feat: POC automation test

JIRA: QA-23477
risk: nonprod

Author: Tubt

.python-version

@@ -1 +1 @@
-3.12.4
+3.11.4

gooddata-sdk/integration_tests/data_response/column_sum_amount_by_stage_name.json

@@ -0,0 +1,21 @@
+{
+  "id": "sum_of_amount_by_stage_name",
+  "title": "Sum of Amount by Stage Name",
+  "visualizationType": "COLUMN",
+  "metrics": [
+      {
+          "id": "f_opportunitysnapshot.f_amount",
+          "type": "fact",
+          "title": "Sum of Amount",
+          "aggFunction": "SUM"
+      }
+  ],
+  "dimensionality": [
+      {
+          "id": "attr.f_stage.stagename",
+          "type": "attribute",
+          "title": "Stage Name"
+      }
+  ],
+  "filters": []
+}

gooddata-sdk/integration_tests/data_response/column_sum_best_case_by_product_filter_department_direct_sales.json

@@ -0,0 +1,27 @@
+{
+    "id": "best_case_by_product_for_direct_sales_department",
+    "title": "Best Case by Product for Direct Sales Department",
+    "visualizationType": "COLUMN",
+    "metrics": [
+        {
+            "id": "best_case",
+            "type": "metric",
+            "title": "Best Case"
+        }
+    ],
+    "dimensionality": [
+        {
+            "id": "attr.f_product.product",
+            "type": "attribute",
+            "title": "Product"
+        }
+    ],
+    "filters": [
+        {
+            "using": "f_owner.department_id",
+            "include": [
+                "Direct Sales"
+            ]
+        }
+    ]
+}

gooddata-sdk/integration_tests/data_response/headline_sum_amount.json

@@ -0,0 +1,15 @@
+{
+    "id": "total_amount",
+    "title": "Total Amount",
+    "visualizationType": "HEADLINE",
+    "metrics": [
+      {
+        "id": "f_opportunitysnapshot.f_amount",
+        "type": "fact",
+        "title": "Sum of Amount",
+        "aggFunction": "SUM"
+      }
+    ],
+    "dimensionality": [],
+    "filters": []
+  }

gooddata-sdk/integration_tests/env.py

@@ -0,0 +1,9 @@
+# (C) 2024 GoodData Corporation
+# env.py
+import os
+
+# Define environment variables
+HOST = os.getenv("GOODDATA_HOST", "")
+TOKEN = os.getenv("GOODDATA_TOKEN", "")
+DATASOURCE_ID = os.getenv("DATASOURCE_ID", "")
+WORKSPACE_ID = ""

gooddata-sdk/integration_tests/fixtures/ai_questions.json

@@ -0,0 +1,14 @@
+[
+    {
+        "question": "generate HEADLINE showing Sum of Amount",
+        "expected_objects_file": "headline_sum_amount.json"
+    },
+    {
+        "question": "generate COLUMN chart showing Sum of Amount sliced by Stage Name",
+        "expected_objects_file": "column_sum_amount_by_stage_name.json"
+    },
+    {
+        "question": "generate COLUMN chart showing Best Case sliced by Product filtered by Department is 'Direct Sales'",
+        "expected_objects_file": "column_sum_best_case_by_product_filter_department_direct_sales.json"
+    }
+]

