# What is this?
## Tests slack alerting on proxy logging object

import sys
import os
import io, asyncio, httpx
from datetime import datetime, timedelta

# import logging
# logging.basicConfig(level=logging.DEBUG)
sys.path.insert(0, os.path.abspath("../.."))
from litellm.proxy.utils import ProxyLogging
from litellm.caching import DualCache
import litellm
import pytest
import asyncio
from unittest.mock import patch, MagicMock
from litellm.caching import DualCache
from litellm.integrations.slack_alerting import SlackAlerting
from litellm.proxy._types import UserAPIKeyAuth
from litellm.proxy.proxy_server import HTTPException


@pytest.mark.parametrize("exception_type", ["llm-exception", "non-llm-exception"])
@pytest.mark.asyncio
async def test_slack_alerting_llm_exceptions(exception_type, monkeypatch):
    """
    Test if non-llm exception -> No request
    Test if llm exception -> Request triggered
    """
    _pl = ProxyLogging(user_api_key_cache=DualCache())
    _pl.update_values(
        alerting=["slack"],
        alerting_threshold=100,
        redis_cache=None,
        alert_types=["llm_exceptions"],
    )

    async def mock_alerting_handler(message, level, alert_type):
        global exception_type

        if exception_type == "llm-exception":
            pass
        elif exception_type == "non-llm-exception":
            pytest.fail("Function should not have been called")

    monkeypatch.setattr(_pl, "alerting_handler", mock_alerting_handler)

    if exception_type == "llm-exception":
        await _pl.post_call_failure_hook(
            original_exception=litellm.APIError(
                status_code=500,
                message="This is a test exception",
                llm_provider="openai",
                model="gpt-3.5-turbo",
                request=httpx.Request(
                    method="completion", url="https://github.com/BerriAI/litellm"
                ),
            ),
            user_api_key_dict=UserAPIKeyAuth(),
        )

        await asyncio.sleep(2)

    elif exception_type == "non-llm-exception":
        await _pl.post_call_failure_hook(
            original_exception=HTTPException(
                status_code=400,
                detail={"error": "this is a test exception"},
            ),
            user_api_key_dict=UserAPIKeyAuth(),
        )

        await asyncio.sleep(2)


@pytest.mark.asyncio
async def test_get_api_base():
    _pl = ProxyLogging(user_api_key_cache=DualCache())
    _pl.update_values(alerting=["slack"], alerting_threshold=100, redis_cache=None)
    model = "chatgpt-v-2"
    messages = [{"role": "user", "content": "Hey how's it going?"}]
    litellm_params = {
        "acompletion": True,
        "api_key": None,
        "api_base": "https://openai-gpt-4-test-v-1.openai.azure.com/",
        "force_timeout": 600,
        "logger_fn": None,
        "verbose": False,
        "custom_llm_provider": "azure",
        "litellm_call_id": "68f46d2d-714d-4ad8-8137-69600ec8755c",
        "model_alias_map": {},
        "completion_call_id": None,
        "metadata": None,
        "model_info": None,
        "proxy_server_request": None,
        "preset_cache_key": None,
        "no-log": False,
        "stream_response": {},
    }
    start_time = datetime.now()
    end_time = datetime.now()

    time_difference_float, model, api_base, messages = (
        _pl.slack_alerting_instance._response_taking_too_long_callback(
            kwargs={
                "model": model,
                "messages": messages,
                "litellm_params": litellm_params,
            },
            start_time=start_time,
            end_time=end_time,
        )
    )

    assert api_base is not None
    assert isinstance(api_base, str)
    assert len(api_base) > 0
    request_info = (
        f"\nRequest Model: `{model}`\nAPI Base: `{api_base}`\nMessages: `{messages}`"
    )
    slow_message = f"`Responses are slow - {round(time_difference_float,2)}s response time > Alerting threshold: {100}s`"
    await _pl.alerting_handler(
        message=slow_message + request_info,
        level="Low",
        alert_type="llm_too_slow",
    )
    print("passed test_get_api_base")


# Create a mock environment for testing
@pytest.fixture
def mock_env(monkeypatch):
    monkeypatch.setenv("SLACK_WEBHOOK_URL", "https://example.com/webhook")
    monkeypatch.setenv("LANGFUSE_HOST", "https://cloud.langfuse.com")
    monkeypatch.setenv("LANGFUSE_PROJECT_ID", "test-project-id")


# Test the __init__ method
def test_init():
    slack_alerting = SlackAlerting(
        alerting_threshold=32, alerting=["slack"], alert_types=["llm_exceptions"]
    )
    assert slack_alerting.alerting_threshold == 32
    assert slack_alerting.alerting == ["slack"]
    assert slack_alerting.alert_types == ["llm_exceptions"]

    slack_no_alerting = SlackAlerting()
    assert slack_no_alerting.alerting == []

    print("passed testing slack alerting init")