Tutorials
These tutorials demonstrate different ways you can build vector search into your applications.
| Tutorial | Description | Stack |
|---|---|---|
| Configure Optimal Use | Configure Qdrant collections for best resource use. | Qdrant |
| Separate Partitions | Serve vectors for many independent users. | Qdrant |
| Bulk Upload Vectors | Upload a large scale dataset. | Qdrant |
| Create Dataset Snapshots | Turn a dataset into a snapshot by exporting it from a collection. | Qdrant |
| Semantic Search for Beginners | Create a simple search engine locally in minutes. | Qdrant |
| Simple Neural Search | Build and deploy a neural search that browses startup data. | Qdrant, BERT, FastAPI |
| Aleph Alpha Search | Build a multimodal search that combines text and image data. | Qdrant, Aleph Alpha |
| Mighty Semantic Search | Build a simple semantic search with an on-demand NLP service. | Qdrant, Mighty |
| Asynchronous API | Communicate with Qdrant server asynchronously with Python SDK. | Qdrant, Python |
| Troubleshooting | Solutions to common errors and fixes | Qdrant |