docker-entrypoint.sh

#!/bin/bash
set -e

echo '=== STARRY HF Space Entrypoint ==='

# ── Start PostgreSQL ──
echo 'Starting PostgreSQL...'
/usr/lib/postgresql/15/bin/pg_ctl -D $PGDATA -l /home/node/postgresql.log start -o "-p 5432"

for i in $(seq 1 15); do
  if /usr/lib/postgresql/15/bin/pg_isready -h 127.0.0.1 -p 5432 -q 2>/dev/null; then
    echo 'PostgreSQL is ready.'
    break
  fi
  echo "  Waiting for PostgreSQL... attempt $i/15"
  sleep 1
done

# Create database
/usr/lib/postgresql/15/bin/psql -h 127.0.0.1 -p 5432 -d postgres -tc "SELECT 1 FROM pg_database WHERE datname='starry_omr'" | grep -q 1 || \
  /usr/lib/postgresql/15/bin/createdb -h 127.0.0.1 -p 5432 starry_omr

# ── Model path resolution from models.yaml ──
MODELS_BASE="/home/node/app/models"
MODELS_YAML="$MODELS_BASE/starry-dist/models.yaml"
HF_REPO="k-l-lambda/starry"

CURL_PROXY=""
if [ -n "$https_proxy" ]; then
  CURL_PROXY="-x $https_proxy"
fi

# Download models.yaml from HuggingFace if not present locally
if [ ! -f "$MODELS_YAML" ] && [ -n "$HF_TOKEN" ]; then
  echo "Downloading models.yaml from HuggingFace..."
  mkdir -p "$MODELS_BASE/starry-dist"
  curl -sfL $CURL_PROXY \
    -H "Authorization: Bearer $HF_TOKEN" \
    -o "$MODELS_YAML" \
    "https://huggingface.co/${HF_REPO}/resolve/main/starry-dist/models.yaml?download=true" \
    || echo "Warning: Failed to download models.yaml (token may lack access)"
fi

# Parse models.yaml and set env vars (only if not already set)
if [ -f "$MODELS_YAML" ]; then
  echo "Parsing model paths from models.yaml..."

  # Helper: extract a field value under a section
  yaml_get() {
    sed -n "/^${1}:/,/^[a-z]/{ /^  ${2}:/{ s/.*${2}: *//; p; } }" "$MODELS_YAML" | head -1
  }

  # bdtopo (ONNX model for regulation)
  if [ -z "$BDTOPO_MODEL_PATH" ]; then
    _bdtopo_path=$(yaml_get bdtopo path)
    _bdtopo_default=$(yaml_get bdtopo default)
    if [ -n "$_bdtopo_path" ] && [ -n "$_bdtopo_default" ]; then
      export BDTOPO_MODEL_PATH="$MODELS_BASE/starry-dist/$_bdtopo_path/$_bdtopo_default"
      echo "  BDTOPO_MODEL_PATH=$BDTOPO_MODEL_PATH"
    fi
  fi

  # PyTorch predictors (starry-dist)
  if [ -z "$LAYOUT_MODEL_PATH" ]; then
    export LAYOUT_MODEL_PATH=$(yaml_get layout path)
    echo "  LAYOUT_MODEL_PATH=$LAYOUT_MODEL_PATH"
  fi
  if [ -z "$MASK_MODEL_PATH" ]; then
    export MASK_MODEL_PATH=$(yaml_get mask path)
    echo "  MASK_MODEL_PATH=$MASK_MODEL_PATH"
  fi
  if [ -z "$SEMANTIC_MODEL_PATH" ]; then
    export SEMANTIC_MODEL_PATH=$(yaml_get semantic path)
    echo "  SEMANTIC_MODEL_PATH=$SEMANTIC_MODEL_PATH"
  fi
  if [ -z "$GAUGE_MODEL_PATH" ]; then
    export GAUGE_MODEL_PATH=$(yaml_get gauge path)
    echo "  GAUGE_MODEL_PATH=$GAUGE_MODEL_PATH"
  fi

  # OCR predictors (ocr-dist)
  if [ -z "$LOC_MODEL_PATH" ]; then
    export LOC_MODEL_PATH=$(yaml_get loc path)
    echo "  LOC_MODEL_PATH=$LOC_MODEL_PATH"
  fi
  if [ -z "$OCR_CONFIG" ]; then
    export OCR_CONFIG=$(yaml_get ocr config)
    echo "  OCR_CONFIG=$OCR_CONFIG"
  fi
  if [ -z "$BRACKETS_CONFIG" ]; then
    export BRACKETS_CONFIG=$(yaml_get brackets config)
    echo "  BRACKETS_CONFIG=$BRACKETS_CONFIG"
  fi
fi

