litellm-mirror/tests/test_openai_fine_tuning.py
2024-07-31 15:58:35 -07:00

53 lines
1.5 KiB
Python

from openai import AsyncOpenAI
import os
import pytest
@pytest.mark.asyncio
async def test_openai_fine_tuning():
"""
[PROD Test] Ensures logprobs are returned correctly
"""
client = AsyncOpenAI(api_key="sk-1234", base_url="http://0.0.0.0:4000")
# file_name = "openai_batch_completions.jsonl"
# _current_dir = os.path.dirname(os.path.abspath(__file__))
# file_path = os.path.join(_current_dir, file_name)
# response = await client.files.create(
# extra_body={"custom_llm_provider": "azure"},
# file=open(file_path, "rb"),
# purpose="fine-tune",
# )
# print("response from files.create: {}".format(response))
# # create fine tuning job
# ft_job = await client.fine_tuning.jobs.create(
# model="gpt-35-turbo-1106",
# training_file=response.id,
# extra_body={"custom_llm_provider": "azure"},
# )
# print("response from ft job={}".format(ft_job))
# # response from example endpoint
# assert ft_job.id == "file-abc123"
# get fine tuning job
# specific_ft_job = await client.fine_tuning.jobs.retrieve(
# fine_tuning_job_id="123",
# extra_body={"custom_llm_provider": "azure"},
# )
# list all fine tuning jobs
list_ft_jobs = await client.fine_tuning.jobs.list(
extra_query={"custom_llm_provider": "azure"}
)
# cancel specific fine tuning job
cancel_ft_job = await client.fine_tuning.jobs.cancel(
fine_tuning_job_id="123",
extra_body={"custom_llm_provider": "azure"},
)