# DeepSeek-V4-Flash-0731 DSpark — 2× GB10 / DGX Spark, TP=2 over RoCE.
#
# This variant uses eugr's prebuilt b12x image (eugr/spark-vllm-b12x) and
# mirrors eugr's recipes/deepseek-v4-flash-0731.yaml on the b12x branch — the
# stack published in NVIDIA forum comment #28:
#   https://forums.developer.nvidia.com/t/instructions-for-running-deepseek-v4-flash-with-dspark-using-eugrs-repo/376220/28
# ("While I'm working on integrating b12x into the build/test pipeline and
# merging into main, I pushed prebuilt container as eugr/spark-vllm-b12x …
# this version supports 3x Sparks with TP=3! To use, just add --tp 3.")
#
# Image: eugr/spark-vllm-b12x:sm121 — the prebuilt base with the
# instanttensor-hybrid-draft-loader mod baked in at build time (see
# docker-images/deepseek-v4-flash-eugr). eugr's recipe applies that mod via
# run-recipe.sh --apply-mod; sm121 has no runtime mod-upload step for Docker
# recipes, so the overlay patches vLLM's model_loader get_model() at image
# build time instead. The recipe therefore carries no [mods] block.
#
# The mod keeps InstantTensor for the primary model while letting the embedded
# dspark/MTP draft use lazy safetensors (avoids a second InstantTensor
# GPU-streaming pass over the checkpoint). It activates only when
# --load-format instanttensor is set (which this recipe does).
#
# Model: deepseek-ai/DeepSeek-V4-Flash-0731 — official release; native
# dspark_block_size = 5, so num_speculative_tokens = 5.
#
# Differences vs recipes/deepseek-v4-flash (aidendle94 production-3.75 image):
#   - attention backend B12X_MLA_SPARSE (eugr) vs FLASHINFER_MLA_SPARSE_DSV4
#   - --linear-backend b12x + --load-format instanttensor (the mod's trigger)
#   - --reasoning-config pinned to deepseek_v4 parser w/ empty start/end strs
#   - draft_sample_method probabilistic + draft attention_backend B12X_MLA_SPARSE
#   - max_num_seqs=8 / batched=8192 / cudagraph=64 (eugr defaults)
#   - VLLM_USE_MEGA_AOT_ARTIFACT="-1" (eugr) vs "0"
#
# 3× Sparks (TP=3): bump tensor_parallel_size + required_nodes to 3 (the eugr
# image supports it per comment #28). k=5 is unchanged (model-native).

engine = "vllm"
name = "DeepSeek V4 Flash DSpark (eugr b12x)"
docker_image = "eugr/spark-vllm-b12x:sm121"
model = "deepseek-ai/DeepSeek-V4-Flash-0731"
required_nodes = 2
tensor_parallel_size = 2
pipeline_parallel_size = 1
distributed_backend = "mp"
shm_size = "32gb"
docker_image_dir = "deepseek-v4-flash-eugr"

entrypoint = ["vllm", "serve"]

