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# # #### What this tests ####
# # # This tests the LiteLLM Class
# import sys, os
# import traceback
# import pytest
# sys.path.insert(
# 0, os.path.abspath("../..")
# ) # Adds the parent directory to the system path
# import litellm
# import asyncio
# # litellm.set_verbose = True
# # from litellm import Router
# import instructor
# from litellm import completion
# from pydantic import BaseModel
# class User(BaseModel):
# name: str
# age: int
# client = instructor.from_litellm(completion)
# litellm.set_verbose = True
# resp = client.chat.completions.create(
# model="gpt-3.5-turbo",
# max_tokens=1024,
# messages=[
# {
# "role": "user",
# "content": "Extract Jason is 25 years old.",
# }
# ],
# response_model=User,
# num_retries=10,
# )
# assert isinstance(resp, User)
# assert resp.name == "Jason"
# assert resp.age == 25
# # from pydantic import BaseModel
# # # This enables response_model keyword
# # # from client.chat.completions.create
# # client = instructor.patch(
# # Router(
# # model_list=[
# # {
# # "model_name": "gpt-3.5-turbo", # openai model name
# # "litellm_params": { # params for litellm completion/embedding call
# # "model": "azure/chatgpt-v-3",
# # "api_key": os.getenv("AZURE_API_KEY"),
# # "api_version": os.getenv("AZURE_API_VERSION"),
# # "api_base": os.getenv("AZURE_API_BASE"),
# # },
# # }
# # ]
# # )
# # )
# # class UserDetail(BaseModel):
# # name: str
# # age: int
# # user = client.chat.completions.create(
# # model="gpt-3.5-turbo",
# # response_model=UserDetail,
# # messages=[
# # {"role": "user", "content": "Extract Jason is 25 years old"},
# # ],
# # )
# # assert isinstance(user, UserDetail)
# # assert user.name == "Jason"
# # assert user.age == 25
# # print(f"user: {user}")
# # # import instructor
# # # from openai import AsyncOpenAI
# # aclient = instructor.apatch(
# # Router(
# # model_list=[
# # {
# # "model_name": "gpt-3.5-turbo", # openai model name
# # "litellm_params": { # params for litellm completion/embedding call
# # "model": "azure/chatgpt-v-3",
# # "api_key": os.getenv("AZURE_API_KEY"),
# # "api_version": os.getenv("AZURE_API_VERSION"),
# # "api_base": os.getenv("AZURE_API_BASE"),
# # },
# # }
# # ],
# # default_litellm_params={"acompletion": True},
# # )
# # )
# # class UserExtract(BaseModel):
# # name: str
# # age: int
# # async def main():
# # model = await aclient.chat.completions.create(
# # model="gpt-3.5-turbo",
# # response_model=UserExtract,
# # messages=[
# # {"role": "user", "content": "Extract jason is 25 years old"},
# # ],
# # )
# # print(f"model: {model}")
# # asyncio.run(main())
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