mirror of
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156 lines
5.4 KiB
Python
156 lines
5.4 KiB
Python
"""
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Support for o1/o3 model family
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https://platform.openai.com/docs/guides/reasoning
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Translations handled by LiteLLM:
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- modalities: image => drop param (if user opts in to dropping param)
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- role: system ==> translate to role 'user'
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- streaming => faked by LiteLLM
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- Tools, response_format => drop param (if user opts in to dropping param)
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- Logprobs => drop param (if user opts in to dropping param)
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"""
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from typing import List, Optional
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import litellm
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from litellm import verbose_logger
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from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
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from litellm.types.llms.openai import AllMessageValues, ChatCompletionUserMessage
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from litellm.utils import (
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supports_function_calling,
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supports_parallel_function_calling,
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supports_response_schema,
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supports_system_messages,
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)
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from .gpt_transformation import OpenAIGPTConfig
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class OpenAIOSeriesConfig(OpenAIGPTConfig):
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"""
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Reference: https://platform.openai.com/docs/guides/reasoning
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"""
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@classmethod
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def get_config(cls):
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return super().get_config()
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def translate_developer_role_to_system_role(
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self, messages: List[AllMessageValues]
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) -> List[AllMessageValues]:
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"""
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O-series models support `developer` role.
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"""
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return messages
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def get_supported_openai_params(self, model: str) -> list:
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"""
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Get the supported OpenAI params for the given model
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"""
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all_openai_params = super().get_supported_openai_params(model=model)
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non_supported_params = [
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"logprobs",
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"top_p",
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"presence_penalty",
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"frequency_penalty",
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"top_logprobs",
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]
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o_series_only_param = ["reasoning_effort"]
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all_openai_params.extend(o_series_only_param)
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try:
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model, custom_llm_provider, api_base, api_key = get_llm_provider(
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model=model
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)
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except Exception:
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verbose_logger.debug(
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f"Unable to infer model provider for model={model}, defaulting to openai for o1 supported param check"
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)
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custom_llm_provider = "openai"
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_supports_function_calling = supports_function_calling(
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model, custom_llm_provider
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)
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_supports_response_schema = supports_response_schema(model, custom_llm_provider)
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_supports_parallel_tool_calls = supports_parallel_function_calling(
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model, custom_llm_provider
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)
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if not _supports_function_calling:
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non_supported_params.append("tools")
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non_supported_params.append("tool_choice")
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non_supported_params.append("function_call")
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non_supported_params.append("functions")
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if not _supports_parallel_tool_calls:
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non_supported_params.append("parallel_tool_calls")
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if not _supports_response_schema:
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non_supported_params.append("response_format")
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return [
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param for param in all_openai_params if param not in non_supported_params
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]
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def map_openai_params(
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self,
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non_default_params: dict,
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optional_params: dict,
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model: str,
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drop_params: bool,
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):
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if "max_tokens" in non_default_params:
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optional_params["max_completion_tokens"] = non_default_params.pop(
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"max_tokens"
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)
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if "temperature" in non_default_params:
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temperature_value: Optional[float] = non_default_params.pop("temperature")
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if temperature_value is not None:
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if temperature_value == 1:
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optional_params["temperature"] = temperature_value
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else:
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## UNSUPPORTED TOOL CHOICE VALUE
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if litellm.drop_params is True or drop_params is True:
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pass
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else:
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raise litellm.utils.UnsupportedParamsError(
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message="O-series models don't support temperature={}. Only temperature=1 is supported. To drop unsupported openai params from the call, set `litellm.drop_params = True`".format(
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temperature_value
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),
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status_code=400,
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)
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return super()._map_openai_params(
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non_default_params, optional_params, model, drop_params
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)
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def is_model_o_series_model(self, model: str) -> bool:
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if model in litellm.open_ai_chat_completion_models and (
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"o1" in model or "o3" in model
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):
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return True
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return False
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def _transform_messages(
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self, messages: List[AllMessageValues], model: str
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) -> List[AllMessageValues]:
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"""
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Handles limitations of O-1 model family.
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- modalities: image => drop param (if user opts in to dropping param)
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- role: system ==> translate to role 'user'
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"""
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_supports_system_messages = supports_system_messages(model, "openai")
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for i, message in enumerate(messages):
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if message["role"] == "system" and not _supports_system_messages:
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new_message = ChatCompletionUserMessage(
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content=message["content"], role="user"
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)
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messages[i] = new_message # Replace the old message with the new one
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messages = super()._transform_messages(messages, model)
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return messages
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