Add unit and integration tests for synthetic data kit provider

These tests follow Llama Stack's provider
testing guidelines to validate:
- Configuration handling and environment variables work as expected
- Provider implementation behaves correctly in both unit and integration scenarios
- Error cases are properly handled
- Integration with Llama Stack's client SDK functions properly

Signed-off-by: Alina Ryan <aliryan@redhat.com>

tests/integration/providers/inline/synthetic_data_generation/test_synthetic_data_kit_integration.py

@@ -0,0 +1,101 @@
+import os
+import pytest
+from typing import cast
+
+from llama_stack.apis.inference import Message
+from llama_stack.apis.synthetic_data_generation import (
+    SyntheticDataGeneration,
+    FilteringFunction,
+)
+from llama_stack.apis.synthetic_data_generation.providers import get_provider_impl
+from llama_stack.distribution.client import LlamaStackAsLibraryClient
+
+
+@pytest.fixture
+async def client():
+    # Use LlamaStackAsLibraryClient for inline testing
+    return LlamaStackAsLibraryClient()
+
+
+@pytest.mark.asyncio
+async def test_synthetic_data_kit_provider_integration(client: LlamaStackAsLibraryClient):
+    provider = await get_provider_impl()
+    assert isinstance(provider, SyntheticDataGeneration)
+
+    # Test single message generation
+    dialogs = [
+        Message(role="user", content="What is artificial intelligence?"),
+    ]
+    
+    response = await provider.synthetic_data_generate(
+        dialogs=dialogs,
+        filtering_function=FilteringFunction.none,
+    )
+    
+    assert response.synthetic_data is not None
+    assert len(response.synthetic_data) > 0
+    assert all(isinstance(item, dict) for item in response.synthetic_data)
+    assert all("question" in item and "answer" in item for item in response.synthetic_data)
+
+
+@pytest.mark.asyncio
+async def test_synthetic_data_kit_provider_with_filtering(client: LlamaStackAsLibraryClient):
+    provider = await get_provider_impl()
+    
+    # Test generation with filtering
+    dialogs = [
+        Message(role="user", content="Explain quantum computing."),
+        Message(role="assistant", content="Quantum computing uses quantum mechanics..."),
+    ]
+    
+    response = await provider.synthetic_data_generate(
+        dialogs=dialogs,
+        filtering_function=FilteringFunction.top_k,
+    )
+    
+    assert response.synthetic_data is not None
+    assert len(response.synthetic_data) > 0
+    assert response.statistics is not None
+    assert "threshold" in response.statistics
+
+
+@pytest.mark.asyncio
+async def test_synthetic_data_kit_provider_error_handling(client: LlamaStackAsLibraryClient):
+    provider = await get_provider_impl()
+    
+    # Test with empty dialogs
+    with pytest.raises(ValueError):
+        await provider.synthetic_data_generate(
+            dialogs=[],
+            filtering_function=FilteringFunction.none,
+        )
+    
+    # Test with invalid model
+    with pytest.raises(RuntimeError):
+        await provider.synthetic_data_generate(
+            dialogs=[Message(role="user", content="Test")],
+            filtering_function=FilteringFunction.none,
+            model="invalid-model",
+        )
+
+
+@pytest.mark.asyncio
+async def test_synthetic_data_kit_provider_with_env_config(client: LlamaStackAsLibraryClient):
+    # Set environment variables for testing
+    os.environ["SYNTHETIC_DATA_KIT_MODEL"] = "meta-llama/Llama-3.2-7B-Instruct"
+    
+    provider = await get_provider_impl()
+    dialogs = [
+        Message(role="user", content="What is deep learning?"),
+        Message(role="assistant", content="Deep learning is a subset of machine learning..."),
+    ]
+    
+    response = await provider.synthetic_data_generate(
+        dialogs=dialogs,
+        filtering_function=FilteringFunction.none,
+    )
+    
+    assert response.synthetic_data is not None
+    assert len(response.synthetic_data) > 0
+    # Clean up environment
+    del os.environ["SYNTHETIC_DATA_KIT_MODEL"] 

