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Article
Building a Foreign Correspondent With MongoDB, Anthropic's Claude, Python
Join guest author Marko Aleksendric to learn how to use MongoDB, Anthropic's Claude and Python to create a simple web application aimed to help a virtual friend in a foreign country translate the local news items.Dec 09, 2024
Tutorial
How to Deploy a Flask Application With MongoDB on Fly.io
Learn how to deploy a Flask Application with MongoDB on Fly.ioDec 02, 2024
Tutorial
How to Implement Working Memory in AI Agents and Agentic Systems for Real-time AI Applications
Nov 18, 2024
Tutorial
Trader Joe's Fall Faves Party Planner With Playwright, LlamaIndex, and MongoDB Atlas Vector Search
In this tutorial, we create a Trader Joe’s AI party planner using Playwright to scrape our fall faves and the LlamaIndex/Atlas Vector Search integration to build a chatbot to answer questions about our items!Nov 12, 2024
Tutorial
How to Choose the Best Embedding Model for Your LLM Application
In this tutorial, we will see why embeddings are important for RAG, and how to choose the best embedding model for your RAG application.
Nov 07, 2024
Tutorial
Simplify Semantic Search With LangChain and MongoDB
Dive into semantic search with our tutorial on integrating LangChain and MongoDB. Simplify loading, transforming, embedding, and storing data.
Oct 28, 2024
Video
Sip, Swig, and Search with Playwright, OpenAI and MongoDB Atlas Search
✅ Atlas Search → https://mdb.link/DzDnm_cB-IAsearch ✅ Playwright → https://playwright.dev/ ✅ OpenAI's Structured Outputs → https://openai.com/index/introducing-structured-outputs-in-the-api/ ✅ MongoDB Developer Forum → https://mdb.link/DzDnm_cB-IA-forum - Join Developer Advocate Anaiya Raisinghani as she takes you through her tutorial finding the best fall drinks from Utah's most famous "dirty" soda chain, Swig! We will be using Playwright, OpenAI's Structured Outputs and MongoDB's Atlas Search to accomplish this goal.Oct 28, 2024
Article
Discover Latent Semantic Structure With Vector Clustering
Leverage the mathematical properties of a population of db AI-embedded vectors to extract potential novel business intelligence.
Oct 11, 2024
SK
Tutorial
How to Use Cohere's Quantized Vectors to Build Cost-effective AI Apps With MongoDB
Learn how to build cost-effective AI apps using Cohere's quantized vectors and MongoDB Atlas. This tutorial covers vector quantization techniques, efficient embedding storage, and optimized vector search operations. Discover how to leverage BSON encoding and int8 quantization to significantly reduce storage requirements while maintaining search accuracy. Ideal for developers looking to scale their AI applications and optimize performance in production environments.
Oct 03, 2024
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