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VenkateshRoshan
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Commit
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6afd1f4
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Parent(s):
f461359
Initial Commit
Browse files- Dog.jpg +0 -0
- dockerfile → __init__.py +0 -0
- __pycache__/__init__.cpython-310.pyc +0 -0
- __pycache__/app.cpython-310.pyc +0 -0
- butterfly.png +0 -0
- requirements.txt +3 -1
- setup.sh +0 -16
- tests/__pycache__/test_module.cpython-310-pytest-8.3.3.pyc +0 -0
- tests/sample.wav +0 -0
- tests/test_module.py +62 -0
Dog.jpg
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dockerfile → __init__.py
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__pycache__/__init__.cpython-310.pyc
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__pycache__/app.cpython-310.pyc
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butterfly.png
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requirements.txt
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git+https://github.com/openai/whisper.git
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transformers
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requests
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huggingface_hub
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git+https://github.com/openai/whisper.git
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transformers
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requests
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huggingface_hub
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pytest
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gradio
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setup.sh
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#!/bin/bash
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# Define the path to the virtual environment
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VENV_DIR="path/to/venv"
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# Create the virtual environment
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python3 -m venv $VENV_DIR
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# Activate the virtual environment
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source $VENV_DIR/bin/activate
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# Install required packages
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pip3 install -r requirements.txt
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# Message to confirm installation completion
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echo "Python environment setup is complete, and packages are installed."
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tests/__pycache__/test_module.cpython-310-pytest-8.3.3.pyc
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tests/sample.wav
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tests/test_module.py
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import pytest
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import os
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import sys
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sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
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from unittest.mock import patch
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from app import transcribe
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# Add the root directory to the Python path so we can import app.py
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sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
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# Test to check if necessary libraries are installed
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def test_libraries_installed():
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try:
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import requests
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import gradio as gr
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import transformers
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import time
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import os
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import tempfile
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from huggingface_hub import InferenceClient
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except ImportError as e:
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pytest.fail(f"Library not installed: {e}")
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# Define a constant for the audio file to be used in tests
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AUDIO_FILE = "tests/sample.wav"
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# Fixture to check if the audio file exists
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@pytest.fixture
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def check_audio_file():
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print(f"Checking if audio file {AUDIO_FILE} exists...")
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assert os.path.exists(AUDIO_FILE), f"Audio file {AUDIO_FILE} does not exist."
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return AUDIO_FILE
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# Need to login Hugging Face account to use the API
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# # Test the transcribe function using the API
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# @patch('app.InferenceClient') # Mock the InferenceClient to simulate API response
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# def test_transcribe_api(mock_client, check_audio_file):
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# # Mocking the return value of the API call
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# mock_client.return_value.automatic_speech_recognition.return_value.text = "This is a test transcription."
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# # Call the transcribe function with the mock and use_api=True
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# result, time_taken = transcribe(check_audio_file, use_api=True)
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# # Assert the mocked transcription matches the expected result
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# assert result == "This is a test transcription."
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# assert time_taken.startswith('Using API it took: ')
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# Test the transcribe function using the local pipeline (when use_api=False)
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@patch('app.pipeline') # Mock the local pipeline function
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def test_transcribe_local(mock_pipeline, check_audio_file):
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# Mocking the local transcription
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mock_pipeline.return_value.return_value['text'] = "Now go away or I shall taunt you a second time!"
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# Call the transcribe function with the mock and use_api=False
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result, time_taken = transcribe(check_audio_file, use_api=False)
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# print(result)
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# Assert the mocked transcription matches the expected result
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assert result.strip() == "Now go away or I shall taunt you a second time!"
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assert time_taken.startswith('Using local pipeline it took: ')
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