
+        return self.models.get(model_id)
+
+    def get_all_models(
+        self, user_id: Optional[str] = None
+    ) -> List[AvailableModel]:
+        return list(self.models.values())
+
+    def get_enabled_models(
+        self, user_id: Optional[str] = None
+    ) -> List[AvailableModel]:
+        return [m for m in self.models.values() if m.enabled]
+
+    def model_exists(
+        self, model_id: str, user_id: Optional[str] = None
+    ) -> bool:
+        return model_id in self.models

application/core/model_settings.py

@@ -5,9 +5,16 @@ from typing import Dict, List, Optional
 
 logger = logging.getLogger(__name__)
 
+# Re-exported here so existing call sites (and tests) that do
+# ``from application.core.model_settings import ModelRegistry`` keep
+# working. The implementation lives in ``application/core/model_registry.py``.
+# Imported lazily inside ``__getattr__`` to avoid an import cycle with
+# ``model_yaml`` → ``model_settings`` (this file).
+
 
 class ModelProvider(str, Enum):
     OPENAI = "openai"
+    OPENAI_COMPATIBLE = "openai_compatible"
     OPENROUTER = "openrouter"
     AZURE_OPENAI = "azure_openai"
     ANTHROPIC = "anthropic"
@@ -41,11 +48,20 @@ class AvailableModel:
     capabilities: ModelCapabilities = field(default_factory=ModelCapabilities)
     enabled: bool = True
     base_url: Optional[str] = None
+    # User-facing label distinct from the dispatch ``provider``. Used by
+    # openai_compatible YAMLs so a Mistral model shows "mistral" in the
+    # API response while still routing through the OpenAI wire format.
+    display_provider: Optional[str] = None
+    # Per-record API key. Operator YAMLs leave this None; populated for
+    # openai_compatible models (resolved from the YAML's ``api_key_env``)
+    # and reserved for the future end-user BYOM phase. Never serialized
+    # into to_dict().
+    api_key: Optional[str] = field(default=None, repr=False, compare=False)
 
     def to_dict(self) -> Dict:
         result = {
             "id": self.id,
-            "provider": self.provider.value,
+            "provider": self.display_provider or self.provider.value,
             "display_name": self.display_name,
             "description": self.description,
             "supported_attachment_types": self.capabilities.supported_attachment_types,
@@ -60,255 +76,14 @@ class AvailableModel:
         return result
 
 
-class ModelRegistry:
-    _instance = None
-    _initialized = False
+def __getattr__(name):
+    """Lazy re-export of ``ModelRegistry`` from ``model_registry.py``.
 
-    def __new__(cls):
-        if cls._instance is None:
-            cls._instance = super().__new__(cls)
-        return cls._instance
+    Done lazily to avoid an import cycle: ``model_registry`` imports
+    ``model_yaml`` which imports the dataclasses from this file.
+    """
+    if name == "ModelRegistry":
+        from application.core.model_registry import ModelRegistry as _MR
 
-    def __init__(self):
-        if not ModelRegistry._initialized:
-            self.models: Dict[str, AvailableModel] = {}
-            self.default_model_id: Optional[str] = None
-            self._load_models()
-            ModelRegistry._initialized = True
-
-    @classmethod
-    def get_instance(cls) -> "ModelRegistry":
-        return cls()
-
-    def _load_models(self):
-        from application.core.settings import settings
-
-        self.models.clear()
-
-        # Skip DocsGPT model if using custom OpenAI-compatible endpoint
-        if not settings.OPENAI_BASE_URL:
-            self._add_docsgpt_models(settings)
-        if (
-            settings.OPENAI_API_KEY
-            or (settings.LLM_PROVIDER == "openai" and settings.API_KEY)
-            or settings.OPENAI_BASE_URL
-        ):
-            self._add_openai_models(settings)
-        if settings.OPENAI_API_BASE or (
-            settings.LLM_PROVIDER == "azure_openai" and settings.API_KEY
-        ):
-            self._add_azure_openai_models(settings)
-        if settings.ANTHROPIC_API_KEY or (
-            settings.LLM_PROVIDER == "anthropic" and settings.API_KEY
-        ):
-            self._add_anthropic_models(settings)
-        if settings.GOOGLE_API_KEY or (
-            settings.LLM_PROVIDER == "google" and settings.API_KEY
-        ):
-            self._add_google_models(settings)
-        if settings.GROQ_API_KEY or (
-            settings.LLM_PROVIDER == "groq" and settings.API_KEY
-        ):
-            self._add_groq_models(settings)
-        if settings.OPEN_ROUTER_API_KEY or (
-            settings.LLM_PROVIDER == "openrouter" and settings.API_KEY
-        ):
-            self._add_openrouter_models(settings)
-        if settings.NOVITA_API_KEY or (
-            settings.LLM_PROVIDER == "novita" and settings.API_KEY
-        ):
-            self._add_novita_models(settings)
-        if settings.HUGGINGFACE_API_KEY or (
-            settings.LLM_PROVIDER == "huggingface" and settings.API_KEY
-        ):
-            self._add_huggingface_models(settings)
-        # Default model selection
-        if settings.LLM_NAME:
-            # Parse LLM_NAME (may be comma-separated)
-            model_names = self._parse_model_names(settings.LLM_NAME)
-            # First model in the list becomes default
-            for model_name in model_names:
-                if model_name in self.models:
-                    self.default_model_id = model_name
-                    break
-            # Backward compat: try exact match if no parsed model found
-            if not self.default_model_id and settings.LLM_NAME in self.models:
-                self.default_model_id = settings.LLM_NAME
-
-        if not self.default_model_id:
-            if settings.LLM_PROVIDER and settings.API_KEY:
-                for model_id, model in self.models.items():
-                    if model.provider.value == settings.LLM_PROVIDER:
-                        self.default_model_id = model_id
-                        break
-
-        if not self.default_model_id and self.models:
-            self.default_model_id = next(iter(self.models.keys()))
-        logger.info(
-            f"ModelRegistry loaded {len(self.models)} models, default: {self.default_model_id}"
-        )
-
-    def _add_openai_models(self, settings):
-        from application.core.model_configs import (
-            OPENAI_MODELS,
-            create_custom_openai_model,
-        )
-
-        # Check if using local OpenAI-compatible endpoint (Ollama, LM Studio, etc.)
-        using_local_endpoint = bool(
-            settings.OPENAI_BASE_URL and settings.OPENAI_BASE_URL.strip()
-        )
-
-        if using_local_endpoint:
-            # When OPENAI_BASE_URL is set, ONLY register custom models from LLM_NAME
-            # Do NOT add standard OpenAI models (gpt-5.1, etc.)
-            if settings.LLM_NAME:
-                model_names = self._parse_model_names(settings.LLM_NAME)
-                for model_name in model_names:
-                    custom_model = create_custom_openai_model(
-                        model_name, settings.OPENAI_BASE_URL
-                    )
-                    self.models[model_name] = custom_model
-                    logger.info(
-                        f"Registered custom OpenAI model: {model_name} at {settings.OPENAI_BASE_URL}"
-                    )
-        else:
-            # Standard OpenAI API usage - add standard models if API key is valid
-            if settings.OPENAI_API_KEY:
-                for model in OPENAI_MODELS:
-                    self.models[model.id] = model
-
-    def _add_azure_openai_models(self, settings):
-        from application.core.model_configs import AZURE_OPENAI_MODELS
-
-        if settings.LLM_PROVIDER == "azure_openai" and settings.LLM_NAME:
-            for model in AZURE_OPENAI_MODELS:
-                if model.id == settings.LLM_NAME:
-                    self.models[model.id] = model
-                    return
-        for model in AZURE_OPENAI_MODELS:
-            self.models[model.id] = model
-
-    def _add_anthropic_models(self, settings):
-        from application.core.model_configs import ANTHROPIC_MODELS
-
-        if settings.ANTHROPIC_API_KEY:
-            for model in ANTHROPIC_MODELS:
-                self.models[model.id] = model
-            return
-        if settings.LLM_PROVIDER == "anthropic" and settings.LLM_NAME:
-            for model in ANTHROPIC_MODELS:
-                if model.id == settings.LLM_NAME:
-                    self.models[model.id] = model
-                    return
-        for model in ANTHROPIC_MODELS:
-            self.models[model.id] = model
-
-    def _add_google_models(self, settings):
-        from application.core.model_configs import GOOGLE_MODELS
-
-        if settings.GOOGLE_API_KEY:
-            for model in GOOGLE_MODELS:
-                self.models[model.id] = model
-            return
-        if settings.LLM_PROVIDER == "google" and settings.LLM_NAME:
-            for model in GOOGLE_MODELS:
-                if model.id == settings.LLM_NAME:
-                    self.models[model.id] = model
-                    return
-        for model in GOOGLE_MODELS:
-            self.models[model.id] = model
-
-    def _add_groq_models(self, settings):
-        from application.core.model_configs import GROQ_MODELS
-
-        if settings.GROQ_API_KEY:
-            for model in GROQ_MODELS:
-                self.models[model.id] = model
-            return
-        if settings.LLM_PROVIDER == "groq" and settings.LLM_NAME:
-            for model in GROQ_MODELS:
-                if model.id == settings.LLM_NAME:
-                    self.models[model.id] = model
-                    return
-        for model in GROQ_MODELS:
-            self.models[model.id] = model
-    
-    def _add_openrouter_models(self, settings):
-        from application.core.model_configs import OPENROUTER_MODELS
-
-        if settings.OPEN_ROUTER_API_KEY:
-            for model in OPENROUTER_MODELS:
-                self.models[model.id] = model
-            return
-        if settings.LLM_PROVIDER == "openrouter" and settings.LLM_NAME:
-            for model in OPENROUTER_MODELS:
-                if model.id == settings.LLM_NAME:
-                    self.models[model.id] = model
-                    return
-        for model in OPENROUTER_MODELS:
-            self.models[model.id] = model
-
-    def _add_novita_models(self, settings):
-        from application.core.model_configs import NOVITA_MODELS
-
-        if settings.NOVITA_API_KEY:
-            for model in NOVITA_MODELS:
-                self.models[model.id] = model
-            return
-        if settings.LLM_PROVIDER == "novita" and settings.LLM_NAME:
-            for model in NOVITA_MODELS:
-                if model.id == settings.LLM_NAME:
-                    self.models[model.id] = model
-                    return
-        for model in NOVITA_MODELS:
-            self.models[model.id] = model
-
-    def _add_docsgpt_models(self, settings):
-        model_id = "docsgpt-local"
-        model = AvailableModel(
-            id=model_id,
-            provider=ModelProvider.DOCSGPT,
-            display_name="DocsGPT Model",
-            description="Local model",
-            capabilities=ModelCapabilities(
-                supports_tools=False,
-                supported_attachment_types=[],
-            ),
-        )
-        self.models[model_id] = model
-
-    def _add_huggingface_models(self, settings):
-        model_id = "huggingface-local"
-        model = AvailableModel(
-            id=model_id,
-            provider=ModelProvider.HUGGINGFACE,
-            display_name="Hugging Face Model",
-            description="Local Hugging Face model",
-            capabilities=ModelCapabilities(
-                supports_tools=False,
-                supported_attachment_types=[],
-            ),
-        )
-        self.models[model_id] = model
-
-    def _parse_model_names(self, llm_name: str) -> List[str]:
-        """
-        Parse LLM_NAME which may contain comma-separated model names.
-        E.g., 'deepseek-r1:1.5b,gemma:2b' -> ['deepseek-r1:1.5b', 'gemma:2b']
-        """
-        if not llm_name:
-            return []
-        return [name.strip() for name in llm_name.split(",") if name.strip()]
-
-    def get_model(self, model_id: str) -> Optional[AvailableModel]:
-        return self.models.get(model_id)
-
-    def get_all_models(self) -> List[AvailableModel]:
-        return list(self.models.values())
-
-    def get_enabled_models(self) -> List[AvailableModel]:
-        return [m for m in self.models.values() if m.enabled]
-
-    def model_exists(self, model_id: str) -> bool:
-        return model_id in self.models
+        return _MR
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")

application/core/model_utils.py

@@ -1,28 +1,22 @@
 from typing import Any, Dict, Optional
 
-from application.core.model_settings import ModelRegistry
+from application.core.model_registry import ModelRegistry
 
 
 def get_api_key_for_provider(provider: str) -> Optional[str]:
-    """Get the appropriate API key for a provider"""
+    """Get the appropriate API key for a provider.
+
+    Delegates to the provider plugin's ``get_api_key``. Falls back to the
+    generic ``settings.API_KEY`` for unknown providers.
+    """
     from application.core.settings import settings
+    from application.llm.providers import PROVIDERS_BY_NAME
 
-    provider_key_map = {
-        "openai": settings.OPENAI_API_KEY,
-        "openrouter": settings.OPEN_ROUTER_API_KEY,
-        "novita": settings.NOVITA_API_KEY,
-        "anthropic": settings.ANTHROPIC_API_KEY,
-        "google": settings.GOOGLE_API_KEY,
-        "groq": settings.GROQ_API_KEY,
-        "huggingface": settings.HUGGINGFACE_API_KEY,
-        "azure_openai": settings.API_KEY,
-        "docsgpt": None,
-        "llama.cpp": None,
-    }
-
-    provider_key = provider_key_map.get(provider)
-    if provider_key:
-        return provider_key
+    plugin = PROVIDERS_BY_NAME.get(provider)
+    if plugin is not None:
+        key = plugin.get_api_key(settings)
+        if key:
+            return key
     return settings.API_KEY
 
 
@@ -91,3 +85,21 @@ def get_base_url_for_model(model_id: str) -> Optional[str]:
     if model:
         return model.base_url
     return None
+
+
+def get_api_key_for_model(model_id: str) -> Optional[str]:
+    """
+    Resolve the API key to use when invoking ``model_id``.
+
+    Priority:
+      1. The model record's own ``api_key`` (reserved for future end-user
+         BYOM where credentials travel with the record).
+      2. The provider plugin's settings-based key.
+    """
+    registry = ModelRegistry.get_instance()
+    model = registry.get_model(model_id)
+    if model is not None and model.api_key:
+        return model.api_key
+    if model is not None:
+        return get_api_key_for_provider(model.provider.value)
+    return None

