draft extract dimensions nooa

pytest-local.ini

@@ -5,6 +5,7 @@ testpaths =
     tests/test_container_smoke.py
     tests/test_data.py
     tests/test_dataframe.py
+    tests/test_nooa_extract_dimensions.py
     tests/test_openai_extract_ai.py
     tests/recipes
     tests/connectors/test_access.py

requirements-full.txt

@@ -14,3 +14,6 @@ psycopg2-binary>=2.9.10
 
 # Parquet file support (file connector)
 pyarrow
+
+# AI agent framework (extract.dimensions), Python 3.12+ only
+nooa==0.0.10; python_version >= "3.12"

tests/recipes/wrangles/test_extract_dimensions.py

@@ -0,0 +1,110 @@
+"""
+Recipe-level wiring tests for extract.dimensions.
+
+Fully offline: the plain wrangles.extract.dimensions() function is mocked,
+so these tests exercise only the recipe wrangle's input/output column
+handling - not the NOOA integration itself (see
+tests/test_nooa_extract_dimensions.py for that).
+"""
+import pandas as pd
+import pytest
+import wrangles
+from unittest.mock import patch
+
+
+class TestExtractDimensions:
+    @patch("wrangles.recipe_wrangles.extract._extract.dimensions")
+    def test_single_input_column(self, dimensions):
+        dimensions.return_value = [
+            {"measurements": []},
+            {"measurements": [{"kind": "length", "value": 6, "unit": "m", "source": "6m cable"}]},
+        ]
+        data = pd.DataFrame({"description": ["wrench 25mm", "6m cable"]})
+        recipe = """
+        wrangles:
+          - extract.dimensions:
+              input: description
+              output: Dimensions
+              model: gpt-5-mini
+              api_key: test-key
+        """
+
+        result = wrangles.recipe.run(recipe, dataframe=data)
+
+        # Single input column -> raw column values passed through, not records
+        dimensions.assert_called_once()
+        assert dimensions.call_args.args[0] == ["wrench 25mm", "6m cable"]
+        assert result["Dimensions"].tolist() == [
+            {"measurements": []},
+            {"measurements": [{"kind": "length", "value": 6, "unit": "m", "source": "6m cable"}]},
+        ]
+
+    @patch("wrangles.recipe_wrangles.extract._extract.dimensions")
+    def test_multiple_input_columns_combined_as_records(self, dimensions):
+        dimensions.return_value = [{"measurements": []}]
+        data = pd.DataFrame({
+            "Description": ["Bottle"],
+            "Size": ["750 mL"],
+        })
+        recipe = """
+        wrangles:
+          - extract.dimensions:
+              input:
+                - Description
+                - Size
+              output: Dimensions
+              api_key: test-key
+        """
+
+        wrangles.recipe.run(recipe, dataframe=data)
+
+        rows = dimensions.call_args.args[0]
+        assert rows == [{"Description": "Bottle", "Size": "750 mL"}]
+
+    @patch("wrangles.recipe_wrangles.extract._extract.dimensions")
+    def test_omitted_input_uses_all_columns(self, dimensions):
+        dimensions.return_value = [{"measurements": []}]
+        data = pd.DataFrame({"Description": ["Bottle"], "Packaging": ["Boxed"]})
+        recipe = """
+        wrangles:
+          - extract.dimensions:
+              output: Dimensions
+              api_key: test-key
+        """
+
+        wrangles.recipe.run(recipe, dataframe=data)
+
+        rows = dimensions.call_args.args[0]
+        assert rows == [{"Description": "Bottle", "Packaging": "Boxed"}]
+
+    @patch("wrangles.recipe_wrangles.extract._extract.dimensions")
+    def test_model_api_key_and_threads_forwarded(self, dimensions):
+        dimensions.return_value = [{"measurements": []}]
+        data = pd.DataFrame({"description": ["wrench 25mm"]})
+        recipe = """
+        wrangles:
+          - extract.dimensions:
+              input: description
+              output: Dimensions
+              model: gpt-5.4-mini
+              api_key: ${API_KEY}
+              threads: 4
+        """
+
+        wrangles.recipe.run(recipe, dataframe=data, variables={"API_KEY": "secret"})
+
+        kwargs = dimensions.call_args.kwargs
+        assert kwargs["model"] == "gpt-5.4-mini"
+        assert kwargs["api_key"] == "secret"
+        assert kwargs["threads"] == 4
+
+    def test_missing_output_is_rejected(self):
+        data = pd.DataFrame({"description": ["wrench 25mm"]})
+        recipe = """
+        wrangles:
+          - extract.dimensions:
+              input: description
+              api_key: test-key
+        """
+        with pytest.raises(Exception):
+            wrangles.recipe.run(recipe, dataframe=data)