#!/usr/bin/env bash
# Pull additional AI models into Ollama
# Run after install: bash models/pull-models.sh --tier=starter
# ─────────────────────────────────────────────
TIER="basic"   # default tier

for arg in "$@"; do
  case $arg in
    --tier=*) TIER="${arg#*=}" ;;
    *)        TIER="$arg" ;;     # allow positional: pull-models.sh pro
  esac
done

# Normalise legacy names
case "$TIER" in
  entry)    TIER="basic" ;;
  mid)      TIER="pro" ;;
  advanced) TIER="max" ;;
esac

# ── Model lists ───────────────────────────────
starter_models=(
  "phi3:mini"              # 3.8B — fits in 32 GB GDDR7 at full precision
  "nomic-embed-text"       # Embedding model for RAG
)

basic_models=(
  "llama3.1:8b"            # General purpose, good baseline
  "mistral:7b"             # Fast, good for APIs
  "nomic-embed-text"       # Embedding model for RAG
  "codellama:13b"          # Code generation
)

pro_models=(
  "${basic_models[@]}"
  "llama3.1:70b"           # Large general purpose (needs 64+ GB VRAM at 4-bit)
  "mixtral:8x7b"           # MoE model, strong reasoning
  "deepseek-coder-v2:16b"  # Code specialist
)

max_models=(
  "${pro_models[@]}"
  "llama3.1:405b"          # Flagship — needs 320+ GB VRAM or multi-node
  "mixtral:8x22b"          # Large MoE
)

case $TIER in
  starter) models=("${starter_models[@]}") ;;
  basic)   models=("${basic_models[@]}") ;;
  pro)     models=("${pro_models[@]}") ;;
  max)     models=("${max_models[@]}") ;;
  *)
    echo "Unknown tier: $TIER"
    echo "Usage: bash pull-models.sh --tier=starter|basic|pro|max"
    exit 1
    ;;
esac

echo "Pulling models for tier: $TIER"
echo ""

for model in "${models[@]}"; do
  echo "→ Pulling $model..."
  ollama pull "$model"
  echo ""
done

echo "✓ Done. List installed models with: ollama list"