mirror of
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93 lines
2.4 KiB
Python
93 lines
2.4 KiB
Python
# #### What this tests ####
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# # This tests the LiteLLM Class
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# import sys, os
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# import traceback
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# import pytest
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# sys.path.insert(
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# 0, os.path.abspath("../..")
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# ) # Adds the parent directory to the system path
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# import litellm
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# import asyncio
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# litellm.set_verbose = True
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# from litellm import Router
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# import instructor
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# from pydantic import BaseModel
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# # This enables response_model keyword
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# # from client.chat.completions.create
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# client = instructor.patch(
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# Router(
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# model_list=[
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# {
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# "model_name": "gpt-3.5-turbo", # openai model name
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# "litellm_params": { # params for litellm completion/embedding call
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# "model": "azure/chatgpt-v-2",
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# "api_key": os.getenv("AZURE_API_KEY"),
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# "api_version": os.getenv("AZURE_API_VERSION"),
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# "api_base": os.getenv("AZURE_API_BASE"),
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# },
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# }
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# ]
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# )
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# )
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# class UserDetail(BaseModel):
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# name: str
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# age: int
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# user = client.chat.completions.create(
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# model="gpt-3.5-turbo",
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# response_model=UserDetail,
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# messages=[
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# {"role": "user", "content": "Extract Jason is 25 years old"},
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# ],
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# )
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# assert isinstance(user, UserDetail)
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# assert user.name == "Jason"
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# assert user.age == 25
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# print(f"user: {user}")
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# # import instructor
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# # from openai import AsyncOpenAI
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# aclient = instructor.apatch(
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# Router(
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# model_list=[
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# {
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# "model_name": "gpt-3.5-turbo", # openai model name
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# "litellm_params": { # params for litellm completion/embedding call
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# "model": "azure/chatgpt-v-2",
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# "api_key": os.getenv("AZURE_API_KEY"),
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# "api_version": os.getenv("AZURE_API_VERSION"),
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# "api_base": os.getenv("AZURE_API_BASE"),
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# },
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# }
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# ],
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# default_litellm_params={"acompletion": True},
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# )
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# )
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# class UserExtract(BaseModel):
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# name: str
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# age: int
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# async def main():
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# model = await aclient.chat.completions.create(
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# model="gpt-3.5-turbo",
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# response_model=UserExtract,
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# messages=[
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# {"role": "user", "content": "Extract jason is 25 years old"},
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# ],
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# )
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# print(f"model: {model}")
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# asyncio.run(main())
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