mirror of
https://github.com/aljazceru/Auto-GPT.git
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bfbe613960
Additional changes: * Improve typing * Modularize message history memory & fix/refactor lots of things * Fix summarization * Move memory relevance calculation to MemoryItem & improve test * Fix import warnings in web_selenium.py * Remove `memory_add` ghost command * Implement overlap in `split_text` * Move memory tests into subdirectory * Remove deprecated `get_ada_embedding()` and helpers * Fix used token calculation in `chat_with_ai` * Replace Message TypedDict by dataclass * Fix AgentManager singleton issues in tests --------- Co-authored-by: Auto-GPT-Bot <github-bot@agpt.co>
129 lines
3.6 KiB
Python
129 lines
3.6 KiB
Python
from unittest.mock import patch
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import pytest
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from openai.error import APIError, RateLimitError
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from autogpt.llm import utils as llm_utils
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@pytest.fixture(params=[RateLimitError, APIError])
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def error(request):
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if request.param == APIError:
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return request.param("Error", http_status=502)
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else:
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return request.param("Error")
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def error_factory(error_instance, error_count, retry_count, warn_user=True):
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class RaisesError:
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def __init__(self):
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self.count = 0
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@llm_utils.retry_openai_api(
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num_retries=retry_count, backoff_base=0.001, warn_user=warn_user
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)
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def __call__(self):
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self.count += 1
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if self.count <= error_count:
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raise error_instance
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return self.count
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return RaisesError()
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def test_retry_open_api_no_error(capsys):
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@llm_utils.retry_openai_api()
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def f():
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return 1
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result = f()
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assert result == 1
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output = capsys.readouterr()
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assert output.out == ""
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assert output.err == ""
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@pytest.mark.parametrize(
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"error_count, retry_count, failure",
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[(2, 10, False), (2, 2, False), (10, 2, True), (3, 2, True), (1, 0, True)],
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ids=["passing", "passing_edge", "failing", "failing_edge", "failing_no_retries"],
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)
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def test_retry_open_api_passing(capsys, error, error_count, retry_count, failure):
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call_count = min(error_count, retry_count) + 1
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raises = error_factory(error, error_count, retry_count)
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if failure:
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with pytest.raises(type(error)):
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raises()
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else:
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result = raises()
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assert result == call_count
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assert raises.count == call_count
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output = capsys.readouterr()
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if error_count and retry_count:
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if type(error) == RateLimitError:
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assert "Reached rate limit, passing..." in output.out
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assert "Please double check" in output.out
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if type(error) == APIError:
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assert "API Bad gateway" in output.out
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else:
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assert output.out == ""
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def test_retry_open_api_rate_limit_no_warn(capsys):
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error_count = 2
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retry_count = 10
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raises = error_factory(RateLimitError, error_count, retry_count, warn_user=False)
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result = raises()
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call_count = min(error_count, retry_count) + 1
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assert result == call_count
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assert raises.count == call_count
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output = capsys.readouterr()
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assert "Reached rate limit, passing..." in output.out
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assert "Please double check" not in output.out
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def test_retry_openapi_other_api_error(capsys):
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error_count = 2
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retry_count = 10
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raises = error_factory(APIError("Error", http_status=500), error_count, retry_count)
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with pytest.raises(APIError):
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raises()
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call_count = 1
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assert raises.count == call_count
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output = capsys.readouterr()
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assert output.out == ""
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def test_check_model(api_manager):
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"""
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Test if check_model() returns original model when valid.
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Test if check_model() returns gpt-3.5-turbo when model is invalid.
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"""
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with patch("openai.Model.list") as mock_list_models:
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# Test when correct model is returned
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mock_list_models.return_value = {"data": [{"id": "gpt-4"}]}
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result = llm_utils.check_model("gpt-4", "smart_llm_model")
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assert result == "gpt-4"
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# Reset api manager models
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api_manager.models = None
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# Test when incorrect model is returned
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mock_list_models.return_value = {"data": [{"id": "gpt-3.5-turbo"}]}
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result = llm_utils.check_model("gpt-4", "fast_llm_model")
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assert result == "gpt-3.5-turbo"
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# Reset api manager models
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api_manager.models = None
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