"""
Pytest configuration and fixtures.
"""

import asyncio
import os
from unittest.mock import AsyncMock, MagicMock

import pytest

# Set test environment variables before importing handler_base
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 settings():
    """Create test settings."""
    from handler_base.config import Settings

    return Settings(
        service_name="test-service",
        service_version="1.0.0-test",
        otel_enabled=False,
        mlflow_enabled=False,
        nats_url="nats://localhost:4222",
        redis_url="redis://localhost:6379",
        milvus_host="localhost",
    )


@pytest.fixture
def mock_httpx_client():
    """Create a mock httpx AsyncClient."""
    client = AsyncMock()
    client.post = AsyncMock()
    client.get = AsyncMock()
    client.aclose = AsyncMock()
    return client


@pytest.fixture
def mock_nats_message():
    """Create a mock NATS message."""
    msg = MagicMock()
    msg.subject = "test.subject"
    msg.reply = "test.reply"
    msg.data = b"\x82\xa8query\xa5hello\xaarequest_id\xa4test"  # msgpack
    return msg


@pytest.fixture
def sample_embedding():
    """Sample embedding vector."""
    return [0.1] * 1024


@pytest.fixture
def sample_documents():
    """Sample documents for testing."""
    return [
        {"text": "Python is a programming language.", "source": "doc1"},
        {"text": "Machine learning is a subset of AI.", "source": "doc2"},
        {"text": "Deep learning uses neural networks.", "source": "doc3"},
    ]