feat: add save_to to classify and section

src/landingai_ade/_client.py

@@ -324,6 +324,7 @@ def classify(
         document: Optional[FileTypes] | Omit = omit,
         document_url: Optional[str] | Omit = omit,
         model: Optional[str] | Omit = omit,
+        save_to: str | Path | None = None,
         # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
         # The extra values given here take precedence over values defined on the client or passed to this method.
         extra_headers: Headers | None = None,
@@ -356,6 +357,11 @@ def classify(
 
           model: Classification model version. Defaults to the latest.
 
+          save_to: Optional output path. If a directory, auto-generates the filename
+              (e.g. {input_file}_classify_output.json, or classify_output.json when no
+              input filename is available). If a full path ending in .json, saves there
+              directly. Parent directories are created automatically.
+
           extra_headers: Send extra headers
 
           extra_query: Add additional query parameters to the request
@@ -364,6 +370,10 @@ def classify(
 
           timeout: Override the client-level default timeout for this request, in seconds
         """
+        # Store original inputs for filename extraction
+        original_document = document
+        original_document_url = document_url
+
         body = deepcopy_with_paths(
             {
                 "classes": classes,
@@ -378,7 +388,7 @@ def classify(
         # sent to the server will contain a `boundary` parameter, e.g.
         # multipart/form-data; boundary=---abc--
         extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})}
-        return self.post(
+        result = self.post(
             "/v1/ade/classify",
             body=maybe_transform(body, client_classify_params.ClientClassifyParams),
             files=files,
@@ -387,6 +397,10 @@ def classify(
             ),
             cast_to=ClassifyResponse,
         )
+        if save_to:
+            filename = _get_input_filename(original_document, original_document_url)
+            _save_response(save_to, filename, "classify", result)
+        return result
 
     def extract(
         self,
@@ -667,6 +681,7 @@ def section(
         markdown: Union[FileTypes, str, None] | Omit = omit,
         markdown_url: Optional[str] | Omit = omit,
         model: Optional[str] | Omit = omit,
+        save_to: str | Path | None = None,
         # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
         # The extra values given here take precedence over values defined on the client or passed to this method.
         extra_headers: Headers | None = None,
@@ -696,6 +711,11 @@ def section(
 
           model: Section model version. Defaults to latest.
 
+          save_to: Optional output path. If a directory, auto-generates the filename
+              (e.g. {input_file}_section_output.json, or section_output.json when no
+              input filename is available). If a full path ending in .json, saves there
+              directly. Parent directories are created automatically.
+
           extra_headers: Send extra headers
 
           extra_query: Add additional query parameters to the request
@@ -704,6 +724,10 @@ def section(
 
           timeout: Override the client-level default timeout for this request, in seconds
         """
+        # Store original inputs for filename extraction
+        original_markdown = markdown
+        original_markdown_url = markdown_url
+
         body = deepcopy_with_paths(
             {
                 "guidelines": guidelines,
@@ -718,7 +742,7 @@ def section(
         # sent to the server will contain a `boundary` parameter, e.g.
         # multipart/form-data; boundary=---abc--
         extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})}
-        return self.post(
+        result = self.post(
             "/v1/ade/section",
             body=maybe_transform(body, client_section_params.ClientSectionParams),
             files=files,
@@ -727,6 +751,10 @@ def section(
             ),
             cast_to=SectionResponse,
         )
+        if save_to:
+            filename = _get_input_filename(original_markdown, original_markdown_url)
+            _save_response(save_to, filename, "section", result)
+        return result
 
     def split(
         self,
@@ -1014,6 +1042,7 @@ async def classify(
         document: Optional[FileTypes] | Omit = omit,
         document_url: Optional[str] | Omit = omit,
         model: Optional[str] | Omit = omit,
+        save_to: str | Path | None = None,
         # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
         # The extra values given here take precedence over values defined on the client or passed to this method.
         extra_headers: Headers | None = None,
@@ -1046,6 +1075,11 @@ async def classify(
 
           model: Classification model version. Defaults to the latest.
 
