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# This will overwrite the llm_api_config.yaml

# TODO: Specifying the context and generation servers in the config file is
# bit confusing. Investigate if we can clean this up.

hostname: localhost
port: 8080
trust_remote_code: true
backend: pytorch

context_servers:
  num_instances: 1
  tensor_parallel_size: 1
  max_num_tokens: 10240
  max_batch_size: 16
  enable_chunked_prefill: false
  kv_cache_config:
    free_gpu_memory_fraction: 0.40
  cache_transceiver_config:
    max_num_tokens: 10240
  # NOTE: pytorch_backend_config section flattened since: https://github.com/NVIDIA/TensorRT-LLM/pull/4603
  # NOTE: This field is called 'enable_overlap_scheduler' in older TRTLLM versions
  # Overlap scheduler not currently supported in context-only
  disable_overlap_scheduler: true
  use_cuda_graph: false
  urls:
      - "localhost:8001"

generation_servers:
  num_instances: 1
  tensor_parallel_size: 1
  max_num_tokens: 256
  max_batch_size: 256
  kv_cache_config:
    free_gpu_memory_fraction: 0.40
  cache_transceiver_config:
    max_num_tokens: 256
  # NOTE: pytorch_backend_config section flattened since: https://github.com/NVIDIA/TensorRT-LLM/pull/4603
  # NOTE: This field is called 'enable_overlap_scheduler' in older TRTLLM versions
  disable_overlap_scheduler: false
  use_cuda_graph: false
  urls:
      - "localhost:8002"
