fix: pass all reference images to OpenAI images.edit endpoint

bulkgen/providers/openai_image.py

@@ -185,25 +185,25 @@ async def _generate_edit(
     project_dir: Path,
     size: _SIZE | None,
 ) -> ImagesResponse:
-    """Generate an image using a reference image via the edits endpoint.
+    """Generate an image using reference images via the edits endpoint.
 
-    gpt-image-* models return b64 by default and reject ``response_format``,
-    so we only pass it for DALL-E models.
+    gpt-image-* models accept up to 16 images and return b64 by default
+    (they reject ``response_format``).  DALL-E 2 accepts only one image.
     """
-    ref_path = project_dir / reference_images[0]
-    image_bytes = ref_path.read_bytes()
+    images = [(project_dir / name).read_bytes() for name in reference_images]
+    image: bytes | list[bytes] = images[0] if len(images) == 1 else images
 
     if model.startswith("gpt-image-"):
         if size is not None:
             return await client.images.edit(
-                image=image_bytes,
+                image=image,
                 prompt=prompt,
                 model=model,
                 n=1,
                 size=size,  # pyright: ignore[reportArgumentType]
             )
         return await client.images.edit(
-            image=image_bytes,
+            image=image,
             prompt=prompt,
             model=model,
             n=1,
@@ -211,7 +211,7 @@ async def _generate_edit(
 
     if size is not None:
         return await client.images.edit(
-            image=image_bytes,
+            image=image,
             prompt=prompt,
             model=model,
             n=1,
@@ -219,7 +219,7 @@ async def _generate_edit(
             size=size,  # pyright: ignore[reportArgumentType]
         )
     return await client.images.edit(
-        image=image_bytes,
+        image=image,
         prompt=prompt,
         model=model,
         n=1,

tests/test_providers.py

@@ -20,6 +20,7 @@ from bulkgen.providers.blackforest import (
 )
 from bulkgen.providers.mistral import MistralProvider
 from bulkgen.providers.models import ModelInfo
+from bulkgen.providers.openai_image import OpenAIImageProvider
 from bulkgen.providers.registry import get_all_models
 
 
@@ -422,3 +423,92 @@ class TestMistralProvider:
             assert isinstance(chunks, list)
             assert chunks[0].text == "Describe the style"
             assert chunks[1].image_url.url.startswith("data:image/png;base64,")
+
+
+def _make_openai_mock(b64_data: str) -> AsyncMock:
+    """Return a mock AsyncOpenAI client that returns b64 image data."""
+    image = MagicMock()
+    image.b64_json = b64_data
+    image.url = None
+
+    response = MagicMock()
+    response.data = [image]
+
+    mock_client = AsyncMock()
+    mock_client.images.generate = AsyncMock(return_value=response)
+    mock_client.images.edit = AsyncMock(return_value=response)
+    mock_client.__aenter__ = AsyncMock(return_value=mock_client)
+    mock_client.__aexit__ = AsyncMock(return_value=False)
+    return mock_client
+
+
+class TestOpenAIImageProvider:
+    """Test OpenAIImageProvider with mocked OpenAI client."""
+
+    @pytest.fixture
+    def image_bytes(self) -> bytes:
+        return b"\x89PNG\r\n\x1a\n" + b"\x00" * 100
+
+    async def test_single_reference_image(
+        self, project_dir: Path, image_bytes: bytes
+    ) -> None:
+        ref = project_dir / "ref.png"
+        _ = ref.write_bytes(b"reference data")
+
+        target_config = TargetConfig(prompt="Edit this", reference_images=["ref.png"])
+        b64 = base64.b64encode(image_bytes).decode()
+        mock_client = _make_openai_mock(b64)
+
+        with patch("bulkgen.providers.openai_image.AsyncOpenAI") as mock_cls:
+            mock_cls.return_value = mock_client
+
+            provider = OpenAIImageProvider(api_key="test-key")
+            await provider.generate(
+                target_name="out.png",
+                target_config=target_config,
+                resolved_prompt="Edit this",
+                resolved_model=_model("gpt-image-1"),
+                project_dir=project_dir,
+            )
+
+            call_args = mock_client.images.edit.call_args
+            # Single reference image should be passed as raw bytes
+            assert call_args.kwargs["image"] == b"reference data"
+
+        output = project_dir / "out.png"
+        assert output.exists()
+        assert output.read_bytes() == image_bytes
+
+    async def test_multiple_reference_images(
+        self, project_dir: Path, image_bytes: bytes
+    ) -> None:
+        ref1 = project_dir / "ref1.png"
+        ref2 = project_dir / "ref2.png"
+        _ = ref1.write_bytes(b"ref1 data")
+        _ = ref2.write_bytes(b"ref2 data")
+
+        target_config = TargetConfig(
+            prompt="Combine", reference_images=["ref1.png", "ref2.png"]
+        )
+        b64 = base64.b64encode(image_bytes).decode()
+        mock_client = _make_openai_mock(b64)
+
+        with patch("bulkgen.providers.openai_image.AsyncOpenAI") as mock_cls:
+            mock_cls.return_value = mock_client
+
+            provider = OpenAIImageProvider(api_key="test-key")
+            await provider.generate(
+                target_name="out.png",
+                target_config=target_config,
+                resolved_prompt="Combine",
+                resolved_model=_model("gpt-image-1"),
+                project_dir=project_dir,
+            )
+
+            call_args = mock_client.images.edit.call_args
+            # Multiple reference images should be passed as a list of bytes
+            image_arg: list[bytes] = call_args.kwargs["image"]
+            assert isinstance(image_arg, list)
+            assert len(image_arg) == 2
+            assert image_arg[0] == b"ref1 data"
+            assert image_arg[1] == b"ref2 data"