Sync from v0.13

tests/models/language/pooling/test_truncation_control.py

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+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+import pytest
+
+MODEL_NAME = "sentence-transformers/all-MiniLM-L12-v2"
+max_model_len = 128
+
+input_str = """Immerse yourself in the enchanting chronicle of calculus, a 
+mathematical domain that has radically transformed our comprehension of 
+change and motion. Despite its roots in ancient civilizations, the 
+formal birth of calculus predominantly occurred in the 17th century, 
+primarily under the influential guidance of Sir Isaac Newton and Gottfried 
+Wilhelm Leibniz. The earliest traces of calculus concepts are found in 
+ancient Greek mathematics,most notably in the works of Eudoxus and 
+Archimedes, around 300 BCE. They utilized the 'method of exhaustion'—a 
+technique for computing areas and volumes through the use of finite sums. 
+This methodology laid crucial foundational work for integral calculus. 
+In the 17th century, both Newton and Leibniz independently pioneered 
+calculus, each contributing unique perspectives that would shape this new 
+field."""
+
+
+def test_smaller_truncation_size(
+    vllm_runner, model_name=MODEL_NAME, input_str=input_str
+):
+    truncate_prompt_tokens = 10
+
+    with vllm_runner(
+        model_name, runner="pooling", max_model_len=max_model_len
+    ) as vllm_model:
+        vllm_output = vllm_model.llm.embed(
+            input_str, truncate_prompt_tokens=truncate_prompt_tokens
+        )
+
+    prompt_tokens = vllm_output[0].prompt_token_ids
+
+    assert len(prompt_tokens) == truncate_prompt_tokens
+
+
+def test_max_truncation_size(vllm_runner, model_name=MODEL_NAME, input_str=input_str):
+    truncate_prompt_tokens = -1
+
+    with vllm_runner(
+        model_name, runner="pooling", max_model_len=max_model_len
+    ) as vllm_model:
+        vllm_output = vllm_model.llm.embed(
+            input_str, truncate_prompt_tokens=truncate_prompt_tokens
+        )
+
+    prompt_tokens = vllm_output[0].prompt_token_ids
+
+    assert len(prompt_tokens) == max_model_len
+
+
+def test_bigger_truncation_size(
+    vllm_runner, model_name=MODEL_NAME, input_str=input_str
+):
+    truncate_prompt_tokens = max_model_len + 1
+
+    with (
+        pytest.raises(ValueError),
+        vllm_runner(
+            model_name, runner="pooling", max_model_len=max_model_len
+        ) as vllm_model,
+    ):
+        llm_output = vllm_model.llm.embed(
+            input_str, truncate_prompt_tokens=truncate_prompt_tokens
+        )
+
+        assert (
+            llm_output
+            == f"""truncate_prompt_tokens value 
+                ({truncate_prompt_tokens}) is greater than 
+                max_model_len ({max_model_len}). Please, select 
+                a smaller truncation size."""
+        )