code/fine_tune_sft_dpo/evaluation_model_en.sh

#!/bin/bash

export CUDA_DEVICE_ORDER=PCI_BUS_ID
export CUDA_VISIBLE_DEVICES=5

# Start NVIDIA MPS for efficient GPU sharing
nvidia-cuda-mps-control -d
echo "✅ MPS started on GPU 2"

# ──────────────────────────────────────────────
# Service 1: vLLM — Llama-3.1-8B-Instruct
# ──────────────────────────────────────────────
vllm serve meta-llama/Llama-3.1-8B-Instruct \
    --port 8031 \
    --served-model-name dspy \
    --dtype bfloat16 \
    --tensor-parallel-size 1 \
    --max-model-len 16384 \
    --gpu-memory-utilization 0.40 \
    --enable-prefix-caching \
    --max-num-seqs 256 &

VLLM_PID=$!
echo "⏳ Loading vLLM (Llama-3.1-8B)... PID: $VLLM_PID"
sleep 40  # wait for vLLM to fully load

# ──────────────────────────────────────────────
# Service 2: FastAPI — HHEM Support Claim API
# ──────────────────────────────────────────────
export SUPPORT_API_PORT=8030
export SUPPORT_API_HOST=0.0.0.0
export HHEM_MODEL_NAME=vectara/hallucination_evaluation_model

SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"

echo "⏳ Starting Support Claim Checking API..."
cd "$SCRIPT_DIR"
python support_claim_api.py &

HHEM_PID=$!
echo "✅ HHEM API started... PID: $HHEM_PID"

# ──────────────────────────────────────────────
echo ""
echo "========================================="
echo "  Both services running on GPU 2"
echo "  vLLM (dspy):       http://0.0.0.0:8031"
echo "  HHEM (support):    http://0.0.0.0:8030"
echo "========================================="
echo ""

# Wait for both processes
wait $VLLM_PID $HHEM_PID