application/core/model_yaml.py

@@ -0,0 +1,325 @@
+"""YAML loader for model catalog files under ``application/core/models/``.
+
+Each ``*.yaml`` file declares one provider's static model catalog. Files
+are validated with Pydantic at load time; any parse, schema, or alias
+error aborts startup with the offending file path in the message.
+
+For most providers, one YAML maps to one catalog. The
+``openai_compatible`` provider is special: each YAML file represents a
+distinct logical endpoint (Mistral, Together, Ollama, ...) with its own
+``api_key_env`` and ``base_url``. The loader returns a flat list so the
+registry can distinguish multiple files with the same ``provider:`` value.
+"""
+
+from __future__ import annotations
+
+import logging
+from pathlib import Path
+from typing import Dict, List, Optional, Sequence
+
+import yaml
+from pydantic import BaseModel, ConfigDict, Field, field_validator
+
+from application.core.model_settings import (
+    AvailableModel,
+    ModelCapabilities,
+    ModelProvider,
+)
+
+logger = logging.getLogger(__name__)
+
+BUILTIN_MODELS_DIR = Path(__file__).parent / "models"
+DEFAULTS_FILENAME = "_defaults.yaml"
+
+
+class _DefaultsFile(BaseModel):
+    """Schema for ``_defaults.yaml``. Currently just attachment aliases."""
+
+    model_config = ConfigDict(extra="forbid")
+
+    attachment_aliases: Dict[str, List[str]] = Field(default_factory=dict)
+
+
+class _CapabilityFields(BaseModel):
+    """Capability fields shared between provider ``defaults:`` and per-model overrides.
+
+    All fields are optional so a per-model override can selectively replace
+    a single field from the provider-level defaults.
+    """
+
+    model_config = ConfigDict(extra="forbid")
+
+    supports_tools: Optional[bool] = None
+    supports_structured_output: Optional[bool] = None
+    supports_streaming: Optional[bool] = None
+    attachments: Optional[List[str]] = None
+    context_window: Optional[int] = None
+    input_cost_per_token: Optional[float] = None
+    output_cost_per_token: Optional[float] = None
+
+
+class _ModelEntry(_CapabilityFields):
+    """Schema for one model row inside a YAML's ``models:`` list."""
+
+    id: str
+    display_name: Optional[str] = None
+    description: str = ""
+    enabled: bool = True
+    base_url: Optional[str] = None
+    aliases: List[str] = Field(default_factory=list)
+
+    @field_validator("id")
+    @classmethod
+    def _id_nonempty(cls, v: str) -> str:
+        if not v or not v.strip():
+            raise ValueError("model id must be a non-empty string")
+        return v
+
+
+class _ProviderFile(BaseModel):
+    """Schema for one ``<provider>.yaml`` catalog file."""
+
+    model_config = ConfigDict(extra="forbid")
+
+    provider: str
+    defaults: _CapabilityFields = Field(default_factory=_CapabilityFields)
+    models: List[_ModelEntry] = Field(default_factory=list)
+    # openai_compatible metadata. Optional for other providers.
+    display_provider: Optional[str] = None
+    api_key_env: Optional[str] = None
+    base_url: Optional[str] = None
+
+
+class ProviderCatalog(BaseModel):
+    """One YAML file's parsed contents, ready for the registry.
+
+    For most providers, multiple catalogs with the same ``provider`` get
+    merged later by the registry. The ``openai_compatible`` provider is
+    the exception: each catalog is treated as a distinct endpoint, with
+    its own ``api_key_env`` and ``base_url``.
+    """
+
+    provider: str
+    models: List[AvailableModel]
+    source_path: Optional[Path] = None
+    display_provider: Optional[str] = None
+    api_key_env: Optional[str] = None
+    base_url: Optional[str] = None
+
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+
+class ModelYAMLError(ValueError):
+    """Raised when a model YAML fails parsing, schema, or alias validation."""
+
+
+def _expand_attachments(
+    attachments: Sequence[str], aliases: Dict[str, List[str]], source: str
+) -> List[str]:
+    """Resolve attachment shorthands (``image``, ``pdf``) to MIME types.
+
+    Raw MIME-typed entries (containing ``/``) pass through unchanged.
+    Unknown aliases raise ``ModelYAMLError``.
+    """
+    expanded: List[str] = []
+    seen: set = set()
+    for entry in attachments:
+        if "/" in entry:
+            if entry not in seen:
+                expanded.append(entry)
+                seen.add(entry)
+            continue
+        if entry not in aliases:
+            valid = ", ".join(sorted(aliases.keys())) or "<none defined>"
+            raise ModelYAMLError(
+                f"{source}: unknown attachment alias '{entry}'. "
+                f"Valid aliases: {valid}. "
+                "(Or use a raw MIME type like 'image/png'.)"
+            )
+        for mime in aliases[entry]:
+            if mime not in seen:
+                expanded.append(mime)
+                seen.add(mime)
+    return expanded
+
+
+def _load_defaults(directory: Path) -> Dict[str, List[str]]:
+    """Load ``_defaults.yaml`` from ``directory`` if it exists."""
+    path = directory / DEFAULTS_FILENAME
+    if not path.exists():
+        return {}
+    try:
+        raw = yaml.safe_load(path.read_text(encoding="utf-8")) or {}
+    except yaml.YAMLError as e:
+        raise ModelYAMLError(f"{path}: invalid YAML: {e}") from e
+    try:
+        parsed = _DefaultsFile.model_validate(raw)
+    except Exception as e:
+        raise ModelYAMLError(f"{path}: schema error: {e}") from e
+    return parsed.attachment_aliases
+
+
+def _resolve_provider_enum(name: str, source: Path) -> ModelProvider:
+    try:
+        return ModelProvider(name)
+    except ValueError as e:
+        valid = ", ".join(p.value for p in ModelProvider)
+        raise ModelYAMLError(
+            f"{source}: unknown provider '{name}'. Valid: {valid}"
+        ) from e
+
+
+def _build_model(
+    entry: _ModelEntry,
+    defaults: _CapabilityFields,
+    provider: ModelProvider,
+    aliases: Dict[str, List[str]],
+    source: Path,
+    display_provider: Optional[str] = None,
+) -> AvailableModel:
+    """Merge defaults + per-model overrides into a final ``AvailableModel``."""
+
+    def pick(field_name: str, fallback):
+        v = getattr(entry, field_name)
+        if v is not None:
+            return v
+        d = getattr(defaults, field_name)
+        if d is not None:
+            return d
+        return fallback
+
+    raw_attachments = entry.attachments
+    if raw_attachments is None:
+        raw_attachments = defaults.attachments
+    if raw_attachments is None:
+        raw_attachments = []
+    expanded = _expand_attachments(
+        raw_attachments, aliases, f"{source} [model={entry.id}]"
+    )
+
+    caps = ModelCapabilities(
+        supports_tools=pick("supports_tools", False),
+        supports_structured_output=pick("supports_structured_output", False),
+        supports_streaming=pick("supports_streaming", True),
+        supported_attachment_types=expanded,
+        context_window=pick("context_window", 128000),
+        input_cost_per_token=pick("input_cost_per_token", None),
+        output_cost_per_token=pick("output_cost_per_token", None),
+    )
+
+    return AvailableModel(
+        id=entry.id,
+        provider=provider,
+        display_name=entry.display_name or entry.id,
+        description=entry.description,
+        capabilities=caps,
+        enabled=entry.enabled,
+        base_url=entry.base_url,
+        display_provider=display_provider,
+    )
+
+
+def _load_one_yaml(
+    path: Path, aliases: Dict[str, List[str]]
+) -> ProviderCatalog:
+    try:
+        raw = yaml.safe_load(path.read_text(encoding="utf-8")) or {}
+    except yaml.YAMLError as e:
+        raise ModelYAMLError(f"{path}: invalid YAML: {e}") from e
+    try:
+        parsed = _ProviderFile.model_validate(raw)
+    except Exception as e:
+        raise ModelYAMLError(f"{path}: schema error: {e}") from e
+
+    provider_enum = _resolve_provider_enum(parsed.provider, path)
+    models = [
+        _build_model(
+            entry,
+            parsed.defaults,
+            provider_enum,
+            aliases,
+            path,
+            display_provider=parsed.display_provider,
+        )
+        for entry in parsed.models
+    ]
+
+    return ProviderCatalog(
+        provider=parsed.provider,
+        models=models,
+        source_path=path,
+        display_provider=parsed.display_provider,
+        api_key_env=parsed.api_key_env,
+        base_url=parsed.base_url,
+    )
+
+
+_BUILTIN_ALIASES_CACHE: Optional[Dict[str, List[str]]] = None
+
+
+def builtin_attachment_aliases() -> Dict[str, List[str]]:
+    """Return the built-in attachment alias map from ``_defaults.yaml``.
+
+    Cached after first read so repeat calls are cheap.
+    """
+    global _BUILTIN_ALIASES_CACHE
+    if _BUILTIN_ALIASES_CACHE is None:
+        _BUILTIN_ALIASES_CACHE = _load_defaults(BUILTIN_MODELS_DIR)
+    return _BUILTIN_ALIASES_CACHE
+
+
+def resolve_attachment_alias(alias: str) -> List[str]:
+    """Resolve a single attachment alias (e.g. ``"image"``) to its
+    canonical MIME-type list. Raises ``ModelYAMLError`` if unknown.
+    """
+    aliases = builtin_attachment_aliases()
+    if alias not in aliases:
+        valid = ", ".join(sorted(aliases.keys())) or "<none defined>"
+        raise ModelYAMLError(
+            f"Unknown attachment alias '{alias}'. Valid: {valid}"
+        )
+    return list(aliases[alias])
+
+
+def load_model_yamls(directories: Sequence[Path]) -> List[ProviderCatalog]:
+    """Load every ``*.yaml`` file (excluding ``_defaults.yaml``) under each
+    directory in order and return a flat list of catalogs.
+
+    Caller is responsible for merging multiple catalogs that target the
+    same provider plugin. The flat-list shape lets ``openai_compatible``
+    keep each file separate (one logical endpoint per file).
+
+    When the same model ``id`` appears in more than one YAML across the
+    directory list, a warning is logged. Order in the returned list
+    preserves load order, so the registry's "later wins" merge gives the
+    later directory's definition.
+    """
+    catalogs: List[ProviderCatalog] = []
+    seen_ids: Dict[str, Path] = {}
+
+    aliases: Dict[str, List[str]] = {}
+    for d in directories:
+        if not d or not d.exists():
+            continue
+        aliases.update(_load_defaults(d))
+
+    for d in directories:
+        if not d or not d.exists():
+            continue
+        for path in sorted(d.glob("*.yaml")):
+            if path.name == DEFAULTS_FILENAME:
+                continue
+            catalog = _load_one_yaml(path, aliases)
+            catalogs.append(catalog)
+            for m in catalog.models:
+                prior = seen_ids.get(m.id)
+                if prior is not None and prior != path:
+                    logger.warning(
+                        "Model id %r redefined: %s overrides %s (later wins)",
+                        m.id,
+                        path,
+                        prior,
+                    )
+                seen_ids[m.id] = path
+
+    return catalogs

application/core/models/README.md

@@ -0,0 +1,213 @@
+# Model catalogs
+
+Each `*.yaml` file in this directory declares one provider's model
+catalog. The registry loads every YAML at boot and joins it to the
+matching provider plugin under `application/llm/providers/`.
+
+To add or edit models, you almost always only touch a YAML here — no
+Python code required.
+
+## Add a model to an existing provider
+
+Open the provider's YAML (e.g. `anthropic.yaml`) and append two lines
+under `models:`:
+
+```yaml
+models:
+  - id: claude-3-7-sonnet
+    display_name: Claude 3.7 Sonnet
+```
+
+Capabilities default to the provider's `defaults:` block. Override
+per-model only when needed:
+
+```yaml
+  - id: claude-3-7-sonnet
+    display_name: Claude 3.7 Sonnet
+    context_window: 500000
+```
+
+Restart the app. The new model appears in `/api/models`.
+
+> The model `id` is what gets stored in agent / workflow records. Once
+> users start picking the model, **don't rename it** — agent and
+> workflow rows reference it as a free-form string and silently fall
+> back to the system default if the id disappears.
+
+## Add an OpenAI-compatible provider (zero Python)
+
+Drop a YAML in this directory (or in your `MODELS_CONFIG_DIR`) that uses
+the `openai_compatible` plugin. Set the env var named in `api_key_env`
+and you're done — no Python, no settings.py edit, no LLMCreator change:
+
+```yaml
+# mistral.yaml
+provider: openai_compatible
+display_provider: mistral             # shown in /api/models response
+api_key_env: MISTRAL_API_KEY          # env var the plugin reads at boot
+base_url: https://api.mistral.ai/v1
+defaults:
+  supports_tools: true
+  context_window: 128000
+models:
+  - id: mistral-large-latest
+    display_name: Mistral Large
+  - id: mistral-small-latest
+    display_name: Mistral Small
+```
+
+`MISTRAL_API_KEY=sk-... ; restart` — Mistral models appear in
+`/api/models` with `provider: "mistral"`. They route through the OpenAI
+wire format (it's `OpenAILLM` under the hood) but with Mistral's
+endpoint and key.
+
+Multiple `openai_compatible` YAMLs coexist: each file is one logical
+endpoint with its own `api_key_env` and `base_url`. Drop in
+`together.yaml`, `fireworks.yaml`, etc. side by side. If an env var
+isn't set, that catalog is silently skipped at boot (logged at INFO) —
+no error.
+
+Working example: `examples/mistral.yaml.example`. Files inside
+`examples/` aren't loaded by the registry; the glob only picks up
+`*.yaml` at the top level.
+
+## Add a provider with its own SDK
+
+For a provider that doesn't speak OpenAI's wire format, add one Python
+file to `application/llm/providers/<name>.py`:
+
+```python
+from application.llm.providers.base import Provider
+from application.llm.my_provider import MyLLM
+
+class MyProvider(Provider):
+    name = "my_provider"
+    llm_class = MyLLM
+
+    def get_api_key(self, settings):
+        return settings.MY_PROVIDER_API_KEY
+```
+
+Register it in `application/llm/providers/__init__.py` (one line in
+`ALL_PROVIDERS`), add `MY_PROVIDER_API_KEY` to `settings.py`, and create
+`my_provider.yaml` here with the model catalog.
+
+## Schema reference
+
+```yaml
+provider: <string, required>          # matches the Provider plugin's `name`
+
+# openai_compatible only — required for that provider, ignored for others
+display_provider: <string>            # label shown in /api/models response
+api_key_env: <string>                 # name of the env var carrying the key
+base_url: <string>                    # endpoint URL
+
+defaults:                              # optional, applied to every model below
+  supports_tools: bool                 # default false
+  supports_structured_output: bool     # default false
+  supports_streaming: bool             # default true
+  attachments: [<alias-or-mime>, ...]  # default []
+  context_window: int                  # default 128000
+  input_cost_per_token: float          # default null
+  output_cost_per_token: float         # default null
+
+models:                                # required
+  - id: <string, required>             # the value persisted in agent records
+    display_name: <string>             # default: id
+    description: <string>              # default: ""
+    enabled: bool                      # default true; false hides from /api/models
+    base_url: <string>                 # optional custom endpoint for this model
+    # All `defaults:` fields above can be overridden here per-model.
+```
+
+### Attachment aliases
+
+The `attachments:` list can mix human-readable aliases with raw MIME
+types. Aliases are defined in `_defaults.yaml`:
+
+| Alias | Expands to |
+|---|---|
+| `image` | `image/png`, `image/jpeg`, `image/jpg`, `image/webp`, `image/gif` |
+| `pdf` | `application/pdf` |
+| `audio` | `audio/mpeg`, `audio/wav`, `audio/ogg` |
+
+Use raw MIME types when you need surgical control:
+
+```yaml
+attachments: [image/png, image/webp]   # only these two
+```
+
+## Operator-supplied YAMLs (`MODELS_CONFIG_DIR`)
+
+Set the `MODELS_CONFIG_DIR` env var (or `.env` entry) to a directory
+path. Every `*.yaml` in that directory is loaded **after** the built-in
+catalog under `application/core/models/`. Operators use this to:
+
+- Add new `openai_compatible` providers (Mistral, Together, Fireworks,
+  Ollama, ...) without forking the repo.
+- Extend an existing provider's catalog with extra models — append
+  models under `provider: anthropic` and they show up alongside the
+  built-ins.
+- Override a built-in model's capabilities — declare the same `id`
+  with different fields (e.g. a higher `context_window`). Later wins;
+  the override is logged as a `WARNING` so you can audit it.
+
+Things you cannot do via `MODELS_CONFIG_DIR`:
+
+- Add a brand-new non-OpenAI provider — that needs a Python plugin
+  under `application/llm/providers/` (see "Add a provider with its own
+  SDK" above). Operator YAMLs may only target a `provider:` value that
+  already has a registered plugin.
+
+### Example: Docker
+
+Mount your model YAMLs into the container and point the env var at the
+mount path:
+
+```yaml
+# docker-compose.yml
+services:
+  app:
+    image: arc53/docsgpt
+    environment:
+      MODELS_CONFIG_DIR: /etc/docsgpt/models
+      MISTRAL_API_KEY: ${MISTRAL_API_KEY}
+    volumes:
+      - ./my-models:/etc/docsgpt/models:ro
+```
+
+Then `./my-models/mistral.yaml` (the file from
+`examples/mistral.yaml.example`) gets picked up at boot.
+
+### Example: Kubernetes
+
+Mount a `ConfigMap` containing your YAMLs at a known path and set
+`MODELS_CONFIG_DIR` on the deployment. The same `examples/mistral.yaml.example`
+becomes a key in the ConfigMap.
+
+### Misconfiguration
+
+If `MODELS_CONFIG_DIR` is set but the path doesn't exist (or isn't a
+directory), the app logs a `WARNING` at boot and continues with just
+the built-in catalog. The app does *not* fail to start — operators can
+ship config drift without taking down the service — but the warning is
+loud enough to surface in any reasonable log aggregator.
+
+## Validation
+
+YAMLs are parsed with Pydantic at boot. The app fails to start with a
+clear error message if:
+
+- a top-level key is unknown
+- a model is missing `id`
+- an attachment alias isn't defined
+- the `provider:` value isn't registered as a plugin
+
+This is intentional — silent fallbacks would mean users don't notice
+their model picks broke until they hit the API.
+
+## Reserved fields (not yet implemented)
+
+- `aliases:` on a model — old IDs that resolve to this model. Reserved
+  for future renames; the schema accepts the field but it is not yet
+  acted on.

