Add unit tests for OpenRouter model discovery

Tests cover:
- Model list validation (non-empty, valid types)
- Provider prefix validation (all models have provider/)
- Data validation (positive dimensions, non-negative pricing)
- Provider validation (valid provider names)
- Specific provider models (OpenAI, Qwen)
- Model ID validation (requires prefix)

All 11 tests passing.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

python/tests/test_openrouter_discovery.py

@@ -0,0 +1,158 @@
+"""
+Unit tests for OpenRouter model discovery service.
+"""
+
+import pytest
+
+from src.server.services.openrouter_discovery_service import (
+    OpenRouterDiscoveryService,
+    OpenRouterEmbeddingModel,
+    OpenRouterModelListResponse,
+)
+
+
+@pytest.fixture
+def discovery_service():
+    """Create OpenRouter discovery service instance."""
+    return OpenRouterDiscoveryService()
+
+
+@pytest.mark.asyncio
+async def test_discover_embedding_models_returns_valid_list(discovery_service):
+    """Test that discover_embedding_models returns a non-empty list of models."""
+    models = await discovery_service.discover_embedding_models()
+
+    assert isinstance(models, list)
+    assert len(models) > 0
+    assert all(isinstance(model, OpenRouterEmbeddingModel) for model in models)
+
+
+@pytest.mark.asyncio
+async def test_all_models_have_provider_prefix(discovery_service):
+    """Test that all model IDs include provider prefix."""
+    models = await discovery_service.discover_embedding_models()
+
+    for model in models:
+        assert "/" in model.id, f"Model ID '{model.id}' missing provider prefix"
+        assert model.id.startswith(
+            f"{model.provider}/"
+        ), f"Model ID '{model.id}' doesn't match provider '{model.provider}'"
+
+
+@pytest.mark.asyncio
+async def test_dimensions_are_positive_integers(discovery_service):
+    """Test that all models have positive integer dimensions."""
+    models = await discovery_service.discover_embedding_models()
+
+    for model in models:
+        assert isinstance(model.dimensions, int), f"Model '{model.id}' dimensions is not an integer"
+        assert model.dimensions > 0, f"Model '{model.id}' has non-positive dimensions: {model.dimensions}"
+
+
+@pytest.mark.asyncio
+async def test_pricing_is_non_negative(discovery_service):
+    """Test that all models have non-negative pricing."""
+    models = await discovery_service.discover_embedding_models()
+
+    for model in models:
+        assert isinstance(
+            model.pricing_per_1m_tokens, (int, float)
+        ), f"Model '{model.id}' pricing is not numeric"
+        assert (
+            model.pricing_per_1m_tokens >= 0
+        ), f"Model '{model.id}' has negative pricing: {model.pricing_per_1m_tokens}"
+
+
+@pytest.mark.asyncio
+async def test_context_length_is_positive(discovery_service):
+    """Test that all models have positive context length."""
+    models = await discovery_service.discover_embedding_models()
+
+    for model in models:
+        assert isinstance(
+            model.context_length, int
+        ), f"Model '{model.id}' context_length is not an integer"
+        assert (
+            model.context_length > 0
+        ), f"Model '{model.id}' has non-positive context_length: {model.context_length}"
+
+
+@pytest.mark.asyncio
+async def test_model_providers_are_valid(discovery_service):
+    """Test that all models have valid provider names."""
+    models = await discovery_service.discover_embedding_models()
+    valid_providers = {"openai", "google", "qwen", "mistralai"}
+
+    for model in models:
+        assert (
+            model.provider in valid_providers
+        ), f"Model '{model.id}' has invalid provider: {model.provider}"
+
+
+@pytest.mark.asyncio
+async def test_openai_models_present(discovery_service):
+    """Test that OpenAI models are included in the list."""
+    models = await discovery_service.discover_embedding_models()
+    openai_models = [m for m in models if m.provider == "openai"]
+
+    assert len(openai_models) > 0, "No OpenAI models found"
+    assert any(
+        "text-embedding-3-small" in m.id for m in openai_models
+    ), "text-embedding-3-small not found"
+    assert any(
+        "text-embedding-3-large" in m.id for m in openai_models
+    ), "text-embedding-3-large not found"
+
+
+@pytest.mark.asyncio
+async def test_qwen_models_present(discovery_service):
+    """Test that Qwen models are included in the list."""
+    models = await discovery_service.discover_embedding_models()
+    qwen_models = [m for m in models if m.provider == "qwen"]
+
+    assert len(qwen_models) > 0, "No Qwen models found"
+    # Verify at least one Qwen3 embedding model is present
+    assert any("qwen3-embedding" in m.id for m in qwen_models), "No Qwen3 embedding models found"
+
+
+@pytest.mark.asyncio
+async def test_model_list_response_structure():
+    """Test OpenRouterModelListResponse structure."""
+    service = OpenRouterDiscoveryService()
+    models = await service.discover_embedding_models()
+
+    response = OpenRouterModelListResponse(embedding_models=models, total_count=len(models))
+
+    assert response.total_count == len(models)
+    assert response.total_count == len(response.embedding_models)
+    assert response.total_count > 0
+
+
+def test_model_id_validation_requires_prefix():
+    """Test that model ID validation enforces provider prefix."""
+    with pytest.raises(ValueError, match="must include provider prefix"):
+        OpenRouterEmbeddingModel(
+            id="text-embedding-3-small",  # Missing provider prefix
+            provider="openai",
+            name="text-embedding-3-small",
+            dimensions=1536,
+            context_length=8191,
+            pricing_per_1m_tokens=0.02,
+            supports_dimension_reduction=True,
+        )
+
+
+def test_model_with_valid_prefix_accepted():
+    """Test that model with valid provider prefix is accepted."""
+    model = OpenRouterEmbeddingModel(
+        id="openai/text-embedding-3-small",
+        provider="openai",
+        name="text-embedding-3-small",
+        dimensions=1536,
+        context_length=8191,
+        pricing_per_1m_tokens=0.02,
+        supports_dimension_reduction=True,
+    )
+
+    assert model.id == "openai/text-embedding-3-small"
+    assert "/" in model.id