gooddata-sdk/integration_tests/scripts/aiChat.py

@@ -0,0 +1,152 @@
+# (C) 2024 GoodData Corporation
+import json
+import os
+import sys
+from pprint import pprint
+
+import gooddata_api_client
+import pytest
+from gooddata_api_client.api import smart_functions_api
+from gooddata_api_client.model.chat_history_request import ChatHistoryRequest
+from gooddata_api_client.model.chat_history_result import ChatHistoryResult
+from gooddata_api_client.model.chat_request import ChatRequest
+
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from env import HOST, TOKEN, WORKSPACE_ID
+
+EXPECTED_OBJECTS_DIR = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "data_response")
+
+QUESTIONS_DIR = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "fixtures")
+
+
+@pytest.fixture(scope="module")
+def api_client():
+    configuration = gooddata_api_client.Configuration(host=HOST)
+    configuration.access_token = TOKEN
+    with gooddata_api_client.ApiClient(configuration) as api_client:
+        yield api_client
+
+
+class GoodDataAiChatApp:
+    def __init__(self, api_client, workspace_id):
+        self.api_instance = smart_functions_api.SmartFunctionsApi(api_client)
+        self.workspace_id = workspace_id
+
+    async def ask_question(self, question: str):
+        chat_request = ChatRequest(question=question)
+        return self.api_instance.ai_chat(self.workspace_id, chat_request)
+
+    async def chat_history(self, chat_history_interaction_id: int, user_feedback: str):
+        chat_history_request = ChatHistoryRequest(
+            chat_history_interaction_id=chat_history_interaction_id,
+            user_feedback=user_feedback,
+        )
+        return self.api_instance.ai_chat_history(self.workspace_id, chat_history_request)
+
+
+def set_authorization_header(api_client, token):
+    api_client.default_headers["Authorization"] = f"Bearer {token}"
+
+
+def snake_to_camel(snake_str):
+    """Convert snake_case to camelCase."""
+    components = snake_str.split("_")
+    return components[0] + "".join(x.title() for x in components[1:])
+
+
+def normalize_metrics(metrics, exclude_keys=None):
+    """Normalize keys in the metrics list, excluding specified keys."""
+    if exclude_keys is None:
+        exclude_keys = []
+    normalized_metrics = []
+    for metric in metrics:
+        if isinstance(metric, dict):
+            normalized_metric = {}
+            for key, value in metric.items():
+                if key in exclude_keys:
+                    continue
+                else:
+                    new_key = snake_to_camel(key)
+                    normalized_metric[new_key] = value
+            normalized_metrics.append(normalized_metric)
+    return normalized_metrics
+
+
+def handle_api_response_ai_chat(api_response, expected_objects):
+    response_dict = api_response.to_dict()
+
+    # Normalize the keys in the actual and expected metrics, excluding 'title'
+    actual_metrics = normalize_metrics(
+        response_dict["created_visualizations"]["objects"][0]["metrics"], exclude_keys=["title"]
+    )
+    expected_metrics = normalize_metrics(expected_objects["metrics"], exclude_keys=["title"])
+
+    assert actual_metrics == expected_metrics, "Metrics do not match"
+    assert (
+        response_dict["created_visualizations"]["objects"][0]["visualization_type"]
+        == expected_objects["visualizationType"]
+    ), "Visualization type does not match"
+    assert (
+        response_dict["created_visualizations"]["objects"][0]["dimensionality"] == expected_objects["dimensionality"]
+    ), "Dimensionality does not match"
+    assert (
+        response_dict["created_visualizations"]["objects"][0]["filters"] == expected_objects["filters"]
+    ), "Filters do not match"
+
+
+def getChatHistoryInteractionId(api_response):
+    chat_history_interaction_id = api_response.chat_history_interaction_id
+    print(f"Chat history interaction id: {chat_history_interaction_id}")
+    return chat_history_interaction_id
+
+
+@pytest.fixture(scope="module")
+def app(api_client):
+    app = GoodDataAiChatApp(api_client, WORKSPACE_ID)
+    set_authorization_header(api_client, TOKEN)
+    return app
+
+
+def load_expected_objects(fixture_folder, filename):
+    with open(os.path.join(fixture_folder, filename)) as file:
+        return json.load(file)
+
+
+questions_list = load_expected_objects(QUESTIONS_DIR, "ai_questions.json")
+
+
+@pytest.mark.parametrize(
+    "question,expected_objects_file",
+    [(item["question"], item["expected_objects_file"]) for item in questions_list],
+    ids=[item["question"] for item in questions_list],
+)
+@pytest.mark.asyncio
+async def test_ai_chat(app, question, expected_objects_file):
+    expected_objects = load_expected_objects(EXPECTED_OBJECTS_DIR, expected_objects_file)
+    try:
+        api_response = await app.ask_question(question)
+        handle_api_response_ai_chat(api_response, expected_objects)
+    except gooddata_api_client.ApiException as e:
+        pytest.fail(f"Exception when calling SmartFunctionsApi->ai_chat: {e}\n")
+    except Exception as e:
+        pytest.fail(f"An unexpected error occurred: {e}\n")
+
+
+@pytest.mark.asyncio
+async def test_ai_chat_history(app):
+    try:
+        api_response = await app.chat_history(1260, "POSITIVE")
+
+        assert isinstance(api_response, ChatHistoryResult), "Response is not of type ChatHistoryResult"
+        pprint(api_response.to_dict())
+    except gooddata_api_client.ApiException as e:
+        print(f"Exception when calling SmartFunctionsApi->ai_chat_history: {e}")
+        pytest.fail(f"Exception when calling SmartFunctionsApi->ai_chat_history: {e}\n")
+    except Exception as e:
+        print(f"An unexpected error occurred: {e}")
+        pytest.fail(f"An unexpected error occurred: {e}\n")
+
+
+if __name__ == "__main__":
+    pytest.main()

gooddata-sdk/integration_tests/scripts/ai_chat.py

@@ -0,0 +1,36 @@
+# (C) 2024 GoodData Corporation
+import os
+import sys
+
+import pytest
+
+# Add the root directory to sys.path
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from env import HOST, TOKEN, WORKSPACE_ID
+from gooddata_sdk import GoodDataSdk
+
+
+@pytest.fixture
+def test_config():
+    return {"host": HOST, "token": TOKEN, "workspace_id": WORKSPACE_ID}
+
+
+questions = [
+    "What is the number of Accounts?",
+    "What is the total of Amount?",
+]
+
+
+@pytest.mark.parametrize("question", questions)
+def test_ask_ai(test_config, question):
+    sdk = GoodDataSdk.create(host_=test_config["host"], token_=test_config["token"])
+    workspace_id = test_config["workspace_id"]
+    chat_ai_res = sdk.compute.ai_chat(workspace_id, question=question)
+
+    print(f"Chat AI response: {chat_ai_res}")
+    assert chat_ai_res is not None, "Response should not be None"
+
+
+if __name__ == "__main__":
+    pytest.main()

gooddata-sdk/integration_tests/scripts/create_ref_workspace.py

@@ -0,0 +1,16 @@
+# (C) 2024 GoodData Corporation
+from env import DATASOURCE_ID, HOST, TOKEN, WORKSPACE_ID
+from workspace_manager import createWorkspace, getDataSource, update_env_file
+
+if __name__ == "__main__":
+    test_config = {"host": HOST, "token": TOKEN}
+
+    if WORKSPACE_ID:
+        print(f"Workspace ID '{WORKSPACE_ID}' already exists. Skipping workspace creation.")
+    else:
+        workspace_id = createWorkspace(test_config)
+        dataSource = getDataSource(DATASOURCE_ID, test_config)
+        if workspace_id:
+            update_env_file(workspace_id)
+        else:
+            print("Failed to create workspace.")

gooddata-sdk/integration_tests/scripts/delete_ref_workspace.py

@@ -0,0 +1,8 @@
+# (C) 2024 GoodData Corporation
+from env import HOST, TOKEN
+from workspace_manager import deleteWorkspace
+
+if __name__ == "__main__":
+    test_config = {"host": HOST, "token": TOKEN}
+
+    deleteWorkspace(test_config)