feat: add batch run beta component (#5489)

* feat: add batch run beta component

* [autofix.ci] apply automated fixes

* Update batch_run to run async using Runnable

* [autofix.ci] apply automated fixes

* refactor: streamline BatchRunComponent by removing unused synchronous model invocation and enhancing async processing

- Consolidated imports and improved type checking for LanguageModel.
- Simplified the run_batch method by directly using the model's asynchronous capabilities.
- Enhanced error handling for missing DataFrame columns.
- Cleaned up comments and improved code readability.

* refactor: update BatchRunComponent to use Runnable for improved async processing

- Added future annotations for better type hinting.
- Replaced LanguageModel with Runnable in type checking and method implementation.
- Enhanced code clarity and maintainability by consolidating imports.

* test: add unit tests for BatchRunComponent functionality

- Introduced a new test suite for BatchRunComponent to validate its behavior.
- Added tests for successful batch runs with and without system messages.
- Implemented tests for handling invalid column names and empty DataFrames.
- Included a test to ensure non-string columns are converted to strings during processing.

* refactor: rename useful.py to mock_language_model.py and update imports

---------

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org>

src/backend/tests/unit/components/helpers/test_batch_run_component.py

@@ -0,0 +1,88 @@
+import re
+
+import pytest
+from langflow.components.helpers.batch_run import BatchRunComponent
+from langflow.schema import DataFrame
+
+from tests.base import ComponentTestBaseWithoutClient
+from tests.unit.mock_language_model import MockLanguageModel
+
+
+class TestBatchRunComponent(ComponentTestBaseWithoutClient):
+    @pytest.fixture
+    def component_class(self):
+        """Return the component class to test."""
+        return BatchRunComponent
+
+    @pytest.fixture
+    def default_kwargs(self):
+        """Return the default kwargs for the component."""
+        return {
+            "model": MockLanguageModel(),
+            "df": DataFrame({"text": ["Hello"]}),
+            "column_name": "text",
+        }
+
+    @pytest.fixture
+    def file_names_mapping(self):
+        """Return an empty list since this component doesn't have version-specific files."""
+        return []
+
+    async def test_successful_batch_run_with_system_message(self):
+        # Create test data
+        test_df = DataFrame({"text": ["Hello", "World", "Test"]})
+
+        component = BatchRunComponent(
+            model=MockLanguageModel(), system_message="You are a helpful assistant", df=test_df, column_name="text"
+        )
+
+        # Run the batch process
+        result = await component.run_batch()
+
+        # Verify the results
+        assert isinstance(result, DataFrame)
+        assert "text_input" in result.columns
+        assert "model_response" in result.columns
+        assert len(result) == 3
+        assert all(isinstance(resp, str) for resp in result["model_response"])
+
+    async def test_batch_run_without_system_message(self):
+        test_df = DataFrame({"text": ["Hello", "World"]})
+
+        component = BatchRunComponent(model=MockLanguageModel(), df=test_df, column_name="text")
+
+        result = await component.run_batch()
+
+        assert isinstance(result, DataFrame)
+        assert len(result) == 2
+        assert all(isinstance(resp, str) for resp in result["model_response"])
+
+    async def test_invalid_column_name(self):
+        component = BatchRunComponent(
+            model=MockLanguageModel(), df=DataFrame({"text": ["Hello"]}), column_name="nonexistent_column"
+        )
+
+        with pytest.raises(ValueError, match=re.escape("Column 'nonexistent_column' not found in the DataFrame.")):
+            await component.run_batch()
+
+    async def test_empty_dataframe(self):
+        component = BatchRunComponent(model=MockLanguageModel(), df=DataFrame({"text": []}), column_name="text")
+
+        result = await component.run_batch()
+        assert isinstance(result, DataFrame)
+        assert len(result) == 0
+
+    async def test_non_string_column_conversion(self):
+        test_df = DataFrame(
+            {
+                "text": [123, 456, 789]  # Numeric values
+            }
+        )
+
+        component = BatchRunComponent(model=MockLanguageModel(), df=test_df, column_name="text")
+
+        result = await component.run_batch()
+
+        assert isinstance(result, DataFrame)
+        assert all(isinstance(text, str) for text in result["text_input"])
+        assert all(str(num) in text for num, text in zip(test_df["text"], result["text_input"], strict=False))

src/backend/tests/unit/components/helpers/test_structured_output_component.py

@@ -8,7 +8,7 @@ from langflow.inputs.inputs import TableInput
 from langflow.schema.data import Data
 from pydantic import BaseModel
 
-from tests.unit.useful import MockLanguageModel
+from tests.unit.mock_language_model import MockLanguageModel
 
 
 class TestStructuredOutputComponent: