OpenHands/tests/unit/test_llm.py

from unittest.mock import patch

import pytest

from opendevin.core.config import LLMConfig
from opendevin.core.metrics import Metrics
from opendevin.llm.llm import LLM


@pytest.fixture
def default_config():
    return LLMConfig(model='gpt-3.5-turbo', api_key='test_key')


def test_llm_init_with_default_config(default_config):
    llm = LLM(default_config)
    assert llm.config.model == 'gpt-3.5-turbo'
    assert llm.config.api_key == 'test_key'
    assert isinstance(llm.metrics, Metrics)


@patch('opendevin.llm.llm.litellm.get_model_info')
def test_llm_init_with_model_info(mock_get_model_info, default_config):
    mock_get_model_info.return_value = {
        'max_input_tokens': 8000,
        'max_output_tokens': 2000,
    }
    llm = LLM(default_config)
    assert llm.config.max_input_tokens == 8000
    assert llm.config.max_output_tokens == 2000


@patch('opendevin.llm.llm.litellm.get_model_info')
def test_llm_init_without_model_info(mock_get_model_info, default_config):
    mock_get_model_info.side_effect = Exception('Model info not available')
    llm = LLM(default_config)
    assert llm.config.max_input_tokens == 4096
    assert llm.config.max_output_tokens == 1024


def test_llm_init_with_custom_config():
    custom_config = LLMConfig(
        model='custom-model',
        api_key='custom_key',
        max_input_tokens=5000,
        max_output_tokens=1500,
        temperature=0.8,
        top_p=0.9,
    )
    llm = LLM(custom_config)
    assert llm.config.model == 'custom-model'
    assert llm.config.api_key == 'custom_key'
    assert llm.config.max_input_tokens == 5000
    assert llm.config.max_output_tokens == 1500
    assert llm.config.temperature == 0.8
    assert llm.config.top_p == 0.9


def test_llm_init_with_metrics():
    config = LLMConfig(model='gpt-3.5-turbo', api_key='test_key')
    metrics = Metrics()
    llm = LLM(config, metrics=metrics)
    assert llm.metrics is metrics


def test_llm_reset():
    llm = LLM(LLMConfig(model='gpt-3.5-turbo', api_key='test_key'))
    initial_metrics = llm.metrics
    llm.reset()
    assert llm.metrics is not initial_metrics
    assert isinstance(llm.metrics, Metrics)


@patch('opendevin.llm.llm.litellm.get_model_info')
def test_llm_init_with_openrouter_model(mock_get_model_info, default_config):
    default_config.model = 'openrouter:gpt-3.5-turbo'
    mock_get_model_info.return_value = {
        'max_input_tokens': 7000,
        'max_output_tokens': 1500,
    }
    llm = LLM(default_config)
    assert llm.config.max_input_tokens == 7000
    assert llm.config.max_output_tokens == 1500
    mock_get_model_info.assert_called_once_with('openrouter:gpt-3.5-turbo')