RA.Aid/tests/ra_aid/test_llm.py

510 lines
18 KiB
Python

import os
import pytest
from unittest.mock import patch, Mock
from langchain_openai.chat_models import ChatOpenAI
from langchain_anthropic.chat_models import ChatAnthropic
from langchain_google_genai.chat_models import ChatGoogleGenerativeAI
from langchain_core.messages import HumanMessage
from dataclasses import dataclass
from ra_aid.agents.ciayn_agent import CiaynAgent
from ra_aid.env import validate_environment
from ra_aid.llm import (
initialize_llm,
initialize_expert_llm,
get_env_var,
get_provider_config,
create_llm_client
)
@pytest.fixture
def clean_env(monkeypatch):
"""Remove relevant environment variables before each test"""
env_vars = [
'ANTHROPIC_API_KEY', 'OPENAI_API_KEY', 'OPENROUTER_API_KEY',
'OPENAI_API_BASE', 'EXPERT_ANTHROPIC_API_KEY', 'EXPERT_OPENAI_API_KEY',
'EXPERT_OPENROUTER_API_KEY', 'EXPERT_OPENAI_API_BASE', 'GEMINI_API_KEY', 'EXPERT_GEMINI_API_KEY'
]
for var in env_vars:
monkeypatch.delenv(var, raising=False)
@pytest.fixture
def mock_openai():
"""
Mock ChatOpenAI class for testing OpenAI provider initialization.
Prevents actual API calls during testing.
"""
with patch('ra_aid.llm.ChatOpenAI') as mock:
mock.return_value = Mock(spec=ChatOpenAI)
yield mock
def test_initialize_expert_defaults(clean_env, mock_openai, monkeypatch):
"""Test expert LLM initialization with default parameters."""
monkeypatch.setenv("EXPERT_OPENAI_API_KEY", "test-key")
llm = initialize_expert_llm()
mock_openai.assert_called_once_with(
api_key="test-key",
model="o1",
temperature=0
)
def test_initialize_expert_openai_custom(clean_env, mock_openai, monkeypatch):
"""Test expert OpenAI initialization with custom parameters."""
monkeypatch.setenv("EXPERT_OPENAI_API_KEY", "test-key")
llm = initialize_expert_llm("openai", "gpt-4-preview")
mock_openai.assert_called_once_with(
api_key="test-key",
model="gpt-4-preview",
temperature=0
)
def test_initialize_expert_gemini(clean_env, mock_gemini, monkeypatch):
"""Test expert Gemini initialization."""
monkeypatch.setenv("EXPERT_GEMINI_API_KEY", "test-key")
llm = initialize_expert_llm("gemini", "gemini-2.0-flash-thinking-exp-1219")
mock_gemini.assert_called_once_with(
api_key="test-key",
model="gemini-2.0-flash-thinking-exp-1219",
temperature=0
)
def test_initialize_expert_anthropic(clean_env, mock_anthropic, monkeypatch):
"""Test expert Anthropic initialization."""
monkeypatch.setenv("EXPERT_ANTHROPIC_API_KEY", "test-key")
llm = initialize_expert_llm("anthropic", "claude-3")
mock_anthropic.assert_called_once_with(
api_key="test-key",
model_name="claude-3",
temperature=0
)
def test_initialize_expert_openrouter(clean_env, mock_openai, monkeypatch):
"""Test expert OpenRouter initialization."""
monkeypatch.setenv("EXPERT_OPENROUTER_API_KEY", "test-key")
llm = initialize_expert_llm("openrouter", "models/mistral-large")
mock_openai.assert_called_once_with(
api_key="test-key",
base_url="https://openrouter.ai/api/v1",
model="models/mistral-large",
temperature=0
)
def test_initialize_expert_openai_compatible(clean_env, mock_openai, monkeypatch):
"""Test expert OpenAI-compatible initialization."""
monkeypatch.setenv("EXPERT_OPENAI_API_KEY", "test-key")
monkeypatch.setenv("EXPERT_OPENAI_API_BASE", "http://test-url")
llm = initialize_expert_llm("openai-compatible", "local-model")
mock_openai.assert_called_once_with(
api_key="test-key",
base_url="http://test-url",
model="local-model",
temperature=0
)
def test_initialize_expert_unsupported_provider(clean_env):
"""Test error handling for unsupported provider in expert mode."""
with pytest.raises(ValueError, match=r"Unsupported provider: unknown"):
initialize_expert_llm("unknown", "model")
def test_estimate_tokens():
"""Test token estimation functionality."""
