Load csv tests

.gitignore

@@ -120,7 +120,8 @@ celerybeat.pid
 *.sage.py
 
 # Environments
-.env
+.env*
+!.env.sample
 .venv
 env/
 venv/
@@ -166,4 +167,5 @@ requirements.txt
 !src/tests/fixtures/*.csv
 !src/tests/fixtures/*.toml
 !sample_data/*.csv
-!sample_data/*.toml
+!sample_data/*.toml
+.vscode

docker-compose.test.yml

@@ -1,4 +1,3 @@
-version: '3.3'
 services:
   db:
     image: pgvector/pgvector:pg15
@@ -7,7 +6,6 @@ services:
       - '5432:5432'
     volumes:
        - ./etc/db-ext-vector-test.sql:/docker-entrypoint-initdb.d/init.sql
-       - postgres_data:/var/lib/postgresql/data/
     environment:
       POSTGRES_USER: talkdai
       POSTGRES_PASSWORD: talkdai
@@ -31,7 +29,4 @@ services:
     env_file:
       - ./src/tests/.env.testing
     volumes:
-      - ./src/tests/:/app/src/tests/
-
-volumes:
-  postgres_data:
+      - ./src/tests/:/app/src/tests/

docker-compose.yml

@@ -1,4 +1,3 @@
-version: '3.3'
 services:
   db:
     image: pgvector/pgvector:pg15
@@ -10,8 +9,8 @@ services:
       POSTGRES_PASSWORD: talkdai
       POSTGRES_DB: talkdai
     volumes:
-       - ./data/db:/var/lib/postgresql/data
-       - ./psql/db-ext-vector.sql:/docker-entrypoint-initdb.d/db-ext-vector.sql
+       - db-data:/var/lib/postgresql/data
+       - ./ext/db-ext-vector.sql:/docker-entrypoint-initdb.d/db-ext-vector.sql
     healthcheck:
       test: ["CMD", "pg_isready", "-d", "talkdai", "-U", "talkdai"]
       interval: 10s
@@ -25,7 +24,6 @@ services:
     tty: true
     volumes:
       - ./:/app
-      - ./.empty:/app/data/db
       - ./static:/app/static
       - ./sample_data:/app/src/sample_data
     ports:
@@ -41,3 +39,4 @@ services:
 
 volumes:
   open-webui:
+  db-data:

src/load_csv.py

@@ -11,7 +11,9 @@
 
 session = next(get_session())
 
-def load_csv_and_generate_embeddings(path, cleardb=False, embed_columns=("content",)):
+def load_csv_and_generate_embeddings(path: str, cleardb=False, embed_columns: None | list[str] = None) -> None:
+    if not embed_columns:
+        embed_columns = ["content"]
     df = pd.read_csv(path)
     necessary_cols = ["category", "subcategory", "question", "content"]
     for col in necessary_cols:

src/tests/conftest.py

@@ -9,8 +9,17 @@
 from dialog_lib.db.utils import create_chat_session
 from dialog.db import get_session
 
+import dotenv
+
+dotenv.load_dotenv()
+
 SQLALCHEMY_DATABASE_URL = "postgresql://talkdai:talkdai@db/test_talkdai"
 
+TEST_DATABASE_URL = os.getenv('TEST_DATABASE_URL')
+if TEST_DATABASE_URL:
+    SQLALCHEMY_DATABASE_URL = TEST_DATABASE_URL
+
+
 @pytest.fixture
 def dbsession(mocker):
     engine = create_engine(SQLALCHEMY_DATABASE_URL)

src/tests/test_load_csv.py

@@ -0,0 +1,104 @@
+import csv
+import pytest
+import tempfile
+
+import load_csv
+
+from unittest.mock import Mock, patch
+
+
+@pytest.fixture
+def csv_file() -> str:
+    temp_file = _create_csv()
+    return temp_file
+
+
+def _create_csv(
+    columns: list[str] | None = None, data: list[list[str]] | None = None
+) -> str:
+    temp_file = tempfile.NamedTemporaryFile(
+        prefix="test-dialog", suffix=".csv", delete=False
+    )
+
+    if not columns:
+        columns = ["category", "subcategory", "question", "content", "dataset"]
+
+    if not data:
+        data = [
+            ["cat1", "subcat1", "q1", "content1", "dataset1"],
+            ["cat2", "subcat2", "q2", "content2", "dataset2"],
+        ]
+
+    with open(temp_file.name, "w", newline="\n") as f:
+        writer = csv.writer(f)
+        writer.writerow(columns)
+        writer.writerows(data)
+    return temp_file.name
+
+
+def test_load_csv(mocker, dbsession, csv_file: str):
+    mock_generate_embeddings: Mock = mocker.patch("load_csv.generate_embeddings")
+    mock_generate_embeddings.return_value = [
+        [0.1] * 1536,
+        [0.2] * 1536,
+    ]  # 1536 is the expected dimension of the embeddings
+
+    load_csv.load_csv_and_generate_embeddings(csv_file, cleardb=True)
+
+    result = dbsession.query(load_csv.CompanyContent).all()
+    assert len(result) == 2
+
+
+def test_multiple_columns_embedding(mocker, dbsession, csv_file: str):
+    mock_generate_embeddings: Mock = mocker.patch("load_csv.generate_embeddings")
+    mock_generate_embeddings.return_value = [
+        [0.1] * 1536,
+        [0.2] * 1536,
+    ]  # 1536 is the expected dimension of the embeddings
+
+    load_csv.load_csv_and_generate_embeddings(
+        csv_file, cleardb=True, embed_columns=["category", "subcategory", "content"]
+    )
+
+    mock_generate_embeddings.assert_called_with(
+        ["cat1\nsubcat1\ncontent1", "cat2\nsubcat2\ncontent2"],
+        embedding_llm_instance=load_csv.EMBEDDINGS_LLM,
+    )
+
+
+def test_clear_db(mocker, dbsession, csv_file: str):
+    mock_generate_embeddings: Mock = mocker.patch("load_csv.generate_embeddings")
+    mock_generate_embeddings.return_value = [
+        [0.1] * 1536,
+        [0.2] * 1536,
+    ]  # 1536 is the expected dimension of the embeddings
+
+    load_csv.load_csv_and_generate_embeddings(csv_file, cleardb=True)
+    initial_run = dbsession.query(load_csv.CompanyContent).all()
+
+    load_csv.load_csv_and_generate_embeddings(csv_file, cleardb=True)
+    clear_db_run = dbsession.query(load_csv.CompanyContent).all()
+
+    other_csv_file = _create_csv(
+        data=[
+            ["cat3", "subcat3", "q3", "content3", "dataset3"],
+            ["cat4", "subcat4", "q4", "content4", "dataset4"],
+        ]
+    )
+    load_csv.load_csv_and_generate_embeddings(other_csv_file, cleardb=False)
+    dont_clear_db_run = dbsession.query(load_csv.CompanyContent).all()
+
+    assert len(initial_run) == 2
+    assert len(clear_db_run) == 2
+    assert len(dont_clear_db_run) == 4
+
+
+def test_ensure_necessary_columns():
+    with pytest.raises(Exception):
+        load_csv.load_csv_and_generate_embeddings(
+            _create_csv(
+                columns=["category", "subcategory", "question"],
+                data=[["cat1", "subcat1", "q1"]],
+            ),
+            cleardb=True,
+        )  # missing content column