refactor: consolidate to handler-base, migrate to pyproject.toml, add tests

tests/conftest.py

@@ -0,0 +1,113 @@
+"""
+Pytest configuration and fixtures for voice-assistant tests.
+"""
+import asyncio
+import base64
+import os
+from typing import AsyncGenerator
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+
+# Set test environment variables before importing
+os.environ.setdefault("NATS_URL", "nats://localhost:4222")
+os.environ.setdefault("REDIS_URL", "redis://localhost:6379")
+os.environ.setdefault("MILVUS_HOST", "localhost")
+os.environ.setdefault("OTEL_ENABLED", "false")
+os.environ.setdefault("MLFLOW_ENABLED", "false")
+
+
+@pytest.fixture(scope="session")
+def event_loop():
+    """Create event loop for async tests."""
+    loop = asyncio.new_event_loop()
+    yield loop
+    loop.close()
+
+
+@pytest.fixture
+def sample_audio_b64():
+    """Sample base64 encoded audio for testing."""
+    # 16-bit PCM silence (44 bytes header + 1000 samples)
+    wav_header = bytes([
+        0x52, 0x49, 0x46, 0x46,  # "RIFF"
+        0x24, 0x08, 0x00, 0x00,  # File size
+        0x57, 0x41, 0x56, 0x45,  # "WAVE"
+        0x66, 0x6D, 0x74, 0x20,  # "fmt "
+        0x10, 0x00, 0x00, 0x00,  # Chunk size
+        0x01, 0x00,              # PCM format
+        0x01, 0x00,              # Mono
+        0x80, 0x3E, 0x00, 0x00,  # Sample rate (16000)
+        0x00, 0x7D, 0x00, 0x00,  # Byte rate
+        0x02, 0x00,              # Block align
+        0x10, 0x00,              # Bits per sample
+        0x64, 0x61, 0x74, 0x61,  # "data"
+        0x00, 0x08, 0x00, 0x00,  # Data size
+    ])
+    silence = bytes([0x00] * 2048)
+    return base64.b64encode(wav_header + silence).decode()
+
+
+@pytest.fixture
+def sample_embedding():
+    """Sample embedding vector."""
+    return [0.1] * 1024
+
+
+@pytest.fixture
+def sample_documents():
+    """Sample search results."""
+    return [
+        {"text": "Machine learning is a subset of AI.", "score": 0.95},
+        {"text": "Deep learning uses neural networks.", "score": 0.90},
+        {"text": "AI enables intelligent automation.", "score": 0.85},
+    ]
+
+
+@pytest.fixture
+def sample_reranked():
+    """Sample reranked results."""
+    return [
+        {"document": "Machine learning is a subset of AI.", "score": 0.98},
+        {"document": "Deep learning uses neural networks.", "score": 0.85},
+    ]
+
+
+@pytest.fixture
+def mock_nats_message():
+    """Create a mock NATS message."""
+    msg = MagicMock()
+    msg.subject = "voice.request"
+    msg.reply = "voice.response.test-123"
+    return msg
+
+
+@pytest.fixture
+def mock_voice_request(sample_audio_b64):
+    """Sample voice request payload."""
+    return {
+        "request_id": "test-request-123",
+        "audio": sample_audio_b64,
+        "language": "en",
+        "collection": "test_collection",
+    }
+
+
+@pytest.fixture
+def mock_clients():
+    """Mock all service clients."""
+    with patch("voice_assistant.STTClient") as stt, \
+         patch("voice_assistant.EmbeddingsClient") as embeddings, \
+         patch("voice_assistant.RerankerClient") as reranker, \
+         patch("voice_assistant.LLMClient") as llm, \
+         patch("voice_assistant.TTSClient") as tts, \
+         patch("voice_assistant.MilvusClient") as milvus:
+        
+        yield {
+            "stt": stt,
+            "embeddings": embeddings,
+            "reranker": reranker,
+            "llm": llm,
+            "tts": tts,
+            "milvus": milvus,
+        }