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Query Operators & Relevancy Controls for Precision Searches
✅ Sign-up for a free cluster at → https://mdb.link/free-U-hAo_TAi9c ✅ Get help on our Community Forums → https://mdb.link/community-U-hAo_TAi9c Atlas Search provides a rich set of query operators and relevancy controls. This episode covers the common query operators, their relevancy controls, and ends with coverage of the must-have Query Analytics feature. 🔗 Resources 🔗 Get Started with Atlas Search → https://mdb.link/cene-U-hAo_TAi9c Atlas Search query operators → https://mdb.link/operators-U-hAo_TAi9c Atlas Search Playlist → https://www.youtube.com/playlist?list=PL4RCxklHWZ9sEaTrqx7DOxQ5FzwDOTWFj ------ ✅ Subscribe to our channel → https://mdb.link/subscribeNov 15, 2023 | 14 min
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Flexible Querying With Atlas Search
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Part #3: Semantically Search Your Data With MongoDB Atlas Vector Search
In this series, we look at how to use Amazon SageMaker and MongoDB Atlas Vector Search to semantically search your data.Jul 11, 2024
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Tutorial
Part #2: Create Your Model Endpoint With Amazon SageMaker, AWS Lambda, and AWS API Gateway
In this series, we look at how to use Amazon SageMaker and MongoDB Atlas Vector Search to semantically search your data.Jul 11, 2024
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Part #1: Build Your Own Vector Search with MongoDB Atlas and Amazon SageMaker
In this series, we look at how to use Amazon SageMaker and MongoDB Atlas Vector Search to semantically search your data.Jul 11, 2024
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Semantic Search Made Easy With LangChain and MongoDB
Discover the power of semantic search with our comprehensive tutorial on integrating LangChain and MongoDB. This step-by-step guide simplifies the complex process of loading, transforming, embedding, and storing data for enhanced search capabilities. Using MongoDB Atlas and the AT&T Wikipedia page as a case study, we demonstrate how to effectively utilize LangChain libraries to streamline semantic search in your projects. Ideal for developers with a MongoDB Atlas subscription and OpenAI API key, this tutorial covers everything from setting up your environment to querying embedded data. Dive into the world of semantic search with our easy-to-follow instructions and expert insights.Jul 03, 2024
Tutorial
Interactive RAG With MongoDB Atlas + Function Calling API
Explore the cutting-edge of knowledge discovery with Interactive Retrieval-Augmented Generation (RAG) using MongoDB Atlas and Function Calling API. Learn how dynamic retrieval strategies, enhanced LLM performance, and real-time data integration can revolutionize your digital investigations. Dive into practical examples, benefits, and the future of interactive RAG in our in-depth guide. Perfect for developers and AI enthusiasts seeking to leverage advanced information access and management techniques.
Jul 03, 2024
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Unlocking Semantic Search: Building a Java-Powered Movie Search Engine with Atlas Vector Search and Spring Boot
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Quickstart
Building RAG Pipelines With Haystack and MongoDB Atlas
In this article, we explore the integration of Haystack with MongoDB Atlas to build robust retrieval-augmented generation (RAG) pipelines. You'll learn how to set up a Haystack-based RAG pipeline using MongoDB Atlas for vector search, from installing necessary dependencies to creating a vector search index, setting up a vector store, and loading documents. Additionally, the article walks you through building a pipeline to retrieve, augment, and generate responses to user queries using Haystack components and MongoDB Atlas. By the end, you'll have a fully functional RAG pipeline capable of handling complex queries and generating informative responses. This tutorial includes practical code examples and links to further resources to deepen your understanding of RAG applications..png&w=3840&q=75)
Jun 13, 2024
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