Nov 24, 2024 · Create embeddings for your data using an OpenAI embedding model. Store and index the embeddings in a vector database or search service. Convert user prompts from your application to embeddings. Run a vector search across your data, comparing the user prompt embedding to the embeddings your database.

Oct 29, 2024 · Microsoft.Extensions.VectorData is a set of core .NET libraries developed in collaboration with Semantic Kernel and the broader .NET ecosystem. These libraries provide a unified layer of C# abstractions for interacting with vector stores.

May 9, 2024 · In vector database, data points are represented by vectors with a fixed number of dimensions, clustered based on similarity. Vector databases are important in different fields. Vector databases can efficiently store, organize, and search high …

Vector databases are designed to efficiently store, index and query data through high-dimensional vector embeddings. Once a user inputs a query or request into the vector database, it commences the following sequence of processes:

Jul 26, 2023 · In this post, we describe the role of vector databases in generative AI applications, and how AWS solutions can help you harness the power of generative AI. At AWS, we believe customers should be able to use the skills and tools they already have to move fast.

May 1, 2024 · Vector databases are responsible for advanced data handling and information retrieval, managing and searching high-dimensional data stored in vectors. They enable conceptual similarity searches, allowing you to find information based on the underlying meaning of …

Jan 14, 2025 · This post explores how Integrated Vector Databases revolutionize AI-powered search by seamlessly combining structured and unstructured data, enabling real-time hybrid analytics. It also highlights the power of building autonomous agents using LangGraph, showcasing their ability to deliver seamless, intelligent user experiences.

Vector databases are integral to modern AI and data-intensive applications. They enable the storage and retrieval of vectors produced by machine learning models, supporting tasks like similarity search and image search.

In this blog post, we’ll demonstrate how Logic Apps can facilitate the data ingestion process to SQL to store data as vector embeddings. We’ll also cover how Logic Apps enables seamless data retrieval and integrates with Azure OpenAI’s LLMs for reasoning on the ingested data.

Jan 9, 2025 · A vector database is a type of database optimized for storing and retrieving data in the form of vectors, or multi-dimensional arrays. In machine learning, vectors are numerical representations of objects such as text, images, or audio.