consciousness/scripts/provision-vllm.sh
Kent Overstreet f83325b44d Fix poc-agent for vllm/Qwen 3.5: reasoning display, tool parser
- Always display reasoning tokens regardless of reasoning_effort
  setting — Qwen 3.5 thinks natively and the reasoning parser
  separates it into its own field
- Remove chat_template_kwargs that disabled thinking when
  reasoning_effort was "none"
- Add chat_template_kwargs field to ChatRequest for vllm compat
- Update provision script: qwen3_xml tool parser, qwen3 reasoning
  parser, 262K context, 95% GPU memory utilization

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-19 00:06:26 -04:00

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#!/bin/bash
# provision-vllm.sh — Set up vllm on a RunPod GPU instance
#
# Usage: ssh into your RunPod instance and run:
# curl -sSL https://raw.githubusercontent.com/... | bash
# Or just scp this script and run it.
#
# Expects: NVIDIA GPU with sufficient VRAM (B200: 192GB, A100: 80GB)
# Installs: vllm with Qwen 3.5 27B
# Exposes: OpenAI-compatible API on port 8000
set -euo pipefail
MODEL="${MODEL:-Qwen/Qwen3.5-27B}"
PORT="${PORT:-8000}"
MAX_MODEL_LEN="${MAX_MODEL_LEN:-262144}"
GPU_MEMORY_UTILIZATION="${GPU_MEMORY_UTILIZATION:-0.95}"
echo "=== vllm provisioning ==="
echo "Model: $MODEL"
echo "Port: $PORT"
echo "Max context: $MAX_MODEL_LEN"
echo ""
# --- Install vllm ---
echo "Installing vllm..."
pip install --upgrade vllm --break-system-packages 2>&1 | tail -3
# --- Use persistent storage ---
export HF_HOME=/workspace/huggingface
# --- Verify GPU ---
echo ""
echo "GPU status:"
nvidia-smi --query-gpu=name,memory.total,memory.free --format=csv,noheader
echo ""
# --- Download model (cached in /root/.cache/huggingface) ---
echo "Downloading model (this may take a while on first run)..."
pip install --upgrade huggingface_hub --break-system-packages -q 2>/dev/null
python3 -c "from huggingface_hub import snapshot_download; snapshot_download('$MODEL')" 2>&1 | tail -5
echo ""
# --- Launch vllm ---
echo "Starting vllm server on port $PORT..."
echo "API will be available at http://0.0.0.0:$PORT/v1"
echo ""
exec vllm serve "$MODEL" \
--port "$PORT" \
--max-model-len "$MAX_MODEL_LEN" \
--gpu-memory-utilization "$GPU_MEMORY_UTILIZATION" \
--enable-prefix-caching \
--tool-call-parser qwen3_xml \
--enable-auto-tool-choice \
--reasoning-parser=qwen3 \
--uvicorn-log-level warning