litellm/tests/local_testing/test_whisper.py

# What is this?
## Tests `litellm.transcription` endpoint. Outside litellm module b/c of audio file used in testing (it's ~700kb).

import asyncio
import logging
import os
import sys
import time
import traceback
from typing import Optional

import aiohttp
import dotenv
import pytest
from dotenv import load_dotenv
from openai import AsyncOpenAI

import litellm
from litellm.integrations.custom_logger import CustomLogger

# Get the current directory of the file being run
pwd = os.path.dirname(os.path.realpath(__file__))
print(pwd)

file_path = os.path.join(pwd, "gettysburg.wav")

audio_file = open(file_path, "rb")


file2_path = os.path.join(pwd, "eagle.wav")
audio_file2 = open(file2_path, "rb")

load_dotenv()

sys.path.insert(
    0, os.path.abspath("../")
)  # Adds the parent directory to the system path
import litellm
from litellm import Router


@pytest.mark.parametrize(
    "model, api_key, api_base",
    [
        ("whisper-1", None, None),
        # ("groq/whisper-large-v3", None, None),
        (
            "azure/azure-whisper",
            os.getenv("AZURE_EUROPE_API_KEY"),
            "https://my-endpoint-europe-berri-992.openai.azure.com/",
        ),
    ],
)
@pytest.mark.parametrize("response_format", ["json", "vtt"])
@pytest.mark.parametrize("sync_mode", [True, False])
@pytest.mark.asyncio
async def test_transcription(model, api_key, api_base, response_format, sync_mode):
    if sync_mode:
        transcript = litellm.transcription(
            model=model,
            file=audio_file,
            api_key=api_key,
            api_base=api_base,
            response_format=response_format,
            drop_params=True,
        )
    else:
        transcript = await litellm.atranscription(
            model=model,
            file=audio_file,
            api_key=api_key,
            api_base=api_base,
            response_format=response_format,
            drop_params=True,
        )
    print(f"transcript: {transcript.model_dump()}")
    print(f"transcript: {transcript._hidden_params}")

    assert transcript.text is not None


@pytest.mark.asyncio()
async def test_transcription_caching():
    import litellm
    from litellm.caching.caching import Cache

    litellm.set_verbose = True
    litellm.cache = Cache()

    # make raw llm api call

    response_1 = await litellm.atranscription(
        model="whisper-1",
        file=audio_file,
    )

    await asyncio.sleep(5)

    # cache hit

    response_2 = await litellm.atranscription(
        model="whisper-1",
        file=audio_file,
    )

    print("response_1", response_1)
    print("response_2", response_2)
    print("response2 hidden params", response_2._hidden_params)
    assert response_2._hidden_params["cache_hit"] is True

    # cache miss

    response_3 = await litellm.atranscription(
        model="whisper-1",
        file=audio_file2,
    )
    print("response_3", response_3)
    print("response3 hidden params", response_3._hidden_params)
    assert response_3._hidden_params.get("cache_hit") is not True
    assert response_3.text != response_2.text

    litellm.cache = None