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from dataclasses import field |
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from openai.types.responses.response_usage import InputTokensDetails, OutputTokensDetails |
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from pydantic.dataclasses import dataclass |
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@dataclass |
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class Usage: |
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requests: int = 0 |
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"""Total requests made to the LLM API.""" |
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input_tokens: int = 0 |
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"""Total input tokens sent, across all requests.""" |
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input_tokens_details: InputTokensDetails = field( |
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default_factory=lambda: InputTokensDetails(cached_tokens=0) |
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) |
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"""Details about the input tokens, matching responses API usage details.""" |
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output_tokens: int = 0 |
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"""Total output tokens received, across all requests.""" |
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output_tokens_details: OutputTokensDetails = field( |
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default_factory=lambda: OutputTokensDetails(reasoning_tokens=0) |
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) |
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"""Details about the output tokens, matching responses API usage details.""" |
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total_tokens: int = 0 |
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"""Total tokens sent and received, across all requests.""" |
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def add(self, other: "Usage") -> None: |
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self.requests += other.requests if other.requests else 0 |
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self.input_tokens += other.input_tokens if other.input_tokens else 0 |
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self.output_tokens += other.output_tokens if other.output_tokens else 0 |
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self.total_tokens += other.total_tokens if other.total_tokens else 0 |
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self.input_tokens_details = InputTokensDetails( |
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cached_tokens=self.input_tokens_details.cached_tokens |
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+ other.input_tokens_details.cached_tokens |
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) |
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self.output_tokens_details = OutputTokensDetails( |
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reasoning_tokens=self.output_tokens_details.reasoning_tokens |
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+ other.output_tokens_details.reasoning_tokens |
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) |
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