application/core/models/_defaults.yaml

@@ -0,0 +1,18 @@
+# Global defaults applied across every model YAML in this directory.
+# Keep this file sparse — per-provider `defaults:` blocks are clearer
+# than a deep global default chain. This file is for things that
+# genuinely never vary, like the meaning of "image".
+
+attachment_aliases:
+  image:
+    - image/png
+    - image/jpeg
+    - image/jpg
+    - image/webp
+    - image/gif
+  pdf:
+    - application/pdf
+  audio:
+    - audio/mpeg
+    - audio/wav
+    - audio/ogg

application/core/models/anthropic.yaml

@@ -0,0 +1,23 @@
+provider: anthropic
+defaults:
+  supports_tools: true
+  attachments: [image]
+  context_window: 200000
+
+models:
+  - id: claude-opus-4-7
+    display_name: Claude Opus 4.7
+    description: Most capable Claude model for complex reasoning and agentic coding
+    context_window: 1000000
+    supports_structured_output: true
+
+  - id: claude-sonnet-4-6
+    display_name: Claude Sonnet 4.6
+    description: Best balance of speed and intelligence with extended thinking
+    context_window: 1000000
+    supports_structured_output: true
+
+  - id: claude-haiku-4-5
+    display_name: Claude Haiku 4.5
+    description: Fastest Claude model with near-frontier intelligence
+    supports_structured_output: true

application/core/models/azure_openai.yaml

@@ -0,0 +1,31 @@
+# Azure OpenAI catalog.
+#
+# IMPORTANT: For Azure OpenAI, the `id` field is the **deployment name**, not
+# a model name. Deployment names are arbitrary strings the operator chooses
+# in Azure portal (or via ARM/Bicep/Terraform) when they create a deployment
+# for a given underlying model + version.
+#
+# The IDs below are sensible defaults that mirror the underlying OpenAI
+# model name (prefixed with `azure-`). Operators almost always need to
+# override them via `MODELS_CONFIG_DIR` to match the deployment names that
+# actually exist in their Azure resource. The `display_name`, capability
+# flags, and `context_window` reflect the underlying OpenAI model.
+provider: azure_openai
+
+defaults:
+  supports_tools: true
+  supports_structured_output: true
+  attachments: [image]
+  context_window: 400000
+
+models:
+  - id: azure-gpt-5.5
+    display_name: Azure OpenAI GPT-5.5
+    description: Azure-hosted flagship frontier model for complex reasoning, coding, and agentic work with a 1M-token context window
+    context_window: 1050000
+  - id: azure-gpt-5.4-mini
+    display_name: Azure OpenAI GPT-5.4 Mini
+    description: Azure-hosted cost-efficient GPT-5.4-class model for high-volume coding, computer use, and subagent workloads
+  - id: azure-gpt-5.4-nano
+    display_name: Azure OpenAI GPT-5.4 Nano
+    description: Azure-hosted cheapest GPT-5.4-class model, optimized for simple high-volume tasks where speed and cost matter most

application/core/models/docsgpt.yaml

@@ -0,0 +1,7 @@
+provider: docsgpt
+
+models:
+  - id: docsgpt-local
+    display_name: DocsGPT Model
+    description: Local model
+    supports_tools: false

application/core/models/examples/mistral.yaml.example

@@ -0,0 +1,31 @@
+# EXAMPLE — copy this file to ../mistral.yaml (or to your
+# MODELS_CONFIG_DIR) and set MISTRAL_API_KEY in your environment.
+#
+# This is the entire integration. No Python required: the
+# `openai_compatible` plugin reads `api_key_env` and `base_url` from
+# the file and routes calls through the OpenAI wire format.
+#
+# Files in this `examples/` directory are NOT loaded by the registry
+# (the loader globs *.yaml at the top level only).
+
+provider: openai_compatible
+display_provider: mistral             # shown in /api/models response
+api_key_env: MISTRAL_API_KEY          # env var the plugin reads
+base_url: https://api.mistral.ai/v1   # OpenAI-compatible endpoint
+
+defaults:
+  supports_tools: true
+  context_window: 128000
+
+models:
+  - id: mistral-large-latest
+    display_name: Mistral Large
+    description: Top-tier reasoning model
+
+  - id: mistral-small-latest
+    display_name: Mistral Small
+    description: Fast, cost-efficient
+
+  - id: codestral-latest
+    display_name: Codestral
+    description: Code-specialized model

application/core/models/google.yaml

@@ -0,0 +1,17 @@
+provider: google
+defaults:
+  supports_tools: true
+  supports_structured_output: true
+  attachments: [pdf, image]
+  context_window: 1048576
+
+models:
+  - id: gemini-3.1-pro-preview
+    display_name: Gemini 3.1 Pro
+    description: Most capable Gemini 3 model with advanced reasoning and agentic coding (preview)
+  - id: gemini-3-flash-preview
+    display_name: Gemini 3 Flash
+    description: Frontier-class performance for low-latency, high-volume tasks (preview)
+  - id: gemini-3.1-flash-lite-preview
+    display_name: Gemini 3.1 Flash-Lite
+    description: Cost-efficient frontier-class multimodal model for high-throughput workloads (preview)

application/core/models/groq.yaml

@@ -0,0 +1,16 @@
+provider: groq
+defaults:
+  supports_tools: true
+  context_window: 131072
+
+models:
+  - id: openai/gpt-oss-120b
+    display_name: GPT-OSS 120B
+    description: OpenAI's open-weight 120B flagship served on Groq's LPU hardware; strong general reasoning with strict structured output support
+    supports_structured_output: true
+  - id: llama-3.3-70b-versatile
+    display_name: Llama 3.3 70B Versatile
+    description: Meta's Llama 3.3 70B for general-purpose chat with parallel tool use
+  - id: llama-3.1-8b-instant
+    display_name: Llama 3.1 8B Instant
+    description: Small, very low-latency Llama model (~560 tok/s) with parallel tool use

application/core/models/huggingface.yaml

@@ -0,0 +1,7 @@
+provider: huggingface
+
+models:
+  - id: huggingface-local
+    display_name: Hugging Face Model
+    description: Local Hugging Face model
+    supports_tools: false

application/core/models/novita.yaml

@@ -0,0 +1,21 @@
+provider: novita
+defaults:
+  supports_tools: true
+  supports_structured_output: true
+
+models:
+  - id: deepseek/deepseek-v4-pro
+    display_name: DeepSeek V4 Pro
+    description: 1.6T MoE (49B active) with 1M context, hybrid CSA/HCA attention, top-tier reasoning and agentic coding
+    context_window: 1048576
+
+  - id: moonshotai/kimi-k2.6
+    display_name: Kimi K2.6
+    description: 1T-parameter open-weight MoE with native vision/video, multi-step tool calling, and agentic long-horizon execution
+    attachments: [image]
+    context_window: 262144
+
+  - id: zai-org/glm-5
+    display_name: GLM-5
+    description: Z.AI 754B-parameter MoE with strong general reasoning, function calling, and structured output
+    context_window: 202800

application/core/models/openai.yaml

@@ -0,0 +1,18 @@
+provider: openai
+defaults:
+  supports_tools: true
+  supports_structured_output: true
+  attachments: [image]
+  context_window: 400000
+
+models:
+  - id: gpt-5.5
+    display_name: GPT-5.5
+    description: Flagship frontier model for complex reasoning, coding, and agentic work with a 1M-token context window
+    context_window: 1050000
+  - id: gpt-5.4-mini
+    display_name: GPT-5.4 Mini
+    description: Cost-efficient GPT-5.4-class model for high-volume coding, computer use, and subagent workloads
+  - id: gpt-5.4-nano
+    display_name: GPT-5.4 Nano
+    description: Cheapest GPT-5.4-class model, optimized for simple high-volume tasks where speed and cost matter most

application/core/models/openrouter.yaml

@@ -0,0 +1,25 @@
+provider: openrouter
+defaults:
+  supports_tools: true
+  attachments: [image]
+  context_window: 128000
+
+models:
+  - id: qwen/qwen3-coder:free
+    display_name: Qwen3 Coder (free)
+    description: Free-tier 480B MoE coder model with strong agentic tool use; rate-limited
+    context_window: 262000
+    attachments: []
+
+  - id: deepseek/deepseek-v3.2
+    display_name: DeepSeek V3.2
+    description: Open-weights reasoning model, very low cost (~$0.25 in / $0.38 out per 1M)
+    context_window: 131072
+    attachments: []
+    supports_structured_output: true
+
+  - id: anthropic/claude-sonnet-4.6
+    display_name: Claude Sonnet 4.6 (via OpenRouter)
+    description: Frontier Sonnet-class model with 1M context, vision, and extended thinking
+    context_window: 1000000
+    supports_structured_output: true

application/core/settings.py

@@ -23,6 +23,10 @@ class Settings(BaseSettings):
     EMBEDDINGS_NAME: str = "huggingface_sentence-transformers/all-mpnet-base-v2"
     EMBEDDINGS_BASE_URL: Optional[str] = None  # Remote embeddings API URL (OpenAI-compatible)
     EMBEDDINGS_KEY: Optional[str] = None  # api key for embeddings (if using openai, just copy API_KEY)
+    # Optional directory of operator-supplied model YAMLs, loaded after the
+    # built-in catalog under application/core/models/. Later wins on
+    # duplicate model id. See application/core/models/README.md.
+    MODELS_CONFIG_DIR: Optional[str] = None
 
     CELERY_BROKER_URL: str = "redis://localhost:6379/0"
     CELERY_RESULT_BACKEND: str = "redis://localhost:6379/1"

application/llm/llm_creator.py

@@ -1,34 +1,11 @@
 import logging
 
-from application.llm.anthropic import AnthropicLLM
-from application.llm.docsgpt_provider import DocsGPTAPILLM
-from application.llm.google_ai import GoogleLLM
-from application.llm.groq import GroqLLM
-from application.llm.llama_cpp import LlamaCpp
-from application.llm.novita import NovitaLLM
-from application.llm.openai import AzureOpenAILLM, OpenAILLM
-from application.llm.premai import PremAILLM
-from application.llm.sagemaker import SagemakerAPILLM
-from application.llm.open_router import OpenRouterLLM
+from application.llm.providers import PROVIDERS_BY_NAME
 
 logger = logging.getLogger(__name__)
 
 
 class LLMCreator:
-    llms = {
-        "openai": OpenAILLM,
-        "azure_openai": AzureOpenAILLM,
-        "sagemaker": SagemakerAPILLM,
-        "llama.cpp": LlamaCpp,
-        "anthropic": AnthropicLLM,
-        "docsgpt": DocsGPTAPILLM,
-        "premai": PremAILLM,
-        "groq": GroqLLM,
-        "google": GoogleLLM,
-        "novita": NovitaLLM,
-        "openrouter": OpenRouterLLM,
-    }
-
     @classmethod
     def create_llm(
         cls,
@@ -42,18 +19,27 @@ class LLMCreator:
         *args,
         **kwargs,
     ):
-        from application.core.model_utils import get_base_url_for_model
+        from application.core.model_registry import ModelRegistry
 
-        llm_class = cls.llms.get(type.lower())
-        if not llm_class:
+        plugin = PROVIDERS_BY_NAME.get(type.lower())
+        if plugin is None or plugin.llm_class is None:
             raise ValueError(f"No LLM class found for type {type}")
 
-        # Extract base_url from model configuration if model_id is provided
+        # Prefer per-model endpoint config from the registry. This is what
+        # makes openai_compatible (and the future end-user BYOM phase)
+        # work without changing every call site: if the registered
+        # AvailableModel carries its own api_key / base_url, they win
+        # over whatever the caller resolved via the provider plugin.
         base_url = None
         if model_id:
-            base_url = get_base_url_for_model(model_id)
+            model = ModelRegistry.get_instance().get_model(model_id)
+            if model is not None:
+                if model.api_key:
+                    api_key = model.api_key
+                if model.base_url:
+                    base_url = model.base_url
 
-        return llm_class(
+        return plugin.llm_class(
             api_key,
             user_api_key,
             decoded_token=decoded_token,

application/llm/openai.py

@@ -389,8 +389,8 @@ class OpenAILLM(BaseLLM):
         Returns:
             list: List of supported MIME types
         """
-        from application.core.model_configs import OPENAI_ATTACHMENTS
-        return OPENAI_ATTACHMENTS
+        from application.core.model_yaml import resolve_attachment_alias
+        return resolve_attachment_alias("image")
 
     def prepare_messages_with_attachments(self, messages, attachments=None):
         """

application/llm/providers/__init__.py

@@ -0,0 +1,51 @@
+"""Provider plugin registry.
+
+Plugins are imported eagerly so import errors surface at app boot rather
+than at first request. ``ALL_PROVIDERS`` is the canonical ordered list;
+``PROVIDERS_BY_NAME`` is a name-keyed lookup for LLMCreator and the
+model registry.
+"""
+
+from __future__ import annotations
+
+from typing import Dict, List
+
+from application.llm.providers.anthropic import AnthropicProvider
+from application.llm.providers.azure_openai import AzureOpenAIProvider
+from application.llm.providers.base import Provider
+from application.llm.providers.docsgpt import DocsGPTProvider
+from application.llm.providers.google import GoogleProvider
+from application.llm.providers.groq import GroqProvider
+from application.llm.providers.huggingface import HuggingFaceProvider
+from application.llm.providers.llama_cpp import LlamaCppProvider
+from application.llm.providers.novita import NovitaProvider
+from application.llm.providers.openai import OpenAIProvider
+from application.llm.providers.openai_compatible import OpenAICompatibleProvider
+from application.llm.providers.openrouter import OpenRouterProvider
+from application.llm.providers.premai import PremAIProvider
+from application.llm.providers.sagemaker import SagemakerProvider
+
+# Order here is the order the registry iterates providers (and therefore
+# the order ``/api/models`` reports them). Match the historical order
+# from the old ModelRegistry._load_models for byte-stable output during
+# the migration. ``openai_compatible`` slots in right after ``openai``
+# so legacy ``OPENAI_BASE_URL`` models keep landing in the same place.
+ALL_PROVIDERS: List[Provider] = [
+    DocsGPTProvider(),
+    OpenAIProvider(),
+    OpenAICompatibleProvider(),
+    AzureOpenAIProvider(),
+    AnthropicProvider(),
+    GoogleProvider(),
+    GroqProvider(),
+    OpenRouterProvider(),
+    NovitaProvider(),
+    HuggingFaceProvider(),
+    LlamaCppProvider(),
+    PremAIProvider(),
+    SagemakerProvider(),
+]
+
+PROVIDERS_BY_NAME: Dict[str, Provider] = {p.name: p for p in ALL_PROVIDERS}
+
+__all__ = ["ALL_PROVIDERS", "PROVIDERS_BY_NAME", "Provider"]

application/llm/providers/_apikey_or_llm_name.py

@@ -0,0 +1,51 @@
+"""Shared helper for providers that follow the
+``<X>_API_KEY or (LLM_PROVIDER==X and API_KEY)`` pattern.
+
+This is the dominant pattern across Anthropic, Google, Groq, OpenRouter,
+and Novita. Extracted here so each plugin stays a few lines long.
+"""
+
+from __future__ import annotations
+
+from typing import List, Optional
+
+from application.core.model_settings import AvailableModel
+
+
+def get_api_key(
+    settings,
+    provider_name: str,
+    provider_specific_key: Optional[str],
+) -> Optional[str]:
+    if provider_specific_key:
+        return provider_specific_key
+    if settings.LLM_PROVIDER == provider_name and settings.API_KEY:
+        return settings.API_KEY
+    return None
+
+
+def filter_models_by_llm_name(
+    settings,
+    provider_name: str,
+    provider_specific_key: Optional[str],
+    models: List[AvailableModel],
+) -> List[AvailableModel]:
+    """Mirrors the historical ``_add_<X>_models`` selection logic.
+
+    Behavior:
+    - If the provider-specific API key is set → load all models.
+    - Else if ``LLM_PROVIDER`` matches and ``LLM_NAME`` matches a known
+      model → load just that model.
+    - Otherwise → load all models (preserved "load anyway" branch from
+      the original methods).
+    """
+    if provider_specific_key:
+        return models
+    if (
+        settings.LLM_PROVIDER == provider_name
+        and settings.LLM_NAME
+    ):
+        named = [m for m in models if m.id == settings.LLM_NAME]
+        if named:
+            return named
+    return models

