mirror of
https://github.com/NVIDIA/dgx-spark-playbooks.git
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de9c46e97e
- 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
53 lines
1.4 KiB
Bash
53 lines
1.4 KiB
Bash
#!/bin/sh
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# Script to initialize Qdrant collection at container startup
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echo "Initializing Qdrant collection..."
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# Wait for the Qdrant service to become available
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echo "Waiting for Qdrant service to start..."
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max_attempts=30
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attempt=1
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while [ $attempt -le $max_attempts ]; do
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if curl -s http://qdrant:6333/healthz > /dev/null; then
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echo "Qdrant service is up!"
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break
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fi
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echo "Waiting for Qdrant service (attempt $attempt/$max_attempts)..."
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attempt=$((attempt + 1))
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sleep 2
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done
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if [ $attempt -gt $max_attempts ]; then
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echo "Timed out waiting for Qdrant service"
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exit 1
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fi
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# Check if collection already exists
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echo "Checking if collection 'entity-embeddings' exists..."
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COLLECTION_EXISTS=$(curl -s http://qdrant:6333/collections/entity-embeddings | grep -c '"status":"ok"' || echo "0")
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if [ "$COLLECTION_EXISTS" -gt "0" ]; then
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echo "Collection 'entity-embeddings' already exists, skipping creation"
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else
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# Create the collection
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echo "Creating collection 'entity-embeddings'..."
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curl -X PUT "http://qdrant:6333/collections/entity-embeddings" \
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-H "Content-Type: application/json" \
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-d '{
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"vectors": {
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"size": 384,
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"distance": "Cosine"
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}
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}'
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if [ $? -eq 0 ]; then
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echo "✅ Collection 'entity-embeddings' created successfully"
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else
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echo "❌ Failed to create collection"
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exit 1
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fi
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fi
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echo "Qdrant initialization complete"
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