docs: add DeepSeekV4 cookbook.

astro.config.mjs

@@ -152,6 +152,11 @@ export default defineConfig({
 									translations: { 'zh-CN': 'DeepSeek' },
 									collapsed: true,
 									items: [
+										{
+											label: 'DeepSeek-V4',
+											translations: { 'zh-CN': 'DeepSeek-V4' },
+											slug: 'cookbook/autoregressive_models/deepseek/deepseek_v4',
+										},
 										{
 											label: 'DeepSeek-V3.2',
 											translations: { 'zh-CN': 'DeepSeek-V3.2' },

src/content/docs/en/cookbook/autoregressive_models.md

@@ -10,7 +10,7 @@ Content will be added as the recipes are organized.
 ## Model Families
 
 - [Qwen](/en/cookbook/autoregressive_models/qwen/qwen3_5/)
-- [DeepSeek](/en/cookbook/autoregressive_models/deepseek/deepseek_v3_2/)
+- [DeepSeek](/en/cookbook/autoregressive_models/deepseek/deepseek_v4/)
 - [GLM](/en/cookbook/autoregressive_models/glm/glm_5/)
 - [Kimi](/en/cookbook/autoregressive_models/kimi/kimi2/)
 - [MinMax](/en/cookbook/autoregressive_models/minmax/minmax_m2_7/)

