|
| 1 | +import csv |
| 2 | +import pytest |
| 3 | +import tempfile |
| 4 | + |
| 5 | +import load_csv |
| 6 | + |
| 7 | +from unittest.mock import Mock, patch |
| 8 | + |
| 9 | + |
| 10 | +@pytest.fixture |
| 11 | +def csv_file() -> str: |
| 12 | + temp_file = _create_csv() |
| 13 | + return temp_file |
| 14 | + |
| 15 | + |
| 16 | +def _create_csv( |
| 17 | + columns: list[str] | None = None, data: list[list[str]] | None = None |
| 18 | +) -> str: |
| 19 | + temp_file = tempfile.NamedTemporaryFile( |
| 20 | + prefix="test-dialog", suffix=".csv", delete=False |
| 21 | + ) |
| 22 | + |
| 23 | + if not columns: |
| 24 | + columns = ["category", "subcategory", "question", "content", "dataset"] |
| 25 | + |
| 26 | + if not data: |
| 27 | + data = [ |
| 28 | + ["cat1", "subcat1", "q1", "content1", "dataset1"], |
| 29 | + ["cat2", "subcat2", "q2", "content2", "dataset2"], |
| 30 | + ] |
| 31 | + |
| 32 | + with open(temp_file.name, "w", newline="\n") as f: |
| 33 | + writer = csv.writer(f) |
| 34 | + writer.writerow(columns) |
| 35 | + writer.writerows(data) |
| 36 | + return temp_file.name |
| 37 | + |
| 38 | + |
| 39 | +def test_load_csv(mocker, dbsession, csv_file: str): |
| 40 | + mock_generate_embeddings: Mock = mocker.patch("load_csv.generate_embeddings") |
| 41 | + mock_generate_embeddings.return_value = [ |
| 42 | + [0.1] * 1536, |
| 43 | + [0.2] * 1536, |
| 44 | + ] # 1536 is the expected dimension of the embeddings |
| 45 | + |
| 46 | + load_csv.load_csv_and_generate_embeddings(csv_file, cleardb=True) |
| 47 | + |
| 48 | + result = dbsession.query(load_csv.CompanyContent).all() |
| 49 | + assert len(result) == 2 |
| 50 | + |
| 51 | + |
| 52 | +def test_multiple_columns_embedding(mocker, dbsession, csv_file: str): |
| 53 | + mock_generate_embeddings: Mock = mocker.patch("load_csv.generate_embeddings") |
| 54 | + mock_generate_embeddings.return_value = [ |
| 55 | + [0.1] * 1536, |
| 56 | + [0.2] * 1536, |
| 57 | + ] # 1536 is the expected dimension of the embeddings |
| 58 | + |
| 59 | + load_csv.load_csv_and_generate_embeddings( |
| 60 | + csv_file, cleardb=True, embed_columns=["category", "subcategory", "content"] |
| 61 | + ) |
| 62 | + |
| 63 | + mock_generate_embeddings.assert_called_with( |
| 64 | + ["cat1\nsubcat1\ncontent1", "cat2\nsubcat2\ncontent2"], |
| 65 | + embedding_llm_instance=load_csv.EMBEDDINGS_LLM, |
| 66 | + ) |
| 67 | + |
| 68 | + |
| 69 | +def test_clear_db(mocker, dbsession, csv_file: str): |
| 70 | + mock_generate_embeddings: Mock = mocker.patch("load_csv.generate_embeddings") |
| 71 | + mock_generate_embeddings.return_value = [ |
| 72 | + [0.1] * 1536, |
| 73 | + [0.2] * 1536, |
| 74 | + ] # 1536 is the expected dimension of the embeddings |
| 75 | + |
| 76 | + load_csv.load_csv_and_generate_embeddings(csv_file, cleardb=True) |
| 77 | + initial_run = dbsession.query(load_csv.CompanyContent).all() |
| 78 | + |
| 79 | + load_csv.load_csv_and_generate_embeddings(csv_file, cleardb=True) |
| 80 | + clear_db_run = dbsession.query(load_csv.CompanyContent).all() |
| 81 | + |
| 82 | + other_csv_file = _create_csv( |
| 83 | + data=[ |
| 84 | + ["cat3", "subcat3", "q3", "content3", "dataset3"], |
| 85 | + ["cat4", "subcat4", "q4", "content4", "dataset4"], |
| 86 | + ] |
| 87 | + ) |
| 88 | + load_csv.load_csv_and_generate_embeddings(other_csv_file, cleardb=False) |
| 89 | + dont_clear_db_run = dbsession.query(load_csv.CompanyContent).all() |
| 90 | + |
| 91 | + assert len(initial_run) == 2 |
| 92 | + assert len(clear_db_run) == 2 |
| 93 | + assert len(dont_clear_db_run) == 4 |
| 94 | + |
| 95 | + |
| 96 | +def test_ensure_necessary_columns(): |
| 97 | + with pytest.raises(Exception): |
| 98 | + load_csv.load_csv_and_generate_embeddings( |
| 99 | + _create_csv( |
| 100 | + columns=["category", "subcategory", "question"], |
| 101 | + data=[["cat1", "subcat1", "q1"]], |
| 102 | + ), |
| 103 | + cleardb=True, |
| 104 | + ) # missing content column |
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