Pre/beta

tests/test_depth_search_graph.py

@@ -0,0 +1,34 @@
+from unittest.mock import patch, MagicMock
+from scrapegraphai.graphs.depth_search_graph import DepthSearchGraph
+from scrapegraphai.graphs.abstract_graph import AbstractGraph
+import pytest
+
+
+class TestDepthSearchGraph:
+    """Test suite for DepthSearchGraph class"""
+
+    @pytest.mark.parametrize(
+        "source, expected_input_key",
+        [
+            ("https://example.com", "url"),
+            ("/path/to/local/directory", "local_dir"),
+        ],
+    )
+    def test_depth_search_graph_initialization(self, source, expected_input_key):
+        """
+        Test that DepthSearchGraph initializes correctly with different source types.
+        This test verifies that the input_key is set to 'url' for web sources and
+        'local_dir' for local directory sources.
+        """
+        prompt = "Test prompt"
+        config = {"llm": {"model": "mock_model"}}
+
+        # Mock both BaseGraph and _create_llm method
+        with patch("scrapegraphai.graphs.depth_search_graph.BaseGraph"), \
+             patch.object(AbstractGraph, '_create_llm', return_value=MagicMock()):
+            graph = DepthSearchGraph(prompt, source, config)
+
+            assert graph.prompt == prompt
+            assert graph.source == source
+            assert graph.config == config
+            assert graph.input_key == expected_input_key

tests/test_json_scraper_graph.py

@@ -1,6 +1,6 @@
 import pytest
 
-from pydantic import BaseModel
+from pydantic import BaseModel, Field
 from scrapegraphai.graphs.json_scraper_graph import JSONScraperGraph
 from unittest.mock import Mock, patch
 
@@ -133,4 +133,60 @@ def test_json_scraper_graph_no_answer_found(self, mock_create_llm, mock_generate
             mock_execute.assert_called_once_with({"user_prompt": "Query that produces no answer", "json": "path/to/empty/file.json"})
             mock_fetch_node.assert_called_once()
             mock_generate_answer_node.assert_called_once()
+            mock_create_llm.assert_called_once_with({"model": "test-model", "temperature": 0})
+
+    @pytest.fixture
+    def mock_llm_model(self):
+        return Mock()
+
+    @pytest.fixture
+    def mock_embedder_model(self):
+        return Mock()
+
+    @patch('scrapegraphai.graphs.json_scraper_graph.FetchNode')
+    @patch('scrapegraphai.graphs.json_scraper_graph.GenerateAnswerNode')
+    @patch.object(JSONScraperGraph, '_create_llm')
+    def test_json_scraper_graph_with_custom_schema(self, mock_create_llm, mock_generate_answer_node, mock_fetch_node, mock_llm_model, mock_embedder_model):
+        """
+        Test JSONScraperGraph with a custom schema.
+        This test checks if the graph correctly handles a custom schema input
+        and passes it to the GenerateAnswerNode.
+        """
+        # Define a custom schema
+        class CustomSchema(BaseModel):
+            name: str = Field(..., description="Name of the attraction")
+            description: str = Field(..., description="Description of the attraction")
+
+        # Mock the _create_llm method to return a mock LLM model
+        mock_create_llm.return_value = mock_llm_model
+
+        # Mock the execute method of BaseGraph
+        with patch('scrapegraphai.graphs.json_scraper_graph.BaseGraph.execute') as mock_execute:
+            mock_execute.return_value = ({"answer": "Mocked answer with custom schema"}, {})
+
+            # Create a JSONScraperGraph instance with a custom schema
+            graph = JSONScraperGraph(
+                prompt="List attractions in Chioggia",
+                source="path/to/chioggia.json",
+                config={"llm": {"model": "test-model", "temperature": 0}},
+                schema=CustomSchema
+            )
+
+            # Set mocked embedder model
+            graph.embedder_model = mock_embedder_model
+
+            # Run the graph
+            result = graph.run()
+
+            # Assertions
+            assert result == "Mocked answer with custom schema"
+            assert graph.input_key == "json"
+            mock_execute.assert_called_once_with({"user_prompt": "List attractions in Chioggia", "json": "path/to/chioggia.json"})
+            mock_fetch_node.assert_called_once()
+            mock_generate_answer_node.assert_called_once()
+
+            # Check if the custom schema was passed to GenerateAnswerNode
+            generate_answer_node_call = mock_generate_answer_node.call_args[1]
+            assert generate_answer_node_call['node_config']['schema'] == CustomSchema
+
             mock_create_llm.assert_called_once_with({"model": "test-model", "temperature": 0})

tests/test_search_graph.py

@@ -79,4 +79,29 @@ def test_max_results_config(self, mock_create_llm, mock_base_graph, mock_merge_a
         # Assert
         mock_search_internet.assert_called_once()
         call_args = mock_search_internet.call_args
-        assert call_args.kwargs['node_config']['max_results'] == max_results
+        assert call_args.kwargs['node_config']['max_results'] == max_results
+
+    @patch('scrapegraphai.graphs.search_graph.SearchInternetNode')
+    @patch('scrapegraphai.graphs.search_graph.GraphIteratorNode')
+    @patch('scrapegraphai.graphs.search_graph.MergeAnswersNode')
+    @patch('scrapegraphai.graphs.search_graph.BaseGraph')
+    @patch('scrapegraphai.graphs.abstract_graph.AbstractGraph._create_llm')
+    def test_custom_search_engine_config(self, mock_create_llm, mock_base_graph, mock_merge_answers, mock_graph_iterator, mock_search_internet):
+        """
+        Test that the custom search_engine parameter from the config is correctly passed to the SearchInternetNode.
+        """
+        # Arrange
+        prompt = "Test prompt"
+        custom_search_engine = "custom_engine"
+        config = {
+            "llm": {"model": "test-model"},
+            "search_engine": custom_search_engine
+        }
+
+        # Act
+        search_graph = SearchGraph(prompt, config)
+
+        # Assert
+        mock_search_internet.assert_called_once()
+        call_args = mock_search_internet.call_args
+        assert call_args.kwargs['node_config']['search_engine'] == custom_search_engine