application/llm/providers/anthropic.py

@@ -0,0 +1,23 @@
+from __future__ import annotations
+
+from typing import Optional
+
+from application.llm.anthropic import AnthropicLLM
+from application.llm.providers._apikey_or_llm_name import (
+    filter_models_by_llm_name,
+    get_api_key,
+)
+from application.llm.providers.base import Provider
+
+
+class AnthropicProvider(Provider):
+    name = "anthropic"
+    llm_class = AnthropicLLM
+
+    def get_api_key(self, settings) -> Optional[str]:
+        return get_api_key(settings, self.name, settings.ANTHROPIC_API_KEY)
+
+    def filter_yaml_models(self, settings, models):
+        return filter_models_by_llm_name(
+            settings, self.name, settings.ANTHROPIC_API_KEY, models
+        )

application/llm/providers/azure_openai.py

@@ -0,0 +1,30 @@
+from __future__ import annotations
+
+from typing import Optional
+
+from application.llm.openai import AzureOpenAILLM
+from application.llm.providers.base import Provider
+
+
+class AzureOpenAIProvider(Provider):
+    name = "azure_openai"
+    llm_class = AzureOpenAILLM
+
+    def get_api_key(self, settings) -> Optional[str]:
+        # Azure historically uses the generic API_KEY field.
+        return settings.API_KEY
+
+    def is_enabled(self, settings) -> bool:
+        if settings.OPENAI_API_BASE:
+            return True
+        return settings.LLM_PROVIDER == self.name and bool(settings.API_KEY)
+
+    def filter_yaml_models(self, settings, models):
+        # Mirrors _add_azure_openai_models: when LLM_PROVIDER==azure_openai
+        # and LLM_NAME matches a known model, narrow to that one model.
+        # Otherwise load the entire catalog.
+        if settings.LLM_PROVIDER == self.name and settings.LLM_NAME:
+            named = [m for m in models if m.id == settings.LLM_NAME]
+            if named:
+                return named
+        return models

application/llm/providers/base.py

@@ -0,0 +1,74 @@
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from typing import TYPE_CHECKING, ClassVar, List, Optional, Type
+
+if TYPE_CHECKING:
+    from application.core.model_settings import AvailableModel
+    from application.core.model_yaml import ProviderCatalog
+    from application.core.settings import Settings
+    from application.llm.base import BaseLLM
+
+
+class Provider(ABC):
+    """Owns the *behavior* of an LLM provider.
+
+    Concrete providers declare their name, the LLM class to instantiate,
+    and how to resolve credentials from settings. Static model catalogs
+    live in YAML under ``application/core/models/`` and are joined to the
+    provider by name at registry load time.
+
+    Most plugins receive zero or one catalog at registry-build time. The
+    ``openai_compatible`` plugin is the exception: it receives one catalog
+    per matching YAML file, each with its own ``api_key_env`` and
+    ``base_url``. Plugins that need per-catalog metadata override
+    ``get_models``; the default implementation merges catalogs and routes
+    through ``filter_yaml_models`` + ``extra_models``.
+    """
+
+    name: ClassVar[str]
+    # ``None`` means the provider appears in the catalog but isn't
+    # dispatchable through LLMCreator (e.g. Hugging Face today, where the
+    # original LLMCreator dict had no entry).
+    llm_class: ClassVar[Optional[Type["BaseLLM"]]] = None
+
+    @abstractmethod
+    def get_api_key(self, settings: "Settings") -> Optional[str]:
+        """Return the API key for this provider, or None if unavailable."""
+
+    def is_enabled(self, settings: "Settings") -> bool:
+        """Whether this provider should contribute models to the registry."""
+        return bool(self.get_api_key(settings))
+
+    def filter_yaml_models(
+        self, settings: "Settings", models: List["AvailableModel"]
+    ) -> List["AvailableModel"]:
+        """Hook to filter YAML-loaded models. Default: return all."""
+        return models
+
+    def extra_models(self, settings: "Settings") -> List["AvailableModel"]:
+        """Hook to add dynamic models not declared in YAML. Default: none."""
+        return []
+
+    def get_models(
+        self,
+        settings: "Settings",
+        catalogs: List["ProviderCatalog"],
+    ) -> List["AvailableModel"]:
+        """Final list of models this plugin contributes.
+
+        Default: merge the models across all matched catalogs (later
+        catalog wins on duplicate id), filter via ``filter_yaml_models``,
+        then append ``extra_models``. Override when per-catalog metadata
+        matters (see ``OpenAICompatibleProvider``).
+        """
+        merged: List["AvailableModel"] = []
+        seen: dict = {}
+        for c in catalogs:
+            for m in c.models:
+                if m.id in seen:
+                    merged[seen[m.id]] = m
+                else:
+                    seen[m.id] = len(merged)
+                    merged.append(m)
+        return self.filter_yaml_models(settings, merged) + self.extra_models(settings)

application/llm/providers/docsgpt.py

@@ -0,0 +1,22 @@
+from __future__ import annotations
+
+from typing import Optional
+
+from application.llm.docsgpt_provider import DocsGPTAPILLM
+from application.llm.providers.base import Provider
+
+
+class DocsGPTProvider(Provider):
+    name = "docsgpt"
+    llm_class = DocsGPTAPILLM
+
+    def get_api_key(self, settings) -> Optional[str]:
+        # No provider-specific key; the LLM class can use the generic
+        # API_KEY fallback if it needs one. Mirrors model_utils' historical
+        # behavior of returning settings.API_KEY when no specific key exists.
+        return settings.API_KEY
+
+    def is_enabled(self, settings) -> bool:
+        # The hosted DocsGPT model is hidden when the deployment is
+        # pointed at a custom OpenAI-compatible endpoint.
+        return not settings.OPENAI_BASE_URL

application/llm/providers/google.py

@@ -0,0 +1,23 @@
+from __future__ import annotations
+
+from typing import Optional
+
+from application.llm.google_ai import GoogleLLM
+from application.llm.providers._apikey_or_llm_name import (
+    filter_models_by_llm_name,
+    get_api_key,
+)
+from application.llm.providers.base import Provider
+
+
+class GoogleProvider(Provider):
+    name = "google"
+    llm_class = GoogleLLM
+
+    def get_api_key(self, settings) -> Optional[str]:
+        return get_api_key(settings, self.name, settings.GOOGLE_API_KEY)
+
+    def filter_yaml_models(self, settings, models):
+        return filter_models_by_llm_name(
+            settings, self.name, settings.GOOGLE_API_KEY, models
+        )

application/llm/providers/groq.py

@@ -0,0 +1,23 @@
+from __future__ import annotations
+
+from typing import Optional
+
+from application.llm.groq import GroqLLM
+from application.llm.providers._apikey_or_llm_name import (
+    filter_models_by_llm_name,
+    get_api_key,
+)
+from application.llm.providers.base import Provider
+
+
+class GroqProvider(Provider):
+    name = "groq"
+    llm_class = GroqLLM
+
+    def get_api_key(self, settings) -> Optional[str]:
+        return get_api_key(settings, self.name, settings.GROQ_API_KEY)
+
+    def filter_yaml_models(self, settings, models):
+        return filter_models_by_llm_name(
+            settings, self.name, settings.GROQ_API_KEY, models
+        )

application/llm/providers/huggingface.py

@@ -0,0 +1,25 @@
+from __future__ import annotations
+
+from typing import Optional
+
+from application.llm.providers._apikey_or_llm_name import (
+    get_api_key as shared_get_api_key,
+)
+from application.llm.providers.base import Provider
+
+
+class HuggingFaceProvider(Provider):
+    """Surfaces ``huggingface-local`` to the model catalog.
+
+    Not dispatchable through LLMCreator — historically there was no
+    HuggingFaceLLM entry in ``LLMCreator.llms``, and calling ``create_llm``
+    with ``"huggingface"`` raised ``ValueError``. We preserve that
+    behavior: the model appears in ``/api/models`` but selecting it
+    surfaces the same error it always did.
+    """
+
+    name = "huggingface"
+    llm_class = None  # not dispatchable
+
+    def get_api_key(self, settings) -> Optional[str]:
+        return shared_get_api_key(settings, self.name, settings.HUGGINGFACE_API_KEY)

application/llm/providers/llama_cpp.py

@@ -0,0 +1,19 @@
+from __future__ import annotations
+
+from typing import Optional
+
+from application.llm.llama_cpp import LlamaCpp
+from application.llm.providers.base import Provider
+
+
+class LlamaCppProvider(Provider):
+    """LLMCreator-only plugin: invocable via LLM_PROVIDER but not in the catalog."""
+
+    name = "llama.cpp"
+    llm_class = LlamaCpp
+
+    def get_api_key(self, settings) -> Optional[str]:
+        return settings.API_KEY
+
+    def is_enabled(self, settings) -> bool:
+        return False

application/llm/providers/novita.py

@@ -0,0 +1,23 @@
+from __future__ import annotations
+
+from typing import Optional
+
+from application.llm.novita import NovitaLLM
+from application.llm.providers._apikey_or_llm_name import (
+    filter_models_by_llm_name,
+    get_api_key,
+)
+from application.llm.providers.base import Provider
+
+
+class NovitaProvider(Provider):
+    name = "novita"
+    llm_class = NovitaLLM
+
+    def get_api_key(self, settings) -> Optional[str]:
+        return get_api_key(settings, self.name, settings.NOVITA_API_KEY)
+
+    def filter_yaml_models(self, settings, models):
+        return filter_models_by_llm_name(
+            settings, self.name, settings.NOVITA_API_KEY, models
+        )

application/llm/providers/openai.py

@@ -0,0 +1,37 @@
+from __future__ import annotations
+
+from typing import Optional
+
+from application.llm.openai import OpenAILLM
+from application.llm.providers.base import Provider
+
+
+class OpenAIProvider(Provider):
+    name = "openai"
+    llm_class = OpenAILLM
+
+    def get_api_key(self, settings) -> Optional[str]:
+        if settings.OPENAI_API_KEY:
+            return settings.OPENAI_API_KEY
+        if settings.LLM_PROVIDER == self.name and settings.API_KEY:
+            return settings.API_KEY
+        return None
+
+    def is_enabled(self, settings) -> bool:
+        # When the deployment is pointed at a custom OpenAI-compatible
+        # endpoint (Ollama, LM Studio, ...), the cloud-OpenAI catalog is
+        # suppressed but ``is_enabled`` stays True — necessary so the
+        # filter below still gets to drop the catalog (rather than the
+        # registry skipping the provider entirely and missing the rule).
+        if settings.OPENAI_BASE_URL:
+            return True
+        return bool(self.get_api_key(settings))
+
+    def filter_yaml_models(self, settings, models):
+        # Legacy local-endpoint mode hides the cloud catalog. The
+        # corresponding dynamic models live in OpenAICompatibleProvider.
+        if settings.OPENAI_BASE_URL:
+            return []
+        if not settings.OPENAI_API_KEY:
+            return []
+        return models

application/llm/providers/openai_compatible.py

@@ -0,0 +1,149 @@
+"""Generic provider for OpenAI-wire-compatible endpoints.
+
+Each ``openai_compatible`` YAML file describes one logical endpoint
+(Mistral, Together, Fireworks, Ollama, ...) with its own
+``api_key_env`` and ``base_url``. Multiple files can coexist; the
+plugin produces one set of models per file, each pre-configured with
+the right credentials and URL.
+
+The plugin also handles the **legacy** ``OPENAI_BASE_URL`` + ``LLM_NAME``
+local-endpoint pattern that previously lived in ``OpenAIProvider``. That
+path generates models dynamically from ``LLM_NAME``, using
+``OPENAI_BASE_URL`` and ``OPENAI_API_KEY`` as the endpoint config.
+"""
+
+from __future__ import annotations
+
+import logging
+import os
+from typing import List, Optional
+
+from application.core.model_settings import (
+    AvailableModel,
+    ModelCapabilities,
+    ModelProvider,
+)
+from application.llm.openai import OpenAILLM
+from application.llm.providers.base import Provider
+
+logger = logging.getLogger(__name__)
+
+
+def _parse_model_names(llm_name: Optional[str]) -> List[str]:
+    if not llm_name:
+        return []
+    return [name.strip() for name in llm_name.split(",") if name.strip()]
+
+
+class OpenAICompatibleProvider(Provider):
+    name = "openai_compatible"
+    llm_class = OpenAILLM
+
+    def get_api_key(self, settings) -> Optional[str]:
+        # Per-model: each catalog supplies its own ``api_key_env``. There
+        # is no single plugin-wide key. LLMCreator reads the per-model
+        # ``api_key`` set during catalog materialization.
+        return None
+
+    def is_enabled(self, settings) -> bool:
+        # Concrete enablement happens per catalog (in ``get_models``).
+        # Returning True lets the registry call ``get_models`` so we can
+        # decide per-file whether to contribute models.
+        return True
+
+    def get_models(self, settings, catalogs) -> List[AvailableModel]:
+        out: List[AvailableModel] = []
+
+        for catalog in catalogs:
+            out.extend(self._materialize_yaml_catalog(catalog))
+
+        if settings.OPENAI_BASE_URL and settings.LLM_NAME:
+            out.extend(self._materialize_legacy_local_endpoint(settings))
+
+        return out
+
+    def _materialize_yaml_catalog(self, catalog) -> List[AvailableModel]:
+        """Resolve one openai_compatible YAML into ready-to-dispatch models.
+
+        Skipped (with an INFO-level log) if ``api_key_env`` resolves to
+        nothing — no point publishing models the user can't actually
+        call. INFO rather than WARNING because operators may legitimately
+        drop multiple provider YAMLs as templates and only set the env
+        vars for the ones they actually use; a missing key is ambiguous,
+        not necessarily a misconfig.
+        """
+        if not catalog.base_url:
+            raise ValueError(
+                f"{catalog.source_path}: openai_compatible YAML must set "
+                "'base_url'."
+            )
+        if not catalog.api_key_env:
+            raise ValueError(
+                f"{catalog.source_path}: openai_compatible YAML must set "
+                "'api_key_env'."
+            )
+
+        api_key = os.environ.get(catalog.api_key_env)
+        if not api_key:
+            logger.info(
+                "openai_compatible catalog %s skipped: env var %s is not set",
+                catalog.source_path,
+                catalog.api_key_env,
+            )
+            return []
+
+        out: List[AvailableModel] = []
+        for m in catalog.models:
+            out.append(self._with_endpoint(m, catalog.base_url, api_key))
+        return out
+
+    def _materialize_legacy_local_endpoint(self, settings) -> List[AvailableModel]:
+        """Generate AvailableModels from ``LLM_NAME`` for the legacy
+        ``OPENAI_BASE_URL`` deployment pattern (Ollama, LM Studio, ...).
+
+        Preserves the historical ``provider="openai"`` display behavior
+        by setting ``display_provider="openai"``.
+        """
+        from application.core.model_yaml import resolve_attachment_alias
+
+        attachments = resolve_attachment_alias("image")
+        api_key = settings.OPENAI_API_KEY or settings.API_KEY
+        out: List[AvailableModel] = []
+        for model_name in _parse_model_names(settings.LLM_NAME):
+            out.append(
+                AvailableModel(
+                    id=model_name,
+                    provider=ModelProvider.OPENAI_COMPATIBLE,
+                    display_name=model_name,
+                    description=f"Custom OpenAI-compatible model at {settings.OPENAI_BASE_URL}",
+                    base_url=settings.OPENAI_BASE_URL,
+                    capabilities=ModelCapabilities(
+                        supports_tools=True,
+                        supported_attachment_types=attachments,
+                    ),
+                    api_key=api_key,
+                    display_provider="openai",
+                )
+            )
+        return out
+
+    @staticmethod
+    def _with_endpoint(
+        model: AvailableModel, base_url: str, api_key: str
+    ) -> AvailableModel:
+        """Return a copy of ``model`` carrying the catalog's endpoint config.
+
+        The catalog-level ``base_url`` is the default; an explicit
+        per-model ``base_url`` in the YAML wins.
+        """
+        return AvailableModel(
+            id=model.id,
+            provider=model.provider,
+            display_name=model.display_name,
+            description=model.description,
+            capabilities=model.capabilities,
+            enabled=model.enabled,
+            base_url=model.base_url or base_url,
+            display_provider=model.display_provider,
+            api_key=api_key,
+        )

