litellm-mirror/litellm/tests/test_class.py
2023-11-13 18:15:14 -08:00

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1.4 KiB
Python

#### 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
mr1 = litellm.ModelResponse(stream=True, model="gpt-3.5-turbo")
mr1.choices[0].finish_reason = "stop"
mr2 = litellm.ModelResponse(stream=True, model="gpt-3.5-turbo")
print(mr2.choices[0].finish_reason)
# 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(user, UserDetail)
# assert user.name == "Jason"
# assert user.age == 25
# print(f"user: {user}")