# 64k-context focused comparison for SGLang vs vLLM on H200.
# Scenarios requested:
#   1) input=65536, output=256,  concurrency=25
#   2) input=65536, output=1024, concurrency=8,  num_prompts=100

EXPERIMENT="dsv4_h200_64k_sglang_vs_vllm"
MODEL_NAME="DeepSeek-V4-Flash"
MODEL_PATH="/data/models/DeepSeek-V4-Flash"
SERVED_MODEL_NAME="deepseek-v4-flash"

SGLANG_PORT="${SGLANG_PORT:-30006}"
VLLM_PORT="${VLLM_PORT:-30005}"

VENV_SGLANG="${VENV_SGLANG:-/data/user1/yy/envs/sglang}"
VENV_VLLM="${VENV_VLLM:-/data/user1/yy/envs/vllm}"

export CUDA_VISIBLE_DEVICES="0,1,2,3,4,5,6,7"
TP=8

# 64k + 1024 output + padding -> use 70000 to keep both backends identical.
MAX_MODEL_LEN=70000
MAX_NUM_SEQS=64
MAX_RUNNING=64

# "concurrency input_len output_len num_prompts"
# Following docs/EXPERIMENT_GUIDE.md: num_prompts = concurrency * 5.
declare -a SCENARIOS=(
  "25 65536 256  125"
  "8  65536 1024 40"
)

VENV_CLIENT="${VENV_CLIENT:-$VENV_SGLANG}"

SGLANG_START_SCRIPT="${SCRIPT_DIR:-.}/start_sglang.sh"
VLLM_START_SCRIPT="${SCRIPT_DIR:-.}/start_vllm.sh"