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from typing import Optional, Union
import litellm
from ..exceptions import UnsupportedParamsError
from ..types.llms.openai import *
def get_optional_params_add_message(
role: Optional[str],
content: Optional[
Union[
str,
List[
Union[
MessageContentTextObject,
MessageContentImageFileObject,
MessageContentImageURLObject,
]
],
]
],
attachments: Optional[List[Attachment]],
metadata: Optional[dict],
custom_llm_provider: str,
**kwargs,
):
"""
Azure doesn't support 'attachments' for creating a message
Reference - https://learn.microsoft.com/en-us/azure/ai-services/openai/assistants-reference-messages?tabs=python#create-message
"""
passed_params = locals()
custom_llm_provider = passed_params.pop("custom_llm_provider")
special_params = passed_params.pop("kwargs")
for k, v in special_params.items():
passed_params[k] = v
default_params = {
"role": None,
"content": None,
"attachments": None,
"metadata": None,
}
non_default_params = {
k: v
for k, v in passed_params.items()
if (k in default_params and v != default_params[k])
}
optional_params = {}
## raise exception if non-default value passed for non-openai/azure embedding calls
def _check_valid_arg(supported_params):
if len(non_default_params.keys()) > 0:
keys = list(non_default_params.keys())
for k in keys:
if (
litellm.drop_params is True and k not in supported_params
): # drop the unsupported non-default values
non_default_params.pop(k, None)
elif k not in supported_params:
raise litellm.utils.UnsupportedParamsError(
status_code=500,
message="k={}, not supported by {}. Supported params={}. To drop it from the call, set `litellm.drop_params = True`.".format(
k, custom_llm_provider, supported_params
),
)
return non_default_params
if custom_llm_provider == "openai":
optional_params = non_default_params
elif custom_llm_provider == "azure":
supported_params = (
litellm.AzureOpenAIAssistantsAPIConfig().get_supported_openai_create_message_params()
)
_check_valid_arg(supported_params=supported_params)
optional_params = litellm.AzureOpenAIAssistantsAPIConfig().map_openai_params_create_message_params(
non_default_params=non_default_params, optional_params=optional_params
)
for k in passed_params.keys():
if k not in default_params.keys():
optional_params[k] = passed_params[k]
return optional_params
def get_optional_params_image_gen(
n: Optional[int] = None,
quality: Optional[str] = None,
response_format: Optional[str] = None,
size: Optional[str] = None,
style: Optional[str] = None,
user: Optional[str] = None,
custom_llm_provider: Optional[str] = None,
**kwargs,
):
# retrieve all parameters passed to the function
passed_params = locals()
custom_llm_provider = passed_params.pop("custom_llm_provider")
special_params = passed_params.pop("kwargs")
for k, v in special_params.items():
passed_params[k] = v
default_params = {
"n": None,
"quality": None,
"response_format": None,
"size": None,
"style": None,
"user": None,
}
non_default_params = {
k: v
for k, v in passed_params.items()
if (k in default_params and v != default_params[k])
}
optional_params = {}
## raise exception if non-default value passed for non-openai/azure embedding calls
def _check_valid_arg(supported_params):
if len(non_default_params.keys()) > 0:
keys = list(non_default_params.keys())
for k in keys:
if (
litellm.drop_params is True and k not in supported_params
): # drop the unsupported non-default values
non_default_params.pop(k, None)
elif k not in supported_params:
raise UnsupportedParamsError(
status_code=500,
message=f"Setting user/encoding format is not supported by {custom_llm_provider}. To drop it from the call, set `litellm.drop_params = True`.",
)
return non_default_params
if (
custom_llm_provider == "openai"
or custom_llm_provider == "azure"
or custom_llm_provider in litellm.openai_compatible_providers
):
optional_params = non_default_params
elif custom_llm_provider == "bedrock":
supported_params = ["size"]
_check_valid_arg(supported_params=supported_params)
if size is not None:
width, height = size.split("x")
optional_params["width"] = int(width)
optional_params["height"] = int(height)
elif custom_llm_provider == "vertex_ai":
supported_params = ["n"]
"""
All params here: https://console.cloud.google.com/vertex-ai/publishers/google/model-garden/imagegeneration?project=adroit-crow-413218
"""
_check_valid_arg(supported_params=supported_params)
if n is not None:
optional_params["sampleCount"] = int(n)
for k in passed_params.keys():
if k not in default_params.keys():
optional_params[k] = passed_params[k]
return optional_params
|
