Leeladhar9/Text-classification-API

1from fastapi.testclient import TestClient # type: ignore
2from main import app
3from main import TextInput
4from fastapi.encoders import jsonable_encoder # type: ignore
5from transformers import pipeline
6
7client = TestClient(app)
8
9# Test the welcome endpoint
10def test_welcome():
11    # Test the welcome endpoint
12    response = client.get("/")
13    assert response.status_code == 200
14    assert response.json() == "Welcome to our Text Classification API"
15
16# Test the sentiment analysis endpoint for positive sentiment
17def test_positive_sentiment():
18    with client:
19        # Define the request payload 
20        # Initialize payload as a TextInput object
21        payload = TextInput(text="I love this product! It's amazing!")
22
23        # Convert TextInput object to JSON-serializable dictionary
24        payload_dict = jsonable_encoder(payload)
25        
26        # Send a POST request to the sentiment analysis endpoint
27        response = client.post("/analyze/{text}", json=payload_dict)
28
29        # Assert that the response status code is 200 OK
30        assert response.status_code == 200
31        
32        # Assert that the sentiment returned is positive
33        assert response.json()[0]['label'] == "positive"
34
35# Test the sentiment analysis endpoint for negative sentiment
36def test_negative_sentiment():
37    with client:
38        # Define the request payload 
39        # Initialize payload as a TextInput object
40        payload = TextInput(text="I'm really disappointed with this service. It's terrible.")
41
42        # Convert TextInput object to JSON-serializable dictionary
43        payload_dict = jsonable_encoder(payload)
44        
45        # Send a POST request to the sentiment analysis endpoint
46        response = client.post("/analyze/{text}", json=payload_dict)
47
48        # Assert that the response status code is 200 OK
49        assert response.status_code == 200
50        
51        # Assert that the sentiment returned is positive
52        assert response.json()[0]['label'] == "negative"
53
54# Test the sentiment analysis endpoint for neutral sentiment
55def test_neutral_sentiment():
56    with client:
57        # Define the request payload 
58        # Initialize payload as a TextInput object
59        payload = TextInput(text="This is a neutral statement.")
60
61        # Convert TextInput object to JSON-serializable dictionary
62        payload_dict = jsonable_encoder(payload)
63        
64        # Send a POST request to the sentiment analysis endpoint
65        response = client.post("/analyze/{text}", json=payload_dict)
66
67        # Assert that the response status code is 200 OK
68        assert response.status_code == 200
69        
70        # Assert that the sentiment returned is positive
71        assert response.json()[0]['label'] == "neutral"