| # #### 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 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-2", | |
| # # "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(model, UserExtract) | |
| # # 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-2", | |
| # "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()) |