# ── Download model files from HuggingFace ──
hf_download() {
  local subdir="$1"
  local relpath="$2"
  local dest="$MODELS_BASE/$subdir/$relpath"

  if [ -z "$relpath" ]; then return; fi
  if [ -e "$dest" ]; then
    echo "  $subdir/$relpath already present, skipping."
    return
  fi

  echo "  Downloading $subdir/$relpath ..."
  mkdir -p "$(dirname "$dest")"
  if curl -sfL $CURL_PROXY \
    -H "Authorization: Bearer $HF_TOKEN" \
    -o "$dest" \
    "https://huggingface.co/${HF_REPO}/resolve/main/${subdir}/${relpath}?download=true"; then
    echo "  $subdir/$relpath downloaded OK."
  else
    rm -f "$dest"
    # Retry with .pt extension (some .state.yaml best: fields omit the extension)
    if curl -sfL $CURL_PROXY \
      -H "Authorization: Bearer $HF_TOKEN" \
      -o "${dest}.pt" \
      "https://huggingface.co/${HF_REPO}/resolve/main/${subdir}/${relpath}.pt?download=true"; then
      echo "  $subdir/$relpath.pt downloaded OK (extension fallback)."
    else
      rm -f "${dest}.pt"
      echo "  WARNING: Failed to download $subdir/$relpath"
    fi
  fi
}

# ── Set predictor addresses (internal ZMQ) ──
export PREDICTOR_LAYOUT="${PREDICTOR_LAYOUT:-tcp://127.0.0.1:12022}"
export PREDICTOR_GAUGE="${PREDICTOR_GAUGE:-tcp://127.0.0.1:12023}"
export PREDICTOR_GAUGE_RENDERER="${PREDICTOR_GAUGE_RENDERER:-tcp://127.0.0.1:15656}"
export PREDICTOR_MASK="${PREDICTOR_MASK:-tcp://127.0.0.1:12024}"
export PREDICTOR_SEMANTIC="${PREDICTOR_SEMANTIC:-tcp://127.0.0.1:12025}"
export PREDICTOR_LOC="${PREDICTOR_LOC:-tcp://127.0.0.1:12026}"
export PREDICTOR_OCR="${PREDICTOR_OCR:-tcp://127.0.0.1:12027}"
export PREDICTOR_BRACKETS="${PREDICTOR_BRACKETS:-tcp://127.0.0.1:12028}"

# ── Download models & start ML predictors (background) ──
# Runs in background so Node services and nginx can start immediately.
(
  if [ -n "$HF_TOKEN" ] && [ -f "$MODELS_YAML" ]; then
    echo "Downloading model files from HuggingFace (background)..."

    # Download bdtopo ONNX models
    if [ -n "$BDTOPO_MODEL_PATH" ] && [ ! -f "$BDTOPO_MODEL_PATH" ]; then
      _bdtopo_path=$(yaml_get bdtopo path)
      _bdtopo_dir="$MODELS_BASE/starry-dist/$_bdtopo_path"
      mkdir -p "$_bdtopo_dir"

      sed -n '/^  files:/,/^[^ ]/{ /^ *- /p }' "$MODELS_YAML" | sed 's/^ *- *//' | while read -r FILE; do
        hf_download "starry-dist" "$_bdtopo_path/$FILE"
      done
    fi

    # Download PyTorch model directories (starry-dist)
    for model_var in LAYOUT_MODEL_PATH MASK_MODEL_PATH SEMANTIC_MODEL_PATH GAUGE_MODEL_PATH; do
      eval model_path=\$$model_var
      if [ -n "$model_path" ]; then
        hf_download "starry-dist" "$model_path/.state.yaml"