application/llm/providers/openrouter.py

@@ -0,0 +1,23 @@
+from __future__ import annotations
+
+from typing import Optional
+
+from application.llm.open_router import OpenRouterLLM
+from application.llm.providers._apikey_or_llm_name import (
+    filter_models_by_llm_name,
+    get_api_key,
+)
+from application.llm.providers.base import Provider
+
+
+class OpenRouterProvider(Provider):
+    name = "openrouter"
+    llm_class = OpenRouterLLM
+
+    def get_api_key(self, settings) -> Optional[str]:
+        return get_api_key(settings, self.name, settings.OPEN_ROUTER_API_KEY)
+
+    def filter_yaml_models(self, settings, models):
+        return filter_models_by_llm_name(
+            settings, self.name, settings.OPEN_ROUTER_API_KEY, models
+        )

application/llm/providers/premai.py

@@ -0,0 +1,19 @@
+from __future__ import annotations
+
+from typing import Optional
+
+from application.llm.premai import PremAILLM
+from application.llm.providers.base import Provider
+
+
+class PremAIProvider(Provider):
+    """LLMCreator-only plugin: invocable via LLM_PROVIDER but not in the catalog."""
+
+    name = "premai"
+    llm_class = PremAILLM
+
+    def get_api_key(self, settings) -> Optional[str]:
+        return settings.API_KEY
+
+    def is_enabled(self, settings) -> bool:
+        return False

application/llm/providers/sagemaker.py

@@ -0,0 +1,24 @@
+from __future__ import annotations
+
+from typing import Optional
+
+from application.llm.sagemaker import SagemakerAPILLM
+from application.llm.providers.base import Provider
+
+
+class SagemakerProvider(Provider):
+    """LLMCreator-only plugin: invocable via LLM_PROVIDER but not in the catalog.
+
+    SageMaker reads its credentials from ``SAGEMAKER_*`` settings inside
+    the LLM class itself; this plugin's ``get_api_key`` exists only for
+    LLMCreator's symmetry.
+    """
+
+    name = "sagemaker"
+    llm_class = SagemakerAPILLM
+
+    def get_api_key(self, settings) -> Optional[str]:
+        return settings.API_KEY
+
+    def is_enabled(self, settings) -> bool:
+        return False

application/requirements.txt

@@ -82,6 +82,7 @@ python-dateutil==2.9.0.post0
 python-dotenv
 python-jose==3.5.0
 python-pptx==1.0.2
+PyYAML
 redis==7.4.0
 referencing>=0.28.0,<0.38.0
 regex==2026.4.4

application/storage/db/repositories/agents.py

@@ -1,7 +1,6 @@
 """Repository for the ``agents`` table.
 
-This is the most complex Phase 2 repository. Covers every write operation
-the legacy Mongo code performs on ``agents_collection``:
+Covers every write operation the legacy Mongo code performs on ``agents_collection``:
 
 - create, update, delete
 - find by key (API key lookup)

application/worker.py

@@ -348,6 +348,16 @@ def run_agent_logic(agent_config, input_data):
             model_id = agent_default_model
         else:
             model_id = get_default_model_id()
+            if agent_default_model:
+                # Stored model_id no longer resolves in the registry. Log so
+                # operators can detect bad YAML edits before users complain;
+                # behavior matches the historical silent fallback.
+                logging.warning(
+                    "Agent %s references unknown model_id %r; falling back to %r",
+                    agent_id,
+                    agent_default_model,
+                    model_id,
+                )
 
         # Get provider and API key for the selected model
         provider = get_provider_from_model_id(model_id) if model_id else settings.LLM_PROVIDER

docs/content/Deploying/DocsGPT-Settings.mdx

@@ -99,6 +99,82 @@ EMBEDDINGS_NAME=huggingface_sentence-transformers/all-mpnet-base-v2 # You can al
 
 In this case, even though you are using Ollama locally, `LLM_PROVIDER` is set to `openai` because Ollama (and many other local inference engines) are designed to be API-compatible with OpenAI. `OPENAI_BASE_URL` points DocsGPT to the local Ollama server.
 
+## Adding Custom Models (`MODELS_CONFIG_DIR`)
+
+DocsGPT ships with a built-in catalog of models for the providers it
+supports out of the box (OpenAI, Anthropic, Google, Groq, OpenRouter,
+Novita, Azure OpenAI, Hugging Face, DocsGPT). To add **your own
+models** without forking the repo — for example, a Mistral or Together
+account, a self-hosted vLLM endpoint, or any other OpenAI-compatible
+API — point `MODELS_CONFIG_DIR` at a directory of YAML files.
+
+```
+MODELS_CONFIG_DIR=/etc/docsgpt/models
+MISTRAL_API_KEY=sk-...
+```
+
+A minimal YAML for one provider:
+
+```yaml
+# /etc/docsgpt/models/mistral.yaml
+provider: openai_compatible
+display_provider: mistral
+api_key_env: MISTRAL_API_KEY
+base_url: https://api.mistral.ai/v1
+defaults:
+  supports_tools: true
+  context_window: 128000
+models:
+  - id: mistral-large-latest
+    display_name: Mistral Large
+  - id: mistral-small-latest
+    display_name: Mistral Small
+```
+
+After restart, those models appear in `/api/models` and are selectable
+in the UI. A working template lives at
+`application/core/models/examples/mistral.yaml.example`.
+
+**What you can do:**
+
+- Add new `openai_compatible` providers (Mistral, Together, Fireworks,
+  Ollama, vLLM, ...) — one YAML per provider, each with its own
+  `api_key_env` and `base_url`.
+- Extend an existing provider's catalog by dropping a YAML with the
+  same `provider:` value as the built-in (e.g. `provider: anthropic`
+  with extra models).
+- Override a built-in model's capabilities by re-declaring the same
+  `id` — later wins, override is logged at `WARNING`.
+
+**What you cannot do via `MODELS_CONFIG_DIR`:** add a brand-new
+non-OpenAI provider. That requires a Python plugin under
+`application/llm/providers/`. See
+`application/core/models/README.md` for the full schema reference.
+
+### Docker
+
+Mount the directory and set the env var:
+
+```yaml
+# docker-compose.yml
+services:
+  app:
+    image: arc53/docsgpt
+    environment:
+      MODELS_CONFIG_DIR: /etc/docsgpt/models
+      MISTRAL_API_KEY: ${MISTRAL_API_KEY}
+    volumes:
+      - ./my-models:/etc/docsgpt/models:ro
+```
+
+### Misconfiguration
+
+If `MODELS_CONFIG_DIR` is set but the path doesn't exist (or isn't a
+directory), the app logs a `WARNING` at boot and continues with just
+the built-in catalog — it does **not** fail to start. If a YAML
+declares an unknown provider name or has a schema error, the app
+**does** fail to start, with the offending file path in the message.
+
 ## Speech-to-Text Settings
 
 DocsGPT can transcribe audio in two places:

tests/api/user/test_tasks.py

@@ -200,7 +200,7 @@ class TestSetupPeriodicTasks:
 
         setup_periodic_tasks(sender)
 
-        assert sender.add_periodic_task.call_count == 4
+        assert sender.add_periodic_task.call_count == 5
 
         calls = sender.add_periodic_task.call_args_list
 
@@ -212,6 +212,8 @@ class TestSetupPeriodicTasks:
         assert calls[2][0][0] == timedelta(days=30)
         # pending_tool_state TTL cleanup (60s)
         assert calls[3][0][0] == timedelta(seconds=60)
+        # version-check (every 7h)
+        assert calls[4][0][0] == timedelta(hours=7)
 
 
 class TestMcpOauthTask:

tests/core/test_model_registry_yaml.py

@@ -0,0 +1,306 @@
+"""Phase 1 regression tests for the YAML-driven ModelRegistry.
+
+These tests encode the contract that persisted agent / workflow /
+conversation references depend on: every model id and core capability
+that existed in the old ``model_configs.py`` lists must continue to be
+produced by the new YAML-backed registry.
+
+If a future YAML edit accidentally renames an id or changes a
+capability, these tests fail at CI before merge — protecting agents and
+workflows from silent fallback to the system default.
+"""
+
+from __future__ import annotations
+
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from application.core.model_registry import ModelRegistry
+from application.core.model_yaml import (
+    BUILTIN_MODELS_DIR,
+    load_model_yamls,
+)
+
+
+# ── Per-provider expected IDs ─────────────────────────────────────────────
+# Snapshot of the current built-in catalog. If you intentionally change
+# what models a provider's YAML lists, update this constant in the same
+# commit. The test exists to catch *unintentional* renames (e.g. a typo
+# in an upstream model id) that would silently break every agent that
+# references the old id.
+EXPECTED_IDS = {
+    "openai": {"gpt-5.5", "gpt-5.4-mini", "gpt-5.4-nano"},
+    "anthropic": {
+        "claude-opus-4-7",
+        "claude-sonnet-4-6",
+        "claude-haiku-4-5",
+    },
+    "google": {
+        "gemini-3.1-pro-preview",
+        "gemini-3-flash-preview",
+        "gemini-3.1-flash-lite-preview",
+    },
+    "groq": {
+        "openai/gpt-oss-120b",
+        "llama-3.3-70b-versatile",
+        "llama-3.1-8b-instant",
+    },
+    "openrouter": {
+        "qwen/qwen3-coder:free",
+        "deepseek/deepseek-v3.2",
+        "anthropic/claude-sonnet-4.6",
+    },
+    "novita": {
+        "deepseek/deepseek-v4-pro",
+        "moonshotai/kimi-k2.6",
+        "zai-org/glm-5",
+    },
+    "azure_openai": {
+        "azure-gpt-5.5",
+        "azure-gpt-5.4-mini",
+        "azure-gpt-5.4-nano",
+    },
+    "docsgpt": {"docsgpt-local"},
+    "huggingface": {"huggingface-local"},
+}
+
+
+def _make_settings(**overrides):
+    s = MagicMock()
+    # All credential / mode flags off by default so each test opts in.
+    s.OPENAI_BASE_URL = None
+    s.OPENAI_API_KEY = None
+    s.OPENAI_API_BASE = None
+    s.ANTHROPIC_API_KEY = None
+    s.GOOGLE_API_KEY = None
+    s.GROQ_API_KEY = None
+    s.OPEN_ROUTER_API_KEY = None
+    s.NOVITA_API_KEY = None
+    s.HUGGINGFACE_API_KEY = None
+    s.LLM_PROVIDER = ""
+    s.LLM_NAME = None
+    s.API_KEY = None
+    s.MODELS_CONFIG_DIR = None
+    for k, v in overrides.items():
+        setattr(s, k, v)
+    return s
+
+
+@pytest.fixture(autouse=True)
+def _reset_registry():
+    ModelRegistry.reset()
+    yield
+    ModelRegistry.reset()
+
+
+# ── YAML schema / loader ─────────────────────────────────────────────────
+
+
+def _by_provider(catalogs):
+    """Group a list of catalogs by provider name. Mirrors the registry's
+    own grouping; useful for asserting per-provider model sets in tests."""
+    out = {}
+    for c in catalogs:
+        out.setdefault(c.provider, []).append(c)
+    return out
+
+
+@pytest.mark.unit
+class TestYAMLLoader:
+    def test_loader_produces_expected_provider_set(self):
+        catalogs = load_model_yamls([BUILTIN_MODELS_DIR])
+        providers = {c.provider for c in catalogs}
+        assert providers == set(EXPECTED_IDS.keys())
+
+    def test_each_provider_has_expected_ids(self):
+        grouped = _by_provider(load_model_yamls([BUILTIN_MODELS_DIR]))
+        for provider, expected in EXPECTED_IDS.items():
+            actual = {m.id for c in grouped[provider] for m in c.models}
+            assert actual == expected, f"{provider}: expected {expected}, got {actual}"
+
+    def test_attachment_alias_image_expands_to_five_mime_types(self):
+        grouped = _by_provider(load_model_yamls([BUILTIN_MODELS_DIR]))
+        # OpenAI uses `attachments: [image]` in its defaults block.
+        for c in grouped["openai"]:
+            for m in c.models:
+                assert "image/png" in m.capabilities.supported_attachment_types
+                assert "image/jpeg" in m.capabilities.supported_attachment_types
+                assert "image/webp" in m.capabilities.supported_attachment_types
+                assert len(m.capabilities.supported_attachment_types) == 5
+
+    def test_attachment_alias_pdf_plus_image_for_google(self):
+        grouped = _by_provider(load_model_yamls([BUILTIN_MODELS_DIR]))
+        for c in grouped["google"]:
+            for m in c.models:
+                assert "application/pdf" in m.capabilities.supported_attachment_types
+                assert "image/png" in m.capabilities.supported_attachment_types
+                assert len(m.capabilities.supported_attachment_types) == 6
+
+    def test_per_model_context_window_overrides_provider_default(self):
+        grouped = _by_provider(load_model_yamls([BUILTIN_MODELS_DIR]))
+        openai = {m.id: m for c in grouped["openai"] for m in c.models}
+        # Provider default is 400_000; gpt-5.5 overrides to 1_050_000.
+        assert openai["gpt-5.4-mini"].capabilities.context_window == 400_000
+        assert openai["gpt-5.5"].capabilities.context_window == 1_050_000
+
+
+# ── Registry × settings: every documented .env permutation ───────────────
+
+
+@pytest.mark.unit
+class TestRegistryPermutations:
+    def test_openai_only(self):
+        s = _make_settings(OPENAI_API_KEY="sk-test", LLM_PROVIDER="openai")
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        ids = {m.id for m in reg.get_all_models()}
+        assert ids == EXPECTED_IDS["openai"] | EXPECTED_IDS["docsgpt"]
+
+    def test_openai_base_url_replaces_catalog_with_dynamic(self):
+        s = _make_settings(
+            OPENAI_BASE_URL="http://localhost:11434/v1",
+            OPENAI_API_KEY="sk-test",
+            LLM_PROVIDER="openai",
+            LLM_NAME="llama3,gemma",
+        )
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        ids = {m.id for m in reg.get_all_models()}
+        # Custom local endpoint suppresses both the openai catalog AND
+        # the docsgpt model (matching legacy behavior).
+        assert ids == {"llama3", "gemma"}
+
+    def test_anthropic_only(self):
+        s = _make_settings(ANTHROPIC_API_KEY="sk-ant")
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        ids = {m.id for m in reg.get_all_models()}
+        assert ids == EXPECTED_IDS["anthropic"] | EXPECTED_IDS["docsgpt"]
+
+    def test_anthropic_via_llm_provider_with_llm_name(self):
+        # Mirrors the historical _add_anthropic_models filter: when only
+        # API_KEY (not ANTHROPIC_API_KEY) is set and LLM_NAME matches a
+        # known model, only that model is loaded.
+        s = _make_settings(
+            LLM_PROVIDER="anthropic", API_KEY="key", LLM_NAME="claude-haiku-4-5"
+        )
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        anthropic_ids = {
+            m.id for m in reg.get_all_models() if m.provider.value == "anthropic"
+        }
+        assert anthropic_ids == {"claude-haiku-4-5"}
+
+    def test_google_only(self):
+        s = _make_settings(GOOGLE_API_KEY="g-test")
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        ids = {m.id for m in reg.get_all_models()}
+        assert ids == EXPECTED_IDS["google"] | EXPECTED_IDS["docsgpt"]
+
+    def test_groq_only(self):
+        s = _make_settings(GROQ_API_KEY="g-test")
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        ids = {m.id for m in reg.get_all_models()}
+        assert ids == EXPECTED_IDS["groq"] | EXPECTED_IDS["docsgpt"]
+
+    def test_openrouter_only(self):
+        s = _make_settings(OPEN_ROUTER_API_KEY="or-test")
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        ids = {m.id for m in reg.get_all_models()}
+        assert ids == EXPECTED_IDS["openrouter"] | EXPECTED_IDS["docsgpt"]
+
+    def test_novita_only(self):
+        s = _make_settings(NOVITA_API_KEY="n-test")
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        ids = {m.id for m in reg.get_all_models()}
+        assert ids == EXPECTED_IDS["novita"] | EXPECTED_IDS["docsgpt"]
+
+    def test_huggingface_only(self):
+        s = _make_settings(HUGGINGFACE_API_KEY="hf-test")
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        ids = {m.id for m in reg.get_all_models()}
+        assert ids == EXPECTED_IDS["huggingface"] | EXPECTED_IDS["docsgpt"]
+
+    def test_no_credentials_only_docsgpt(self):
+        s = _make_settings()
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        ids = {m.id for m in reg.get_all_models()}
+        assert ids == EXPECTED_IDS["docsgpt"]
+
+    def test_azure_via_provider(self):
+        s = _make_settings(LLM_PROVIDER="azure_openai", API_KEY="key")
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        ids = {m.id for m in reg.get_all_models()}
+        assert "azure-gpt-5.5" in ids
+
+    def test_azure_via_api_base(self):
+        s = _make_settings(OPENAI_API_BASE="https://x.openai.azure.com")
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        ids = {m.id for m in reg.get_all_models()}
+        assert "azure-gpt-5.5" in ids
+
+    def test_everything_set(self):
+        s = _make_settings(
+            OPENAI_API_KEY="x",
+            ANTHROPIC_API_KEY="x",
+            GOOGLE_API_KEY="x",
+            GROQ_API_KEY="x",
+            OPEN_ROUTER_API_KEY="x",
+            NOVITA_API_KEY="x",
+            HUGGINGFACE_API_KEY="x",
+            OPENAI_API_BASE="x",
+        )
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        ids = {m.id for m in reg.get_all_models()}
+        all_expected = set()
+        for v in EXPECTED_IDS.values():
+            all_expected |= v
+        assert ids == all_expected
+
+
+# ── Default model resolution ─────────────────────────────────────────────
+
+
+@pytest.mark.unit
+class TestDefaultModelResolution:
+    def test_llm_name_picks_default(self):
+        s = _make_settings(
+            ANTHROPIC_API_KEY="sk-ant", LLM_NAME="claude-opus-4-7"
+        )
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        assert reg.default_model_id == "claude-opus-4-7"
+
+    def test_falls_back_to_first_model_when_no_match(self):
+        s = _make_settings()
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        assert reg.default_model_id is not None
+        assert reg.default_model_id in reg.models
+
+
+# ── Forward-compat: user_id parameter is accepted everywhere ─────────────
+
+
+@pytest.mark.unit
+class TestUserIdForwardCompat:
+    def test_lookup_methods_accept_user_id(self):
+        s = _make_settings(OPENAI_API_KEY="sk-test")
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        # All lookup methods must accept user_id (currently ignored,
+        # reserved for end-user BYOM).
+        assert reg.get_model("gpt-5.5", user_id="alice") is not None
+        assert len(reg.get_all_models(user_id="alice")) > 0
+        assert len(reg.get_enabled_models(user_id="alice")) > 0
+        assert reg.model_exists("gpt-5.5", user_id="alice") is True

