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* [Fix] Recover the azure config load function * [Style] Apply black, isort, mypy, autoflake * [Fix] Rename the return parameter from 'azure_model_map' to 'azure_model_to_deployment_id_map' * [Feat] Change the azure config file path to be dynamically configurable * [Test] Add azure_config and azure deployment_id_for_model * [Style] Apply black, isort, mypy, autoflake * [Style] Apply black, isort, mypy, autoflake * Refactor Azure configuration - Refactor the `azure_config_file` attribute in the `Config` class to be optional. - Refactor the `azure_model_to_deployment_id_map` attribute in the `Config` class to be optional and provide default values. - Update the `get_azure_deployment_id_for_model` function to accept additional parameters. - Update references to `get_azure_deployment_id_for_model` in `create_text_completion`, `create_chat_completion`, and `get_embedding` functions to pass the required parameters. * Clean up process for azure * Docstring * revert some unneccessary fiddling * Avoid altering args to models * Retry on 404s * Don't permanently change the environment * Formatting --------- Co-authored-by: Luke <2609441+lc0rp@users.noreply.github.com> Co-authored-by: lc0rp <2609411+lc0rp@users.noreply.github.com> Co-authored-by: collijk <collijk@uw.edu>
269 lines
8.3 KiB
Python
269 lines
8.3 KiB
Python
"""
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Test cases for the config class, which handles the configuration settings
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for the AI and ensures it behaves as a singleton.
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"""
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import os
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from unittest import mock
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from unittest.mock import patch
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import pytest
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from autogpt.config import Config, ConfigBuilder
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from autogpt.configurator import GPT_3_MODEL, GPT_4_MODEL, create_config
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from autogpt.workspace.workspace import Workspace
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def test_initial_values(config: Config):
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"""
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Test if the initial values of the config class attributes are set correctly.
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"""
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assert config.debug_mode == False
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assert config.continuous_mode == False
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assert config.speak_mode == False
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assert config.fast_llm_model == "gpt-3.5-turbo"
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assert config.smart_llm_model == "gpt-3.5-turbo"
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def test_set_continuous_mode(config: Config):
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"""
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Test if the set_continuous_mode() method updates the continuous_mode attribute.
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"""
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# Store continuous mode to reset it after the test
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continuous_mode = config.continuous_mode
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config.continuous_mode = True
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assert config.continuous_mode == True
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# Reset continuous mode
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config.continuous_mode = continuous_mode
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def test_set_speak_mode(config: Config):
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"""
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Test if the set_speak_mode() method updates the speak_mode attribute.
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"""
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# Store speak mode to reset it after the test
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speak_mode = config.speak_mode
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config.speak_mode = True
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assert config.speak_mode == True
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# Reset speak mode
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config.speak_mode = speak_mode
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def test_set_fast_llm_model(config: Config):
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"""
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Test if the set_fast_llm_model() method updates the fast_llm_model attribute.
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"""
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# Store model name to reset it after the test
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fast_llm_model = config.fast_llm_model
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config.fast_llm_model = "gpt-3.5-turbo-test"
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assert config.fast_llm_model == "gpt-3.5-turbo-test"
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# Reset model name
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config.fast_llm_model = fast_llm_model
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def test_set_smart_llm_model(config: Config):
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"""
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Test if the set_smart_llm_model() method updates the smart_llm_model attribute.
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"""
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# Store model name to reset it after the test
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smart_llm_model = config.smart_llm_model
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config.smart_llm_model = "gpt-4-test"
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assert config.smart_llm_model == "gpt-4-test"
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# Reset model name
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config.smart_llm_model = smart_llm_model
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def test_set_debug_mode(config: Config):
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"""
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Test if the set_debug_mode() method updates the debug_mode attribute.
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"""
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# Store debug mode to reset it after the test
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debug_mode = config.debug_mode
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config.debug_mode = True
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assert config.debug_mode == True
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# Reset debug mode
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config.debug_mode = debug_mode
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@patch("openai.Model.list")
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def test_smart_and_fast_llm_models_set_to_gpt4(mock_list_models, config: Config):
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"""
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Test if models update to gpt-3.5-turbo if both are set to gpt-4.