+          save_to: Optional output path. If a directory, auto-generates the filename
+              (e.g. {input_file}_classify_output.json, or classify_output.json when no
+              input filename is available). If a full path ending in .json, saves there
+              directly. Parent directories are created automatically.
+
           extra_headers: Send extra headers
 
           extra_query: Add additional query parameters to the request
@@ -1054,6 +1088,10 @@ async def classify(
 
           timeout: Override the client-level default timeout for this request, in seconds
         """
+        # Store original inputs for filename extraction
+        original_document = document
+        original_document_url = document_url
+
         body = deepcopy_with_paths(
             {
                 "classes": classes,
@@ -1068,7 +1106,7 @@ async def classify(
         # sent to the server will contain a `boundary` parameter, e.g.
         # multipart/form-data; boundary=---abc--
         extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})}
-        return await self.post(
+        result = await self.post(
             "/v1/ade/classify",
             body=await async_maybe_transform(body, client_classify_params.ClientClassifyParams),
             files=files,
@@ -1077,6 +1115,10 @@ async def classify(
             ),
             cast_to=ClassifyResponse,
         )
+        if save_to:
+            filename = _get_input_filename(original_document, original_document_url)
+            _save_response(save_to, filename, "classify", result)
+        return result
 
     async def extract(
         self,
@@ -1358,6 +1400,7 @@ async def section(
         markdown: Union[FileTypes, str, None] | Omit = omit,
         markdown_url: Optional[str] | Omit = omit,
         model: Optional[str] | Omit = omit,
+        save_to: str | Path | None = None,
         # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
         # The extra values given here take precedence over values defined on the client or passed to this method.
         extra_headers: Headers | None = None,
@@ -1387,6 +1430,11 @@ async def section(
 
           model: Section model version. Defaults to latest.
 
+          save_to: Optional output path. If a directory, auto-generates the filename
+              (e.g. {input_file}_section_output.json, or section_output.json when no
+              input filename is available). If a full path ending in .json, saves there
+              directly. Parent directories are created automatically.
+
           extra_headers: Send extra headers
 
           extra_query: Add additional query parameters to the request
@@ -1395,6 +1443,10 @@ async def section(
 
           timeout: Override the client-level default timeout for this request, in seconds
         """
+        # Store original inputs for filename extraction
+        original_markdown = markdown
+        original_markdown_url = markdown_url
+
         body = deepcopy_with_paths(
             {
                 "guidelines": guidelines,
@@ -1409,7 +1461,7 @@ async def section(
         # sent to the server will contain a `boundary` parameter, e.g.
         # multipart/form-data; boundary=---abc--
         extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})}
-        return await self.post(
+        result = await self.post(
             "/v1/ade/section",
             body=await async_maybe_transform(body, client_section_params.ClientSectionParams),
             files=files,
@@ -1418,6 +1470,10 @@ async def section(
             ),
             cast_to=SectionResponse,
         )
+        if save_to:
+            filename = _get_input_filename(original_markdown, original_markdown_url)
+            _save_response(save_to, filename, "section", result)
+        return result
 
     async def split(
         self,

tests/test_save_to.py

@@ -8,7 +8,7 @@
 
 import pytest
 
-from landingai_ade import AsyncLandingAIADE
+from landingai_ade import LandingAIADE, AsyncLandingAIADE
 from landingai_ade._client import _save_response, _get_input_filename
 from landingai_ade._exceptions import LandingAiadeError
 
@@ -128,7 +128,7 @@ def test_correct_filename_format(self, tmp_path: Path) -> None:
         mock_result = MagicMock()
         mock_result.to_json.return_value = "{}"
 
-        for method in ["parse", "extract", "split"]:
+        for method in ["parse", "extract", "split", "classify", "section"]:
             _save_response(tmp_path, "myinput", method, mock_result)
             expected_file = tmp_path / f"myinput_{method}_output.json"
             assert expected_file.exists(), f"Expected {expected_file} to exist"
@@ -165,7 +165,7 @@ def test_output_filename_skips_redundant_prefix(self, tmp_path: Path) -> None:
         mock_result = MagicMock()
         mock_result.to_json.return_value = "{}"
 
-        for method in ["parse", "extract", "split"]:
+        for method in ["parse", "extract", "split", "classify", "section"]:
             _save_response(tmp_path, "output", method, mock_result)
             expected = tmp_path / f"{method}_output.json"
             assert expected.exists(), f"Expected {expected} to exist"
@@ -266,6 +266,62 @@ async def test_async_split_save_to(self, tmp_path: Path, mock_response: MagicMoc
 
         assert (tmp_path / "doc_split_output.json").exists()
 
