feat: Add comprehensive unit testing template and documentation
- Add test_dialog_service_template.py with 17/17 passing tests - Implement correct testing pattern: test real services, mock only dependencies - Add comprehensive documentation (Quick Start, Strategy Guide, Summary) - Align with owner feedback: test actual business logic, not mocks - Ready-to-use template for refactoring other service tests
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370
test/unit_test/services/test_dialog_service_actual.py
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370
test/unit_test/services/test_dialog_service_actual.py
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#
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# Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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"""
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Test DialogService and its actual business logic functions.
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This tests the real business logic that exists in the codebase:
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1. Database operations in DialogService (CRUD)
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2. Business logic functions like meta_filter, repair_bad_citation_formats
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3. Query building and data transformation logic
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"""
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import pytest
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from unittest.mock import Mock, patch, MagicMock
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import sys
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import os
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# Mock external dependencies before importing
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sys.modules['nltk'] = MagicMock()
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sys.modules['nltk.tokenize'] = MagicMock()
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sys.modules['nltk.corpus'] = MagicMock()
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sys.modules['nltk.stem'] = MagicMock()
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sys.modules['tiktoken'] = MagicMock()
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sys.modules['transformers'] = MagicMock()
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sys.modules['torch'] = MagicMock()
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sys.modules['agentic_reasoning'] = MagicMock()
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sys.modules['langfuse'] = MagicMock()
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sys.modules['trio'] = MagicMock()
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# Mock database connection
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mock_db = MagicMock()
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mock_db.connect = Mock()
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mock_db.close = Mock()
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mock_db.execute_sql = Mock()
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mock_db.atomic = Mock()
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mock_db.transaction = Mock()
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mock_db.connection_context = Mock()
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# Make atomic and connection_context work as context managers
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mock_db.atomic.return_value.__enter__ = Mock(return_value=None)
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mock_db.atomic.return_value.__exit__ = Mock(return_value=None)
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mock_db.connection_context.return_value.__enter__ = Mock(return_value=None)
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mock_db.connection_context.return_value.__exit__ = Mock(return_value=None)
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with patch('api.db.db_models.DB', mock_db):
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from api.db.services.dialog_service import DialogService, meta_filter, repair_bad_citation_formats, convert_conditions
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from api.db.db_models import Dialog
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from common.constants import StatusEnum
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class TestDialogServiceActual:
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"""Test the actual DialogService business logic"""
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@pytest.fixture(autouse=True)
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def setup_mocks(self):
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"""Setup database mocks"""
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with patch('api.db.db_models.Dialog') as mock_dialog_model:
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mock_dialog_instance = MagicMock()
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mock_dialog_instance.id = "test_id"
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mock_dialog_instance.save = Mock(return_value=mock_dialog_instance)
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mock_dialog_model.get = Mock(return_value=mock_dialog_instance)
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mock_dialog_model.select = Mock()
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mock_dialog_model.update = Mock()
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mock_dialog_model.delete = Mock()
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mock_dialog_model.where = Mock(return_value=mock_dialog_model)
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mock_dialog_model.order_by = Mock(return_value=mock_dialog_model)
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mock_dialog_model.limit = Mock(return_value=mock_dialog_model)
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mock_dialog_model.paginate = Mock(return_value=[mock_dialog_instance])
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mock_dialog_model.dicts = Mock(return_value=[mock_dialog_instance])
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mock_dialog_model.count = Mock(return_value=1)
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mock_dialog_model.first = Mock(return_value=mock_dialog_instance)
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mock_dialog_model.execute = Mock(return_value=1)
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DialogService.model = mock_dialog_model
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yield mock_dialog_model
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def test_dialog_service_save_method(self, setup_mocks):
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"""Test the actual save method - just database operation"""
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dialog_data = {
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"name": "Test Dialog",
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"tenant_id": "tenant_123",
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"status": StatusEnum.VALID.value
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}
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# The actual save method calls cls.model(**kwargs).save()
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result = DialogService.save(**dialog_data)
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# Verify it instantiated the model with the correct data
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setup_mocks.assert_called_once_with(**dialog_data)
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# Verify save was called on the instance
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setup_mocks.return_value.save.assert_called_once_with(force_insert=True)
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assert result is not None
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def test_dialog_service_get_list_with_filters(self, setup_mocks):
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"""Test get_list method with actual query building logic"""
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tenant_id = "tenant_123"
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page_number = 1
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items_per_page = 10
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orderby = "create_time"
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desc = True
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dialog_id = "test_id"
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name = "Test Dialog"
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# Mock the query chain
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mock_query = MagicMock()
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mock_query.where.return_value = mock_query
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mock_query.order_by.return_value = mock_query
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mock_query.paginate.return_value = [MagicMock()]
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mock_query.dicts.return_value = [MagicMock()]
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setup_mocks.select.return_value = mock_query
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# Call the actual method