tests/core/test_model_settings.py

@@ -1,6 +1,17 @@
-"""Tests for application/core/model_settings.py"""
+"""Tests for application/core/model_settings.py.
 
-from unittest.mock import MagicMock, patch
+The provider-specific load logic that used to live in private
+``_add_<X>_models`` methods now lives in plugin classes under
+``application/llm/providers/`` and YAML catalogs under
+``application/core/models/``. End-to-end coverage of the registry +
+plugin pipeline is in ``tests/core/test_model_registry_yaml.py``.
+
+This file covers the data classes (``AvailableModel``,
+``ModelCapabilities``, ``ModelProvider``) and the singleton/lookup
+contract on ``ModelRegistry``.
+"""
+
+from unittest.mock import patch
 
 import pytest
 
@@ -13,7 +24,6 @@ from application.core.model_settings import (
 
 
 class TestModelProvider:
-
     @pytest.mark.unit
     def test_all_providers_exist(self):
         assert ModelProvider.OPENAI == "openai"
@@ -31,7 +41,6 @@ class TestModelProvider:
 
 
 class TestModelCapabilities:
-
     @pytest.mark.unit
     def test_defaults(self):
         caps = ModelCapabilities()
@@ -56,7 +65,6 @@ class TestModelCapabilities:
 
 
 class TestAvailableModel:
-
     @pytest.mark.unit
     def test_to_dict_basic(self):
         model = AvailableModel(
@@ -78,35 +86,67 @@ class TestAvailableModel:
             id="local-model",
             provider=ModelProvider.OPENAI,
             display_name="Local",
-            base_url="http://localhost:11434",
+            base_url="http://localhost:11434/v1",
         )
         d = model.to_dict()
-        assert d["base_url"] == "http://localhost:11434"
+        assert d["base_url"] == "http://localhost:11434/v1"
 
     @pytest.mark.unit
     def test_to_dict_includes_capabilities(self):
-        caps = ModelCapabilities(supports_tools=True, context_window=64000)
+        caps = ModelCapabilities(
+            supports_tools=True,
+            supports_structured_output=True,
+            context_window=200000,
+            supported_attachment_types=["image/png"],
+        )
         model = AvailableModel(
-            id="m1",
-            provider=ModelProvider.ANTHROPIC,
-            display_name="M1",
+            id="m",
+            provider=ModelProvider.OPENAI,
+            display_name="M",
             capabilities=caps,
         )
         d = model.to_dict()
         assert d["supports_tools"] is True
-        assert d["context_window"] == 64000
+        assert d["supports_structured_output"] is True
+        assert d["context_window"] == 200000
+        assert d["supported_attachment_types"] == ["image/png"]
+
+    @pytest.mark.unit
+    def test_to_dict_disabled_model(self):
+        model = AvailableModel(
+            id="disabled",
+            provider=ModelProvider.OPENAI,
+            display_name="Disabled",
+            enabled=False,
+        )
+        d = model.to_dict()
+        assert d["enabled"] is False
+
+    @pytest.mark.unit
+    def test_api_key_field_never_serialized(self):
+        """Forward-compat hook: AvailableModel.api_key (reserved for the
+        future end-user BYOM phase) must never leak into the wire format."""
+        model = AvailableModel(
+            id="byom",
+            provider=ModelProvider.OPENAI,
+            display_name="BYOM",
+            api_key="secret-key-do-not-leak",
+        )
+        d = model.to_dict()
+        assert "api_key" not in d
+        for v in d.values():
+            assert v != "secret-key-do-not-leak"
 
 
-class TestModelRegistry:
+class TestModelRegistryPublicAPI:
+    """Covers the public lookup contract. Loading behavior is exercised
+    end-to-end in tests/core/test_model_registry_yaml.py."""
 
     @pytest.fixture(autouse=True)
     def _reset_singleton(self):
-        """Reset singleton between tests."""
-        ModelRegistry._instance = None
-        ModelRegistry._initialized = False
+        ModelRegistry.reset()
         yield
-        ModelRegistry._instance = None
-        ModelRegistry._initialized = False
+        ModelRegistry.reset()
 
     @pytest.mark.unit
     def test_singleton(self):
@@ -125,7 +165,9 @@ class TestModelRegistry:
     def test_get_model(self):
         with patch.object(ModelRegistry, "_load_models"):
             reg = ModelRegistry()
-            model = AvailableModel(id="test", provider=ModelProvider.OPENAI, display_name="Test")
+            model = AvailableModel(
+                id="test", provider=ModelProvider.OPENAI, display_name="Test"
+            )
             reg.models["test"] = model
             assert reg.get_model("test") is model
             assert reg.get_model("nonexistent") is None
@@ -134,16 +176,30 @@ class TestModelRegistry:
     def test_get_all_models(self):
         with patch.object(ModelRegistry, "_load_models"):
             reg = ModelRegistry()
-            reg.models["m1"] = AvailableModel(id="m1", provider=ModelProvider.OPENAI, display_name="M1")
-            reg.models["m2"] = AvailableModel(id="m2", provider=ModelProvider.ANTHROPIC, display_name="M2")
+            reg.models["m1"] = AvailableModel(
+                id="m1", provider=ModelProvider.OPENAI, display_name="M1"
+            )
+            reg.models["m2"] = AvailableModel(
+                id="m2", provider=ModelProvider.ANTHROPIC, display_name="M2"
+            )
             assert len(reg.get_all_models()) == 2
 
     @pytest.mark.unit
     def test_get_enabled_models(self):
         with patch.object(ModelRegistry, "_load_models"):
             reg = ModelRegistry()
-            reg.models["m1"] = AvailableModel(id="m1", provider=ModelProvider.OPENAI, display_name="M1", enabled=True)
-            reg.models["m2"] = AvailableModel(id="m2", provider=ModelProvider.OPENAI, display_name="M2", enabled=False)
+            reg.models["m1"] = AvailableModel(
+                id="m1",
+                provider=ModelProvider.OPENAI,
+                display_name="M1",
+                enabled=True,
+            )
+            reg.models["m2"] = AvailableModel(
+                id="m2",
+                provider=ModelProvider.OPENAI,
+                display_name="M2",
+                enabled=False,
+            )
             enabled = reg.get_enabled_models()
             assert len(enabled) == 1
             assert enabled[0].id == "m1"
@@ -152,652 +208,29 @@ class TestModelRegistry:
     def test_model_exists(self):
         with patch.object(ModelRegistry, "_load_models"):
             reg = ModelRegistry()
-            reg.models["m1"] = AvailableModel(id="m1", provider=ModelProvider.OPENAI, display_name="M1")
+            reg.models["m1"] = AvailableModel(
+                id="m1", provider=ModelProvider.OPENAI, display_name="M1"
+            )
             assert reg.model_exists("m1") is True
             assert reg.model_exists("m2") is False
 
