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@@ -5,6 +5,7 @@ from pydantic.v1 import BaseModel
from ..core import get_logger
from ..core.db import AsyncSession
from ..core.settings import settings
from .price import sats_usd_price
logger = get_logger(__name__)
@@ -64,6 +65,56 @@ async def calculate_cost( # todo: can be sync
)
return cost_data
usage_data = response_data["usage"]
usd_cost = 0.0
# Prioritize cost_details.upstream_inference_cost
if "cost_details" in usage_data:
usd_cost = float(
usage_data["cost_details"].get("upstream_inference_cost", 0) or 0
)
# Fallback to cost field if upstream_inference_cost is 0
if usd_cost == 0 and "cost" in usage_data:
try:
usd_cost = float(usage_data.get("cost", 0) or 0)
except Exception:
pass
if usd_cost > 0:
try:
sats_per_usd = 1.0 / sats_usd_price()
cost_in_sats = usd_cost * sats_per_usd
cost_in_msats = math.ceil(cost_in_sats * 1000)
logger.info(
"Using cost from usage data/details",
extra={
"usd_cost": usd_cost,
"cost_in_sats": cost_in_sats,
"cost_in_msats": cost_in_msats,
"model": response_data.get("model", "unknown"),
},
)
return CostData(
base_msats=-1,
input_msats=-1, # Cost field doesn't break down by token type
output_msats=-1,
total_msats=cost_in_msats,
)
except Exception as e:
logger.warning(
"Error calculating cost from usage data",
extra={
"error": str(e),
"usd_cost": usd_cost,
"model": response_data.get("model", "unknown"),
},
)
# Fall through to token-based calculation
MSATS_PER_1K_INPUT_TOKENS: float = (
float(settings.fixed_per_1k_input_tokens) * 1000.0
)
@@ -129,10 +180,19 @@ async def calculate_cost( # todo: can be sync
)
return cost_data
input_tokens = response_data.get("usage", {}).get("prompt_tokens", 0)
output_tokens = response_data.get("usage", {}).get("completion_tokens", 0)
input_tokens = usage_data.get("prompt_tokens", 0)
output_tokens = usage_data.get("completion_tokens", 0)
# added for response api
input_tokens = (
input_tokens if input_tokens != 0 else usage_data.get("input_tokens", 0)
)
output_tokens = (
output_tokens if output_tokens != 0 else usage_data.get("output_tokens", 0)
)
input_msats = round(input_tokens / 1000 * MSATS_PER_1K_INPUT_TOKENS, 3)
output_msats = round(output_tokens / 1000 * MSATS_PER_1K_OUTPUT_TOKENS, 3)
token_based_cost = math.ceil(input_msats + output_msats)