Initial Commit

requirements.txt

@@ -1,4 +1,6 @@
 git+https://github.com/openai/whisper.git
 transformers
 requests
-huggingface_hub
+huggingface_hub
+pytest
+gradio

setup.sh

@@ -1,16 +0,0 @@
-#!/bin/bash
-
-# Define the path to the virtual environment
-VENV_DIR="path/to/venv"
-
-# Create the virtual environment
-python3 -m venv $VENV_DIR
-
-# Activate the virtual environment
-source $VENV_DIR/bin/activate
-
-# Install required packages
-pip3 install -r requirements.txt
-
-# Message to confirm installation completion
-echo "Python environment setup is complete, and packages are installed."

tests/test_module.py

@@ -0,0 +1,62 @@
+import pytest
+import os
+import sys
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
+from unittest.mock import patch
+from app import transcribe
+
+# Add the root directory to the Python path so we can import app.py
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
+
+# Test to check if necessary libraries are installed
+def test_libraries_installed():
+    try:
+        import requests
+        import gradio as gr
+        import transformers
+        import time
+        import os
+        import tempfile
+        from huggingface_hub import InferenceClient
+    except ImportError as e:
+        pytest.fail(f"Library not installed: {e}")
+
+# Define a constant for the audio file to be used in tests
+AUDIO_FILE = "tests/sample.wav"
+
+# Fixture to check if the audio file exists
+@pytest.fixture
+def check_audio_file():
+    print(f"Checking if audio file {AUDIO_FILE} exists...")
+    assert os.path.exists(AUDIO_FILE), f"Audio file {AUDIO_FILE} does not exist."
+    return AUDIO_FILE
+
+# Need to login Hugging Face account to use the API
+# # Test the transcribe function using the API
+# @patch('app.InferenceClient')  # Mock the InferenceClient to simulate API response
+# def test_transcribe_api(mock_client, check_audio_file):
+#     # Mocking the return value of the API call
+#     mock_client.return_value.automatic_speech_recognition.return_value.text = "This is a test transcription."
+    
+#     # Call the transcribe function with the mock and use_api=True
+#     result, time_taken = transcribe(check_audio_file, use_api=True)
+    
+#     # Assert the mocked transcription matches the expected result
+#     assert result == "This is a test transcription."
+#     assert time_taken.startswith('Using API it took: ')
+
+# Test the transcribe function using the local pipeline (when use_api=False)
+@patch('app.pipeline')  # Mock the local pipeline function
+def test_transcribe_local(mock_pipeline, check_audio_file):
+    # Mocking the local transcription
+    mock_pipeline.return_value.return_value['text'] = "Now go away or I shall taunt you a second time!"
+    
+    # Call the transcribe function with the mock and use_api=False
+    result, time_taken = transcribe(check_audio_file, use_api=False)
+
+    # print(result)
+    
+    # Assert the mocked transcription matches the expected result
+    assert result.strip() == "Now go away or I shall taunt you a second time!"
+    assert time_taken.startswith('Using local pipeline it took: ')
+