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support nested dicts #26414

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merged 6 commits into from
Sep 13, 2024
Merged

support nested dicts #26414

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10bc534
support nested dicts
hwchase17 Sep 13, 2024
cd475be
cr
hwchase17 Sep 13, 2024
2301697
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hwchase17 Sep 13, 2024
3ff2d15
Merge branch 'master' into harrison/update-openai
efriis Sep 13, 2024
e243faa
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efriis Sep 13, 2024
b6be448
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efriis Sep 13, 2024
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20 changes: 19 additions & 1 deletion libs/community/langchain_community/chat_models/openai.py
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Original file line number Diff line number Diff line change
Expand Up @@ -146,6 +146,22 @@ def _convert_delta_to_message_chunk(
return default_class(content=content) # type: ignore[call-arg]


def _update_token_usage(
overall_token_usage: Union[int, dict], new_usage: Union[int, dict]
):
# Token usage is either ints or dictionaries
# `reasoning_tokens` is nested inside `completion_tokens_details`
if isinstance(new_usage, int):
return new_usage
elif isinstance(new_usage, dict):
return {
k: _update_token_usage(overall_token_usage.get(k, 0), v)
for k, v in new_usage.items()
}
else:
raise TypeError(f"Unexpected type for token usage: {type(new_usage)}")


@deprecated(
since="0.0.10", removal="1.0", alternative_import="langchain_openai.ChatOpenAI"
)
Expand Down Expand Up @@ -374,7 +390,9 @@ def _combine_llm_outputs(self, llm_outputs: List[Optional[dict]]) -> dict:
if token_usage is not None:
for k, v in token_usage.items():
if k in overall_token_usage:
overall_token_usage[k] += v
overall_token_usage[k] = _update_token_usage(
overall_token_usage[k], v
)
else:
overall_token_usage[k] = v
if system_fingerprint is None:
Expand Down
20 changes: 19 additions & 1 deletion libs/partners/openai/langchain_openai/chat_models/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -335,6 +335,22 @@ def _convert_chunk_to_generation_chunk(
return generation_chunk


def _update_token_usage(
overall_token_usage: Union[int, dict], new_usage: Union[int, dict]
):
# Token usage is either ints or dictionaries
# `reasoning_tokens` is nested inside `completion_tokens_details`
if isinstance(new_usage, int):
return new_usage
elif isinstance(new_usage, dict):
return {
k: _update_token_usage(overall_token_usage.get(k, 0), v)
for k, v in new_usage.items()
Comment on lines +357 to +358
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I would suggest inspecting the value to ensure it's an integer. The OpenAI API may add additional fields within usage that are not integers in the future.

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Believe this actually handles what you're asking for! Recursively calls the same function, the adding only happens if it's an int. Otherwise hits the warning "else" case at the bottom

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Agreed with @efriis , The best way to handle this by checking the instance types programmatically for int and dict. And the else case will then take care of warnings.

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Makes sense, thanks! I don't think you need to warn in the else condition though — we may add non-integer fields in usage in the future, and that's not a breaking change or unexpected.

}
else:
raise TypeError(f"Unexpected type for token usage: {type(new_usage)}")


class _FunctionCall(TypedDict):
name: str

Expand Down Expand Up @@ -561,7 +577,9 @@ def _combine_llm_outputs(self, llm_outputs: List[Optional[dict]]) -> dict:
if token_usage is not None:
for k, v in token_usage.items():
if k in overall_token_usage:
overall_token_usage[k] += v
overall_token_usage[k] = _update_token_usage(
overall_token_usage[k], v
)
else:
overall_token_usage[k] = v
if system_fingerprint is None:
Expand Down
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