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74 lines
2.5 KiB
Python
74 lines
2.5 KiB
Python
import json
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from typing import Any, Dict
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import litellm
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from litellm.llms.base_llm.responses.transformation import BaseResponsesAPIConfig
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from litellm.types.llms.openai import (
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ResponseAPIUsage,
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ResponsesAPIOptionalRequestParams,
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ResponsesAPIRequestParams,
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)
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from litellm.types.utils import Usage
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def get_optional_params_responses_api(
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model: str,
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responses_api_provider_config: BaseResponsesAPIConfig,
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response_api_optional_params: ResponsesAPIOptionalRequestParams,
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) -> Dict:
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"""
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Get optional parameters for the responses API.
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Args:
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params: Dictionary of all parameters
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model: The model name
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responses_api_provider_config: The provider configuration for responses API
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Returns:
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A dictionary of supported parameters for the responses API
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"""
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# Remove None values and internal parameters
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# Get supported parameters for the model
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supported_params = responses_api_provider_config.get_supported_openai_params(model)
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# Check for unsupported parameters
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unsupported_params = [
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param for param in response_api_optional_params if param not in supported_params
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]
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if unsupported_params:
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raise litellm.UnsupportedParamsError(
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model=model,
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message=f"The following parameters are not supported for model {model}: {', '.join(unsupported_params)}",
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)
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# Map parameters to provider-specific format
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mapped_params = responses_api_provider_config.map_openai_params(
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response_api_optional_params=response_api_optional_params,
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model=model,
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drop_params=litellm.drop_params,
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)
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return mapped_params
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class ResponseAPILoggingUtils:
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@staticmethod
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def _is_response_api_usage(usage: dict) -> bool:
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"""returns True if usage is from OpenAI Response API"""
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if "input_tokens" in usage and "output_tokens" in usage:
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return True
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return False
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@staticmethod
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def _transform_response_api_usage_to_chat_usage(usage: dict) -> Usage:
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"""Tranforms the ResponseAPIUsage object to a Usage object"""
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response_api_usage: ResponseAPIUsage = ResponseAPIUsage(**usage)
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prompt_tokens: int = response_api_usage.input_tokens or 0
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completion_tokens: int = response_api_usage.output_tokens or 0
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return Usage(
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prompt_tokens=prompt_tokens,
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completion_tokens=completion_tokens,
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total_tokens=prompt_tokens + completion_tokens,
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)
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