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docker/Dockerfile.vllm

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+# MiroThinker-v1.0-30B-FP8 with vLLM
+# Recommended: TP=2 with 2x 24GB+ GPUs
+#
+# Build:
+#   docker build -f Dockerfile.vllm -t mirothinker-fp8 .
+#
+# Run (TP=2, recommended):
+#   docker run --gpus all -p 8000:8000 mirothinker-fp8
+#
+# Run (single GPU, not recommended):
+#   docker run --gpus '"device=0"' -p 8000:8000 -e SINGLE_GPU=1 mirothinker-fp8
+
+FROM vllm/vllm-openai:v0.11.2
+
+# Download model from HuggingFace on first run
+ENV MODEL_ID="Doradus/MiroThinker-v1.0-30B-FP8"
+ENV HOST="0.0.0.0"
+ENV PORT="8000"
+
+# Default: TP=2 for 2x GPUs (recommended)
+ENV TENSOR_PARALLEL_SIZE="2"
+ENV MAX_MODEL_LEN="32768"
+ENV GPU_MEMORY_UTILIZATION="0.90"
+
+# For single GPU fallback (set SINGLE_GPU=1)
+ENV SINGLE_GPU=""
+
+EXPOSE 8000
+
+CMD if [ -n "$SINGLE_GPU" ]; then \
+      echo "WARNING: Single GPU mode - limited context and throughput" && \
+      python -m vllm.entrypoints.openai.api_server \
+        --model $MODEL_ID \
+        --host $HOST \
+        --port $PORT \
+        --tensor-parallel-size 1 \
+        --max-model-len 2048 \
+        --max-num-seqs 4 \
+        --gpu-memory-utilization 0.95 \
+        --enforce-eager \
+        --trust-remote-code; \
+    else \
+      python -m vllm.entrypoints.openai.api_server \
+        --model $MODEL_ID \
+        --host $HOST \
+        --port $PORT \
+        --tensor-parallel-size $TENSOR_PARALLEL_SIZE \
+        --max-model-len $MAX_MODEL_LEN \
+        --gpu-memory-utilization $GPU_MEMORY_UTILIZATION \
+        --trust-remote-code \
+        --enable-chunked-prefill; \
+    fi