[CI/Build] Test both text and token IDs in batched OpenAI Completions API (#5568)

tests/entrypoints/test_openai_server.py

@@ -655,50 +655,52 @@ async def test_completion_stream_options(client: openai.AsyncOpenAI,
     [MODEL_NAME, "zephyr-lora"],
 )
 async def test_batch_completions(client: openai.AsyncOpenAI, model_name: str):
-    # test simple list
-    batch = await client.completions.create(
-        model=model_name,
-        prompt=["Hello, my name is", "Hello, my name is"],
-        max_tokens=5,
-        temperature=0.0,
-    )
-    assert len(batch.choices) == 2
-    assert batch.choices[0].text == batch.choices[1].text
-
-    # test n = 2
-    batch = await client.completions.create(
-        model=model_name,
-        prompt=["Hello, my name is", "Hello, my name is"],
-        n=2,
-        max_tokens=5,
-        temperature=0.0,
-        extra_body=dict(
-            # NOTE: this has to be true for n > 1 in vLLM, but not necessary
-            # for official client.
-            use_beam_search=True),
-    )
-    assert len(batch.choices) == 4
-    assert batch.choices[0].text != batch.choices[
-        1].text, "beam search should be different"
-    assert batch.choices[0].text == batch.choices[
-        2].text, "two copies of the same prompt should be the same"
-    assert batch.choices[1].text == batch.choices[
-        3].text, "two copies of the same prompt should be the same"
+    # test both text and token IDs
+    for prompts in (["Hello, my name is"] * 2, [[0, 0, 0, 0, 0]] * 2):
+        # test simple list
+        batch = await client.completions.create(
+            model=model_name,
+            prompt=prompts,
+            max_tokens=5,
+            temperature=0.0,
+        )
+        assert len(batch.choices) == 2
+        assert batch.choices[0].text == batch.choices[1].text
 
-    # test streaming
-    batch = await client.completions.create(
-        model=model_name,
-        prompt=["Hello, my name is", "Hello, my name is"],
-        max_tokens=5,
-        temperature=0.0,
-        stream=True,
-    )
-    texts = [""] * 2
-    async for chunk in batch:
-        assert len(chunk.choices) == 1
-        choice = chunk.choices[0]
-        texts[choice.index] += choice.text
-    assert texts[0] == texts[1]
+        # test n = 2
+        batch = await client.completions.create(
+            model=model_name,
+            prompt=prompts,
+            n=2,
+            max_tokens=5,
+            temperature=0.0,
+            extra_body=dict(
+                # NOTE: this has to be true for n > 1 in vLLM, but not necessary
+                # for official client.
+                use_beam_search=True),
+        )
+        assert len(batch.choices) == 4
+        assert batch.choices[0].text != batch.choices[
+            1].text, "beam search should be different"
+        assert batch.choices[0].text == batch.choices[
+            2].text, "two copies of the same prompt should be the same"
+        assert batch.choices[1].text == batch.choices[
+            3].text, "two copies of the same prompt should be the same"
+
+        # test streaming
+        batch = await client.completions.create(
+            model=model_name,
+            prompt=prompts,
+            max_tokens=5,
+            temperature=0.0,
+            stream=True,
+        )
+        texts = [""] * 2
+        async for chunk in batch:
+            assert len(chunk.choices) == 1
+            choice = chunk.choices[0]
+            texts[choice.index] += choice.text
+        assert texts[0] == texts[1]
 
 
 @pytest.mark.asyncio