Fix image upload processing and img2img pipeline in diffusers backend (#8879)

* fix: add missing bufio.Flush in processImageFile

The processImageFile function writes decoded image data (from base64
or URL download) through a bufio.NewWriter but never calls Flush()
before closing the underlying file. Since bufio's default buffer is
4096 bytes, small images produce 0-byte files and large images are
truncated — causing PIL to fail with "cannot identify image file".

This breaks all image input paths: file, files, and ref_images
parameters in /v1/images/generations, making img2img, inpainting,
and reference image features non-functional.

Signed-off-by: Attila Györffy <attila+git@attilagyorffy.com>

* fix: merge options into kwargs in diffusers GenerateImage

The GenerateImage method builds a local `options` dict containing the
source image (PIL), negative_prompt, and num_inference_steps, but
never merges it into `kwargs` before calling self.pipe(**kwargs).
This causes img2img to fail with "Input is in incorrect format"
because the pipeline never receives the image parameter.

Signed-off-by: Attila Györffy <attila+git@attilagyorffy.com>

* test: add unit test for processImageFile base64 decoding

Verifies that a base64-encoded PNG survives the write path
(encode → decode → bufio.Write → Flush → file on disk) with
byte-for-byte fidelity. The test image is small enough to fit
entirely in bufio's 4096-byte buffer, which is the exact scenario
where the missing Flush() produced a 0-byte file.

Also tests that invalid base64 input is handled gracefully.

Signed-off-by: Attila Györffy <attila+git@attilagyorffy.com>

* test: verify GenerateImage merges options into pipeline kwargs

Mocks the diffusers pipeline and calls GenerateImage with a source
image and negative prompt. Asserts that the pipeline receives the
image, negative_prompt, and num_inference_steps via kwargs — the
exact parameters that were silently dropped before the fix.

Signed-off-by: Attila Györffy <attila+git@attilagyorffy.com>

* fix: move kwargs.update(options) earlier in GenerateImage

Move the options merge right after self.options merge (L742) so that
image, negative_prompt, and num_inference_steps are available to all
downstream code paths including img2vid and txt2vid.

Signed-off-by: Attila Györffy <attila+git@attilagyorffy.com>

* test: convert processImageFile tests to ginkgo

Replace standard testing with ginkgo/gomega to be consistent with
the rest of the test suites in the project.

Signed-off-by: Attila Györffy <attila+git@attilagyorffy.com>

---------

Signed-off-by: Attila Györffy <attila+git@attilagyorffy.com>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>

backend/python/diffusers/backend.py

@@ -741,6 +741,8 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
         # populate kwargs from self.options.
         kwargs.update(self.options)
 
+        kwargs.update(options)
+
         # Set seed
         if request.seed > 0:
             kwargs["generator"] = torch.Generator(device=self.device).manual_seed(

backend/python/diffusers/test.py

@@ -312,3 +312,64 @@ class TestDiffusersDynamicLoaderWithMocks(unittest.TestCase):
         # or fail depending on network, but the fallback path should work.
         cls = loader.resolve_pipeline_class(model_id="some/nonexistent/model")
         self.assertEqual(cls, DiffusionPipeline)
+
+
+@unittest.skipUnless(GRPC_AVAILABLE, "gRPC modules not available")
+class TestGenerateImageOptionsKwargsMerge(unittest.TestCase):
+    """Test that GenerateImage merges the options dict into pipeline kwargs.
+
+    The options dict holds image (PIL), negative_prompt, and
+    num_inference_steps. Without the merge, img2img pipelines never
+    receive the source image and fail with 'Input is in incorrect format'.
+    """
+
+    def test_options_merged_into_pipeline_kwargs(self):
+        from backend import BackendServicer
+        from PIL import Image
+        import tempfile, os
+
+        svc = BackendServicer.__new__(BackendServicer)
+        # Minimal attributes the method reads
+        svc.pipe = MagicMock()
+        svc.pipe.return_value.images = [Image.new("RGB", (4, 4))]
+        svc.cfg_scale = 7.5
+        svc.controlnet = None
+        svc.img2vid = False
+        svc.txt2vid = False
+        svc.clip_skip = 0
+        svc.PipelineType = "StableDiffusionImg2ImgPipeline"
+        svc.options = {}
+
+        # Create a tiny source image for the request's src field
+        src_file = tempfile.NamedTemporaryFile(suffix=".png", delete=False)
+        Image.new("RGB", (4, 4), color="red").save(src_file, format="PNG")
+        src_file.close()
+
+        dst_file = tempfile.NamedTemporaryFile(suffix=".png", delete=False)
+        dst_file.close()
+
+        try:
+            request = MagicMock()
+            request.positive_prompt = "a test prompt"
+            request.negative_prompt = "bad quality"
+            request.step = 10
+            request.seed = 0
+            request.width = 0
+            request.height = 0
+            request.src = src_file.name
+            request.ref_images = []
+            request.dst = dst_file.name
+
+            svc.GenerateImage(request, context=None)
+
+            # The pipeline must have been called with the image kwarg
+            svc.pipe.assert_called_once()
+            _, call_kwargs = svc.pipe.call_args
+            self.assertIn("image", call_kwargs,
+                          "source image must be passed to pipeline via kwargs")
+            self.assertIn("negative_prompt", call_kwargs,
+                          "negative_prompt must be passed to pipeline via kwargs")
+            self.assertEqual(call_kwargs["num_inference_steps"], 10)
+        finally:
+            os.unlink(src_file.name)
+            os.unlink(dst_file.name)