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Building a Semantic Search Application with MongoDB and Quarkus using Vector Search
✅ Try MongoDB 8.0 → https://mdb.link/91SzYGDmFoI ✅ Sign-up for a free cluster → https://mdb.link/91SzYGDmFoI-try ✅ Article link → https://mdb.link/91SzYGDmFoI-read - Discover how to harness the power of MongoDB's vector search capability to build a semantic search application using the Quarkus framework. In this comprehensive tutorial, we'll guide you step-by-step from understanding vector search fundamentals to implementing a functional Java application. Learn how to use Gemini AI for vector embeddings, create optimized queries, and set up your MongoDB Atlas cluster for seamless integration. Whether you're new to vector search or looking to enhance your generative AI applications, this video provides all the tools you need to get started. - 📚 Git repo: https://github.com/mongodb-developer/mongodb-vector-search-with-quarkus Resources: 📚 Vector Embeddings: https://mdb.link/91SzYGDmFoI-models 📚 Gemini AI: https://ai.google.dev/api?lang=python https://ai.google.dev/gemini-api/docs/api-key Similarity values: 📚 Euclidean: https://en.wikipedia.org/wiki/Euclidean_distance 📚 Cosine: https://en.wikipedia.org/wiki/Cosine_similarity 📚 Dot Product: https://en.wikipedia.org/wiki/Dot_productJan 21, 2025 | 30 min
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Video
Building a Semantic Search Application with MongoDB and Quarkus using Vector Search
✅ Try MongoDB 8.0 → https://mdb.link/91SzYGDmFoI ✅ Sign-up for a free cluster → https://mdb.link/91SzYGDmFoI-try ✅ Article link → https://mdb.link/91SzYGDmFoI-read - Discover how to harness the power of MongoDB's vector search capability to build a semantic search application using the Quarkus framework. In this comprehensive tutorial, we'll guide you step-by-step from understanding vector search fundamentals to implementing a functional Java application. Learn how to use Gemini AI for vector embeddings, create optimized queries, and set up your MongoDB Atlas cluster for seamless integration. Whether you're new to vector search or looking to enhance your generative AI applications, this video provides all the tools you need to get started. - 📚 Git repo: https://github.com/mongodb-developer/mongodb-vector-search-with-quarkus Resources: 📚 Vector Embeddings: https://mdb.link/91SzYGDmFoI-models 📚 Gemini AI: https://ai.google.dev/api?lang=python https://ai.google.dev/gemini-api/docs/api-key Similarity values: 📚 Euclidean: https://en.wikipedia.org/wiki/Euclidean_distance 📚 Cosine: https://en.wikipedia.org/wiki/Cosine_similarity 📚 Dot Product: https://en.wikipedia.org/wiki/Dot_product
Jan 21, 2025
Quickstart
Building Quarkus Application with MongoDB and Panache
In this tutorial, we will learn about building a Quarkus application with Panache and MongoDB. Panache is a Quarkus-specific library that simplifies the development of your Hibernate-based persistence layer.Dec 03, 2024
Article
Building a Quarkus Application to Perform MongoDB Vector Search
This article explores building a Quarkus application using MongoDB's vector search for smarter, context-aware search results. We'll cover generating embeddings with Gemini AI and creating a vector index in MongoDB. Learn how to enhance your application's search capabilities with this modern approach.Oct 07, 2024
Quickstart
How to Build a CRUD Application With MongoDB, Quarkus, and GraalVM
Explore the seamless integration of Quarkus, GraalVM, and MongoDB for lightning-fast CRUD RESTful APIs. Harness Quarkus' rapid startup time and Kubernetes compatibility for streamlined deployment.
Aug 29, 2024