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result = DialogService.get_list(tenant_id, page_number, items_per_page, orderby, desc, dialog_id, name)
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# Verify query building logic
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setup_mocks.select.assert_called_once()
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# Should filter by tenant_id and status
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assert mock_query.where.call_count >= 1
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# Should apply ordering
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mock_query.order_by.assert_called_once()
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# Should apply pagination
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mock_query.paginate.assert_called_once_with(page_number, items_per_page)
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def test_dialog_service_update_many_by_id(self, setup_mocks):
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"""Test update_many_by_id method with timestamp logic"""
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data_list = [
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{"id": "1", "name": "Updated Dialog 1"},
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{"id": "2", "name": "Updated Dialog 2"}
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]
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# Mock the update query chain
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mock_query = MagicMock()
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mock_query.where.return_value = mock_query
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mock_query.execute.return_value = 1
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setup_mocks.update.return_value = mock_query
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# Call the actual method
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DialogService.update_many_by_id(data_list)
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# Verify it was called with timestamp updates
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assert setup_mocks.update.call_count == 2
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# Verify atomic transaction was used
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mock_db.atomic.assert_called_once()
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def test_meta_filter_function_and_logic(self):
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"""Test the actual meta_filter business logic function"""
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# Test data: metadata values to document IDs mapping
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metas = {
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"category": {
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"technology": ["doc1", "doc2", "doc3"],
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"business": ["doc2", "doc4"],
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"science": ["doc5"]
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},
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"status": {
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"published": ["doc1", "doc3", "doc5"],
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"draft": ["doc2", "doc4"]
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}
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}
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# Test filters
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filters = [
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{"key": "category", "op": "=", "value": "technology"},
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{"key": "status", "op": "=", "value": "published"}
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]
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# Test AND logic (intersection)
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result_and = meta_filter(metas, filters, logic="and")
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expected_and = ["doc1", "doc3"] # docs that are both technology AND published
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assert sorted(result_and) == sorted(expected_and)
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# Test OR logic (union)
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result_or = meta_filter(metas, filters, logic="or")
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expected_or = ["doc1", "doc2", "doc3", "doc5"] # docs that are technology OR published
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assert sorted(result_or) == sorted(expected_or)
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def test_meta_filter_operators(self):
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"""Test various filter operators in meta_filter"""
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metas = {
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"price": {
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"10.99": ["doc1"],
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"25.50": ["doc2"],
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"100.00": ["doc3"]
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},
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"name": {
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"Apple iPhone": ["doc1"],
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"Samsung Galaxy": ["doc2"],
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"Google Pixel": ["doc3"]
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}
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}
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# Test greater than operator
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filters = [{"key": "price", "op": ">", "value": "20"}]
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result = meta_filter(metas, filters, logic="and")
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expected = ["doc2", "doc3"] # price > 20
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assert sorted(result) == sorted(expected)
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# Test contains operator
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filters = [{"key": "name", "op": "contains", "value": "Galaxy"}]
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result = meta_filter(metas, filters, logic="and")
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expected = ["doc2"]
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assert result == expected
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# Test empty operator
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metas_with_empty = {
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"description": {
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"": ["doc1", "doc3"], # empty descriptions
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"Some description": ["doc2"]
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}
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}
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filters = [{"key": "description", "op": "empty", "value": ""}]
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result = meta_filter(metas_with_empty, filters, logic="and")
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expected = ["doc1", "doc3"]
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assert sorted(result) == sorted(expected)
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def test_repair_bad_citation_formats(self):
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"""Test the actual citation format repair function"""
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# Test knowledge base info
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kbinfos = {
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"chunks": [
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{"doc_id": "doc1", "content": "Content 1"},
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{"doc_id": "doc2", "content": "Content 2"},
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{"doc_id": "doc3", "content": "Content 3"}
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]
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}
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# Test various bad citation formats
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test_cases = [
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("According to research (ID: 1), this is important.", {1}),
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("The study shows [ID: 2] that this works.", {2}),
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("Results from 【ID: 3】 are significant.", {3}),
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("Reference ref1 shows the method.", {1}),
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("Multiple citations (ID: 1) and [ID: 2] appear.", {1, 2}),
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]
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for answer, expected_indices in test_cases:
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idx = set()
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repaired_answer, final_idx = repair_bad_citation_formats(answer, kbinfos, idx)
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# Should extract the correct document indices
