These examples demonstrate how you might build vector search into your
applications with Pinecone. You can view their source code to jumpstart your
Our Learn section explains the basics of vector search and vector databases.
How to create a simple semantic text search using Pinecone's similarity search service.Basic hybrid search
How to pair semantic search with a basic keyword filter.Generative question answering (OpenAI)
How to build retrieval enhanced generative QA systems with OpenAI.Extractive question answering
How to build an extractive QA application with similarity search.Abstractive question answering
How to build an abstractive (generative) QA application with similarity search.Tabular question answering
How to build a question-answering application for extracting answers from tables with similarity search.NER search
How to automatically extract entities from text and use them to improve search results.Video transcription search
How to create an app that searches video transcription data.GIF description search
How to create a GIF search app.
How to build advanced image search applications.Facial similarity search
Find your celebrity doppelganger with facial similarity search.Audio similarity search
How to build advanced audio search applications.
How to use Pinecone to create a simple personalized article or content recommender.Movie recommender
How to create a movie recommendation system with the MovieLens dataset.
How to create a simple application for identifying duplicate documents.IT threat detection
How to build an application for detecting rare events in IT threat detection.Extreme classification
How to label new texts automatically when there is an enormous number of potential labels.Time series similarity search
How to perform time-series "pattern" matching using a similarity search service.
Updated 10 days ago