tests/unit/providers/inline/synthetic_data_generation/test_synthetic_data_kit.py

@@ -0,0 +1,132 @@
+import os
+import pytest
+from typing import cast
+from unittest.mock import AsyncMock, MagicMock, patch
+
+from llama_stack.apis.inference import Message
+from llama_stack.apis.synthetic_data_generation import (
+    SyntheticDataGeneration,
+    SyntheticDataGenerationResponse,
+    FilteringFunction,
+)
+from llama_stack.providers.inline.synthetic_data_generation.synthetic_data_kit.config import (
+    SyntheticDataKitConfig,
+)
+from llama_stack.providers.inline.synthetic_data_generation.synthetic_data_kit.synthetic_data_kit import (
+    SyntheticDataKitProvider,
+)
+
+
+def test_config_defaults():
+    """Test default configuration values"""
+    config = SyntheticDataKitConfig()
+    assert config.llm["provider"] == "vllm"
+    assert config.llm["model"] == "meta-llama/Llama-3.2-3B-Instruct"
+    assert config.vllm["api_base"] == "http://localhost:8000/v1"
+    assert config.generation["temperature"] == 0.7
+    assert config.generation["chunk_size"] == 4000
+    assert config.curate["threshold"] == 7.0
+
+
+def test_sample_run_config():
+    """Test sample configuration with environment variables"""
+    # Test default configuration
+    config = SyntheticDataKitConfig.sample_run_config()
+    assert isinstance(config, SyntheticDataKitConfig)
+    assert config.llm["model"] == "meta-llama/Llama-3.2-3B-Instruct"
+    
+    # Test environment variable override
+    os.environ["SYNTHETIC_DATA_KIT_MODEL"] = "meta-llama/Llama-3.2-7B-Instruct"
+    config = SyntheticDataKitConfig.sample_run_config()
+    assert config.llm["model"] == "meta-llama/Llama-3.2-7B-Instruct"
+
+
+@pytest.fixture
+def mock_sdk():
+    """Create a mock SDK instance"""
+    with patch("synthetic_data_kit.SyntheticDataKit") as mock:
+        sdk_instance = MagicMock()
+        sdk_instance.create = AsyncMock()
+        sdk_instance.curate = AsyncMock()
+        mock.return_value = sdk_instance
+        yield sdk_instance
+
+
+@pytest.fixture
+def config():
+    return SyntheticDataKitConfig()
+
+
+@pytest.fixture
+def provider(config: SyntheticDataKitConfig, mock_sdk):
+    return SyntheticDataKitProvider(config)
+
+
+@pytest.mark.asyncio
+async def test_synthetic_data_generate_basic(provider: SyntheticDataGeneration, mock_sdk):
+    # Setup mock response
+    mock_sdk.create.return_value = {
+        "synthetic_data": [{"question": "What is ML?", "answer": "Machine learning..."}],
+        "statistics": {"count": 1}
+    }
+    
+    dialogs = [Message(role="user", content="What is machine learning?")]
+    response = await provider.synthetic_data_generate(
+        dialogs=dialogs,
+        filtering_function=FilteringFunction.none,
+    )
+    
+    # Verify SDK was called correctly
+    mock_sdk.create.assert_called_once_with("What is machine learning?", type="qa")
+    assert isinstance(response, SyntheticDataGenerationResponse)
+    assert len(response.synthetic_data) == 1
+    assert response.statistics == {"count": 1}
+
+
+@pytest.mark.asyncio
+async def test_synthetic_data_generate_with_filtering(provider: SyntheticDataGeneration, mock_sdk):
+    # Setup mock responses
+    mock_sdk.create.return_value = {
+        "synthetic_data": [{"question": "What is quantum?", "answer": "Quantum..."}],
+    }
+    mock_sdk.curate.return_value = {
+        "synthetic_data": [{"question": "What is quantum?", "answer": "Quantum..."}],
+        "statistics": {"threshold": 7.5}
+    }
+    
+    dialogs = [Message(role="user", content="Explain quantum computing.")]
+    response = await provider.synthetic_data_generate(
+        dialogs=dialogs,
+        filtering_function=FilteringFunction.top_k,
+    )
+    
+    # Verify both create and curate were called
+    mock_sdk.create.assert_called_once_with("Explain quantum computing.", type="qa")
+    mock_sdk.curate.assert_called_once()
+    assert isinstance(response, SyntheticDataGenerationResponse)
+    assert response.statistics["threshold"] == 7.5
+
+
+@pytest.mark.asyncio
+async def test_synthetic_data_generate_multiple_messages(provider: SyntheticDataGeneration, mock_sdk):
+    mock_sdk.create.return_value = {
+        "synthetic_data": [{"question": "What is deep learning?", "answer": "Deep..."}],
+        "statistics": {"count": 1}
+    }
+    
+    dialogs = [
+        Message(role="user", content="What is deep learning?"),
+        Message(role="assistant", content="Deep learning is..."),
+        Message(role="user", content="Can you explain more?")
+    ]
+    
+    response = await provider.synthetic_data_generate(
+        dialogs=dialogs,
+        filtering_function=FilteringFunction.none,
+    )
+    
+    # Verify content was joined correctly
+    expected_content = "What is deep learning?\nDeep learning is...\nCan you explain more?"
+    mock_sdk.create.assert_called_once_with(expected_content, type="qa")
+    assert isinstance(response, SyntheticDataGenerationResponse)
+    assert response.synthetic_data is not None