args = [
    "--kv-cache-dtype", "fp8",
    "--block-size", "256",
    "--load-format", "instanttensor",
    "--max-model-len", "auto",
    "--max-num-seqs", "8",
    "--max-num-batched-tokens", "8192",
    "--max-cudagraph-capture-size", "64",
    # 0.78, not higher: the SvangenStudios agent-serving benchmark (v0.1.1) on
    # this exact stack found "0.80 boots but dies under traffic". GMU is a KV
    # lever, not a safety lever, when weights dominate memory (~77.7 GiB of
    # ~119.6 GiB node). For interactive agent traffic prefer the
    # deepseek-v4-flash-eugr-agent profile (2048 chunk). See
    # specs/tech-architecture/dgx-spark-agent-serving-findings.md.
    "--gpu-memory-utilization", "0.78",
    "--served-model-name", "deepseek-v4-flash",
    # Engine backends — b12x across attention / MoE / linear
    "--attention-backend", "B12X_MLA_SPARSE",
    "--moe-backend", "b12x",
    "--linear-backend", "b12x",
    # Prefix caching
    "--enable-prefix-caching",
    # Compilation
    "--compilation-config", """
'{"cudagraph_mode":"FULL_AND_PIECEWISE","custom_ops":["all"]}'""",
    # DSpark speculative decoding — k=5 (DeepSeek-V4-Flash native
    # dspark_block_size). draft_sample_method per eugr recipe; draft attention
    # backend B12X_MLA_SPARSE. The baked mod makes the embedded draft load via
    # lazy safetensors while the target stays on InstantTensor.
    "--speculative-config", """
'{"method":"dspark","num_speculative_tokens":5,"draft_sample_method":"probabilistic","attention_backend":"B12X_MLA_SPARSE"}'""",
    # Tokenizer / reasoning — reasoning-config pins the parser + empty
    # reasoning markers (deepseek_v4 tokenizer mode emits them itself).
    "--tokenizer-mode", "deepseek_v4",
    "--tool-call-parser", "deepseek_v4",
    "--reasoning-parser", "deepseek_v4",
    "--reasoning-config", """
'{"reasoning_parser":"deepseek_v4","reasoning_start_str":"","reasoning_end_str":""}'""",
    "--enable-auto-tool-choice",
    "--generation-config", "vllm",
    "--default-chat-template-kwargs.thinking=true",
    "--default-chat-template-kwargs.reasoning_effort=high",
    "--disable-custom-all-reduce",
    "--trust-remote-code",
]

# Persistent vLLM compile cache (speeds up restarts). Mounted at vLLM's
# default cache root for root (/root/.cache/vllm); the HF cache is already
# mounted at /root/.cache/huggingface by the launcher.
[[extra_mounts]]
host = "~/.cache/vllm-ds4-eugr"
container = "/root/.cache/vllm"

[env]
# --- b12x + compile (from eugr's recipe env, verbatim) ---
CUTE_DSL_ARCH = "sm_121a"
VLLM_USE_AOT_COMPILE = "1"
VLLM_USE_BREAKABLE_CUDAGRAPH = "0"
VLLM_USE_MEGA_AOT_ARTIFACT = "-1"
VLLM_MEMORY_PROFILE_INCLUDE_ATTN = "1"
VLLM_USE_FLASHINFER_SAMPLER = "1"
VLLM_USE_B12X_WO_PROJECTION = "1"
VLLM_USE_B12X_MHC = "1"
VLLM_USE_B12X_FP8_GEMM = "1"
VLLM_USE_B12X_MOE = "1"
VLLM_USE_B12X_SPARSE_INDEXER = "1"
VLLM_USE_V2_MODEL_RUNNER = "1"
B12X_MLA_SM120_UNIFIED = "1"
B12X_MOE_FORCE_A8 = "1"

# --- arch / memory / GPU isolation (operational on the sm121 cluster) ---
TORCH_CUDA_ARCH_LIST = "12.1a"
PYTORCH_CUDA_ALLOC_CONF = "expandable_segments:True"
OMP_NUM_THREADS = "4"
CUDA_VISIBLE_DEVICES = "0"
CUDA_DEVICE_ORDER = "PCI_BUS_ID"
CUDA_CACHE_MAXSIZE = "4294967296"

# --- offline ---
HF_HUB_OFFLINE = "1"

# --- NCCL overrides (GB10 single-NIC tuning; image-agnostic — mirrors
#     recipes/deepseek-v4-flash. The launcher still injects IB/HCA/socket
#     vars from the cluster config; these are recipe-level extras.) ---
NCCL_P2P_LEVEL = "SYS"
NCCL_CUMEM_ENABLE = "0"
NCCL_IB_TIMEOUT = "24"
NCCL_IB_QPS_PER_CONNECTION = "8"
NCCL_BUFFERSIZE = "16777216"
NCCL_SOCKET_FAMILY = "inet"

# PCIe allreduce not needed on GB10 single-NIC
VLLM_ENABLE_PCIE_ALLREDUCE = "0"
VLLM_PCIE_ALLREDUCE_BACKEND = "cpp"