mirror of
https://github.com/BerriAI/litellm.git
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d6ca7fed18
* fix(vertex_llm_base.py): Handle api_base = "" Fixes https://github.com/BerriAI/litellm/issues/5798 * fix(o1_transformation.py): handle stream_options not being supported https://github.com/BerriAI/litellm/issues/5803 * docs(routing.md): fix docs Closes https://github.com/BerriAI/litellm/issues/5808 * perf(internal_user_endpoints.py): reduce db calls for getting team_alias for a key Use the list gotten earlier in `/user/info` endpoint Reduces ui keys tab load time to 800ms (prev. 28s+) * feat(proxy_server.py): support CONFIG_FILE_PATH as env var Closes https://github.com/BerriAI/litellm/issues/5744 * feat(get_llm_provider_logic.py): add `litellm_proxy/` as a known openai-compatible route simplifies calling litellm proxy Reduces confusion when calling models on litellm proxy from litellm sdk * docs(litellm_proxy.md): cleanup docs * fix(internal_user_endpoints.py): fix pydantic obj * test(test_key_generate_prisma.py): fix test
116 lines
3.8 KiB
Python
116 lines
3.8 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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"temperature",
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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, non_default_params: dict, optional_params: dict, model: str
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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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return super()._map_openai_params(non_default_params, optional_params, model)
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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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