# Dedicated high-performance venv for qwen3_vllm_score: .venv-reranker-score
  #
  # Create / refresh:
  #   ./scripts/setup_reranker_venv.sh qwen3_vllm_score
  #
  # vLLM 0.17+ replaces LLM(task="score") with runner/convert auto + LLM.score().
  # Pin vLLM for reproducible perf baselines; bump after validating CUDA/driver on your hosts.
  # If pip cannot find a wheel for your CUDA version, edit the vllm line or install from:
  #   https://docs.vllm.ai/en/latest/getting_started/installation.html
  
  -r requirements_reranker_base.txt

  # FlashInfer JIT (vLLM may select it on Turing when TRITON_ATTN is not forced) needs a ninja binary on PATH.
  ninja>=1.11

  vllm==0.18.0
  # Match vLLM 0.18 stack; cap <5 to avoid pip prefetching incompatible transformers 5.x.
  transformers>=4.51.0,<5