import pytest
import asyncio
import os
from unittest.mock import patch
from httpx import AsyncClient

os.environ.setdefault("GROQ_API_KEY", "test-key-12345")
os.environ.setdefault("JWT_SECRET_KEY", "test-secret-key-67890")
os.environ.setdefault("MONGODB_URI", "mongodb://localhost:27017/test")
os.environ.setdefault("REDIS_URL", "redis://localhost:6379/0")
os.environ.setdefault("QDRANT_URL", "http://localhost:6333")
os.environ.setdefault("QDRANT_API_KEY", "test-qdrant-key")

from app.main import app
from app.db.redis_client import redis_client
from app.db.mongodb import mongodb
from app.core.cache import semantic_cache


@pytest.fixture(scope="session")
def event_loop():
    loop = asyncio.get_event_loop_policy().new_event_loop()
    yield loop
    loop.close()


@pytest.fixture
async def client():
    async with AsyncClient(app=app, base_url="http://test") as ac:
        yield ac


@pytest.fixture
async def clear_cache():
    await semantic_cache.clear()
    yield
    await semantic_cache.clear()


@pytest.fixture
def sample_query():
    return "What is the attention mechanism?"


@pytest.fixture
def sample_document_text():
    return """
    The attention mechanism is a key component of modern neural networks.
    It allows the model to focus on different parts of the input when processing.
    This is particularly useful in sequence-to-sequence tasks.
    """