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Elastic Learned Sparse Retriever (ELSR)
Shares tags: analyze, indexing & search, retrievers
AI Tool
Unlock the Power of Data with Nomic Atlas Retriever
Effortless Vector Search for RAG Applications
Visit Nomic Atlas Retriever→
AnalyzeIndexing & SearchRetrievers
1Seamlessly integrate with popular frameworks like LlamaIndex and LangChain for enhanced AI capabilities.
2Discover insights faster with upgraded algorithms and precise semantic search endpoints.
3Scale your applications efficiently with robust support for multimodal data and high-performance retrieval.
overview
What is Nomic Atlas Retriever?
Nomic Atlas Retriever is a cutting-edge vector retriever designed to facilitate the building of advanced Retrieval-Augmented Generation applications. It supports both text and multimodal data, making it an ideal solution for developers and data scientists dealing with large-scale unstructured datasets.
features
Key Features
Nomic Atlas Retriever encompasses a range of innovative features that enhance data retrieval and analysis capabilities. Its powerful algorithms and user-friendly interface make it a must-have tool for any data-driven project.
- 1Transparent embeddings and comprehensive data maps for intuitive visualizations.
- 2Advanced programmatic selection endpoints for customized search filters.
- 3Enhanced projection algorithms improving speed and accuracy across datasets.
use cases
Applications of Nomic Atlas Retriever
With its scalable architecture, Nomic Atlas Retriever caters to various use cases from academic research to commercial applications. Its versatility strikes a balance between performance and usability, easing complex tasks.
- 1Powering RAG applications with precise, context-aware search.
- 2Exploring large unstructured datasets for insights and patterns.
- 3Building AI applications with seamless integration into existing workflows.
insights
Latest Insights and Enhancements
Recent updates to Nomic Atlas Retriever have introduced semantic search API endpoints and improved 2D data mapping algorithms. These enhancements ensure users have access to the most precise retrieval capabilities available today.
- 1Availability of UMAP as the default for smaller datasets.
- 2Integration improvements for advanced filtering using regex and kNN.
- 3Optimized for smooth usage across diverse data domains.
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Frequently Asked Questions
+What kind of data can I retrieve using Nomic Atlas Retriever?
You can retrieve both text and multimodal data, making it suitable for a wide range of applications such as NLP, image processing, and more.
+Is Nomic Atlas Retriever easy to integrate with existing systems?
Yes, it is designed for seamless integration with popular frameworks like LlamaIndex and LangChain, ensuring a smooth setup process.
+How often does Nomic Atlas Retriever receive updates?
We continuously enhance Nomic Atlas Retriever with regular updates that introduce new features, optimizations, and improvements based on user feedback.