[Bugfix][Core] Prevent token lengths exceeding max_model_len in V0 (#19348)

Signed-off-by: 22quinn <33176974+22quinn@users.noreply.github.com>

tests/entrypoints/llm/test_generate.py

@@ -25,6 +25,12 @@ TOKEN_IDS = [
 ]
 
 
+@pytest.fixture(autouse=True)
+def v1(run_with_both_engines):
+    """We can run both engines for this test."""
+    pass
+
+
 @pytest.fixture(scope="module")
 def llm():
     # pytest caches the fixture so we use weakref.proxy to
@@ -104,3 +110,19 @@ def test_multiple_sampling_params(llm: LLM):
     # sampling_params is None, default params should be applied
     outputs = llm.generate(PROMPTS, sampling_params=None)
     assert len(PROMPTS) == len(outputs)
+
+
+def test_max_model_len():
+    max_model_len = 20
+    llm = LLM(
+        model=MODEL_NAME,
+        max_model_len=max_model_len,
+        gpu_memory_utilization=0.10,
+        enforce_eager=True,  # reduce test time
+    )
+    sampling_params = SamplingParams(max_tokens=max_model_len + 10)
+    outputs = llm.generate(PROMPTS, sampling_params)
+    for output in outputs:
+        num_total_tokens = len(output.prompt_token_ids) + len(
+            output.outputs[0].token_ids)
+        assert num_total_tokens == max_model_len

vllm/engine/output_processor/stop_checker.py

@@ -82,7 +82,7 @@ class StopChecker:
             return
 
         # Check if the sequence has reached max_model_len.
-        if seq.get_len() > self._get_max_model_len(lora_req):
+        if seq.get_len() >= self._get_max_model_len(lora_req):
             seq.status = SequenceStatus.FINISHED_LENGTH_CAPPED
             return