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"""
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fast_llm_model = config.fast_llm_model
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smart_llm_model = config.smart_llm_model
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config.fast_llm_model = "gpt-4"
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config.smart_llm_model = "gpt-4"
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mock_list_models.return_value = {"data": [{"id": "gpt-3.5-turbo"}]}
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create_config(
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config=config,
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continuous=False,
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continuous_limit=False,
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ai_settings_file="",
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prompt_settings_file="",
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skip_reprompt=False,
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speak=False,
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debug=False,
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gpt3only=False,
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gpt4only=False,
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memory_type="",
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browser_name="",
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allow_downloads=False,
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skip_news=False,
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)
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assert config.fast_llm_model == "gpt-3.5-turbo"
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assert config.smart_llm_model == "gpt-3.5-turbo"
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# Reset config
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config.fast_llm_model = fast_llm_model
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config.smart_llm_model = smart_llm_model
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def test_missing_azure_config(workspace: Workspace):
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config_file = workspace.get_path("azure_config.yaml")
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with pytest.raises(FileNotFoundError):
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ConfigBuilder.load_azure_config(str(config_file))
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config_file.write_text("")
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azure_config = ConfigBuilder.load_azure_config(str(config_file))
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assert azure_config["openai_api_type"] == "azure"
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assert azure_config["openai_api_base"] == ""
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assert azure_config["openai_api_version"] == "2023-03-15-preview"
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assert azure_config["azure_model_to_deployment_id_map"] == {}
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def test_azure_config(workspace: Workspace) -> None:
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yaml_content = """
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azure_api_type: azure
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azure_api_base: https://dummy.openai.azure.com
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azure_api_version: 2023-06-01-preview
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azure_model_map:
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fast_llm_model_deployment_id: gpt-3.5-turbo
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smart_llm_model_deployment_id: gpt-4
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embedding_model_deployment_id: embedding-deployment-id-for-azure
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"""
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config_file = workspace.get_path("azure.yaml")
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config_file.write_text(yaml_content)
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os.environ["USE_AZURE"] = "True"
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os.environ["AZURE_CONFIG_FILE"] = str(config_file)
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config = ConfigBuilder.build_config_from_env()
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assert config.openai_api_type == "azure"
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assert config.openai_api_base == "https://dummy.openai.azure.com"
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assert config.openai_api_version == "2023-06-01-preview"
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assert config.azure_model_to_deployment_id_map == {
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"fast_llm_model_deployment_id": "gpt-3.5-turbo",
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"smart_llm_model_deployment_id": "gpt-4",
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"embedding_model_deployment_id": "embedding-deployment-id-for-azure",
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}
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del os.environ["USE_AZURE"]
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del os.environ["AZURE_CONFIG_FILE"]
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def test_azure_deployment_id_for_model(workspace: Workspace) -> None:
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yaml_content = """
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azure_api_type: azure
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azure_api_base: https://dummy.openai.azure.com
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azure_api_version: 2023-06-01-preview
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azure_model_map:
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fast_llm_model_deployment_id: gpt-3.5-turbo
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smart_llm_model_deployment_id: gpt-4
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embedding_model_deployment_id: embedding-deployment-id-for-azure
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"""
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config_file = workspace.get_path("azure.yaml")
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config_file.write_text(yaml_content)
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os.environ["USE_AZURE"] = "True"
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os.environ["AZURE_CONFIG_FILE"] = str(config_file)
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config = ConfigBuilder.build_config_from_env()
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config.fast_llm_model = "fast_llm_model"
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config.smart_llm_model = "smart_llm_model"
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def _get_deployment_id(model):
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kwargs = config.get_azure_kwargs(model)
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return kwargs.get("deployment_id", kwargs.get("engine"))
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assert _get_deployment_id(config.fast_llm_model) == "gpt-3.5-turbo"
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assert _get_deployment_id(config.smart_llm_model) == "gpt-4"
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assert (
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_get_deployment_id("text-embedding-ada-002")
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== "embedding-deployment-id-for-azure"
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)
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assert _get_deployment_id("dummy") is None
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del os.environ["USE_AZURE"]
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del os.environ["AZURE_CONFIG_FILE"]
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def test_create_config_gpt4only(config: Config) -> None:
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fast_llm_model = config.fast_llm_model
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smart_llm_model = config.smart_llm_model
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with mock.patch("autogpt.llm.api_manager.ApiManager.get_models") as mock_get_models:
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mock_get_models.return_value = [{"id": GPT_4_MODEL}]
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create_config(
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config=config,
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continuous=False,
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continuous_limit=None,
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ai_settings_file=None,
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prompt_settings_file=None,
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skip_reprompt=False,
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speak=False,
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debug=False,
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gpt3only=False,
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gpt4only=True,
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memory_type=None,
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browser_name=None,
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allow_downloads=False,
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skip_news=False,
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)
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assert config.fast_llm_model == GPT_4_MODEL
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assert config.smart_llm_model == GPT_4_MODEL
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# Reset config
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config.fast_llm_model = fast_llm_model
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config.smart_llm_model = smart_llm_model
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def test_create_config_gpt3only(config: Config) -> None:
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fast_llm_model = config.fast_llm_model
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smart_llm_model = config.smart_llm_model
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with mock.patch("autogpt.llm.api_manager.ApiManager.get_models") as mock_get_models:
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mock_get_models.return_value = [{"id": GPT_3_MODEL}]
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create_config(
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config=config,
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continuous=False,
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continuous_limit=None,
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ai_settings_file=None,
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prompt_settings_file=None,
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skip_reprompt=False,
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speak=False,
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debug=False,
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gpt3only=True,
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gpt4only=False,
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memory_type=None,
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browser_name=None,
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allow_downloads=False,
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skip_news=False,
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)
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assert config.fast_llm_model == GPT_3_MODEL
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assert config.smart_llm_model == GPT_3_MODEL
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# Reset config
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config.fast_llm_model = fast_llm_model
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config.smart_llm_model = smart_llm_model
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