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chore: import upstream snapshot with attribution
2026-07-13 12:02:32 +08:00

113 lines
2.4 KiB
Python

from datetime import datetime
from typing import Any, TypeVar
from pydantic import BaseModel, Field
from browser_use.llm.views import ChatInvokeUsage
T = TypeVar('T', bound=BaseModel)
class TokenUsageEntry(BaseModel):
"""Single token usage entry"""
model: str
timestamp: datetime
usage: ChatInvokeUsage
class TokenCostCalculated(BaseModel):
"""Token cost"""
new_prompt_tokens: int
new_prompt_cost: float
prompt_read_cached_tokens: int | None
prompt_read_cached_cost: float | None
prompt_cached_creation_tokens: int | None
prompt_cache_creation_cost: float | None
"""Anthropic only: The cost of creating the cache."""
completion_tokens: int
completion_cost: float
@property
def prompt_cost(self) -> float:
return self.new_prompt_cost + (self.prompt_read_cached_cost or 0) + (self.prompt_cache_creation_cost or 0)
@property
def total_cost(self) -> float:
return (
self.new_prompt_cost
+ (self.prompt_read_cached_cost or 0)
+ (self.prompt_cache_creation_cost or 0)
+ self.completion_cost
)
class ModelPricing(BaseModel):
"""Pricing information for a model"""
model: str
input_cost_per_token: float | None
output_cost_per_token: float | None
cache_read_input_token_cost: float | None
cache_creation_input_token_cost: float | None
cache_creation_1h_input_token_cost: float | None = None
max_tokens: int | None
max_input_tokens: int | None
max_output_tokens: int | None
class CachedPricingData(BaseModel):
"""Cached pricing data with timestamp"""
timestamp: datetime
source_url: str | None = None
data: dict[str, Any]
class ModelUsageStats(BaseModel):
"""Usage statistics for a single model"""
model: str
prompt_tokens: int = 0
completion_tokens: int = 0
total_tokens: int = 0
cost: float = 0.0
invocations: int = 0
average_tokens_per_invocation: float = 0.0
class ModelUsageTokens(BaseModel):
"""Usage tokens for a single model"""
model: str
prompt_tokens: int
prompt_cached_tokens: int
completion_tokens: int
total_tokens: int
class UsageSummary(BaseModel):
"""Summary of token usage and costs"""
total_prompt_tokens: int
total_prompt_cost: float
total_prompt_cached_tokens: int
total_prompt_cached_cost: float
total_prompt_cache_creation_tokens: int = 0
total_prompt_cache_creation_cost: float = 0.0
total_completion_tokens: int
total_completion_cost: float
total_tokens: int
total_cost: float
entry_count: int
by_model: dict[str, ModelUsageStats] = Field(default_factory=dict)