# Test empty/None cases
assert CiaynAgent._estimate_tokens(None) == 0
assert CiaynAgent._estimate_tokens('') == 0
# Test string content
assert CiaynAgent._estimate_tokens('test') == 1 # 4 bytes
assert CiaynAgent._estimate_tokens('hello world') == 2 # 11 bytes
assert CiaynAgent._estimate_tokens('🚀') == 1 # 4 bytes
# Test message content
msg = HumanMessage(content='test message')
assert CiaynAgent._estimate_tokens(msg) == 3 # 11 bytes
def test_initialize_openai(clean_env, mock_openai):
"""Test OpenAI provider initialization"""
os.environ["OPENAI_API_KEY"] = "test-key"
model = initialize_llm("openai", "gpt-4")
mock_openai.assert_called_once_with(
api_key="test-key",
model="gpt-4"
)
def test_initialize_gemini(clean_env, mock_gemini):
"""Test Gemini provider initialization"""
os.environ["GEMINI_API_KEY"] = "test-key"
model = initialize_llm("gemini", "gemini-2.0-flash-thinking-exp-1219")
mock_gemini.assert_called_once_with(
api_key="test-key",
model="gemini-2.0-flash-thinking-exp-1219"
)
def test_initialize_anthropic(clean_env, mock_anthropic):
"""Test Anthropic provider initialization"""
os.environ["ANTHROPIC_API_KEY"] = "test-key"
model = initialize_llm("anthropic", "claude-3")
mock_anthropic.assert_called_once_with(
api_key="test-key",
model_name="claude-3"
)
def test_initialize_openrouter(clean_env, mock_openai):
"""Test OpenRouter provider initialization"""
os.environ["OPENROUTER_API_KEY"] = "test-key"
model = initialize_llm("openrouter", "mistral-large")
mock_openai.assert_called_once_with(
api_key="test-key",
base_url="https://openrouter.ai/api/v1",
model="mistral-large"
)
def test_initialize_openai_compatible(clean_env, mock_openai):
"""Test OpenAI-compatible provider initialization"""
os.environ["OPENAI_API_KEY"] = "test-key"
os.environ["OPENAI_API_BASE"] = "https://custom-endpoint/v1"
model = initialize_llm("openai-compatible", "local-model")
mock_openai.assert_called_once_with(
api_key="test-key",
base_url="https://custom-endpoint/v1",
model="local-model",
temperature=0.3,
)
def test_initialize_unsupported_provider(clean_env):
"""Test initialization with unsupported provider raises ValueError"""
with pytest.raises(ValueError) as exc_info:
initialize_llm("unsupported", "model")
assert str(exc_info.value) == "Unsupported provider: unsupported"
def test_temperature_defaults(clean_env, mock_openai, mock_anthropic, mock_gemini):
"""Test default temperature behavior for different providers."""
os.environ["OPENAI_API_KEY"] = "test-key"
os.environ["ANTHROPIC_API_KEY"] = "test-key"
os.environ["OPENAI_API_BASE"] = "http://test-url"
os.environ["GEMINI_API_KEY"] = "test-key"
# Test openai-compatible default temperature
initialize_llm("openai-compatible", "test-model")
mock_openai.assert_called_with(
api_key="test-key",
base_url="http://test-url",
model="test-model",
temperature=0.3
)
# Test other providers don't set temperature by default
initialize_llm("openai", "test-model")
mock_openai.assert_called_with(
api_key="test-key",
model="test-model"
)
initialize_llm("anthropic", "test-model")
mock_anthropic.assert_called_with(
api_key="test-key",
model_name="test-model"
)
initialize_llm("gemini", "test-model")
mock_gemini.assert_called_with(
api_key="test-key",
model="test-model"
)
def test_explicit_temperature(clean_env, mock_openai, mock_anthropic, mock_gemini):
"""Test explicit temperature setting for each provider."""
os.environ["OPENAI_API_KEY"] = "test-key"
os.environ["ANTHROPIC_API_KEY"] = "test-key"
os.environ["OPENROUTER_API_KEY"] = "test-key"
os.environ["GEMINI_API_KEY"] = "test-key"
test_temp = 0.7
# Test OpenAI
initialize_llm("openai", "test-model", temperature=test_temp)
mock_openai.assert_called_with(
api_key="test-key",
model="test-model",
temperature=test_temp
)
# Test Gemini
initialize_llm("gemini", "test-model", temperature=test_temp)
mock_gemini.assert_called_with(
api_key="test-key",
model="test-model",
temperature=test_temp
)
# Test Anthropic
initialize_llm("anthropic", "test-model", temperature=test_temp)
mock_anthropic.assert_called_with(
api_key="test-key",
model_name="test-model",
temperature=test_temp
)
# Test OpenRouter
initialize_llm("openrouter", "test-model", temperature=test_temp)
mock_openai.assert_called_with(
api_key="test-key",
base_url="https://openrouter.ai/api/v1",
model="test-model",
temperature=test_temp
)
def test_temperature_validation(clean_env, mock_openai):
"""Test temperature validation in command line arguments."""
