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Use Config class w/ arbitrary_types_allowed for pydantic v1

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pydantic v2 warns about using a Config class.
But without this, pydantic v1 will raise an error:
    RuntimeError: no validator found for <class 'openai.Timeout'>,
    see `arbitrary_types_allowed` in Config
Putting arbitrary_types_allowed = True in the ConfigDict doesn't work in pydantic v1.
So we mostly use model_config = ConfigDict(...) and then only use the Config
class with arbitrary_types_allowed = True for pydantic v1.
This commit is contained in:
Marc Abramowitz 2024-05-13 11:22:50 -07:00
parent f233cde36c
commit e261a9b2c2
1 changed files with 25 additions and 7 deletions
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32
litellm/types/router.py
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@ -1,6 +1,6 @@
from typing import List, Optional, Union, Dict, Tuple, Literal
import httpx
from pydantic import ConfigDict, BaseModel, validator, Field
from pydantic import ConfigDict, BaseModel, validator, Field, __version__ as pydantic_version
from .completion import CompletionRequest
from .embedding import EmbeddingRequest
import uuid, enum
@ -184,9 +184,18 @@ class GenericLiteLLMParams(BaseModel):
max_retries = int(max_retries) # cast to int
super().__init__(max_retries=max_retries, **args, **params)
class Config:
extra = "allow"
arbitrary_types_allowed = True
model_config = ConfigDict(
extra = "allow",
arbitrary_types_allowed = True,
)
if pydantic_version.startswith("1"):
# pydantic v2 warns about using a Config class.
# But without this, pydantic v1 will raise an error:
# RuntimeError: no validator found for <class 'openai.Timeout'>,
# see `arbitrary_types_allowed` in Config
# Putting arbitrary_types_allowed = True in the ConfigDict doesn't work in pydantic v1.
class Config:
arbitrary_types_allowed = True
def __contains__(self, key):
# Define custom behavior for the 'in' operator
@ -245,9 +254,18 @@ class LiteLLM_Params(GenericLiteLLMParams):
max_retries = int(max_retries) # cast to int
super().__init__(max_retries=max_retries, **args, **params)
class Config:
extra = "allow"
arbitrary_types_allowed = True
model_config = ConfigDict(
extra = "allow",
arbitrary_types_allowed = True,
)
if pydantic_version.startswith("1"):
# pydantic v2 warns about using a Config class.
# But without this, pydantic v1 will raise an error:
# RuntimeError: no validator found for <class 'openai.Timeout'>,
# see `arbitrary_types_allowed` in Config
# Putting arbitrary_types_allowed = True in the ConfigDict doesn't work in pydantic v1.
class Config:
arbitrary_types_allowed = True
def __contains__(self, key):
# Define custom behavior for the 'in' operator