src/content/docs/en/cookbook/autoregressive_models/deepseek/deepseek_v4.md

@@ -0,0 +1,269 @@
+---
+title: "DeepSeek-V4"
+description: "DeepSeek-V4 inference guide with xLLM on Ascend A3 devices"
+---
+
+# Inference with xLLM on Ascend A3 Devices
+
+Source code: https://github.com/jd-opensource/xllm
+
+China mirror: https://gitcode.com/xLLM-AI/xllm
+
+Weight Download
+Flash weights:
+https://modelers.cn/models/Eco-Tech/DeepSeek-V4-Flash-w8a8-mtp
+
+Pro weights:
+https://modelers.cn/models/Eco-Tech/DeepSeek-V4-Pro-w4a8-mtp
+
+
+## 1. Pull the Docker Image
+
+First, pull the xLLM-provided image:
+
+```bash
+# A2 x86
+docker pull quay.io/jd_xllm/xllm-ai:xllm-dev-a2-x86-cann9-20260605
+# A2 arm
+docker pull quay.io/jd_xllm/xllm-ai:xllm-dev-a2-arm-cann9-20260605
+# A3 arm
+docker pull quay.io/jd_xllm/xllm-ai:xllm-dev-a3-arm-cann9-20260605
+```
+
+Then create the container:
+
+```bash
+sudo docker run -it --ipc=host -u 0 --privileged --name mydocker --network=host \
+ -v /var/queue_schedule:/var/queue_schedule \
+ -v /usr/local/Ascend/driver:/usr/local/Ascend/driver \
+ -v /usr/local/Ascend/add-ons/:/usr/local/Ascend/add-ons/ \
+ -v /usr/local/sbin/npu-smi:/usr/local/sbin/npu-smi \
+ -v /var/log/npu/conf/slog/slog.conf:/var/log/npu/conf/slog/slog.conf \
+ -v /var/log/npu/slog/:/var/log/npu/slog \
+ -v ~/.ssh:/root/.ssh  \
+ -v /var/log/npu/profiling/:/var/log/npu/profiling \
+ -v /var/log/npu/dump/:/var/log/npu/dump \
+ -v /runtime/:/runtime/ -v /etc/hccn.conf:/etc/hccn.conf \
+ -v /export/home:/export/home \
+ -v /home/:/home/  \
+ -w /export/home \
+ quay.io/jd_xllm/xllm-ai:xllm-dev-a3-arm-cann9-20260605
+```
+
+## 2. Clone Source Code and Build
+
+Clone the official repository and module dependencies:
+
+```bash
+git clone https://github.com/jd-opensource/xllm
+cd xllm 
+git submodule update --init --recursive
+```
+
+Install dependencies:
+
+```bash
+pip install --upgrade pre-commit
+```
+
+Build the project; the executable `build/xllm/core/server/xllm` will be generated under `build/`:
+
+```bash
+python setup.py build --device npu
+```
+
+## 3. Launch the Model
+
+### If restarting after a machine reboot, initialize the device first
+
+> If not executed and the NPU is not initialized, the xllm process may fail to start
+
+```bash
+python -c "import torch_npu
+for i in range(16):torch_npu.npu.set_device(i)"
+```
+
+### Export MTP weights
+
+```bash
+python tools/export_mtp.py --input-dir ${W4A8/W8A8 weights directory} --output-dir ${Exported MTP weights directory}
+```
+
+### Environment variables
+
+```bash
+##### 1. Configure dependency path environment variables
+
+source /usr/local/Ascend/ascend-toolkit/set_env.sh
+source /usr/local/Ascend/nnal/atb/set_env.sh
+source ${ASCEND_TOOLKIT_HOME}/opp/vendors/custom_xllm_math/bin/set_env.bash
+
+##### 2. Configure logging environment variables
+rm -rf /root/ascend/log/
+rm -rf core.*
+
+##### 3. Configure performance and communication environment variables
+export HCCL_IF_BASE_PORT=43432
+export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
+export NPU_MEMORY_FRACTION=0.96
+export ATB_WORKSPACE_MEM_ALLOC_ALG_TYPE=3
+export ATB_WORKSPACE_MEM_ALLOC_GLOBAL=1
+export ATB_LAYER_INTERNAL_TENSOR_REUSE=1
+export ATB_CONTEXT_WORKSPACE_SIZE=0
+export OMP_NUM_THREADS=12
+export ALLOW_INTERNAL_FORMAT=1
+
+```
+
+## Launch Command - Single-Node Example
+
+```bash
+BATCH_SIZE=256
+# Maximum batch size for inference
+XLLM_PATH="./myxllm/xllm/build/xllm/core/server/xllm"
+# Path to the inference entry file (build artifact from the previous step)
+MODEL_PATH=/path/to/dsv4
+# Model path
+DRAFT_MODEL_PATH=/path/to/dsv4_mtp
+# Exported MTP weights path
+
+MASTER_NODE_ADDR="11.87.49.110:10015"
+LOCAL_HOST="11.87.49.110"
+# Service Port
+START_PORT=18994
+START_DEVICE=0
+LOG_DIR="logs"
+NNODES=8
+
+for (( i=0; i<$NNODES; i++ ))
+do
+  PORT=$((START_PORT + i))
+  DEVICE=$((START_DEVICE + i))
+  LOG_FILE="$LOG_DIR/node_$i.log"
+  nohup $XLLM_PATH -model-id ds \
+    --model $MODEL_PATH \
+    --host $LOCAL_HOST \
+    --port $PORT \
+    --devices="npu:$DEVICE" \
+    --master_node_addr=$MASTER_NODE_ADDR \
