Fix OutOfMemoryError

✅ Solution

OutOfMemoryError in vllm often arises from insufficient GPU memory when loading large models or processing extensive sequences. Reduce `gpu_memory_utilization` in the LLM class during initialization to reserve more GPU space for operations. Alternatively, try enabling CPU offloading, or decreasing `max_model_len` if you are processing a long sequence.