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6a0d03914c
* test: drop the cwd-relative sys.path.insert calls from the test suite
TQ003 stands at 1,077 across 1,058 files, and 1,015 of them are the same shape:
sys.path.insert(0, os.path.abspath("../..")) and its deeper siblings. The
argument resolves against the working directory rather than the file, so from
the repo root, where every job runs pytest, it inserts the directory two levels
above the checkout. It has never pointed at litellm. The package is installed
into the environment anyway, which is what actually makes the import work, and
what the rule's message has said all along.
Removing them leaves 1,634 imports of sys and os with no remaining reference,
and those go too, except where another test module imports the name back out of
the file. The rest of TQ003 is 62 call sites that resolve against __file__ or a
variable, which are a different question and are left alone.
Collection is identical either way: 45,871 tests and the same 51 pre-existing
collection errors before and after, and ruff reports no new undefined name.
* test: drop the duplicate imports the sys.path sweep exposed to F811
* test(pre-call-utils): restore the os import the new bedrock tests need
141 lines
4.8 KiB
Python
141 lines
4.8 KiB
Python
import json
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from datetime import datetime
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from unittest.mock import AsyncMock
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import httpx
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import pytest
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import litellm
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from litellm import Choices, Message, ModelResponse
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from litellm.types.utils import StreamingChoices, ChatCompletionAudioResponse
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import base64
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import requests
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def check_non_streaming_response(completion):
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assert completion.choices[0].message.audio is not None, "Audio response is missing"
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assert isinstance(
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completion.choices[0].message.audio, ChatCompletionAudioResponse
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), "Invalid audio response type"
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assert len(completion.choices[0].message.audio.data) > 0, "Audio data is empty"
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async def check_streaming_response(completion):
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_audio_bytes = None
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_audio_transcript = None
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_audio_id = None
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async for chunk in completion:
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print(chunk)
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if len(chunk.choices) == 0:
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continue
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_choice: StreamingChoices = chunk.choices[0]
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if _choice.delta is not None and _choice.delta.audio is not None:
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if _choice.delta.audio.get("data") is not None:
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_audio_bytes = _choice.delta.audio["data"]
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if _choice.delta.audio.get("transcript") is not None:
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_audio_transcript = _choice.delta.audio["transcript"]
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if _choice.delta.audio.get("id") is not None:
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_audio_id = _choice.delta.audio["id"]
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# Atleast one chunk should have set _audio_bytes, _audio_transcript, _audio_id
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assert _audio_bytes is not None
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assert _audio_transcript is not None
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assert _audio_id is not None
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@pytest.mark.asyncio
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# @pytest.mark.flaky(retries=3, delay=1)
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@pytest.mark.parametrize("stream", [True, False])
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async def test_audio_output_from_model(stream):
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audio_format = "pcm16"
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if stream is False:
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audio_format = "wav"
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litellm.set_verbose = False
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try:
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completion = await litellm.acompletion(
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model="gpt-audio-1.5",
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modalities=["text", "audio"],
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audio={"voice": "alloy", "format": "pcm16"},
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messages=[{"role": "user", "content": "response in 1 word - yes or no"}],
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stream=stream,
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)
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except litellm.Timeout as e:
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print(e)
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pytest.skip("Skipping test due to timeout")
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except Exception as e:
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err = str(e).lower()
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if (
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"model_not_found" in err
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or "does not exist" in err
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or "openai-internal" in err
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):
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pytest.skip(f"Skipping - upstream gpt-audio-1.5 unavailable: {e}")
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raise
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if stream is True:
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await check_streaming_response(completion)
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else:
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print("response= ", completion)
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check_non_streaming_response(completion)
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wav_bytes = base64.b64decode(completion.choices[0].message.audio.data)
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with open("dog.wav", "wb") as f:
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f.write(wav_bytes)
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@pytest.mark.asyncio
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@pytest.mark.parametrize("stream", [True, False])
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@pytest.mark.parametrize("model", ["gpt-audio-1.5"])
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async def test_audio_input_to_model(stream, model):
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# Fetch the audio file and convert it to a base64 encoded string
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audio_format = "pcm16"
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if stream is False:
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audio_format = "wav"
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litellm._turn_on_debug()
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litellm.drop_params = True
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url = "https://openaiassets.blob.core.windows.net/$web/API/docs/audio/alloy.wav"
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response = requests.get(url)
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response.raise_for_status()
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wav_data = response.content
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encoded_string = base64.b64encode(wav_data).decode("utf-8")
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try:
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completion = await litellm.acompletion(
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model=model,
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modalities=["text", "audio"],
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audio={"voice": "alloy", "format": audio_format},
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stream=stream,
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messages=[
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{
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"role": "user",
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"content": [
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{"type": "text", "text": "What is in this recording?"},
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{
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"type": "input_audio",
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"input_audio": {"data": encoded_string, "format": "wav"},
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},
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],
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},
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],
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)
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except litellm.Timeout as e:
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print(e)
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pytest.skip("Skipping test due to timeout")
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except Exception as e:
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err = str(e).lower()
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if (
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"model_not_found" in err
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or "does not exist" in err
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or "openai-internal" in err
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):
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pytest.skip(f"Skipping - upstream gpt-audio-1.5 unavailable: {e}")
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raise
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if stream is True:
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await check_streaming_response(completion)
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else:
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print("response= ", completion)
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check_non_streaming_response(completion)
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wav_bytes = base64.b64decode(completion.choices[0].message.audio.data)
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with open("dog.wav", "wb") as f:
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f.write(wav_bytes)
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