litellm-mirror/litellm/llms/OpenAI/o1_transformation.py
Krish Dholakia 713d762411 LiteLLM Minor Fixes and Improvements (09/13/2024) (#5689)
* refactor: cleanup unused variables + fix pyright errors

* feat(health_check.py): Closes https://github.com/BerriAI/litellm/issues/5686

* fix(o1_reasoning.py): add stricter check for o-1 reasoning model

* refactor(mistral/): make it easier to see mistral transformation logic

* fix(openai.py): fix openai o-1 model param mapping

Fixes https://github.com/BerriAI/litellm/issues/5685

* feat(main.py): infer finetuned gemini model from base model

Fixes https://github.com/BerriAI/litellm/issues/5678

* docs(vertex.md): update docs to call finetuned gemini models

* feat(proxy_server.py): allow admin to hide proxy model aliases

Closes https://github.com/BerriAI/litellm/issues/5692

* docs(load_balancing.md): add docs on hiding alias models from proxy config

* fix(base.py): don't raise notimplemented error

* fix(user_api_key_auth.py): fix model max budget check

* fix(router.py): fix elif

* fix(user_api_key_auth.py): don't set team_id to empty str

* fix(team_endpoints.py): fix response type

* test(test_completion.py): handle predibase error

* test(test_proxy_server.py): fix test

* fix(o1_transformation.py): fix max_completion_token mapping

* test(test_image_generation.py): mark flaky test
2024-09-14 10:02:55 -07:00

107 lines
3.6 KiB
Python

"""
Support for o1 model family
https://platform.openai.com/docs/guides/reasoning
Translations handled by LiteLLM:
- modalities: image => drop param (if user opts in to dropping param)
- role: system ==> translate to role 'user'
- streaming => faked by LiteLLM
- Tools, response_format => drop param (if user opts in to dropping param)
- Logprobs => drop param (if user opts in to dropping param)
"""
import types
from typing import Any, List, Optional, Union
import litellm
from litellm.types.llms.openai import AllMessageValues, ChatCompletionUserMessage
from .gpt_transformation import OpenAIGPTConfig
class OpenAIO1Config(OpenAIGPTConfig):
"""
Reference: https://platform.openai.com/docs/guides/reasoning
"""
@classmethod
def get_config(cls):
return {
k: v
for k, v in cls.__dict__.items()
if not k.startswith("__")
and not isinstance(
v,
(
types.FunctionType,
types.BuiltinFunctionType,
classmethod,
staticmethod,
),
)
and v is not None
}
def get_supported_openai_params(self, model: str) -> list:
"""
Get the supported OpenAI params for the given model
"""
all_openai_params = super().get_supported_openai_params(model=model)
non_supported_params = [
"logprobs",
"tools",
"tool_choice",
"parallel_tool_calls",
"function_call",
"functions",
]
return [
param for param in all_openai_params if param not in non_supported_params
]
def map_openai_params(
self, non_default_params: dict, optional_params: dict, model: str
):
if "max_tokens" in non_default_params:
optional_params["max_completion_tokens"] = non_default_params.pop(
"max_tokens"
)
return super()._map_openai_params(non_default_params, optional_params, model)
def is_model_o1_reasoning_model(self, model: str) -> bool:
if model in litellm.open_ai_chat_completion_models and "o1" in model:
return True
return False
def o1_prompt_factory(self, messages: List[AllMessageValues]):
"""
Handles limitations of O-1 model family.
- modalities: image => drop param (if user opts in to dropping param)
- role: system ==> translate to role 'user'
"""
for i, message in enumerate(messages):
if message["role"] == "system":
new_message = ChatCompletionUserMessage(
content=message["content"], role="user"
)
messages[i] = new_message # Replace the old message with the new one
if "content" in message and isinstance(message["content"], list):
new_content = []
for content_item in message["content"]:
if content_item.get("type") == "image_url":
if litellm.drop_params is not True:
raise ValueError(
"Image content is not supported for O-1 models. Set litellm.drop_param to True to drop image content."
)
# If drop_param is True, we simply don't add the image content to new_content
else:
new_content.append(content_item)
message["content"] = new_content
return messages