+    --nnodes=$NNODES \
+    --node_rank=$i \
+    --max_memory_utilization=0.9 \
+    --max_tokens_per_batch=2048 \
+    --max_seqs_per_batch=32 \
+    --block_size=128 \
+    --communication_backend="hccl" \
+    --tool_call_parser=deepseekv4 \
+    --enable_prefix_cache=false \
+    --enable_chunked_prefill=true \
+    --enable_schedule_overlap=true \
+    --enable_graph=true \
+    --npu_kernel_backend=TORCH \
+    --ep_size=8 \
+    --dp_size=2 \
+    > $LOG_FILE 2>&1 &
+done
+
+    # Variables required when MTP is enabled
+    # --draft_model=$DRAFT_MODEL_PATH \
+    # --draft_devices="npu:$DEVICE" \
+    # --num_speculative_tokens=1 \
+
+# numactl -C xxxxx          NUMA core binding (query with: npu-smi info -t topo)
+#--max_memory_utilization   Max memory usage ratio per NPU card
+#--max_tokens_per_batch     Max tokens per batch (mainly limits prefill)
+#--max_seqs_per_batch       Max sequences per batch (mainly limits decode)
+#--communication_backend    Communication backend (hccl / lccl, hccl recommended here)
+#--enable_schedule_overlap  Enable async scheduling
+#--enable_prefix_cache      Enable prefix cache
+#--enable_chunked_prefill   Enable chunked prefill
+#--enable_graph             Enable aclgraph
+#--draft_model              MTP - MTP weights path
+#--draft_devices            MTP - MTP inference device (same as main model)
+#--num_speculative_tokens   MTP - Number of speculative tokens
+```
+
+A log message "Brpc Server Started" indicates the service has started successfully.
+
+## Other Optional Environment Variables
+
+```bash
+#Enable deterministic computation
+export LCCL_DETERMINISTIC=1
+export HCCL_DETERMINISTIC=true
+export ATB_MATMUL_SHUFFLE_K_ENABLE=0
+
+# #Enable dynamic profiling mode
+# export PROFILING_MODE=dynamic
+# \rm -rf ~/dynamic_profiling_socket_*
+```
+
+## Launch Command - Dual-Node Example
+
+### Node0 (master)
+
+```bash
+MASTER_NODE_ADDR="11.87.49.110:19990"
+LOCAL_HOST="11.87.49.110"
+START_PORT=15890
+START_DEVICE=0
+LOG_DIR="logs"
+NNODES=32
+LOCAL_NODES=16
+export HCCL_IF_BASE_PORT=48439
+unset HCCL_OP_EXPANSION_MODE
+
+for (( i=0; i<$LOCAL_NODES; i++ )); do
+  PORT=$((START_PORT + i))
+  DEVICE=$((START_DEVICE + i)); LOG_FILE="$LOG_DIR/node_$i.log"
+  nohup $XLLM_PATH \
+    --model $MODEL_PATH \
+    --host $LOCAL_HOST \
+    --port $PORT \
+    --devices="npu:$DEVICE" \
+    --master_node_addr=$MASTER_NODE_ADDR \
+    --nnodes=$NNODES \
+    --node_rank=$i \
+    ......
+    --rank_tablefile=/yourPath/ranktable.json \
+    > $LOG_FILE 2>&1 &
+done
+```
+
+#### Node1 (worker)
+
+```bash
+MASTER_NODE_ADDR="11.87.49.110:19990"
+LOCAL_HOST="11.87.49.111"
+START_PORT=15890
+START_DEVICE=0
+LOG_DIR="logs"
+NNODES=32
+LOCAL_NODES=16
+export HCCL_IF_BASE_PORT=48439
+unset HCCL_OP_EXPANSION_MODE
+
+for (( i=0; i<$LOCAL_NODES; i++ )); do
+  PORT=$((START_PORT + i))
+  DEVICE=$((START_DEVICE + i)); LOG_FILE="$LOG_DIR/node_$i.log"
+  nohup  $XLLM_PATH \
+    --model $MODEL_PATH \
+    --host $LOCAL_HOST \
+    --port $PORT \
+    --devices="npu:$DEVICE" \
+    --master_node_addr=$MASTER_NODE_ADDR \
+    --nnodes=$NNODES \
+    --node_rank=$((i + LOCAL_NODES)) \
+    ......
+    --rank_tablefile=/yourPath/ranktable.json \
+    > $LOG_FILE 2>&1 &
+done
+```
+
+### ranktable reference
+
+ [A3 ranktable configuration](https://www.hiascend.com/document/detail/zh/canncommercial/900/API/hcclug/hcclug_000066.html)
+
+ [A2 ranktable configuration](https://www.hiascend.com/document/detail/zh/canncommercial/900/API/hcclug/hcclug_000067.html)
+
+ (Note the ranktable format differences between A3 and A2)

src/content/docs/zh/cookbook/autoregressive_models.md

@@ -10,7 +10,7 @@ description: "xLLM 自回归模型推理实践"
 ## 模型系列
 
 - [Qwen](/zh/cookbook/autoregressive_models/qwen/qwen3_5/)
-- [DeepSeek](/zh/cookbook/autoregressive_models/deepseek/deepseek_v3_2/)
+- [DeepSeek](/zh/cookbook/autoregressive_models/deepseek/deepseek_v4/)
 - [GLM](/zh/cookbook/autoregressive_models/glm/glm_5/)
 - [Kimi](/zh/cookbook/autoregressive_models/kimi/kimi2/)
 - [MinMax](/zh/cookbook/autoregressive_models/minmax/minmax_m2_7/)