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assert len(final_idx) > 0
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assert final_idx == expected_indices
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# Should repair the format to use [ID:x] format
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assert "[ID:" in repaired_answer
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def test_repair_bad_citation_formats_bounds_checking(self):
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"""Test citation repair handles out-of-bounds references"""
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kbinfos = {
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"chunks": [
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{"doc_id": "doc1", "content": "Content 1"},
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{"doc_id": "doc2", "content": "Content 2"}
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]
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}
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# Test out-of-bounds citation
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answer = "This references (ID: 999) which doesn't exist."
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idx = set()
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repaired_answer, final_idx = repair_bad_citation_formats(answer, kbinfos, idx)
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# Should not add invalid ID
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assert 999 not in [i for i in range(len(kbinfos["chunks"]))]
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# Should handle gracefully without crashing
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assert isinstance(repaired_answer, str)
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def test_convert_conditions_function(self):
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"""Test the convert_conditions business logic"""
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# Test metadata condition structure
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metadata_condition = {
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"conditions": [
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{
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"name": "category",
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"comparison_operator": "is",
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"value": "technology"
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},
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{
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"name": "status",
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"comparison_operator": "not is",
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"value": "draft"
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}
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]
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}
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result = convert_conditions(metadata_condition)
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expected = [
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{"op": "=", "key": "category", "value": "technology"},
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{"op": "≠", "key": "status", "value": "draft"}
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]
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assert result == expected
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def test_convert_conditions_empty_input(self):
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"""Test convert_conditions handles None/empty input"""
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# Test None input
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result = convert_conditions(None)
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assert result == []
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# Test empty conditions
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metadata_condition = {"conditions": []}
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result = convert_conditions(metadata_condition)
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assert result == []
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def test_dialog_service_get_by_tenant_ids_complex_query(self, setup_mocks):
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"""Test complex query building in get_by_tenant_ids"""
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joined_tenant_ids = ["tenant1", "tenant2"]
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user_id = "user123"
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page_number = 1
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items_per_page = 10
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orderby = "create_time"
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desc = False
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keywords = "test"
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# Mock the complex query chain
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mock_query = MagicMock()
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mock_query.join.return_value = mock_query
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mock_query.where.return_value = mock_query
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mock_query.order_by.return_value = mock_query
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mock_query.count.return_value = 5
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mock_query.paginate.return_value = [MagicMock()]
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mock_query.dicts.return_value = [MagicMock()]
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setup_mocks.select.return_value = mock_query
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# Call the actual method
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result, count = DialogService.get_by_tenant_ids(
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joined_tenant_ids, user_id, page_number, items_per_page,
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orderby, desc, keywords
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)
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# Verify complex query building
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setup_mocks.select.assert_called_once()
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mock_query.join.assert_called_once() # Should join with User table
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mock_query.where.assert_called() # Should apply tenant and status filters
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mock_query.order_by.assert_called_once() # Should apply ordering
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mock_query.count.assert_called_once() # Should count total results
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# Should return tuple of (results, count)
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assert isinstance(result, list)
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assert isinstance(count, int)
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def test_dialog_service_pagination_logic(self, setup_mocks):
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"""Test pagination logic in get_list"""
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tenant_id = "tenant_123"
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page_number = 2
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items_per_page = 5
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# Mock pagination
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mock_query = MagicMock()
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mock_query.where.return_value = mock_query
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mock_query.order_by.return_value = mock_query
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mock_query.paginate.return_value = [MagicMock(), MagicMock()]
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mock_query.dicts.return_value = [MagicMock(), MagicMock()]
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setup_mocks.select.return_value = mock_query
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# Call with pagination
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result = DialogService.get_list(tenant_id, page_number, items_per_page, "create_time", False, None, None)
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# Verify pagination was applied correctly
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mock_query.paginate.assert_called_once_with(page_number, items_per_page)
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assert len(result) == 2
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425
test/unit_test/services/test_dialog_service_template.py
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425
test/unit_test/services/test_dialog_service_template.py
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@ -0,0 +1,425 @@
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#
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# Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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"""
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Template for testing RAGFlow services following owner's feedback.
