Add : Unit Testing

testapp.py

@@ -0,0 +1,61 @@
+import pytest
+from app import app
+from helper_functions import predict_class, transform_list_of_texts, prepare_text, inference
+import torch
+from transformers import DistilBertForSequenceClassification, AutoTokenizer
+
+@pytest.fixture
+def client():
+    app.config['TESTING'] = True
+    with app.test_client() as client:
+        yield client
+
+# Unit tests
+
+def test_predict_class():
+    # Mock the model and tokenizer
+    model = DistilBertForSequenceClassification.from_pretrained("distilbert-base-uncased")
+    text = ["This is a sample text for testing."]
+    
+    predicted_class, class_probabilities = predict_class(text, model)
+    
+    assert isinstance(predicted_class, tuple)
+    assert isinstance(class_probabilities, dict)
+    assert len(class_probabilities) == 17  # Assuming 17 classes
+
+def test_transform_list_of_texts():
+    tokenizer = AutoTokenizer.from_pretrained("distilbert-base-uncased")
+    texts = ["This is a sample text.", "Another sample text."]
+    
+    result = transform_list_of_texts(texts, tokenizer, 510, 510, 1, 2550)
+    
+    assert isinstance(result, dict)
+    assert "input_ids" in result
+    assert "attention_mask" in result
+
+# Integration tests
+
+def test_pdf_upload(client):
+    # You'll need to create a sample PDF file for testing
+    with open('sample.pdf', 'rb') as pdf_file:
+        data = {'file': (pdf_file, 'sample.pdf')}
+        response = client.post('/pdf/upload', data=data, content_type='multipart/form-data')
+    
+    assert response.status_code == 200
+    assert b'class_probabilities' in response.data
+
+def test_sentence_endpoint(client):
+    data = {'text': 'This is a sample sentence for testing.'}
+    response = client.post('/sentence', data=data)
+    
+    assert response.status_code == 200
+    assert b'predicted_class' in response.data
+
+def test_voice_endpoint(client):
+    # You'll need to create a sample audio file for testing
+    with open('sample_audio.wav', 'rb') as audio_file:
+        data = {'audio': (audio_file, 'sample_audio.wav')}
+        response = client.post('/voice', data=data, content_type='multipart/form-data')
+    
+    assert response.status_code == 200
+    assert b'extracted_text' in response.data