Add support for OpenAI api "image_url" input in chat for image-text-to-text pipeline (#34562)

* add support for openai api image_url input

* change continue to elif

* Explicitely add support for OpenAI/TGI chat format

* rewrite content to transformers chat format and add tests

* Add support for typing of image type in chat templates

* add base64 to possible image types

* refactor nesting

tests/pipelines/test_pipelines_image_text_to_text.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import base64
 import unittest
 
 from transformers import MODEL_FOR_IMAGE_TEXT_TO_TEXT_MAPPING, is_vision_available
@@ -258,3 +259,46 @@ class ImageTextToTextPipelineTests(unittest.TestCase):
                 }
             ],
         )
+
+    @slow
+    @require_torch
+    def test_model_pt_chat_template_image_url(self):
+        pipe = pipeline("image-text-to-text", model="llava-hf/llava-onevision-qwen2-0.5b-ov-hf")
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "image_url",
+                        "image_url": {
+                            "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
+                        },
+                    },
+                    {"type": "text", "text": "Describe this image in one sentence."},
+                ],
+            }
+        ]
+        outputs = pipe(text=messages, return_full_text=False, max_new_tokens=10)[0]["generated_text"]
+        self.assertEqual(outputs, "The image captures the iconic Statue of Liberty, a")
+
+    @slow
+    @require_torch
+    def test_model_pt_chat_template_image_url_base64(self):
+        with open("./tests/fixtures/tests_samples/COCO/000000039769.png", "rb") as image_file:
+            base64_image = base64.b64encode(image_file.read()).decode("utf-8")
+
+        pipe = pipeline("image-text-to-text", model="llava-hf/llava-onevision-qwen2-0.5b-ov-hf")
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"},
+                    },
+                    {"type": "text", "text": "Describe this image in one sentence."},
+                ],
+            }
+        ]
+        outputs = pipe(text=messages, return_full_text=False, max_new_tokens=10)[0]["generated_text"]
+        self.assertEqual(outputs, "Two cats are sleeping on a pink blanket, with")