dgx-spark-playbooks/nvidia/txt2kg/assets/deploy/app/qdrant-init.sh
Santosh Bhavani de9c46e97e Replace Pinecone with Qdrant for ARM64 compatibility
- Migrate from Pinecone to Qdrant vector database for native ARM64 support
- Add Qdrant service with automatic collection initialization in docker-compose
- Implement QdrantService with UUID-based point IDs to meet Qdrant requirements
- Update all API routes and frontend components to use Qdrant
- Enhance Storage Connections UI with detailed stats (vectors, status, dimensions)
- Add icons and tooltips to Vector DB section matching Graph DB UX
2025-10-24 23:16:44 -07:00

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#!/bin/sh
# Script to initialize Qdrant collection at container startup
echo "Initializing Qdrant collection..."
# Wait for the Qdrant service to become available
echo "Waiting for Qdrant service to start..."
max_attempts=30
attempt=1
while [ $attempt -le $max_attempts ]; do
if curl -s http://qdrant:6333/healthz > /dev/null; then
echo "Qdrant service is up!"
break
fi
echo "Waiting for Qdrant service (attempt $attempt/$max_attempts)..."
attempt=$((attempt + 1))
sleep 2
done
if [ $attempt -gt $max_attempts ]; then
echo "Timed out waiting for Qdrant service"
exit 1
fi
# Check if collection already exists
echo "Checking if collection 'entity-embeddings' exists..."
COLLECTION_EXISTS=$(curl -s http://qdrant:6333/collections/entity-embeddings | grep -c '"status":"ok"' || echo "0")
if [ "$COLLECTION_EXISTS" -gt "0" ]; then
echo "Collection 'entity-embeddings' already exists, skipping creation"
else
# Create the collection
echo "Creating collection 'entity-embeddings'..."
curl -X PUT "http://qdrant:6333/collections/entity-embeddings" \
-H "Content-Type: application/json" \
-d '{
"vectors": {
"size": 384,
"distance": "Cosine"
}
}'
if [ $? -eq 0 ]; then
echo "✅ Collection 'entity-embeddings' created successfully"
else
echo "❌ Failed to create collection"
exit 1
fi
fi
echo "Qdrant initialization complete"