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import json
import os
import threading
import time
from difflib import SequenceMatcher
from typing import Generator
import pytest
from fastapi import WebSocketDisconnect
from fastapi.testclient import TestClient
from starlette.testclient import WebSocketTestSession
from speaches.config import BYTES_PER_SECOND
from speaches.main import app
from speaches.server_models import TranscriptionVerboseResponse
SIMILARITY_THRESHOLD = 0.97
@pytest.fixture()
def client() -> Generator[TestClient, None, None]:
with TestClient(app) as client:
yield client
def get_audio_file_paths():
file_paths = []
directory = "tests/data"
for filename in reversed(os.listdir(directory)[5:6]):
if filename.endswith(".raw"):
file_paths.append(os.path.join(directory, filename))
return file_paths
file_paths = get_audio_file_paths()
def stream_audio_data(
ws: WebSocketTestSession, data: bytes, *, chunk_size: int = 4000, speed: float = 1.0
):
for i in range(0, len(data), chunk_size):
ws.send_bytes(data[i : i + chunk_size])
delay = len(data[i : i + chunk_size]) / BYTES_PER_SECOND / speed
time.sleep(delay)
def transcribe_audio_data(
client: TestClient, data: bytes
) -> TranscriptionVerboseResponse:
response = client.post(
"/v1/audio/transcriptions?response_format=verbose_json",
files={"file": ("audio.raw", data, "audio/raw")},
)
data = json.loads(response.json()) # TODO: figure this out
return TranscriptionVerboseResponse(**data) # type: ignore
@pytest.mark.parametrize("file_path", file_paths)
def test_ws_audio_transcriptions(client: TestClient, file_path: str):
with open(file_path, "rb") as file:
data = file.read()
streaming_transcription: TranscriptionVerboseResponse = None # type: ignore
with client.websocket_connect(
"/v1/audio/transcriptions?response_format=verbose_json"
) as ws:
thread = threading.Thread(
target=stream_audio_data, args=(ws, data), kwargs={"speed": 4.0}
)
thread.start()
while True:
try:
streaming_transcription = TranscriptionVerboseResponse(
**ws.receive_json()
)
except WebSocketDisconnect:
break
ws.close()
file_transcription = transcribe_audio_data(client, data)
s = SequenceMatcher(
lambda x: x == " ", file_transcription.text, streaming_transcription.text
)
assert (
s.ratio() > SIMILARITY_THRESHOLD
), f"\nExpected: {file_transcription.text}\nReceived: {streaming_transcription.text}"
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