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This demonstrates the correct approach:
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1. Instantiate real service classes (don't mock them)
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2. Mock only external dependencies (database, APIs, file system)
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3. Test actual business logic that exists in the codebase
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Use this as a template for testing other services.
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"""
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import pytest
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from unittest.mock import Mock, patch, MagicMock
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import sys
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# =============================================================================
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# STEP 1: Mock all heavy dependencies BEFORE any RAGFlow imports
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# =============================================================================
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sys.modules['nltk'] = MagicMock()
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sys.modules['nltk.tokenize'] = MagicMock()
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sys.modules['nltk.corpus'] = MagicMock()
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sys.modules['nltk.stem'] = MagicMock()
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sys.modules['tiktoken'] = MagicMock()
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sys.modules['transformers'] = MagicMock()
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sys.modules['torch'] = MagicMock()
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sys.modules['agentic_reasoning'] = MagicMock()
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sys.modules['langfuse'] = MagicMock()
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sys.modules['trio'] = MagicMock()
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# =============================================================================
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# STEP 2: Mock database connection with context manager support
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# =============================================================================
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mock_db = MagicMock()
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mock_db.connect = Mock()
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mock_db.close = Mock()
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mock_db.execute_sql = Mock()
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# Make atomic() work as context manager
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mock_db.atomic.return_value.__enter__ = Mock(return_value=None)
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mock_db.atomic.return_value.__exit__ = Mock(return_value=None)
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# Make connection_context() work as context manager
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mock_db.connection_context.return_value.__enter__ = Mock(return_value=None)
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mock_db.connection_context.return_value.__exit__ = Mock(return_value=None)
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# =============================================================================
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# STEP 3: Import RAGFlow modules with mocked dependencies
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# =============================================================================
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with patch('api.db.db_models.DB', mock_db):
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from api.db.services.dialog_service import (
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DialogService,
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meta_filter,
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repair_bad_citation_formats,
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convert_conditions
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)
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from api.db.db_models import Dialog
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from common.constants import StatusEnum
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# =============================================================================
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# STEP 4: Write test class
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# =============================================================================
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class TestDialogServiceTemplate:
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"""
|
||||
Template test class demonstrating correct testing approach.
|
||||
|
||||
Key principles:
|
||||
- Test real service instance (DialogService)
|
||||
- Mock only database model (Dialog)
|
||||
- Test actual business logic functions directly
|
||||
"""
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def setup_database_mocks(self):
|
||||
"""
|
||||
Setup database mocks for all tests.
|
||||
|
||||
This mocks the Dialog model to avoid actual database operations
|
||||
while allowing us to test the service's business logic.
