Files
JARVIS/backend/app/agents/runtime_metrics.py

87 lines
2.8 KiB
Python

from __future__ import annotations
from typing import Any
INPUT_TOKEN_USD_RATE = 0.000003
OUTPUT_TOKEN_USD_RATE = 0.000015
DEFAULT_COST_THRESHOLDS = {
"total_tokens": 4000,
"estimated_cost": 0.02,
}
def estimate_token_cost(input_tokens: int, output_tokens: int) -> float | None:
total_tokens = max(input_tokens, 0) + max(output_tokens, 0)
if total_tokens <= 0:
return None
return round(
(max(input_tokens, 0) * INPUT_TOKEN_USD_RATE)
+ (max(output_tokens, 0) * OUTPUT_TOKEN_USD_RATE),
6,
)
def extract_token_usage(response: Any) -> tuple[int, int]:
usage_metadata = getattr(response, "usage_metadata", None) or {}
if isinstance(usage_metadata, dict):
input_tokens = int(
usage_metadata.get("input_tokens")
or usage_metadata.get("prompt_tokens")
or 0
)
output_tokens = int(
usage_metadata.get("output_tokens")
or usage_metadata.get("completion_tokens")
or 0
)
if input_tokens or output_tokens:
return input_tokens, output_tokens
response_metadata = getattr(response, "response_metadata", None) or {}
token_usage = {}
if isinstance(response_metadata, dict):
token_usage = response_metadata.get("token_usage") or response_metadata.get("usage") or {}
if isinstance(token_usage, dict):
input_tokens = int(
token_usage.get("prompt_tokens")
or token_usage.get("input_tokens")
or 0
)
output_tokens = int(
token_usage.get("completion_tokens")
or token_usage.get("output_tokens")
or 0
)
if input_tokens or output_tokens:
return input_tokens, output_tokens
return 0, 0
def coerce_cost_thresholds(raw_thresholds: Any) -> dict[str, float]:
thresholds: dict[str, float] = dict(DEFAULT_COST_THRESHOLDS)
if not isinstance(raw_thresholds, dict):
return thresholds
for key in DEFAULT_COST_THRESHOLDS:
value = raw_thresholds.get(key)
if isinstance(value, (int, float)) and value > 0:
thresholds[key] = float(value)
return thresholds
def is_cost_budget_warning(
input_tokens: int,
output_tokens: int,
estimated_cost: float | None,
thresholds: dict[str, float] | None = None,
) -> bool:
effective_thresholds = thresholds or DEFAULT_COST_THRESHOLDS
total_tokens = max(input_tokens, 0) + max(output_tokens, 0)
token_threshold = float(effective_thresholds.get("total_tokens") or 0)
cost_threshold = float(effective_thresholds.get("estimated_cost") or 0)
return (
(token_threshold > 0 and total_tokens >= token_threshold)
or (cost_threshold > 0 and estimated_cost is not None and estimated_cost >= cost_threshold)
)