     @pytest.mark.unit
-    def test_parse_model_names(self):
+    def test_lookups_accept_user_id_kwarg(self):
+        """Reserved for the future end-user BYOM phase. Currently ignored."""
         with patch.object(ModelRegistry, "_load_models"):
             reg = ModelRegistry()
-            assert reg._parse_model_names("model1,model2") == ["model1", "model2"]
-            assert reg._parse_model_names("model1 , model2 ") == ["model1", "model2"]
-            assert reg._parse_model_names("single") == ["single"]
-            assert reg._parse_model_names("") == []
-            assert reg._parse_model_names(None) == []
-
-    @pytest.mark.unit
-    def test_add_docsgpt_models(self):
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            reg._add_docsgpt_models(mock_settings)
-            assert "docsgpt-local" in reg.models
-
-    @pytest.mark.unit
-    def test_add_huggingface_models(self):
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            reg._add_huggingface_models(mock_settings)
-            assert "huggingface-local" in reg.models
-
-    @pytest.mark.unit
-    def test_load_models_with_openai_key(self):
-        mock_settings = MagicMock()
-        mock_settings.OPENAI_BASE_URL = None
-        mock_settings.OPENAI_API_KEY = "sk-test"
-        mock_settings.OPENAI_API_BASE = None
-        mock_settings.ANTHROPIC_API_KEY = None
-        mock_settings.GOOGLE_API_KEY = None
-        mock_settings.GROQ_API_KEY = None
-        mock_settings.OPEN_ROUTER_API_KEY = None
-        mock_settings.NOVITA_API_KEY = None
-        mock_settings.HUGGINGFACE_API_KEY = None
-        mock_settings.LLM_PROVIDER = "openai"
-        mock_settings.LLM_NAME = ""
-        mock_settings.API_KEY = None
-
-        with patch("application.core.settings.settings", mock_settings):
-            reg = ModelRegistry()
-            assert len(reg.models) > 0
-
-    @pytest.mark.unit
-    def test_load_models_custom_openai_base_url(self):
-        mock_settings = MagicMock()
-        mock_settings.OPENAI_BASE_URL = "http://localhost:11434/v1"
-        mock_settings.OPENAI_API_KEY = "sk-test"
-        mock_settings.OPENAI_API_BASE = None
-        mock_settings.ANTHROPIC_API_KEY = None
-        mock_settings.GOOGLE_API_KEY = None
-        mock_settings.GROQ_API_KEY = None
-        mock_settings.OPEN_ROUTER_API_KEY = None
-        mock_settings.NOVITA_API_KEY = None
-        mock_settings.HUGGINGFACE_API_KEY = None
-        mock_settings.LLM_PROVIDER = "openai"
-        mock_settings.LLM_NAME = "llama3,gemma"
-        mock_settings.API_KEY = None
-
-        with patch("application.core.settings.settings", mock_settings):
-            reg = ModelRegistry()
-            assert "llama3" in reg.models
-            assert "gemma" in reg.models
-
-    @pytest.mark.unit
-    def test_default_model_selection_from_llm_name(self):
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {"gpt-4": AvailableModel(id="gpt-4", provider=ModelProvider.OPENAI, display_name="GPT-4")}
-            reg.default_model_id = "gpt-4"
-            assert reg.default_model_id == "gpt-4"
-
-    @pytest.mark.unit
-    def test_add_anthropic_models_with_key(self):
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.ANTHROPIC_API_KEY = "sk-ant-test"
-            mock_settings.LLM_PROVIDER = ""
-            mock_settings.LLM_NAME = ""
-            reg._add_anthropic_models(mock_settings)
-            assert len(reg.models) > 0
-
-    @pytest.mark.unit
-    def test_add_google_models_with_key(self):
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.GOOGLE_API_KEY = "google-test"
-            mock_settings.LLM_PROVIDER = ""
-            mock_settings.LLM_NAME = ""
-            reg._add_google_models(mock_settings)
-            assert len(reg.models) > 0
-
-    @pytest.mark.unit
-    def test_add_groq_models_with_key(self):
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.GROQ_API_KEY = "groq-test"
-            mock_settings.LLM_PROVIDER = ""
-            mock_settings.LLM_NAME = ""
-            reg._add_groq_models(mock_settings)
-            assert len(reg.models) > 0
-
-    @pytest.mark.unit
-    def test_add_openrouter_models_with_key(self):
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.OPEN_ROUTER_API_KEY = "or-test"
-            mock_settings.LLM_PROVIDER = ""
-            mock_settings.LLM_NAME = ""
-            reg._add_openrouter_models(mock_settings)
-            assert len(reg.models) > 0
-
-    @pytest.mark.unit
-    def test_add_novita_models_with_key(self):
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.NOVITA_API_KEY = "novita-test"
-            mock_settings.LLM_PROVIDER = ""
-            mock_settings.LLM_NAME = ""
-            reg._add_novita_models(mock_settings)
-            assert len(reg.models) > 0
-
-    @pytest.mark.unit
-    def test_add_azure_openai_models_specific(self):
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.LLM_PROVIDER = "azure_openai"
-            mock_settings.LLM_NAME = "nonexistent-model"
-            reg._add_azure_openai_models(mock_settings)
-            # Falls through to adding all azure models
-            assert len(reg.models) > 0
-
-    @pytest.mark.unit
-    def test_add_anthropic_models_no_key_with_provider(self):
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.ANTHROPIC_API_KEY = None
-            mock_settings.LLM_PROVIDER = "anthropic"
-            mock_settings.LLM_NAME = "nonexistent"
-            reg._add_anthropic_models(mock_settings)
-            assert len(reg.models) > 0
-
-    @pytest.mark.unit
-    def test_default_model_fallback_to_first(self):
-        mock_settings = MagicMock()
-        mock_settings.OPENAI_BASE_URL = None
-        mock_settings.OPENAI_API_KEY = None
-        mock_settings.OPENAI_API_BASE = None
-        mock_settings.ANTHROPIC_API_KEY = None
-        mock_settings.GOOGLE_API_KEY = None
-        mock_settings.GROQ_API_KEY = None
-        mock_settings.OPEN_ROUTER_API_KEY = None
-        mock_settings.NOVITA_API_KEY = None
-        mock_settings.HUGGINGFACE_API_KEY = None
-        mock_settings.LLM_PROVIDER = ""
-        mock_settings.LLM_NAME = ""
-        mock_settings.API_KEY = None
-
-        with patch("application.core.settings.settings", mock_settings):
-            reg = ModelRegistry()
-            # Should have at least docsgpt-local
-            assert reg.default_model_id is not None
-
-    @pytest.mark.unit
-    def test_default_model_from_provider_fallback(self):
-        """When LLM_NAME is not set but LLM_PROVIDER and API_KEY are,
-        default should be first model of that provider."""
-        mock_settings = MagicMock()
-        mock_settings.OPENAI_BASE_URL = None
-        mock_settings.OPENAI_API_KEY = "sk-test"
-        mock_settings.OPENAI_API_BASE = None
-        mock_settings.ANTHROPIC_API_KEY = None
-        mock_settings.GOOGLE_API_KEY = None
-        mock_settings.GROQ_API_KEY = None
-        mock_settings.OPEN_ROUTER_API_KEY = None
-        mock_settings.NOVITA_API_KEY = None
-        mock_settings.HUGGINGFACE_API_KEY = None
-        mock_settings.LLM_PROVIDER = "openai"
-        mock_settings.LLM_NAME = None
-        mock_settings.API_KEY = "sk-test"
-
-        with patch("application.core.settings.settings", mock_settings):
-            reg = ModelRegistry()
-            assert reg.default_model_id is not None
-
-    @pytest.mark.unit
-    def test_add_google_models_no_key_with_provider(self):
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.GOOGLE_API_KEY = None
-            mock_settings.LLM_PROVIDER = "google"
-            mock_settings.LLM_NAME = "nonexistent"
-            reg._add_google_models(mock_settings)
-            assert len(reg.models) > 0
-
-    @pytest.mark.unit
-    def test_add_groq_models_no_key_with_provider(self):
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.GROQ_API_KEY = None
-            mock_settings.LLM_PROVIDER = "groq"
-            mock_settings.LLM_NAME = "nonexistent"
-            reg._add_groq_models(mock_settings)
-            assert len(reg.models) > 0
-
-    @pytest.mark.unit
-    def test_add_openrouter_models_no_key_with_provider(self):
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.OPEN_ROUTER_API_KEY = None
-            mock_settings.LLM_PROVIDER = "openrouter"
-            mock_settings.LLM_NAME = "nonexistent"
-            reg._add_openrouter_models(mock_settings)
-            assert len(reg.models) > 0
-
-    @pytest.mark.unit
-    def test_add_novita_models_no_key_with_provider(self):
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.NOVITA_API_KEY = None
-            mock_settings.LLM_PROVIDER = "novita"
-            mock_settings.LLM_NAME = "nonexistent"
-            reg._add_novita_models(mock_settings)
-            assert len(reg.models) > 0
-
-    @pytest.mark.unit
-    def test_to_dict_disabled_model(self):
-        model = AvailableModel(
-            id="disabled",
-            provider=ModelProvider.OPENAI,
-            display_name="Disabled",
-            enabled=False,
-        )
-        d = model.to_dict()
-        assert d["enabled"] is False
-
-    @pytest.mark.unit
-    def test_to_dict_with_attachment_types(self):
-        caps = ModelCapabilities(
-            supported_attachment_types=["image/png", "application/pdf"],
-        )
-        model = AvailableModel(
-            id="vision",
-            provider=ModelProvider.OPENAI,
-            display_name="Vision",
-            capabilities=caps,
-        )
-        d = model.to_dict()
-        assert d["supported_attachment_types"] == ["image/png", "application/pdf"]
-
-    # ----------------------------------------------------------------
-    # Coverage for _add_* methods with matching LLM_NAME
-    # Lines: 100, 105, 147, 171, 179, 186, 199-201, 204, 210, 213,
-    #        218, 229, 233, 241, 250
-    # ----------------------------------------------------------------
-
-    @pytest.mark.unit
-    def test_add_azure_openai_models_with_matching_name(self):
-        """Cover line 186: azure model matching LLM_NAME returns early."""
-        from application.core.model_configs import AZURE_OPENAI_MODELS
-
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.LLM_PROVIDER = "azure_openai"
-            if AZURE_OPENAI_MODELS:
-                mock_settings.LLM_NAME = AZURE_OPENAI_MODELS[0].id
-            else:
-                mock_settings.LLM_NAME = "nonexistent"
-            reg._add_azure_openai_models(mock_settings)
-            # Should have added at least one model
-            assert len(reg.models) >= 1
-
-    @pytest.mark.unit
-    def test_add_anthropic_no_key_no_provider_fallthrough(self):
-        """Cover lines 199-204: no key, provider set but name not found -> add all."""
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.ANTHROPIC_API_KEY = None
-            mock_settings.LLM_PROVIDER = "anthropic"
-            mock_settings.LLM_NAME = "nonexistent-model"
-            reg._add_anthropic_models(mock_settings)
-            # Falls through to add all anthropic models
-            assert len(reg.models) > 0
-
-    @pytest.mark.unit
-    def test_add_google_no_key_matching_name(self):
-        """Cover lines 213-218: Google fallback with matching name."""
-        from application.core.model_configs import GOOGLE_MODELS
-
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.GOOGLE_API_KEY = None
-            mock_settings.LLM_PROVIDER = "google"
-            if GOOGLE_MODELS:
-                mock_settings.LLM_NAME = GOOGLE_MODELS[0].id
-            else:
-                mock_settings.LLM_NAME = "nonexistent"
-            reg._add_google_models(mock_settings)
-            assert len(reg.models) >= 1
-
-    @pytest.mark.unit
-    def test_add_groq_no_key_matching_name(self):
-        """Cover lines 229-233: Groq fallback with matching name."""
-        from application.core.model_configs import GROQ_MODELS
-
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.GROQ_API_KEY = None
-            mock_settings.LLM_PROVIDER = "groq"
-            if GROQ_MODELS:
-                mock_settings.LLM_NAME = GROQ_MODELS[0].id
-            else:
-                mock_settings.LLM_NAME = "nonexistent"
-            reg._add_groq_models(mock_settings)
-            assert len(reg.models) >= 1
-
-    @pytest.mark.unit
-    def test_add_openrouter_no_key_matching_name(self):
-        """Cover lines 241-250: OpenRouter fallback with matching name."""
-        from application.core.model_configs import OPENROUTER_MODELS
-
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.OPEN_ROUTER_API_KEY = None
-            mock_settings.LLM_PROVIDER = "openrouter"
-            if OPENROUTER_MODELS:
-                mock_settings.LLM_NAME = OPENROUTER_MODELS[0].id
-            else:
-                mock_settings.LLM_NAME = "nonexistent"
-            reg._add_openrouter_models(mock_settings)
-            assert len(reg.models) >= 1
-
-    @pytest.mark.unit
-    def test_add_novita_no_key_matching_name(self):
-        """Cover novita fallback with matching name."""
-        from application.core.model_configs import NOVITA_MODELS
-
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.NOVITA_API_KEY = None
-            mock_settings.LLM_PROVIDER = "novita"
-            if NOVITA_MODELS:
-                mock_settings.LLM_NAME = NOVITA_MODELS[0].id
-            else:
-                mock_settings.LLM_NAME = "nonexistent"
-            reg._add_novita_models(mock_settings)
-            assert len(reg.models) >= 1
-
-    @pytest.mark.unit
-    def test_load_models_default_from_llm_name_exact_match(self):
-        """Cover line 136/147: exact LLM_NAME match for default model."""
-        mock_settings = MagicMock()
-        mock_settings.OPENAI_BASE_URL = None
-        mock_settings.OPENAI_API_KEY = "sk-test"
-        mock_settings.OPENAI_API_BASE = None
-        mock_settings.ANTHROPIC_API_KEY = None
-        mock_settings.GOOGLE_API_KEY = None
-        mock_settings.GROQ_API_KEY = None
-        mock_settings.OPEN_ROUTER_API_KEY = None
-        mock_settings.NOVITA_API_KEY = None
-        mock_settings.HUGGINGFACE_API_KEY = None
-        mock_settings.LLM_PROVIDER = "openai"
-        mock_settings.API_KEY = None
-
-        from application.core.model_configs import OPENAI_MODELS
-
-        if OPENAI_MODELS:
-            mock_settings.LLM_NAME = OPENAI_MODELS[0].id
-        else:
-            mock_settings.LLM_NAME = "gpt-4o"
-
-        with patch("application.core.settings.settings", mock_settings):
-            reg = ModelRegistry()
-            assert reg.default_model_id is not None
-
-    @pytest.mark.unit
-    def test_add_openai_models_local_endpoint_no_name(self):
-        """Cover line 171: local endpoint without LLM_NAME adds nothing."""
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.OPENAI_BASE_URL = "http://localhost:11434/v1"
-            mock_settings.OPENAI_API_KEY = "sk-test"
-            mock_settings.LLM_NAME = None
-            reg._add_openai_models(mock_settings)
-            assert len(reg.models) == 0
-
-    @pytest.mark.unit
-    def test_add_openai_standard_no_api_key(self):
-        """Cover line 179: standard OpenAI without API key adds nothing."""
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.OPENAI_BASE_URL = None
-            mock_settings.OPENAI_API_KEY = None
-            reg._add_openai_models(mock_settings)
-            assert len(reg.models) == 0
-
-
-# ---------------------------------------------------------------------------
-# Coverage — additional uncovered lines: 100, 105, 147, 171, 179, 186, 250
-# ---------------------------------------------------------------------------
-
-
-@pytest.mark.unit
-class TestModelRegistryAdditionalCoverage:
-
-    def test_add_azure_openai_models_specific_name(self):
-        """Cover line 186: azure_openai with specific LLM_NAME match."""
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.LLM_PROVIDER = "azure_openai"
-            mock_settings.LLM_NAME = "gpt-4o"
-
-            # Create a fake model that matches
-            fake_model = MagicMock()
-            fake_model.id = "gpt-4o"
-            with patch(
-                "application.core.model_configs.AZURE_OPENAI_MODELS",
-                [fake_model],
-            ):
-                reg._add_azure_openai_models(mock_settings)
-            assert "gpt-4o" in reg.models
-
-    def test_add_anthropic_models_with_api_key(self):
-        """Cover line 100: anthropic with API key."""
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.ANTHROPIC_API_KEY = "sk-test"
-            mock_settings.LLM_PROVIDER = "anthropic"
-            reg._add_anthropic_models(mock_settings)
-            assert len(reg.models) > 0
-
-    def test_add_google_models_with_api_key(self):
-        """Cover line 105: google with API key."""
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.GOOGLE_API_KEY = "test-key"
-            mock_settings.LLM_PROVIDER = "google"
-            reg._add_google_models(mock_settings)
-            assert len(reg.models) > 0
-
-    def test_default_model_from_provider(self):
-        """Cover line 147: default model selected from provider."""
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            reg.default_model_id = None
-
-            fake_model = MagicMock()
-            fake_model.provider = MagicMock()
-            fake_model.provider.value = "openai"
-            reg.models["gpt-4o"] = fake_model
-
-            mock_settings = MagicMock()
-            mock_settings.LLM_NAME = None
-            mock_settings.LLM_PROVIDER = "openai"
-            mock_settings.API_KEY = "key"
-
-            # Simulate the default selection logic
-            if not reg.default_model_id:
-                for model_id, model in reg.models.items():
-                    if model.provider.value == mock_settings.LLM_PROVIDER:
-                        reg.default_model_id = model_id
-                        break
-
-            assert reg.default_model_id == "gpt-4o"
-
-    def test_add_openai_local_endpoint_with_llm_name(self):
-        """Cover line 171: local endpoint registers custom models from LLM_NAME."""
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.OPENAI_BASE_URL = "http://localhost:11434/v1"
-            mock_settings.OPENAI_API_KEY = "sk-test"
-            mock_settings.LLM_NAME = "llama3,phi3"
-            reg._add_openai_models(mock_settings)
-            assert "llama3" in reg.models
-            assert "phi3" in reg.models
-
-    def test_add_openai_standard_with_api_key(self):
-        """Cover line 179: standard OpenAI with API key adds models."""
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.OPENAI_BASE_URL = None
-            mock_settings.OPENAI_API_KEY = "sk-real-key"
-            reg._add_openai_models(mock_settings)
-            assert len(reg.models) > 0
-
-    def test_add_openrouter_models(self):
-        """Cover line 250: openrouter models added."""
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            mock_settings = MagicMock()
-            mock_settings.OPEN_ROUTER_API_KEY = "or-key"
-            mock_settings.LLM_PROVIDER = "openrouter"
-            reg._add_openrouter_models(mock_settings)
-            assert len(reg.models) > 0
-
-
-# ---------------------------------------------------------------------------
-# Additional coverage for model_settings.py
-# Lines: 135-136 (backward compat LLM_NAME), 138-143 (provider fallback),
-# 145-146 (first model as default)
-# ---------------------------------------------------------------------------
-# Imports already at the top of the file; no additional imports needed
-
-
-@pytest.mark.unit
-class TestDefaultModelSelectionBackwardCompat:
-    """Cover lines 135-136: backward compat exact match on LLM_NAME."""
-
-    def test_llm_name_exact_match_as_default(self):
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            reg.default_model_id = None
-            # Add a model with composite ID
-            model = AvailableModel(
-                id="my-composite-model",
-                provider=ModelProvider.OPENAI,
-                display_name="Composite",
-                description="test",
-                capabilities=ModelCapabilities(),
+            reg.models["m1"] = AvailableModel(
+                id="m1", provider=ModelProvider.OPENAI, display_name="M1"
             )
-            reg.models["my-composite-model"] = model
+            assert reg.get_model("m1", user_id="alice") is not None
+            assert reg.model_exists("m1", user_id="alice") is True
+            assert len(reg.get_all_models(user_id="alice")) == 1
+            assert len(reg.get_enabled_models(user_id="alice")) == 1
 
-            # Simulate _parse_model_names returning something different
-            # so that the first for-loop doesn't match
-            mock_settings = MagicMock()
-            mock_settings.LLM_NAME = "my-composite-model"
-            mock_settings.LLM_PROVIDER = None
-            mock_settings.API_KEY = None
-
-            # Call the logic directly
-            model_names = reg._parse_model_names(mock_settings.LLM_NAME)
-            for mn in model_names:
-                if mn in reg.models:
-                    reg.default_model_id = mn
-                    break
-
-            assert reg.default_model_id == "my-composite-model"
-
-
-@pytest.mark.unit
-class TestDefaultModelSelectionByProvider:
-    """Cover lines 138-143: default model by provider when LLM_NAME doesn't match."""
-
-    def test_default_by_provider(self):
+    @pytest.mark.unit
+    def test_reset(self):
         with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            reg.default_model_id = None
-            model = AvailableModel(
-                id="gpt-4",
-                provider=ModelProvider.OPENAI,
-                display_name="GPT-4",
-                description="test",
-                capabilities=ModelCapabilities(),
-            )
-            reg.models["gpt-4"] = model
-
-            # Simulate: LLM_NAME doesn't exist/match, but LLM_PROVIDER + API_KEY set
-            if not reg.default_model_id:
-                for model_id, m in reg.models.items():
-                    if m.provider.value == "openai":
-                        reg.default_model_id = model_id
-                        break
-
-            assert reg.default_model_id == "gpt-4"
-
-
-@pytest.mark.unit
-class TestDefaultModelSelectionFirstModel:
-    """Cover lines 145-146: first model as default when nothing else matches."""
-
-    def test_first_model_as_default(self):
-        with patch.object(ModelRegistry, "_load_models"):
-            reg = ModelRegistry()
-            reg.models = {}
-            reg.default_model_id = None
-            model = AvailableModel(
-                id="fallback-model",
-                provider=ModelProvider.OPENAI,
-                display_name="Fallback",
-                description="test",
-                capabilities=ModelCapabilities(),
-            )
-            reg.models["fallback-model"] = model
-
-            if not reg.default_model_id and reg.models:
-                reg.default_model_id = next(iter(reg.models.keys()))
-
-            assert reg.default_model_id == "fallback-model"
+            r1 = ModelRegistry()
+            ModelRegistry.reset()
+            r2 = ModelRegistry()
+            assert r1 is not r2

