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comet-ml--opik/sdks/python/tests/unit/llm_usage/test_google_usage.py
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chore: import upstream snapshot with attribution
2026-07-13 13:25:44 +08:00

105 lines
3.7 KiB
Python

import pytest
import pydantic
from opik.llm_usage.google_usage import GoogleGeminiUsage
def test_google_gemini_usage_creation__happyflow():
usage_data = {
"candidates_token_count": 100,
"prompt_token_count": 50,
"total_token_count": 150,
"cached_content_token_count": 20,
}
usage = GoogleGeminiUsage.from_original_usage_dict(usage_data)
assert usage.candidates_token_count == 100
assert usage.prompt_token_count == 50
assert usage.total_token_count == 150
assert usage.cached_content_token_count == 20
def test_google_gemini_usage_creation__no_cache_key__cached_content_token_count_is_None():
usage_data = {
"candidates_token_count": 100,
"prompt_token_count": 50,
"total_token_count": 150,
}
usage = GoogleGeminiUsage.from_original_usage_dict(usage_data)
assert usage.candidates_token_count == 100
assert usage.prompt_token_count == 50
assert usage.total_token_count == 150
assert usage.cached_content_token_count is None
def test_google_gemini_usage__to_backend_compatible_flat_dict__happyflow():
usage_data = {
"candidates_token_count": 100,
"prompt_token_count": 50,
"total_token_count": 150,
"cached_content_token_count": 10,
}
usage = GoogleGeminiUsage.from_original_usage_dict(usage_data)
flat_dict = usage.to_backend_compatible_flat_dict("original_usage")
assert flat_dict == {
"original_usage.candidates_token_count": 100,
"original_usage.prompt_token_count": 50,
"original_usage.total_token_count": 150,
"original_usage.cached_content_token_count": 10,
}
def test_google_gemini_usage__to_backend_compatible_flat_dict__no_cache_tokens_key():
usage_data = {
"candidates_token_count": 100,
"prompt_token_count": 50,
"total_token_count": 150,
}
usage = GoogleGeminiUsage.from_original_usage_dict(usage_data)
flat_dict = usage.to_backend_compatible_flat_dict("original_usage")
assert flat_dict == {
"original_usage.candidates_token_count": 100,
"original_usage.prompt_token_count": 50,
"original_usage.total_token_count": 150,
}
def test_google_gemini_usage__invalid_data_passed__validation_error_is_raised():
usage_data = {
"candidates_token_count": "invalid",
"prompt_token_count": None,
"total_token_count": 150,
"cached_content_token_count": "wrong_type",
}
with pytest.raises(pydantic.ValidationError):
GoogleGeminiUsage.from_original_usage_dict(usage_data)
def test_google_gemini_usage__extra_unknown_keys_are_passed__fields_are_accepted__all_integers_included_to_the_resulting_flat_dict():
usage_data = {
"candidates_token_count": 100,
"prompt_token_count": 50,
"total_token_count": 150,
"cached_content_token_count": 10,
"some_newly_added_int": 42,
"some_newly_added_details_dict": {
"detail_int": 333,
"detail_string": "some-string",
},
}
usage = GoogleGeminiUsage.from_original_usage_dict(usage_data)
assert usage.some_newly_added_int == 42
assert usage.some_newly_added_details_dict == {
"detail_int": 333,
"detail_string": "some-string",
}
flat_dict = usage.to_backend_compatible_flat_dict("original_usage")
assert flat_dict == {
"original_usage.candidates_token_count": 100,
"original_usage.prompt_token_count": 50,
"original_usage.total_token_count": 150,
"original_usage.cached_content_token_count": 10,
"original_usage.some_newly_added_int": 42,
"original_usage.some_newly_added_details_dict.detail_int": 333,
}