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perf: skip cost component calculations when usage values are zero

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Add early-out checks in _calculate_input_cost() to skip calculate_cost_component()
calls when audio_tokens, image_tokens, character_count, image_count,
video_length_seconds, or cache_creation_tokens are 0.
This commit is contained in:
Ryan Crabbe 2026-02-05 15:55:27 -08:00
parent b96fdda76f
commit 00a1ba7bdc
1 changed files with 36 additions and 31 deletions
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67
litellm/litellm_core_utils/llm_cost_calc/utils.py
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@ -518,47 +518,52 @@ def _calculate_input_cost(
prompt_cost += float(prompt_tokens_details["cache_hit_tokens"]) * cache_read_cost
### AUDIO COST
prompt_cost += calculate_cost_component(
model_info, "input_cost_per_audio_token", prompt_tokens_details["audio_tokens"]
)
if prompt_tokens_details["audio_tokens"]:
prompt_cost += calculate_cost_component(
model_info, "input_cost_per_audio_token", prompt_tokens_details["audio_tokens"]
)
### IMAGE TOKEN COST
# For image token costs:
# First check if input_cost_per_image_token is available. If not, default to generic input_cost_per_token.
image_token_cost_key = "input_cost_per_image_token"
if model_info.get(image_token_cost_key) is None:
image_token_cost_key = "input_cost_per_token"
prompt_cost += calculate_cost_component(
model_info, image_token_cost_key, prompt_tokens_details["image_tokens"]
)
if prompt_tokens_details["image_tokens"]:
# For image token costs:
# First check if input_cost_per_image_token is available. If not, default to generic input_cost_per_token.
image_token_cost_key = "input_cost_per_image_token"
if model_info.get(image_token_cost_key) is None:
image_token_cost_key = "input_cost_per_token"
prompt_cost += calculate_cost_component(
model_info, image_token_cost_key, prompt_tokens_details["image_tokens"]
)
### CACHE WRITING COST - Now uses tiered pricing
prompt_cost += calculate_cache_writing_cost(
cache_creation_tokens=prompt_tokens_details["cache_creation_tokens"],
cache_creation_token_details=prompt_tokens_details[
"cache_creation_token_details"
],
cache_creation_cost_above_1hr=cache_creation_cost_above_1hr,
cache_creation_cost=cache_creation_cost,
)
if prompt_tokens_details["cache_creation_tokens"]:
prompt_cost += calculate_cache_writing_cost(
cache_creation_tokens=prompt_tokens_details["cache_creation_tokens"],
cache_creation_token_details=prompt_tokens_details[
"cache_creation_token_details"
],
cache_creation_cost_above_1hr=cache_creation_cost_above_1hr,
cache_creation_cost=cache_creation_cost,
)
### CHARACTER COST
prompt_cost += calculate_cost_component(
model_info, "input_cost_per_character", prompt_tokens_details["character_count"]
)
if prompt_tokens_details["character_count"]:
prompt_cost += calculate_cost_component(
model_info, "input_cost_per_character", prompt_tokens_details["character_count"]
)
### IMAGE COUNT COST
prompt_cost += calculate_cost_component(
model_info, "input_cost_per_image", prompt_tokens_details["image_count"]
)
if prompt_tokens_details["image_count"]:
prompt_cost += calculate_cost_component(
model_info, "input_cost_per_image", prompt_tokens_details["image_count"]
)
### VIDEO LENGTH COST
prompt_cost += calculate_cost_component(
model_info,
"input_cost_per_video_per_second",
prompt_tokens_details["video_length_seconds"],
)
if prompt_tokens_details["video_length_seconds"]:
prompt_cost += calculate_cost_component(
model_info,
"input_cost_per_video_per_second",
prompt_tokens_details["video_length_seconds"],
)
return prompt_cost