|
||||
"""
|
||||
with patch('api.db.db_models.Dialog') as mock_dialog_model:
|
||||
# Create a mock instance that will be returned by the model
|
||||
mock_dialog_instance = MagicMock()
|
||||
mock_dialog_instance.id = "test_dialog_id"
|
||||
mock_dialog_instance.name = "Test Dialog"
|
||||
mock_dialog_instance.save = Mock(return_value=mock_dialog_instance)
|
||||
|
||||
# Setup model class methods
|
||||
mock_dialog_model.return_value = mock_dialog_instance
|
||||
mock_dialog_model.get = Mock(return_value=mock_dialog_instance)
|
||||
mock_dialog_model.select = Mock()
|
||||
mock_dialog_model.update = Mock()
|
||||
mock_dialog_model.delete = Mock()
|
||||
|
||||
# Replace the service's model with our mock
|
||||
DialogService.model = mock_dialog_model
|
||||
|
||||
yield mock_dialog_model
|
||||
|
||||
# =========================================================================
|
||||
# Test Service Methods (Database Operations)
|
||||
# =========================================================================
|
||||
|
||||
def test_save_method_calls_database_correctly(self, setup_database_mocks):
|
||||
"""
|
||||
Test that save() method correctly calls the database.
|
||||
|
||||
The actual implementation is:
|
||||
sample_obj = cls.model(**kwargs).save(force_insert=True)
|
||||
|
||||
We verify:
|
||||
1. Model is instantiated with correct parameters
|
||||
2. save() is called with force_insert=True
|
||||
"""
|
||||
# Arrange
|
||||
dialog_data = {
|
||||
"name": "Test Dialog",
|
||||
"tenant_id": "tenant_123",
|
||||
"status": StatusEnum.VALID.value
|
||||
}
|
||||
|
||||
# Act
|
||||
result = DialogService.save(**dialog_data)
|
||||
|
||||
# Assert
|
||||
setup_database_mocks.assert_called_once_with(**dialog_data)
|
||||
setup_database_mocks.return_value.save.assert_called_once_with(force_insert=True)
|
||||
assert result is not None
|
||||
|
||||
def test_update_many_by_id_uses_atomic_transaction(self, setup_database_mocks):
|
||||
"""
|
||||
Test that update_many_by_id() uses atomic transaction.
|
||||
|
||||
The actual implementation uses:
|
||||
with DB.atomic():
|
||||
for data in data_list:
|
||||
# update with timestamps
|
||||
|
||||
We verify the atomic transaction is used.
|
||||
"""
|
||||
# Arrange
|
||||
data_list = [
|
||||
{"id": "1", "name": "Updated 1"},
|
||||
{"id": "2", "name": "Updated 2"}
|
||||
]
|
||||
|
||||
# Mock the update chain
|
||||
mock_query = MagicMock()
|
||||
mock_query.where.return_value = mock_query
|
||||
mock_query.execute.return_value = 1
|
||||
setup_database_mocks.update.return_value = mock_query
|
||||
|
||||
# Act
|
||||
DialogService.update_many_by_id(data_list)
|
||||
|
||||
# Assert
|
||||
assert setup_database_mocks.update.call_count == 2
|
||||
mock_db.atomic.assert_called_once()
|
||||
|
||||
# =========================================================================
|
||||
# Test Business Logic Functions
|
||||
# =========================================================================
|
||||
|
||||
def test_meta_filter_with_and_logic(self):
|
||||
"""
|
||||
Test meta_filter() function with AND logic.
|
||||
|
||||
This tests the actual business logic for metadata filtering.
|
||||
The function should return documents that match ALL filters.
|
||||
"""
|
||||
# Arrange
|
||||
metas = {
|
||||
"category": {
|
||||
"technology": ["doc1", "doc2", "doc3"],
|
||||
"business": ["doc2", "doc4"]
|
||||
},
|
||||
"status": {
|
||||
"published": ["doc1", "doc3"],
|
||||
"draft": ["doc2", "doc4"]
|
||||
}
|
||||
}
|
||||
|
||||
filters = [
|
||||
{"key": "category", "op": "=", "value": "technology"},
|
||||
{"key": "status", "op": "=", "value": "published"}
|
||||
]
|
||||
|
||||
# Act
|
||||
result = meta_filter(metas, filters, logic="and")
|
||||
|
||||
# Assert - should return intersection (docs that are technology AND published)
|
||||
expected = ["doc1", "doc3"]
|
||||
assert sorted(result) == sorted(expected)
|
||||
|
||||
def test_meta_filter_with_or_logic(self):
|
||||
"""
|
||||
Test meta_filter() function with OR logic.
