[Frontend] Chat-based Embeddings API (#9759)

tests/entrypoints/openai/test_vision_embedding.py

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+from typing import Dict
+
+import pytest
+import pytest_asyncio
+import requests
+
+from vllm.multimodal.utils import encode_image_base64, fetch_image
+
+from ...utils import RemoteOpenAIServer
+
+MODEL_NAME = "TIGER-Lab/VLM2Vec-Full"
+MAXIMUM_IMAGES = 2
+
+# Test different image extensions (JPG/PNG) and formats (gray/RGB/RGBA)
+TEST_IMAGE_URLS = [
+    "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg",
+    "https://upload.wikimedia.org/wikipedia/commons/f/fa/Grayscale_8bits_palette_sample_image.png",
+    "https://upload.wikimedia.org/wikipedia/commons/thumb/9/91/Venn_diagram_rgb.svg/1280px-Venn_diagram_rgb.svg.png",
+    "https://upload.wikimedia.org/wikipedia/commons/0/0b/RGBA_comp.png",
+]
+
+
+@pytest.fixture(scope="module")
+def server():
+    args = [
+        "--task",
+        "embedding",
+        "--dtype",
+        "bfloat16",
+        "--max-model-len",
+        "2048",
+        "--max-num-seqs",
+        "5",
+        "--enforce-eager",
+        "--trust-remote-code",
+        "--limit-mm-per-prompt",
+        f"image={MAXIMUM_IMAGES}",
+    ]
+
+    with RemoteOpenAIServer(MODEL_NAME, args) as remote_server:
+        yield remote_server
+
+
+@pytest_asyncio.fixture
+async def client(server):
+    async with server.get_async_client() as async_client:
+        yield async_client
+
+
+@pytest.fixture(scope="session")
+def base64_encoded_image() -> Dict[str, str]:
+    return {
+        image_url: encode_image_base64(fetch_image(image_url))
+        for image_url in TEST_IMAGE_URLS
+    }
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("model_name", [MODEL_NAME])
+@pytest.mark.parametrize("image_url", TEST_IMAGE_URLS)
+async def test_image_embedding(server: RemoteOpenAIServer, model_name: str,
+                               image_url: str):
+    messages = [{
+        "role":
+        "user",
+        "content": [
+            {
+                "type": "image_url",
+                "image_url": {
+                    "url": image_url
+                }
+            },
+            {
+                "type": "text",
+                "text": "Represent the given image."
+            },
+        ],
+    }]
+
+    response = requests.post(server.url_for("v1/embeddings"),
+                             json={
+                                 "model": model_name,
+                                 "messages": messages,
+                                 "encoding_format": "float"
+                             })
+    response.raise_for_status()
+
+    embeddings = response.json()
+    assert embeddings["id"] is not None
+    assert len(embeddings["data"]) == 1
+    assert len(embeddings["data"][0]["embedding"]) == 3072
+    assert embeddings["usage"]["completion_tokens"] == 0
+    assert embeddings["usage"]["prompt_tokens"] == 771
+    assert embeddings["usage"]["total_tokens"] == 771