Tutorials

These tutorials demonstrate different ways you can build vector search into your applications.

Essential How-Tos	Description	Stack
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
Neural Search with FastEmbed	Build and deploy a neural search with our FastEmbed library.	Qdrant
Bulk Upload Vectors	Upload a large scale dataset.	Qdrant
Asynchronous API	Communicate with Qdrant server asynchronously with Python SDK.	Qdrant, Python
Create Dataset Snapshots	Turn a dataset into a snapshot by exporting it from a collection.	Qdrant
Load HuggingFace Dataset	Load a Hugging Face dataset to Qdrant	Qdrant, Python, datasets
Measure retrieval quality	Measure and fine-tune the retrieval quality	Qdrant, Python, datasets
Use semantic search to navigate your codebase	Implement semantic search application for code search task	Qdrant, Python, sentence-transformers, Jina