        state_yaml="$MODELS_BASE/starry-dist/$model_path/.state.yaml"
        if [ -f "$state_yaml" ]; then
          # Model weight file is in "best:" field (not "file:")
          model_file=$(sed -n 's/^best: *//p' "$state_yaml" | head -1)
          if [ -n "$model_file" ]; then
            hf_download "starry-dist" "$model_path/$model_file"
          fi
          # Sub-models listed under "subs:" (skip commented lines starting with #)
          sed -n '/^subs:/,/^[a-z]/{ /^[^#]*- /p }' "$state_yaml" | sed 's/^ *- *//' | while read -r sub; do
            if [ -n "$sub" ]; then
              hf_download "starry-dist" "$model_path/$sub/.state.yaml"
              sub_state="$MODELS_BASE/starry-dist/$model_path/$sub/.state.yaml"
              if [ -f "$sub_state" ]; then
                sub_file=$(sed -n 's/^best: *//p' "$sub_state" | head -1)
                if [ -n "$sub_file" ]; then
                  hf_download "starry-dist" "$model_path/$sub/$sub_file"
                fi
              fi
            fi
          done
        fi
      fi
    done

    # Download LOC model (a single file, not a directory)
    if [ -n "$LOC_MODEL_PATH" ]; then
      hf_download "ocr-dist" "$LOC_MODEL_PATH"
    fi

    # Download OCR/TF config yamls and all referenced files
    for config_var in OCR_CONFIG BRACKETS_CONFIG; do
      eval config_path=\$$config_var
      if [ -n "$config_path" ]; then
        hf_download "ocr-dist" "$config_path"
        config_file="$MODELS_BASE/ocr-dist/$config_path"
        if [ -f "$config_file" ]; then
          _dir=$(dirname "$config_path")
          # Download all *_path values referenced in the yaml
          grep '_path:' "$config_file" | sed 's/^[^:]*: *//' | while read -r ref_path; do
            if [ -n "$ref_path" ]; then
              # Resolve ./ relative paths
              ref_path=$(echo "$ref_path" | sed 's|^\./||')
              hf_download "ocr-dist" "${_dir:+$_dir/}$ref_path"
            fi
          done
        fi
      fi
    done

    echo "Model download complete."
  fi

  # Start ML predictors after models are downloaded
  if [ -f /home/node/app/supervisord.conf ] && [ -d /home/node/app/backend/python-services ]; then
    if [ -n "$LAYOUT_MODEL_PATH" ]; then
      echo "Starting Python ML predictors via supervisord..."
      supervisord -c /home/node/app/supervisord.conf
    else
      echo "Skipping ML predictors (no model paths configured)."
    fi
  fi
) &

# ── Run database migrations ──
echo 'Running database migrations...'
cd /home/node/app/backend/omr-service
DB_HOST=127.0.0.1 DB_PORT=5432 DB_NAME=starry_omr DB_USER=node DB_PASSWORD= \
  npx tsx src/db/migrate.ts 2>&1 || echo 'Warning: Migration failed or skipped'

# Seed example score data + pre-computed regulation solutions
if [ -f /home/node/app/seed-data.sql.gz ]; then
  echo 'Loading seed data (example score + regulation solutions)...'
  zcat /home/node/app/seed-data.sql.gz | \
    /usr/lib/postgresql/15/bin/psql -h 127.0.0.1 -p 5432 -U node -d starry_omr 2>&1 | tail -1
fi

# Extract pre-generated upload images (page sources + mask + background)
if [ -f /home/node/app/seed-uploads.tar.gz ]; then
  echo 'Extracting seed upload images...'
  tar xzf /home/node/app/seed-uploads.tar.gz -C /tmp/starry-uploads/
fi

# ── Start cluster-server (port 3999) ──
echo 'Starting cluster-server on port 3999...'
cd /home/node/app/backend/cluster-server
PORT=3999 node dist/src/main.js &

# ── Start omr-service (port 3080) ──
echo 'Starting omr-service on port 3080...'
cd /home/node/app/backend/omr-service
export PORT=3080
export DB_HOST=127.0.0.1
export DB_PORT=5432
export DB_NAME=starry_omr
export DB_USER=node
export DB_PASSWORD=
export REGULATION_ENABLED=${REGULATION_ENABLED:-true}
npx tsx src/index.ts &

# Wait for omr-service to be ready
echo 'Waiting for omr-service...'
for i in $(seq 1 30); do
  if curl -sf http://127.0.0.1:3080/health > /dev/null 2>&1; then
    echo 'omr-service is ready.'
    break
  fi
  sleep 1
done

# ── Start nginx (port 7860, foreground) ──
echo 'Starting nginx on port 7860...'
exec nginx -g 'daemon off;'