from ra_aid.__main__ import parse_arguments
# Test temperature below minimum
with pytest.raises(SystemExit):
parse_arguments(['--message', 'test', '--temperature', '-0.1'])
# Test temperature above maximum
with pytest.raises(SystemExit):
parse_arguments(['--message', 'test', '--temperature', '2.1'])
# Test valid temperature
args = parse_arguments(['--message', 'test', '--temperature', '0.7'])
assert args.temperature == 0.7
def test_provider_name_validation():
"""Test provider name validation and normalization."""
# Test all supported providers
providers = ["openai", "anthropic", "openrouter", "openai-compatible", "gemini"]
for provider in providers:
try:
with patch(f'ra_aid.llm.ChatOpenAI'), patch('ra_aid.llm.ChatAnthropic'):
initialize_llm(provider, "test-model")
except ValueError:
pytest.fail(f"Valid provider {provider} raised ValueError")
# Test case sensitivity
with patch('ra_aid.llm.ChatOpenAI'):
with pytest.raises(ValueError):
initialize_llm("OpenAI", "test-model")
def test_initialize_llm_cross_provider(clean_env, mock_openai, mock_anthropic, mock_gemini, monkeypatch):
"""Test initializing different providers in sequence."""
# Initialize OpenAI
monkeypatch.setenv("OPENAI_API_KEY", "openai-key")
llm1 = initialize_llm("openai", "gpt-4")
# Initialize Anthropic
monkeypatch.setenv("ANTHROPIC_API_KEY", "anthropic-key")
llm2 = initialize_llm("anthropic", "claude-3")
# Initialize Gemini
monkeypatch.setenv("GEMINI_API_KEY", "gemini-key")
llm3 = initialize_llm("gemini", "gemini-2.0-flash-thinking-exp-1219")
# Verify both were initialized correctly
mock_openai.assert_called_once_with(
api_key="openai-key",
model="gpt-4"
)
mock_anthropic.assert_called_once_with(
api_key="anthropic-key",
model_name="claude-3"
)
mock_gemini.assert_called_once_with(
api_key="gemini-key",
model="gemini-2.0-flash-thinking-exp-1219"
)
@dataclass
class Args:
"""Test arguments class."""
provider: str
expert_provider: str
model: str = None
expert_model: str = None
def test_environment_variable_precedence(clean_env, mock_openai, monkeypatch):
"""Test environment variable precedence and fallback."""
# Test get_env_var helper with fallback
monkeypatch.setenv("TEST_KEY", "base-value")
monkeypatch.setenv("EXPERT_TEST_KEY", "expert-value")
assert get_env_var("TEST_KEY") == "base-value"
assert get_env_var("TEST_KEY", expert=True) == "expert-value"
# Test fallback when expert value not set
monkeypatch.delenv("EXPERT_TEST_KEY", raising=False)
assert get_env_var("TEST_KEY", expert=True) == "base-value"
# Test provider config
monkeypatch.setenv("EXPERT_OPENAI_API_KEY", "expert-key")
config = get_provider_config("openai", is_expert=True)
assert config["api_key"] == "expert-key"
# Test LLM client creation with expert mode
llm = create_llm_client("openai", "o1", is_expert=True)
mock_openai.assert_called_with(
api_key="expert-key",
model="o1",
temperature=0
)
# Test environment validation
monkeypatch.setenv("EXPERT_OPENAI_API_KEY", "")
monkeypatch.delenv("OPENAI_API_KEY", raising=False)
monkeypatch.delenv("TAVILY_API_KEY", raising=False)
monkeypatch.setenv("ANTHROPIC_API_KEY", "anthropic-key")
monkeypatch.setenv("GEMINI_API_KEY", "gemini-key")
monkeypatch.setenv("ANTHROPIC_MODEL", "claude-3-haiku-20240307")
args = Args(provider="anthropic", expert_provider="openai")
expert_enabled, expert_missing, web_enabled, web_missing = validate_environment(args)
assert not expert_enabled
assert expert_missing
assert not web_enabled
assert web_missing
@pytest.fixture
def mock_anthropic():
"""
Mock ChatAnthropic class for testing Anthropic provider initialization.
Prevents actual API calls during testing.
