Testing Configuration Management and Model Deployment in AutoGPT
This test suite validates the configuration management system in AutoGPT, focusing on proper initialization of AI settings and handling of model configurations. It ensures correct singleton behavior and tests both standard OpenAI and Azure deployment scenarios.
Test Coverage Overview
Implementation Analysis
Technical Details
Best Practices Demonstrated
significant-gravitas/autogpt
classic/original_autogpt/tests/unit/test_config.py
"""
Test cases for the config class, which handles the configuration settings
for the AI and ensures it behaves as a singleton.
"""
import asyncio
import os
from typing import Any
from unittest import mock
import pytest
from openai.pagination import AsyncPage
from openai.types import Model
from pydantic import SecretStr
from autogpt.app.config import GPT_3_MODEL, GPT_4_MODEL, AppConfig, ConfigBuilder
from autogpt.app.configurator import apply_overrides_to_config
def test_initial_values(config: AppConfig) -> None:
"""
Test if the initial values of the config class attributes are set correctly.
"""
assert config.continuous_mode is False
assert config.tts_config.speak_mode is False
assert config.fast_llm.startswith("gpt-3.5-turbo")
assert config.smart_llm.startswith("gpt-4")
@pytest.mark.asyncio
@mock.patch("openai.resources.models.AsyncModels.list")
async def test_fallback_to_gpt3_if_gpt4_not_available(
mock_list_models: Any, config: AppConfig
) -> None:
"""
Test if models update to gpt-3.5-turbo if gpt-4 is not available.
"""
config.fast_llm = GPT_4_MODEL
config.smart_llm = GPT_4_MODEL
mock_list_models.return_value = asyncio.Future()
mock_list_models.return_value.set_result(
AsyncPage(
data=[Model(id=GPT_3_MODEL, created=0, object="model", owned_by="AutoGPT")],
object="Models", # no idea what this should be, but irrelevant
)
)
await apply_overrides_to_config(config=config)
assert config.fast_llm == GPT_3_MODEL
assert config.smart_llm == GPT_3_MODEL
def test_missing_azure_config(config: AppConfig) -> None:
assert config.openai_credentials is not None
config_file = config.app_data_dir / "azure_config.yaml"
with pytest.raises(FileNotFoundError):
config.openai_credentials.load_azure_config(config_file)
config_file.write_text("")
with pytest.raises(ValueError):
config.openai_credentials.load_azure_config(config_file)
assert config.openai_credentials.api_type != SecretStr("azure")
assert config.openai_credentials.api_version is None
assert config.openai_credentials.azure_model_to_deploy_id_map is None
@pytest.fixture
def config_with_azure(config: AppConfig):
config_file = config.app_data_dir / "azure_config.yaml"
config_file.write_text(
f"""
azure_api_type: azure
azure_api_version: 2023-06-01-preview
azure_endpoint: https://dummy.openai.azure.com
azure_model_map:
{config.fast_llm}: FAST-LLM_ID
{config.smart_llm}: SMART-LLM_ID
{config.embedding_model}: embedding-deployment-id-for-azure
"""
)
os.environ["USE_AZURE"] = "True"
os.environ["AZURE_CONFIG_FILE"] = str(config_file)
config_with_azure = ConfigBuilder.build_config_from_env(
project_root=config.project_root
)
yield config_with_azure
del os.environ["USE_AZURE"]
del os.environ["AZURE_CONFIG_FILE"]
def test_azure_config(config_with_azure: AppConfig) -> None:
assert (credentials := config_with_azure.openai_credentials) is not None
assert credentials.api_type == SecretStr("azure")
assert credentials.api_version == SecretStr("2023-06-01-preview")
assert credentials.azure_endpoint == SecretStr("https://dummy.openai.azure.com")
assert credentials.azure_model_to_deploy_id_map == {
config_with_azure.fast_llm: "FAST-LLM_ID",
config_with_azure.smart_llm: "SMART-LLM_ID",
config_with_azure.embedding_model: "embedding-deployment-id-for-azure",
}
fast_llm = config_with_azure.fast_llm
smart_llm = config_with_azure.smart_llm
assert (
credentials.get_model_access_kwargs(config_with_azure.fast_llm)["model"]
== "FAST-LLM_ID"
)
assert (
credentials.get_model_access_kwargs(config_with_azure.smart_llm)["model"]
== "SMART-LLM_ID"
)
# Emulate --gpt4only
config_with_azure.fast_llm = smart_llm
assert (
credentials.get_model_access_kwargs(config_with_azure.fast_llm)["model"]
== "SMART-LLM_ID"
)
assert (
credentials.get_model_access_kwargs(config_with_azure.smart_llm)["model"]
== "SMART-LLM_ID"
)
# Emulate --gpt3only
config_with_azure.fast_llm = config_with_azure.smart_llm = fast_llm
assert (
credentials.get_model_access_kwargs(config_with_azure.fast_llm)["model"]
== "FAST-LLM_ID"
)
assert (
credentials.get_model_access_kwargs(config_with_azure.smart_llm)["model"]
== "FAST-LLM_ID"
)