+    @pytest.mark.asyncio
+    async def test_async_classify_save_to_directory(self, tmp_path: Path, mock_response: MagicMock) -> None:
+        from unittest.mock import AsyncMock, patch
+
+        async with AsyncLandingAIADE(apikey="test-key", base_url="http://localhost") as client:
+            with patch.object(client, "post", new_callable=AsyncMock, return_value=mock_response):
+                await client.classify(
+                    classes=[{"class": "invoice"}],
+                    document=Path("/path/to/doc.pdf"),
+                    save_to=tmp_path,
+                )
+
+        assert (tmp_path / "doc_classify_output.json").exists()
+
+    @pytest.mark.asyncio
+    async def test_async_classify_save_to_json_path(self, tmp_path: Path, mock_response: MagicMock) -> None:
+        from unittest.mock import AsyncMock, patch
+
+        output_file = tmp_path / "custom.json"
+        async with AsyncLandingAIADE(apikey="test-key", base_url="http://localhost") as client:
+            with patch.object(client, "post", new_callable=AsyncMock, return_value=mock_response):
+                await client.classify(
+                    classes=[{"class": "invoice"}],
+                    document_url="https://example.com/doc.pdf",
+                    save_to=output_file,
+                )
+
+        assert output_file.exists()
+
+    @pytest.mark.asyncio
+    async def test_async_section_save_to_directory(self, tmp_path: Path, mock_response: MagicMock) -> None:
+        from unittest.mock import AsyncMock, patch
+
+        async with AsyncLandingAIADE(apikey="test-key", base_url="http://localhost") as client:
+            with patch.object(client, "post", new_callable=AsyncMock, return_value=mock_response):
+                await client.section(
+                    markdown=Path("/path/to/doc.md"),
+                    save_to=tmp_path,
+                )
+
+        assert (tmp_path / "doc_section_output.json").exists()
+
+    @pytest.mark.asyncio
+    async def test_async_section_save_to_with_string_input(self, tmp_path: Path, mock_response: MagicMock) -> None:
+        """Section commonly receives raw markdown strings — filename should fall back to 'output'."""
+        from unittest.mock import AsyncMock, patch
+
+        async with AsyncLandingAIADE(apikey="test-key", base_url="http://localhost") as client:
+            with patch.object(client, "post", new_callable=AsyncMock, return_value=mock_response):
+                await client.section(
+                    markdown="# Heading\n\nbody content",
+                    save_to=tmp_path,
+                )
+
+        assert (tmp_path / "section_output.json").exists()
+
     @pytest.mark.asyncio
     async def test_async_no_save_when_save_to_none(self, tmp_path: Path, mock_response: MagicMock) -> None:
         from unittest.mock import AsyncMock, patch
@@ -276,3 +332,39 @@ async def test_async_no_save_when_save_to_none(self, tmp_path: Path, mock_respon
 
         assert result is mock_response
         assert not list(tmp_path.iterdir())
+
+
+class TestSyncSaveTo:
+    """Tests that sync client methods accept save_to and save correctly for classify/section."""
+
+    @pytest.fixture
+    def mock_response(self) -> MagicMock:
+        mock = MagicMock()
+        mock.to_json.return_value = '{"result": "ok"}'
+        return mock
+
+    def test_sync_classify_save_to_directory(self, tmp_path: Path, mock_response: MagicMock) -> None:
+        from unittest.mock import patch
+
+        client = LandingAIADE(apikey="test-key", base_url="http://localhost")
+        with patch.object(client, "post", return_value=mock_response):
+            client.classify(
+                classes=[{"class": "invoice"}],
+                document=Path("/path/to/doc.pdf"),
+                save_to=tmp_path,
+            )
+
+        assert (tmp_path / "doc_classify_output.json").exists()
+
+    def test_sync_section_save_to_json_path(self, tmp_path: Path, mock_response: MagicMock) -> None:
+        from unittest.mock import patch
+
+        output_file = tmp_path / "toc.json"
+        client = LandingAIADE(apikey="test-key", base_url="http://localhost")
+        with patch.object(client, "post", return_value=mock_response):
+            client.section(
+                markdown=Path("/path/to/doc.md"),
+                save_to=output_file,
+            )
+
+        assert output_file.exists()