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Example Apps

AVS delivers an Approximate Nearest Neighbor (ANN) search using the Hierarchical Navigable Small World (HNSW) algorithm. AVS provides a new set of capabilities and APIs for performing vector operations. The following example apps are available:

  • Basic search: A simple Python application that demonstrates vector ANN index creation, vector record insertion, and basic ANN query against an AVS server using the Python client.

  • Prism image search: Provides semantic search for a set of images by indexing them using the CLIP model created by OpenAI. This model generates vectors with semantic meaning from each image and stores it as a vector embedding in Aerospike. When a user performs a query, a vector embedding for the provided text is generated and AVS performs ANN search to find relevant results.

  • Quote semantic search: Provides semantic search for an included dataset of quotes by indexing them using the MiniLM model. This model generates vectors with semantic meaning from each quote and stores it as a vector embedding in Aerospike. When a user performs a query a vector embedding for the provided text is generated and AVS performs ANN search to find relevant results.