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

Essential How-TosDescriptionStack
Semantic Search for BeginnersCreate a simple search engine locally in minutes.Qdrant
Simple Neural SearchBuild and deploy a neural search that browses startup data.Qdrant, BERT, FastAPI
Neural Search with FastEmbedBuild and deploy a neural search with our FastEmbed library.Qdrant
Bulk Upload VectorsUpload a large scale dataset.Qdrant
Asynchronous APICommunicate with Qdrant server asynchronously with Python SDK.Qdrant, Python
Create Dataset SnapshotsTurn a dataset into a snapshot by exporting it from a collection.Qdrant
Load HuggingFace DatasetLoad a Hugging Face dataset to QdrantQdrant, Python, datasets
Measure retrieval qualityMeasure and fine-tune the retrieval qualityQdrant, Python, datasets
Use semantic search to navigate your codebaseImplement semantic search application for code search taskQdrant, Python, sentence-transformers, Jina