| """ |
| This file contains tests for the API of your model. You can run these tests by installing test requirements: |
| |
| ```bash |
| pip install -r requirements-test.txt |
| ``` |
| Then execute `pytest` in the directory of this file. |
| |
| - Change `NewModel` to the name of the class in your model.py file. |
| - Change the `request` and `expected_response` variables to match the input and output of your model. |
| """ |
|
|
| import pytest |
| import json |
| from model import GLiNERModel |
|
|
|
|
| @pytest.fixture |
| def client(): |
| from _wsgi import init_app |
| app = init_app(model_class=GLiNERModel) |
| app.config['TESTING'] = True |
| with app.test_client() as client: |
| yield client |
|
|
|
|
| def test_predict(client): |
| request = { |
| 'tasks': [{'id': 6, |
| 'data': {'id': '5316', 'sample_id': '83dd3f62-4dd5-45eb-8626-ee8539963194', |
| 'tokens': ['atomoxetine', '[', 'oral', 'suspension', ']', 'norepinephrine', 'reuptake', |
| 'inhibitor'], |
| 'ner_tags': ['B-Medication/Vaccine', 'O', 'O', 'O', 'O', 'O', 'O', 'O'], |
| 'ner_tags_index': [63, 0, 0, 0, 0, 0, 0, 0], |
| 'text': 'atomoxetine [ oral suspension ] norepinephrine reuptake inhibitor'}, |
| 'meta': {}, |
| 'created_at': '2024-04-13T19:22:37.153686Z', |
| 'updated_at': '2024-05-03T00:03:22.356871Z', |
| 'is_labeled': False, |
| 'overlap': 1, |
| 'inner_id': 6, |
| 'total_annotations': 1, |
| 'cancelled_annotations': 0, |
| 'total_predictions': 0, |
| 'comment_count': 0, |
| 'unresolved_comment_count': 0, |
| 'last_comment_updated_at': None, |
| 'project': 2, |
| 'updated_by': 1, |
| 'file_upload': None, |
| 'comment_authors': [], |
| 'predictions': [], |
| }], |
| |
| 'label_config': '<View> \\n <Labels name="label" toName="text">\\n<Label value="Medication/Vaccine" background="red"/>\\n<Label value="MedicalProcedure" background="blue"/>\\n<Label value="AnatomicalStructure" background="orange"/>\\n<Label value="Symptom" background="green"/>\\n<Label value="Disease" background="purple"/>\\n</Labels>\\n<Text name="text" value="$text"/>\\n</View>' |
| } |
|
|
| expected_response = {"results": [{"model_version": "GLiNERModel-v0.0.1", "result": [ |
| {"from_name": "label", "score": 0.922, "to_name": "text", "type": "labels", |
| "value": {"end": 11, "labels": ["Medication/Vaccine"], "start": 0, "text": "atomoxetine"}}, |
| {"from_name": "label", "score": 0.7053, "to_name": "text", "type": "labels", |
| "value": {"end": 65, "labels": ["Medication/Vaccine"], "start": 32, |
| "text": "norepinephrine reuptake inhibitor"}}], "score": 0.7053}]} |
|
|
| response = client.post('/predict', data=json.dumps(request), content_type='application/json') |
| assert response.status_code == 200 |
| response = json.loads(response.data) |
| assert expected_response == response |
|
|