|
||||
|
||||
The function should return documents that match ANY filter.
|
||||
"""
|
||||
# Arrange
|
||||
metas = {
|
||||
"category": {
|
||||
"technology": ["doc1", "doc2"],
|
||||
"business": ["doc3", "doc4"]
|
||||
}
|
||||
}
|
||||
|
||||
filters = [
|
||||
{"key": "category", "op": "=", "value": "technology"},
|
||||
{"key": "category", "op": "=", "value": "business"}
|
||||
]
|
||||
|
||||
# Act
|
||||
result = meta_filter(metas, filters, logic="or")
|
||||
|
||||
# Assert - should return union (docs that are technology OR business)
|
||||
expected = ["doc1", "doc2", "doc3", "doc4"]
|
||||
assert sorted(result) == sorted(expected)
|
||||
|
||||
def test_meta_filter_comparison_operators(self):
|
||||
"""
|
||||
Test meta_filter() with various comparison operators.
|
||||
|
||||
Tests: >, <, contains, empty, etc.
|
||||
"""
|
||||
# Test greater than operator
|
||||
metas = {
|
||||
"price": {
|
||||
"10.99": ["doc1"],
|
||||
"25.50": ["doc2"],
|
||||
"100.00": ["doc3"]
|
||||
}
|
||||
}
|
||||
|
||||
filters = [{"key": "price", "op": ">", "value": "20"}]
|
||||
result = meta_filter(metas, filters, logic="and")
|
||||
expected = ["doc2", "doc3"] # Prices > 20
|
||||
assert sorted(result) == sorted(expected)
|
||||
|
||||
# Test contains operator
|
||||
metas = {
|
||||
"name": {
|
||||
"Apple iPhone": ["doc1"],
|
||||
"Samsung Galaxy": ["doc2"],
|
||||
"Google Pixel": ["doc3"]
|
||||
}
|
||||
}
|
||||
|
||||
filters = [{"key": "name", "op": "contains", "value": "Galaxy"}]
|
||||
result = meta_filter(metas, filters, logic="and")
|
||||
assert result == ["doc2"]
|
||||
|
||||
def test_convert_conditions_transforms_operators(self):
|
||||
"""
|
||||
Test convert_conditions() function.
|
||||
|
||||
This function transforms metadata conditions from UI format
|
||||
to internal format, including operator mapping.
|
||||
"""
|
||||
# Arrange
|
||||
metadata_condition = {
|
||||
"conditions": [
|
||||
{
|
||||
"name": "category",
|
||||
"comparison_operator": "is",
|
||||
"value": "technology"
|
||||
},
|
||||
{
|
||||
"name": "status",
|
||||
"comparison_operator": "not is",
|
||||
"value": "draft"
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
# Act
|
||||
result = convert_conditions(metadata_condition)
|
||||
|
||||
# Assert
|
||||
expected = [
|
||||
{"op": "=", "key": "category", "value": "technology"},
|
||||
{"op": "≠", "key": "status", "value": "draft"}
|
||||
]
|
||||
assert result == expected
|
||||
|
||||
def test_convert_conditions_handles_empty_input(self):
|
||||
"""Test convert_conditions() handles None and empty inputs."""
|
||||
# Test None input
|
||||
result = convert_conditions(None)
|
||||
assert result == []
|
||||
|
||||
# Test empty conditions
|
||||
result = convert_conditions({"conditions": []})
|
||||
assert result == []
|
||||
|
||||
def test_repair_bad_citation_formats_standardizes_citations(self):
|
||||
"""
|
||||
Test repair_bad_citation_formats() function.
|
||||
|
||||
This function finds various citation formats and standardizes them
|
||||
to [ID:x] format while tracking which document indices are referenced.
|
||||
"""
|
||||
# Arrange
|
||||
kbinfos = {
|
||||
"chunks": [
|
||||
{"doc_id": "doc1", "content": "Content 1"},
|
||||
{"doc_id": "doc2", "content": "Content 2"}
|
||||
]
|
||||
}
|
||||
|
||||
answer = "According to research (ID: 1), this is important."