tests/core/test_models_config_dir.py

@@ -0,0 +1,208 @@
+"""Phase 3 tests: operator MODELS_CONFIG_DIR.
+
+Covers the operator-supplied directory of model YAMLs that's loaded
+after the built-in catalog. Operators use this to add new
+``openai_compatible`` providers, extend an existing provider's catalog
+with extra models, or override a built-in model's capabilities — all
+without forking the repo.
+"""
+
+from __future__ import annotations
+
+import logging
+from textwrap import dedent
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from application.core.model_registry import ModelRegistry
+
+
+def _make_settings(**overrides):
+    s = MagicMock()
+    s.OPENAI_BASE_URL = None
+    s.OPENAI_API_KEY = None
+    s.OPENAI_API_BASE = None
+    s.ANTHROPIC_API_KEY = None
+    s.GOOGLE_API_KEY = None
+    s.GROQ_API_KEY = None
+    s.OPEN_ROUTER_API_KEY = None
+    s.NOVITA_API_KEY = None
+    s.HUGGINGFACE_API_KEY = None
+    s.LLM_PROVIDER = ""
+    s.LLM_NAME = None
+    s.API_KEY = None
+    s.MODELS_CONFIG_DIR = None
+    for k, v in overrides.items():
+        setattr(s, k, v)
+    return s
+
+
+@pytest.fixture(autouse=True)
+def _reset_registry():
+    ModelRegistry.reset()
+    yield
+    ModelRegistry.reset()
+
+
+# ── New provider via openai_compatible ───────────────────────────────────
+
+
+@pytest.mark.unit
+class TestOperatorAddsNewProvider:
+    def test_drop_in_yaml_appears_in_registry(
+        self, tmp_path, monkeypatch
+    ):
+        (tmp_path / "fireworks.yaml").write_text(dedent("""
+            provider: openai_compatible
+            display_provider: fireworks
+            api_key_env: FIREWORKS_API_KEY
+            base_url: https://api.fireworks.ai/inference/v1
+            defaults:
+              supports_tools: true
+            models:
+              - id: accounts/fireworks/models/llama-v3p3-70b-instruct
+                display_name: Llama 3.3 70B (Fireworks)
+        """))
+        monkeypatch.setenv("FIREWORKS_API_KEY", "fw-key")
+
+        s = _make_settings(MODELS_CONFIG_DIR=str(tmp_path))
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+
+        m = reg.get_model("accounts/fireworks/models/llama-v3p3-70b-instruct")
+        assert m is not None
+        assert m.api_key == "fw-key"
+        assert m.base_url == "https://api.fireworks.ai/inference/v1"
+        assert m.display_provider == "fireworks"
+
+
+# ── Extending an existing provider's catalog ─────────────────────────────
+
+
+@pytest.mark.unit
+class TestOperatorExtendsExistingProvider:
+    def test_operator_adds_anthropic_model_to_builtin_catalog(
+        self, tmp_path
+    ):
+        (tmp_path / "anthropic-extra.yaml").write_text(dedent("""
+            provider: anthropic
+            defaults:
+              supports_tools: true
+              context_window: 200000
+            models:
+              - id: claude-haiku-5-0-future
+                display_name: Claude Haiku 5.0
+        """))
+
+        s = _make_settings(
+            ANTHROPIC_API_KEY="sk-ant",
+            MODELS_CONFIG_DIR=str(tmp_path),
+        )
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+
+        # Built-in models still present
+        assert reg.get_model("claude-sonnet-4-6") is not None
+        assert reg.get_model("claude-opus-4-7") is not None
+        # Operator-added model also present
+        added = reg.get_model("claude-haiku-5-0-future")
+        assert added is not None
+        assert added.display_name == "Claude Haiku 5.0"
+
+
+# ── Overriding a built-in model's capabilities ───────────────────────────
+
+
+@pytest.mark.unit
+class TestOperatorOverridesBuiltinCapabilities:
+    def test_operator_yaml_overrides_builtin_context_window(
+        self, tmp_path, caplog
+    ):
+        # Override anthropic claude-haiku-4-5 to claim a 1M context window
+        (tmp_path / "anthropic-override.yaml").write_text(dedent("""
+            provider: anthropic
+            defaults:
+              supports_tools: true
+              attachments: [image]
+              context_window: 1000000
+            models:
+              - id: claude-haiku-4-5
+                display_name: Claude Haiku 4.5 (extended)
+                description: Operator-overridden capabilities
+        """))
+
+        s = _make_settings(
+            ANTHROPIC_API_KEY="sk-ant",
+            MODELS_CONFIG_DIR=str(tmp_path),
+        )
+        with caplog.at_level(logging.WARNING):
+            with patch("application.core.settings.settings", s):
+                reg = ModelRegistry()
+
+        m = reg.get_model("claude-haiku-4-5")
+        assert m.display_name == "Claude Haiku 4.5 (extended)"
+        assert m.description == "Operator-overridden capabilities"
+        assert m.capabilities.context_window == 1_000_000
+
+        # And the override warning fires so the operator can audit it
+        assert any(
+            "claude-haiku-4-5" in rec.message and "redefined" in rec.message
+            for rec in caplog.records
+        )
+
+
+# ── Misconfigured MODELS_CONFIG_DIR ──────────────────────────────────────
+
+
+@pytest.mark.unit
+class TestMisconfiguredOperatorDir:
+    def test_missing_dir_logs_warning_and_continues(
+        self, tmp_path, caplog
+    ):
+        bogus = tmp_path / "does-not-exist"
+        s = _make_settings(MODELS_CONFIG_DIR=str(bogus))
+
+        with caplog.at_level(logging.WARNING):
+            with patch("application.core.settings.settings", s):
+                reg = ModelRegistry()
+
+        # Built-in catalog still loaded
+        assert reg.get_model("docsgpt-local") is not None
+        # And the operator was warned
+        assert any("does not exist" in rec.message for rec in caplog.records)
+
+    def test_path_is_a_file_logs_warning(self, tmp_path, caplog):
+        afile = tmp_path / "not-a-dir.yaml"
+        afile.write_text("provider: anthropic\nmodels: []")
+
+        s = _make_settings(MODELS_CONFIG_DIR=str(afile))
+        with caplog.at_level(logging.WARNING):
+            with patch("application.core.settings.settings", s):
+                reg = ModelRegistry()
+
+        assert reg.get_model("docsgpt-local") is not None
+        assert any("not a directory" in rec.message for rec in caplog.records)
+
+
+# ── Validation: unknown provider rejected ────────────────────────────────
+
+
+@pytest.mark.unit
+class TestOperatorValidation:
+    def test_unknown_provider_in_operator_yaml_aborts_boot(self, tmp_path):
+        (tmp_path / "bogus.yaml").write_text(dedent("""
+            provider: not_a_real_provider
+            models:
+              - id: x
+                display_name: X
+        """))
+
+        s = _make_settings(MODELS_CONFIG_DIR=str(tmp_path))
+        with patch("application.core.settings.settings", s):
+            with pytest.raises(Exception) as exc_info:
+                ModelRegistry()
+        # Could be ModelYAMLError (enum check) or ValueError (registry check);
+        # either way the message must surface what's wrong.
+        msg = str(exc_info.value)
+        assert "not_a_real_provider" in msg

tests/core/test_openai_compatible.py

@@ -0,0 +1,298 @@
+"""Phase 2 tests for the openai_compatible provider.
+
+Covers YAML loading from a temp directory, multiple coexisting catalogs
+(Mistral + Together), env-var-based credential resolution, the legacy
+OPENAI_BASE_URL + LLM_NAME fallback, and end-to-end model dispatch
+through LLMCreator.
+"""
+
+from __future__ import annotations
+
+from pathlib import Path
+from textwrap import dedent
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from application.core.model_registry import ModelRegistry
+from application.core.model_settings import ModelProvider
+
+
+def _make_settings(**overrides):
+    s = MagicMock()
+    s.OPENAI_BASE_URL = None
+    s.OPENAI_API_KEY = None
+    s.OPENAI_API_BASE = None
+    s.ANTHROPIC_API_KEY = None
+    s.GOOGLE_API_KEY = None
+    s.GROQ_API_KEY = None
+    s.OPEN_ROUTER_API_KEY = None
+    s.NOVITA_API_KEY = None
+    s.HUGGINGFACE_API_KEY = None
+    s.LLM_PROVIDER = ""
+    s.LLM_NAME = None
+    s.API_KEY = None
+    s.MODELS_CONFIG_DIR = None
+    for k, v in overrides.items():
+        setattr(s, k, v)
+    return s
+
+
+def _write_mistral_yaml(directory: Path) -> Path:
+    path = directory / "mistral.yaml"
+    path.write_text(dedent("""
+        provider: openai_compatible
+        display_provider: mistral
+        api_key_env: MISTRAL_API_KEY
+        base_url: https://api.mistral.ai/v1
+        defaults:
+          supports_tools: true
+          context_window: 128000
+        models:
+          - id: mistral-large-latest
+            display_name: Mistral Large
+          - id: mistral-small-latest
+            display_name: Mistral Small
+    """))
+    return path
+
+
+def _write_together_yaml(directory: Path) -> Path:
+    path = directory / "together.yaml"
+    path.write_text(dedent("""
+        provider: openai_compatible
+        display_provider: together
+        api_key_env: TOGETHER_API_KEY
+        base_url: https://api.together.xyz/v1
+        defaults:
+          supports_tools: true
+        models:
+          - id: meta-llama/Llama-3.3-70B-Instruct-Turbo
+            display_name: Llama 3.3 70B (Together)
+    """))
+    return path
+
+
+@pytest.fixture(autouse=True)
+def _reset_registry():
+    ModelRegistry.reset()
+    yield
+    ModelRegistry.reset()
+
+
+# ── YAML-driven catalogs ─────────────────────────────────────────────────
+
+
+@pytest.mark.unit
+class TestYAMLCompatibleProvider:
+    def test_mistral_yaml_loads_with_env_key(
+        self, tmp_path, monkeypatch
+    ):
+        _write_mistral_yaml(tmp_path)
+        monkeypatch.setenv("MISTRAL_API_KEY", "sk-mistral-test")
+
+        s = _make_settings(MODELS_CONFIG_DIR=str(tmp_path))
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+
+        m = reg.get_model("mistral-large-latest")
+        assert m is not None
+        assert m.provider == ModelProvider.OPENAI_COMPATIBLE
+        assert m.display_provider == "mistral"
+        assert m.base_url == "https://api.mistral.ai/v1"
+        assert m.api_key == "sk-mistral-test"
+        assert m.capabilities.supports_tools is True
+        assert m.capabilities.context_window == 128000
+
+    def test_yaml_skipped_when_env_var_missing(
+        self, tmp_path, monkeypatch
+    ):
+        _write_mistral_yaml(tmp_path)
+        monkeypatch.delenv("MISTRAL_API_KEY", raising=False)
+
+        s = _make_settings(MODELS_CONFIG_DIR=str(tmp_path))
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+
+        # Catalog skipped when no key — no Mistral models in the registry
+        assert reg.get_model("mistral-large-latest") is None
+
+    def test_two_compatible_catalogs_coexist_with_separate_keys(
+        self, tmp_path, monkeypatch
+    ):
+        _write_mistral_yaml(tmp_path)
+        _write_together_yaml(tmp_path)
+        monkeypatch.setenv("MISTRAL_API_KEY", "sk-mistral")
+        monkeypatch.setenv("TOGETHER_API_KEY", "sk-together")
+
+        s = _make_settings(MODELS_CONFIG_DIR=str(tmp_path))
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+
+        mistral = reg.get_model("mistral-large-latest")
+        together = reg.get_model("meta-llama/Llama-3.3-70B-Instruct-Turbo")
+
+        assert mistral.api_key == "sk-mistral"
+        assert mistral.base_url == "https://api.mistral.ai/v1"
+        assert mistral.display_provider == "mistral"
+
+        assert together.api_key == "sk-together"
+        assert together.base_url == "https://api.together.xyz/v1"
+        assert together.display_provider == "together"
+
+    def test_one_catalog_enabled_other_skipped(
+        self, tmp_path, monkeypatch
+    ):
+        _write_mistral_yaml(tmp_path)
+        _write_together_yaml(tmp_path)
+        monkeypatch.setenv("MISTRAL_API_KEY", "sk-mistral")
+        monkeypatch.delenv("TOGETHER_API_KEY", raising=False)
+
+        s = _make_settings(MODELS_CONFIG_DIR=str(tmp_path))
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+
+        assert reg.get_model("mistral-large-latest") is not None
+        assert reg.get_model("meta-llama/Llama-3.3-70B-Instruct-Turbo") is None
+
+    def test_missing_base_url_raises(self, tmp_path, monkeypatch):
+        bad = tmp_path / "broken.yaml"
+        bad.write_text(dedent("""
+            provider: openai_compatible
+            api_key_env: SOME_KEY
+            models:
+              - id: x
+                display_name: X
+        """))
+        monkeypatch.setenv("SOME_KEY", "k")
+
+        s = _make_settings(MODELS_CONFIG_DIR=str(tmp_path))
+        with patch("application.core.settings.settings", s):
+            with pytest.raises(ValueError, match="must set 'base_url'"):
+                ModelRegistry()
+
+    def test_missing_api_key_env_raises(self, tmp_path, monkeypatch):
+        bad = tmp_path / "broken.yaml"
+        bad.write_text(dedent("""
+            provider: openai_compatible
+            base_url: https://x/v1
+            models:
+              - id: x
+                display_name: X
+        """))
+
+        s = _make_settings(MODELS_CONFIG_DIR=str(tmp_path))
+        with patch("application.core.settings.settings", s):
+            with pytest.raises(ValueError, match="must set 'api_key_env'"):
+                ModelRegistry()
+
+    def test_to_dict_uses_display_provider(
+        self, tmp_path, monkeypatch
+    ):
+        _write_mistral_yaml(tmp_path)
+        monkeypatch.setenv("MISTRAL_API_KEY", "sk")
+
+        s = _make_settings(MODELS_CONFIG_DIR=str(tmp_path))
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+
+        d = reg.get_model("mistral-large-latest").to_dict()
+        # /api/models response shows "mistral", not "openai_compatible"
+        assert d["provider"] == "mistral"
+        # api_key never leaks into the wire format
+        assert "api_key" not in d
+        for v in d.values():
+            assert v != "sk"
+
+
+# ── Legacy OPENAI_BASE_URL fallback ──────────────────────────────────────
+
+
+@pytest.mark.unit
+class TestLegacyOpenAIBaseURLPath:
+    def test_legacy_models_now_provided_by_openai_compatible(self):
+        s = _make_settings(
+            OPENAI_BASE_URL="http://localhost:11434/v1",
+            OPENAI_API_KEY="sk-local",
+            LLM_PROVIDER="openai",
+            LLM_NAME="llama3,gemma",
+        )
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+
+        ids = {m.id for m in reg.get_all_models()}
+        assert ids == {"llama3", "gemma"}
+
+        llama = reg.get_model("llama3")
+        assert llama.base_url == "http://localhost:11434/v1"
+        assert llama.api_key == "sk-local"
+        assert llama.provider == ModelProvider.OPENAI_COMPATIBLE
+        # Display provider preserves the historical "openai" label
+        assert llama.display_provider == "openai"
+        assert llama.to_dict()["provider"] == "openai"
+
+    def test_legacy_uses_api_key_fallback_when_openai_api_key_missing(self):
+        s = _make_settings(
+            OPENAI_BASE_URL="http://localhost:11434/v1",
+            OPENAI_API_KEY=None,
+            API_KEY="sk-generic",
+            LLM_PROVIDER="openai",
+            LLM_NAME="llama3",
+        )
+        with patch("application.core.settings.settings", s):
+            reg = ModelRegistry()
+        assert reg.get_model("llama3").api_key == "sk-generic"
+
+
+# ── Dispatch through LLMCreator ──────────────────────────────────────────
+
+
+@pytest.mark.unit
+class TestLLMCreatorDispatch:
+    def test_llmcreator_uses_per_model_api_key_and_base_url(
+        self, tmp_path, monkeypatch
+    ):
+        """End-to-end: when an openai_compatible model is dispatched, the
+        per-model api_key + base_url from the registry must override
+        whatever the caller passed."""
+        _write_mistral_yaml(tmp_path)
+        monkeypatch.setenv("MISTRAL_API_KEY", "sk-mistral-real")
+
+        s = _make_settings(MODELS_CONFIG_DIR=str(tmp_path))
+
+        captured = {}
+
+        class _FakeLLM:
+            def __init__(
+                self, api_key, user_api_key, *args, **kwargs
+            ):
+                captured["api_key"] = api_key
+                captured["base_url"] = kwargs.get("base_url")
+                captured["model_id"] = kwargs.get("model_id")
+
+        with patch("application.core.settings.settings", s):
+            ModelRegistry.reset()
+            ModelRegistry()  # warm up the registry under patched settings
+
+            # Now patch the OpenAI plugin's class so we can capture the
+            # constructor args without spinning up the real OpenAILLM.
+            from application.llm.providers import PROVIDERS_BY_NAME
+
+            with patch.object(
+                PROVIDERS_BY_NAME["openai_compatible"],
+                "llm_class",
+                _FakeLLM,
+            ):
+                from application.llm.llm_creator import LLMCreator
+
+                LLMCreator.create_llm(
+                    type="openai_compatible",
+                    api_key="caller-passed-WRONG-key",
+                    user_api_key=None,
+                    decoded_token={"sub": "u"},
+                    model_id="mistral-large-latest",
+                )
+
+        assert captured["api_key"] == "sk-mistral-real"
+        assert captured["base_url"] == "https://api.mistral.ai/v1"
+        assert captured["model_id"] == "mistral-large-latest"