Document Q&A system with Voyage-Context-3 embeddings and MongoDB Atlas

About This Workflow

What This Workflow Does

This workflow automates the interactions between a Document Q&A system, Voyage-Context-3 embeddings, and MongoDB Atlas. It enables users to create a seamless integration for context-aware question-answering and document retrieval. The workflow processes user queries, generates relevant embeddings, and retrieves answers from a MongoDB Atlas database.

Who Should Use This

This workflow is ideal for software engineers and AI/ML developers who want to leverage the power of Voyage-Context-3 embeddings and MongoDB Atlas to build context-aware Q&A systems. It is also suitable for anyone interested in exploring the potential of embeddings models for document retrieval and question-answering applications.

Key Features

• Voyage-Context-3 Embeddings: The workflow generates Voyage-Context-3 embeddings for user queries, enabling context-aware document retrieval and question-answering.
• MongoDB Atlas Integration: The workflow retrieves and stores documents from a MongoDB Atlas database, allowing for efficient and scalable document management.
• Document Retrieval and Question-Answering: The workflow enables users to retrieve relevant documents and answers from the MongoDB Atlas database based on user queries.
• Context-Aware Query Processing: The workflow processes user queries and generates context-aware embeddings to improve the accuracy of document retrieval and question-answering.

How to Get Started

To use this workflow, simply import it into your n8n instance and customize the settings to match your MongoDB Atlas database credentials and document schema. You can then test the workflow by sending user queries and observing the generated answers and retrieved documents.