"""
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,
        }