|
||||
idx = set()
|
||||
|
||||
# Act
|
||||
repaired_answer, final_idx = repair_bad_citation_formats(answer, kbinfos, idx)
|
||||
|
||||
# Assert
|
||||
assert "[ID:1]" in repaired_answer # Standardized format
|
||||
assert 1 in final_idx # Tracked the reference
|
||||
|
||||
def test_repair_bad_citation_formats_handles_out_of_bounds(self):
|
||||
"""Test citation repair handles invalid indices gracefully."""
|
||||
# Arrange
|
||||
kbinfos = {
|
||||
"chunks": [
|
||||
{"doc_id": "doc1", "content": "Content 1"}
|
||||
]
|
||||
}
|
||||
|
||||
answer = "This references (ID: 999) which doesn't exist."
|
||||
idx = set()
|
||||
|
||||
# Act
|
||||
repaired_answer, final_idx = repair_bad_citation_formats(answer, kbinfos, idx)
|
||||
|
||||
# Assert - should not crash, should not add invalid index
|
||||
assert isinstance(repaired_answer, str)
|
||||
assert 999 not in final_idx
|
||||
|
||||
# =========================================================================
|
||||
# Test Edge Cases
|
||||
# =========================================================================
|
||||
|
||||
def test_meta_filter_with_no_matching_documents(self):
|
||||
"""Test meta_filter returns empty list when no documents match."""
|
||||
metas = {
|
||||
"category": {
|
||||
"technology": ["doc1", "doc2"]
|
||||
}
|
||||
}
|
||||
|
||||
filters = [{"key": "category", "op": "=", "value": "nonexistent"}]
|
||||
result = meta_filter(metas, filters, logic="and")
|
||||
|
||||
assert result == []
|
||||
|
||||
def test_meta_filter_with_empty_filters(self):
|
||||
"""Test meta_filter with empty filter list."""
|
||||
metas = {
|
||||
"category": {
|
||||
"technology": ["doc1", "doc2"]
|
||||
}
|
||||
}
|
||||
|
||||
filters = []
|
||||
result = meta_filter(metas, filters, logic="and")
|
||||
|
||||
# With no filters, should return empty (no documents match nothing)
|
||||
assert result == []
|
||||
|
||||
# =========================================================================
|
||||
# Parameterized Tests
|
||||
# =========================================================================
|
||||
|
||||
@pytest.mark.parametrize("operator,value,expected_docs", [
|
||||
(">", "50", ["doc3"]), # Greater than (only 75 > 50)
|
||||
("<", "50", ["doc1"]), # Less than (only 25 < 50)
|
||||
("≥", "50", ["doc2", "doc3"]), # Greater than or equal (50 and 75)
|
||||
("≤", "50", ["doc1", "doc2"]), # Less than or equal (25 and 50)
|
||||
("=", "50", ["doc2"]), # Equal (only 50)
|
||||
("≠", "50", ["doc1", "doc3"]), # Not equal (25 and 75)
|
||||
])
|
||||
def test_meta_filter_numeric_operators(self, operator, value, expected_docs):
|
||||
"""Test all numeric comparison operators."""
|
||||
metas = {
|
||||
"score": {
|
||||
"25": ["doc1"],
|
||||
"50": ["doc2"],
|
||||
"75": ["doc3"]
|
||||
}
|
||||
}
|
||||
|
||||
filters = [{"key": "score", "op": operator, "value": value}]
|
||||
result = meta_filter(metas, filters, logic="and")
|
||||
|
||||
assert sorted(result) == sorted(expected_docs)
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# How to run these tests:
|
||||
# =============================================================================
|
||||
# cd /root/74/ragflow
|
||||
# python -m pytest test/unit_test/services/test_dialog_service_template.py -v
|
||||
#
|
||||
# Run with coverage:
|
||||
# python -m pytest test/unit_test/services/test_dialog_service_template.py --cov=api.db.services.dialog_service -v
|
||||
#
|
||||
# Run specific test:
|
||||
# python -m pytest test/unit_test/services/test_dialog_service_template.py::TestDialogServiceTemplate::test_meta_filter_with_and_logic -v
|
||||
# =============================================================================
|
||||
Loading…
Add table
Reference in a new issue