litellm-mirror/litellm/tests/test_fine_tuning_api.py

import os
import sys
import traceback

import pytest

sys.path.insert(
    0, os.path.abspath("../..")
)  # Adds the parent directory to the system path
from openai import APITimeoutError as Timeout

import litellm

litellm.num_retries = 0
import asyncio
import logging

from litellm import create_fine_tuning_job
from litellm._logging import verbose_logger


def test_create_fine_tune_job():
    verbose_logger.setLevel(logging.DEBUG)
    file_name = "openai_batch_completions.jsonl"
    _current_dir = os.path.dirname(os.path.abspath(__file__))
    file_path = os.path.join(_current_dir, file_name)

    file_obj = litellm.create_file(
        file=open(file_path, "rb"),
        purpose="fine-tune",
        custom_llm_provider="openai",
    )
    print("Response from creating file=", file_obj)

    create_fine_tuning_response = litellm.create_fine_tuning_job(
        model="gpt-3.5-turbo-0125",
        training_file=file_obj.id,
    )

    print("response from litellm.create_fine_tuning_job=", create_fine_tuning_response)

    assert create_fine_tuning_response.id is not None
    assert create_fine_tuning_response.model == "gpt-3.5-turbo-0125"

    # list fine tuning jobs
    print("listing ft jobs")
    ft_jobs = litellm.list_fine_tuning_jobs(limit=2)
    print("response from litellm.list_fine_tuning_jobs=", ft_jobs)

    assert len(list(ft_jobs)) > 0

    # delete file

    litellm.file_delete(
        file_id=file_obj.id,
    )

    # cancel ft job
    response = litellm.cancel_fine_tuning_job(
        fine_tuning_job_id=create_fine_tuning_response.id,
    )

    print("response from litellm.cancel_fine_tuning_job=", response)

    assert response.status == "cancelled"
    assert response.id == create_fine_tuning_response.id
    pass


@pytest.mark.asyncio
async def test_create_fine_tune_jobs_async():
    verbose_logger.setLevel(logging.DEBUG)
    file_name = "openai_batch_completions.jsonl"
    _current_dir = os.path.dirname(os.path.abspath(__file__))
    file_path = os.path.join(_current_dir, file_name)

    file_obj = await litellm.acreate_file(
        file=open(file_path, "rb"),
        purpose="fine-tune",
        custom_llm_provider="openai",
    )
    print("Response from creating file=", file_obj)

    create_fine_tuning_response = await litellm.acreate_fine_tuning_job(
        model="gpt-3.5-turbo-0125",
        training_file=file_obj.id,
    )

    print("response from litellm.create_fine_tuning_job=", create_fine_tuning_response)

    assert create_fine_tuning_response.id is not None
    assert create_fine_tuning_response.model == "gpt-3.5-turbo-0125"

    # list fine tuning jobs
    print("listing ft jobs")
    ft_jobs = await litellm.alist_fine_tuning_jobs(limit=2)
    print("response from litellm.list_fine_tuning_jobs=", ft_jobs)
    assert len(list(ft_jobs)) > 0

    # delete file

    await litellm.afile_delete(
        file_id=file_obj.id,
    )

    # cancel ft job
    response = await litellm.acancel_fine_tuning_job(
        fine_tuning_job_id=create_fine_tuning_response.id,
    )

    print("response from litellm.cancel_fine_tuning_job=", response)

    assert response.status == "cancelled"
    assert response.id == create_fine_tuning_response.id
    pass


@pytest.mark.asyncio
async def test_azure_create_fine_tune_jobs_async():
    verbose_logger.setLevel(logging.DEBUG)
    file_name = "azure_fine_tune.jsonl"
    _current_dir = os.path.dirname(os.path.abspath(__file__))
    file_path = os.path.join(_current_dir, file_name)

    file_obj = await litellm.acreate_file(
        file=open(file_path, "rb"),
        purpose="fine-tune",
        custom_llm_provider="azure",
        api_key=os.getenv("AZURE_SWEDEN_API_KEY"),
        api_base="https://my-endpoint-sweden-berri992.openai.azure.com/",
    )
    print("Response from creating file=", file_obj)

    await asyncio.sleep(5)

    create_fine_tuning_response = await litellm.acreate_fine_tuning_job(
        model="gpt-35-turbo-1106",
        training_file=file_obj.id,
        custom_llm_provider="azure",
        api_key=os.getenv("AZURE_SWEDEN_API_KEY"),
        api_base="https://my-endpoint-sweden-berri992.openai.azure.com/",
    )

    print("response from litellm.create_fine_tuning_job=", create_fine_tuning_response)

    assert create_fine_tuning_response.id is not None
    assert create_fine_tuning_response.model == "gpt-35-turbo-1106"

    # # list fine tuning jobs
    # print("listing ft jobs")
    # ft_jobs = await litellm.alist_fine_tuning_jobs(limit=2)
    # print("response from litellm.list_fine_tuning_jobs=", ft_jobs)
    # assert len(list(ft_jobs)) > 0

    # # delete file

    # await litellm.afile_delete(
    #     file_id=file_obj.id,
    # )

    # # cancel ft job
    # response = await litellm.acancel_fine_tuning_job(
    #     fine_tuning_job_id=create_fine_tuning_response.id,
    # )

    # print("response from litellm.cancel_fine_tuning_job=", response)

    # assert response.status == "cancelled"
    # assert response.id == create_fine_tuning_response.id
    # pass