"""
with patch('ra_aid.llm.ChatAnthropic') as mock:
mock.return_value = Mock(spec=ChatAnthropic)
yield mock
@pytest.fixture
def mock_gemini():
"""Mock ChatGoogleGenerativeAI class for testing Gemini provider initialization."""
with patch('ra_aid.llm.ChatGoogleGenerativeAI') as mock:
mock.return_value = Mock(spec=ChatGoogleGenerativeAI)
yield mock
@pytest.fixture
def mock_deepseek_reasoner():
"""Mock ChatDeepseekReasoner for testing DeepSeek provider initialization."""
with patch('ra_aid.llm.ChatDeepseekReasoner') as mock:
mock.return_value = Mock()
yield mock
def test_initialize_deepseek(clean_env, mock_openai, mock_deepseek_reasoner, monkeypatch):
"""Test DeepSeek provider initialization with different models."""
monkeypatch.setenv("DEEPSEEK_API_KEY", "test-key")
# Test with reasoner model
model = initialize_llm("deepseek", "deepseek-reasoner")
mock_deepseek_reasoner.assert_called_with(
api_key="test-key",
base_url="https://api.deepseek.com",
temperature=1,
model="deepseek-reasoner"
)
# Test with non-reasoner model
model = initialize_llm("deepseek", "deepseek-chat")
mock_openai.assert_called_with(
api_key="test-key",
base_url="https://api.deepseek.com",
temperature=1,
model="deepseek-chat"
)
def test_initialize_expert_deepseek(clean_env, mock_openai, mock_deepseek_reasoner, monkeypatch):
"""Test expert DeepSeek provider initialization."""
monkeypatch.setenv("EXPERT_DEEPSEEK_API_KEY", "test-key")
# Test with reasoner model
model = initialize_expert_llm("deepseek", "deepseek-reasoner")
mock_deepseek_reasoner.assert_called_with(
api_key="test-key",
base_url="https://api.deepseek.com",
temperature=0,
model="deepseek-reasoner"
)
# Test with non-reasoner model
model = initialize_expert_llm("deepseek", "deepseek-chat")
mock_openai.assert_called_with(
api_key="test-key",
base_url="https://api.deepseek.com",
temperature=0,
model="deepseek-chat"
)
def test_initialize_openrouter_deepseek(clean_env, mock_openai, mock_deepseek_reasoner, monkeypatch):
"""Test OpenRouter DeepSeek model initialization."""
monkeypatch.setenv("OPENROUTER_API_KEY", "test-key")
# Test with DeepSeek R1 model
model = initialize_llm("openrouter", "deepseek/deepseek-r1")
mock_deepseek_reasoner.assert_called_with(
api_key="test-key",
base_url="https://openrouter.ai/api/v1",
temperature=1,
model="deepseek/deepseek-r1"
)
# Test with non-DeepSeek model
model = initialize_llm("openrouter", "mistral/mistral-large")
mock_openai.assert_called_with(
api_key="test-key",
base_url="https://openrouter.ai/api/v1",
model="mistral/mistral-large"
)
def test_initialize_expert_openrouter_deepseek(clean_env, mock_openai, mock_deepseek_reasoner, monkeypatch):
"""Test expert OpenRouter DeepSeek model initialization."""
monkeypatch.setenv("EXPERT_OPENROUTER_API_KEY", "test-key")
# Test with DeepSeek R1 model via create_llm_client
model = create_llm_client("openrouter", "deepseek/deepseek-r1", is_expert=True)
mock_deepseek_reasoner.assert_called_with(
api_key="test-key",
base_url="https://openrouter.ai/api/v1",
temperature=0,
model="deepseek/deepseek-r1"
)
# Test with non-DeepSeek model
model = create_llm_client("openrouter", "mistral/mistral-large", is_expert=True)
mock_openai.assert_called_with(
api_key="test-key",
base_url="https://openrouter.ai/api/v1",
model="mistral/mistral-large",
temperature=0
)
def test_deepseek_environment_fallback(clean_env, mock_deepseek_reasoner, monkeypatch):
"""Test DeepSeek environment variable fallback behavior."""
# Test environment variable helper with fallback
monkeypatch.setenv("DEEPSEEK_API_KEY", "base-key")
assert get_env_var("DEEPSEEK_API_KEY", expert=True) == "base-key"
# Test provider config with fallback
config = get_provider_config("deepseek", is_expert=True)
assert config["api_key"] == "base-key"
assert config["base_url"] == "https://api.deepseek.com"
# Test with expert key
monkeypatch.setenv("EXPERT_DEEPSEEK_API_KEY", "expert-key")
config = get_provider_config("deepseek", is_expert=True)
assert config["api_key"] == "expert-key"
# Test client creation with expert key
model = create_llm_client("deepseek", "deepseek-reasoner", is_expert=True)
mock_deepseek_reasoner.assert_called_with(
api_key="expert-key",
base_url="https://api.deepseek.com",
temperature=0,
model="deepseek-reasoner"
)