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_create_usage_metadata_responses() — langchain Function Reference

Architecture documentation for the _create_usage_metadata_responses() function in base.py from the langchain codebase.

Function python LangChainCore LanguageModelBase called by 1

Entity Profile

Dependency Diagram

graph TD
  2a873213_75a9_7f1f_1e88_61e17ed10c52["_create_usage_metadata_responses()"]
  2b046911_ea21_8e2e_ba0d_9d03da8d7bda["base.py"]
  2a873213_75a9_7f1f_1e88_61e17ed10c52 -->|defined in| 2b046911_ea21_8e2e_ba0d_9d03da8d7bda
  06595fa5_189f_7f73_3a37_309f84e5179d["_construct_lc_result_from_responses_api()"]
  06595fa5_189f_7f73_3a37_309f84e5179d -->|calls| 2a873213_75a9_7f1f_1e88_61e17ed10c52
  style 2a873213_75a9_7f1f_1e88_61e17ed10c52 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/partners/openai/langchain_openai/chat_models/base.py lines 3770–3808

def _create_usage_metadata_responses(
    oai_token_usage: dict, service_tier: str | None = None
) -> UsageMetadata:
    input_tokens = oai_token_usage.get("input_tokens", 0)
    output_tokens = oai_token_usage.get("output_tokens", 0)
    total_tokens = oai_token_usage.get("total_tokens", input_tokens + output_tokens)
    if service_tier not in {"priority", "flex"}:
        service_tier = None
    service_tier_prefix = f"{service_tier}_" if service_tier else ""
    output_token_details: dict = {
        f"{service_tier_prefix}reasoning": (
            oai_token_usage.get("output_tokens_details") or {}
        ).get("reasoning_tokens")
    }
    input_token_details: dict = {
        f"{service_tier_prefix}cache_read": (
            oai_token_usage.get("input_tokens_details") or {}
        ).get("cached_tokens")
    }
    if service_tier is not None:
        # Avoid counting cache and reasoning tokens towards the service tier token
        # counts, since service tier tokens are already priced differently
        output_token_details[service_tier] = output_tokens - output_token_details.get(
            f"{service_tier_prefix}reasoning", 0
        )
        input_token_details[service_tier] = input_tokens - input_token_details.get(
            f"{service_tier_prefix}cache_read", 0
        )
    return UsageMetadata(
        input_tokens=input_tokens,
        output_tokens=output_tokens,
        total_tokens=total_tokens,
        input_token_details=InputTokenDetails(
            **{k: v for k, v in input_token_details.items() if v is not None}
        ),
        output_token_details=OutputTokenDetails(
            **{k: v for k, v in output_token_details.items() if v is not None}
        ),
    )

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Defined In

Called By

Source

Frequently Asked Questions

What does _create_usage_metadata_responses() do?
_create_usage_metadata_responses() is a function in the langchain codebase, defined in libs/partners/openai/langchain_openai/chat_models/base.py.
Where is _create_usage_metadata_responses() defined?
_create_usage_metadata_responses() is defined in libs/partners/openai/langchain_openai/chat_models/base.py at line 3770.
What calls _create_usage_metadata_responses()?
_create_usage_metadata_responses() is called by 1 function(s): _construct_lc_result_from_responses_api.

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