feat!: breaking change - OpenRouter models are now read from conf/openrouter_models.json while Custom / Self-hosted models are read from conf/custom_models.json

feat: Azure OpenAI / Azure AI Foundry support. Models should be defined in conf/azure_models.json (or a custom path). See .env.example for environment variables or see readme. https://github.com/BeehiveInnovations/zen-mcp-server/issues/265

feat: OpenRouter / Custom Models / Azure can separately also use custom config paths now (see .env.example )

refactor: Model registry class made abstract, OpenRouter / Custom Provider / Azure OpenAI now subclass these

refactor: breaking change: `is_custom` property has been removed from model_capabilities.py (and thus custom_models.json) given each models are now read from separate configuration files

tests/test_azure_openai_provider.py

@@ -0,0 +1,145 @@
+import sys
+import types
+
+import pytest
+
+if "openai" not in sys.modules:  # pragma: no cover - test shim for optional dependency
+    stub = types.ModuleType("openai")
+    stub.AzureOpenAI = object  # Replaced with a mock inside tests
+    sys.modules["openai"] = stub
+
+from providers.azure_openai import AzureOpenAIProvider
+from providers.shared import ModelCapabilities, ProviderType
+
+
+class _DummyResponse:
+    def __init__(self):
+        self.choices = [
+            types.SimpleNamespace(
+                message=types.SimpleNamespace(content="hello"),
+                finish_reason="stop",
+            )
+        ]
+        self.model = "prod-gpt4o"
+        self.id = "resp-123"
+        self.created = 0
+        self.usage = types.SimpleNamespace(
+            prompt_tokens=5,
+            completion_tokens=3,
+            total_tokens=8,
+        )
+
+
+@pytest.fixture
+def dummy_azure_client(monkeypatch):
+    captured = {}
+
+    class _DummyAzureClient:
+        def __init__(self, **kwargs):
+            captured["client_kwargs"] = kwargs
+            self.chat = types.SimpleNamespace(completions=types.SimpleNamespace(create=self._create_completion))
+            self.responses = types.SimpleNamespace(create=self._create_response)
+
+        def _create_completion(self, **kwargs):
+            captured["request_kwargs"] = kwargs
+            return _DummyResponse()
+
+        def _create_response(self, **kwargs):
+            captured["responses_kwargs"] = kwargs
+            return _DummyResponse()
+
+    monkeypatch.delenv("AZURE_OPENAI_ALLOWED_MODELS", raising=False)
+    monkeypatch.setattr("providers.azure_openai.AzureOpenAI", _DummyAzureClient)
+    return captured
+
+
+def test_generate_content_uses_deployment_mapping(dummy_azure_client):
+    provider = AzureOpenAIProvider(
+        api_key="key",
+        azure_endpoint="https://example.openai.azure.com/",
+        deployments={"gpt-4o": "prod-gpt4o"},
+    )
+
+    result = provider.generate_content("hello", "gpt-4o")
+
+    assert dummy_azure_client["request_kwargs"]["model"] == "prod-gpt4o"
+    assert result.model_name == "gpt-4o"
+    assert result.provider == ProviderType.AZURE
+    assert provider.validate_model_name("prod-gpt4o")
+
+
+def test_generate_content_accepts_deployment_alias(dummy_azure_client):
+    provider = AzureOpenAIProvider(
+        api_key="key",
+        azure_endpoint="https://example.openai.azure.com/",
+        deployments={"gpt-4o-mini": "mini-deployment"},
+    )
+
+    # Calling with the deployment alias should still resolve properly.
+    result = provider.generate_content("hi", "mini-deployment")
+
+    assert dummy_azure_client["request_kwargs"]["model"] == "mini-deployment"
+    assert result.model_name == "gpt-4o-mini"
+
+
+def test_client_initialization_uses_endpoint_and_version(dummy_azure_client):
+    provider = AzureOpenAIProvider(
+        api_key="key",
+        azure_endpoint="https://example.openai.azure.com/",
+        api_version="2024-03-15-preview",
+        deployments={"gpt-4o": "prod"},
+    )
+
+    _ = provider.client
+
+    assert dummy_azure_client["client_kwargs"]["azure_endpoint"] == "https://example.openai.azure.com"
+    assert dummy_azure_client["client_kwargs"]["api_version"] == "2024-03-15-preview"
+
+
+def test_deployment_overrides_capabilities(dummy_azure_client):
+    provider = AzureOpenAIProvider(
+        api_key="key",
+        azure_endpoint="https://example.openai.azure.com/",
+        deployments={
+            "gpt-4o": {
+                "deployment": "prod-gpt4o",
+                "friendly_name": "Azure GPT-4o EU",
+                "intelligence_score": 19,
+                "supports_temperature": False,
+                "temperature_constraint": "fixed",
+            }
+        },
+    )
+
+    caps = provider.get_capabilities("gpt-4o")
+    assert caps.friendly_name == "Azure GPT-4o EU"
+    assert caps.intelligence_score == 19
+    assert not caps.supports_temperature
+
+
+def test_registry_configuration_merges_capabilities(dummy_azure_client, monkeypatch):
+    def fake_registry_entries(self):
+        capability = ModelCapabilities(
+            provider=ProviderType.AZURE,
+            model_name="gpt-4o",
+            friendly_name="Azure GPT-4o Registry",
+            context_window=500_000,
+            max_output_tokens=128_000,
+        )
+        return {"gpt-4o": {"deployment": "registry-deployment", "capability": capability}}
+
+    monkeypatch.setattr(AzureOpenAIProvider, "_load_registry_entries", fake_registry_entries)
+
+    provider = AzureOpenAIProvider(
+        api_key="key",
+        azure_endpoint="https://example.openai.azure.com/",
+    )
+
+    # Capability should come from registry
+    caps = provider.get_capabilities("gpt-4o")
+    assert caps.friendly_name == "Azure GPT-4o Registry"
+    assert caps.context_window == 500_000
+
+    # API call should use deployment defined in registry
+    provider.generate_content("hello", "gpt-4o")
+    assert dummy_azure_client["request_kwargs"]["model"] == "registry-deployment"