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serverAppConfigs/validate-vllm.sh
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#!/usr/bin/env bash
# End-to-end validation test for vLLM Qwen3.6-35B-A3B-FP8 on dankserver
# Measures prompt processing speed (tokens/second)
set -euo pipefail
HOST="${1:-127.0.0.1}"
PORT="${2:-8001}"
echo "=== Validating vLLM on ${HOST}:${PORT} ==="
# Test health endpoint
echo "Health check..."
if ! curl -sf "http://${HOST}:${PORT}/health" > /dev/null 2>&1; then
echo "FAIL: Health check failed"
exit 1
fi
# Test chat completions with timing
echo "Running prompt test..."
START=$(date +%s%N)
RESPONSE=$(curl -s -X POST "http://${HOST}:${PORT}/v1/chat/completions" \
-H "Content-Type: application/json" \
-d '{
"model": "Qwen/Qwen3.6-35B-A3B-FP8",
"messages": [
{"role": "user", "content": "Explain the difference between supervised, unsupervised, and reinforcement learning in machine learning. For each type, provide a concrete real-world example, describe the training process, and discuss the advantages and limitations. Then compare them across three dimensions: data requirements, interpretability of results, and computational cost. Finally, describe a hybrid scenario where combining two of these approaches would outperform using either alone."}
],
"max_tokens": 256
}')
END=$(date +%s%N)
ELAPSED_MS=$(( (END - START) / 1000000 ))
# Extract metrics from response
PROMPT_TOKENS=$(echo "$RESPONSE" | python3 -c "import sys,json; print(json.load(sys.stdin)['usage']['prompt_tokens'])")
COMPLETION_TOKENS=$(echo "$RESPONSE" | python3 -c "import sys,json; print(json.load(sys.stdin)['usage']['completion_tokens'])")
CONTENT=$(echo "$RESPONSE" | python3 -c "import sys,json; print(json.load(sys.stdin)['choices'][0]['message']['content'][:100])")
# Calculate speed
if [ "$ELAPSED_MS" -gt 0 ]; then
PROMPT_SPEED=$(python3 -c "print(f'{${PROMPT_TOKENS}/${ELAPSED_MS}*1000:.2f}')")
COMPLETION_SPEED=$(python3 -c "print(f'{${COMPLETION_TOKENS}/${ELAPSED_MS}*1000:.2f}')")
else
PROMPT_SPEED="N/A"
COMPLETION_SPEED="N/A"
fi
echo ""
echo "=== Results ==="
echo "Prompt tokens: ${PROMPT_TOKENS}"
echo "Completion tokens: ${COMPLETION_TOKENS}"
echo "Total time: ${ELAPSED_MS}ms"
echo "Prompt speed: ${PROMPT_SPEED} tok/s"
echo "Completion speed: ${COMPLETION_SPEED} tok/s"
echo "Sample output: ${CONTENT}..."
echo ""
# Fail if prompt speed < 5 tok/s
if [ "$ELAPSED_MS" -gt 0 ] && [ "$PROMPT_TOKENS" -gt 0 ]; then
TOO_SLOW=$(python3 -c "print('yes' if ${PROMPT_TOKENS}/${ELAPSED_MS}*1000 < 5 else 'no')")
if [ "$TOO_SLOW" = "yes" ]; then
echo "FAIL: Prompt speed ${PROMPT_SPEED} tok/s is below 5 tok/s threshold"
exit 1
fi
fi
echo "PASS: Validation successful"
echo "$PROMPT_SPEED" > /tmp/vllm_prompt_speed.txt