feat: support multi-image image generation

apps/ai/tests.py

@@ -22,6 +22,7 @@ from apps.ai.providers.openai_compatible import (
     ChatCompletionsProvider,
     GeminiProvider,
     ImagesEditsProvider,
+    ImagesGenerationProvider,
 )
 from apps.ai.providers.utils import image_request_timeout, resolution_to_size
 
@@ -207,6 +208,34 @@ class ChatCompletionsProviderTests(SimpleTestCase):
         self.assertEqual(content[0], {"type": "text", "text": "Generate product image"})
         self.assertTrue(content[1]["image_url"]["url"].startswith("data:image/jpeg;base64,"))
 
+    def test_generate_image_sends_multiple_chat_images_in_order(self):
+        encoded = base64.b64encode(b"generated-image").decode("ascii")
+        session = FakeSession(
+            FakeResponse({"data": [{"b64_json": encoded}]})
+        )
+        provider = ChatCompletionsProvider(session=session)
+        model = ResolvedModel(
+            name="Nano Banana 2",
+            url="https://api.vectorengine.ai/v1/chat/completions",
+            model="gemini-3.1-flash-image-preview",
+            api_key="test-key",
+            api_type="chat",
+        )
+
+        provider.generate_image(
+            "Generate product image",
+            model,
+            images=(
+                MultimodalImage(b"main-image", "image/jpeg", "main.jpg"),
+                MultimodalImage(b"reference-image", "image/png", "reference.png"),
+            ),
+        )
+
+        content = session.posts[0]["json"]["messages"][0]["content"]
+        self.assertEqual(content[0]["text"], "Generate product image")
+        self.assertTrue(content[1]["image_url"]["url"].startswith("data:image/jpeg;base64,"))
+        self.assertTrue(content[2]["image_url"]["url"].startswith("data:image/png;base64,"))
+
     @override_settings(AI_IMAGE_UPSTREAM_DEADLINE_SECONDS=180)
     def test_generate_image_caps_post_and_download_timeouts(self):
         session = FakeSession(
@@ -345,6 +374,34 @@ class ChatCompletionsProviderTests(SimpleTestCase):
         )
 
 
+class ImagesGenerationProviderTests(SimpleTestCase):
+    def test_generate_image_sends_multiple_json_images_in_order(self):
+        encoded = base64.b64encode(b"generated-image").decode("ascii")
+        session = FakeSession(FakeResponse({"data": [{"b64_json": encoded}]}))
+        provider = ImagesGenerationProvider(session=session)
+        model = ResolvedModel(
+            name="JSON image provider",
+            url="https://images.example.test/v1/images/generations",
+            model="image-model",
+            api_key="test-key",
+            api_type="images",
+        )
+
+        provider.generate_image(
+            "Use the first image as the main product",
+            model,
+            images=(
+                MultimodalImage(b"main-image", "image/jpeg", "main.jpg"),
+                MultimodalImage(b"reference-image", "image/png", "reference.png"),
+            ),
+        )
+
+        image_urls = session.posts[0]["json"]["image_urls"]
+        self.assertEqual(len(image_urls), 2)
+        self.assertTrue(image_urls[0].startswith("data:image/jpeg;base64,"))
+        self.assertTrue(image_urls[1].startswith("data:image/png;base64,"))
+
+
 class ImagesEditsProviderTests(SimpleTestCase):
     def test_generate_image_builds_multipart_request_and_parses_base64(self):
         generated = b"edited-image"
@@ -379,6 +436,35 @@ class ImagesEditsProviderTests(SimpleTestCase):
             ("source.png", b"source-image", "image/png"),
         )
 
+    def test_generate_image_sends_multiple_multipart_images_in_order(self):
+        encoded = base64.b64encode(b"edited-image").decode("ascii")
+        session = FakeSession(FakeResponse({"data": [{"b64_json": encoded}]}))
+        provider = ImagesEditsProvider(session=session)
+        model = ResolvedModel(
+            name="GPT Image 2",
+            url="https://api.vectorengine.ai/v1/images/edits",
+            model="gpt-image-2",
+            api_key="test-key",
+            api_type="images_edits",
+        )
+
+        provider.generate_image(
+            "Use the first image as the main product",
+            model,
+            images=(
+                MultimodalImage(b"main-image", "image/jpeg", "main.jpg"),
+                MultimodalImage(b"reference-image", "image/png", "reference.png"),
+            ),
+        )
+
+        self.assertEqual(
+            session.posts[0]["files"],
+            [
+                ("image", ("main.jpg", b"main-image", "image/jpeg")),
+                ("image", ("reference.png", b"reference-image", "image/png")),
+            ],
+        )
+
     def test_parameters_cannot_override_core_images_edits_fields(self):
         generated = b"edited-image"
         encoded = base64.b64encode(generated).decode("ascii")