mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-26 19:24:27 +00:00
0a03f2f11e
* fix(langfuse.py): support new langfuse prompt_chat class init params * fix(langfuse.py): handle new init values on prompt chat + prompt text templates fixes error caused during langfuse logging * docs(openai_compatible.md): clarify `openai/` handles correct routing for `/v1/completions` route Fixes https://github.com/BerriAI/litellm/issues/5876 * fix(utils.py): handle unmapped gemini model optional param translation Fixes https://github.com/BerriAI/litellm/issues/5888 * fix(o1_transformation.py): fix o-1 validation, to not raise error if temperature=1 Fixes https://github.com/BerriAI/litellm/issues/5884 * fix(prisma_client.py): refresh iam token Fixes https://github.com/BerriAI/litellm/issues/5896 * fix: pass drop params where required * fix(utils.py): pass drop_params correctly * fix(types/vertex_ai.py): fix generation config * test(test_max_completion_tokens.py): fix test * fix(vertex_and_google_ai_studio_gemini.py): fix map openai params
138 lines
4.7 KiB
Python
138 lines
4.7 KiB
Python
"""
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Support for o1 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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import types
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from typing import Any, List, Optional, Union
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import litellm
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from litellm.types.llms.openai import AllMessageValues, ChatCompletionUserMessage
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from .gpt_transformation import OpenAIGPTConfig
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class OpenAIO1Config(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 {
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k: v
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for k, v in cls.__dict__.items()
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if not k.startswith("__")
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and not isinstance(
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v,
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(
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types.FunctionType,
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types.BuiltinFunctionType,
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classmethod,
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staticmethod,
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),
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)
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and v is not None
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}
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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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"tools",
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"tool_choice",
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"parallel_tool_calls",
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"function_call",
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"functions",
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"top_p",
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"n",
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"presence_penalty",
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"frequency_penalty",
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"top_logprobs",
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"response_format",
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"stop",
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"stream_options",
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]
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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 == 0 or 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-1 doesn't support temperature={}. 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_o1_reasoning_model(self, model: str) -> bool:
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if model in litellm.open_ai_chat_completion_models and "o1" in model:
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return True
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return False
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def o1_prompt_factory(self, messages: 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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for i, message in enumerate(messages):
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if message["role"] == "system":
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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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if "content" in message and isinstance(message["content"], list):
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new_content = []
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for content_item in message["content"]:
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if content_item.get("type") == "image_url":
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if litellm.drop_params is not True:
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raise ValueError(
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"Image content is not supported for O-1 models. Set litellm.drop_param to True to drop image content."
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)
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# If drop_param is True, we simply don't add the image content to new_content
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else:
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new_content.append(content_item)
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message["content"] = new_content
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return messages
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