Voyage AI joins MongoDB to power more accurate and trustworthy AI applications on Atlas.

Explore Developer Center's New Chatbot! MongoDB AI Chatbot can be accessed at the top of your navigation to answer all your MongoDB questions.

MongoDB Developer
Python
plus
Sign in to follow topics
MongoDB Developer Center
chevron-right
Developer Topics
chevron-right
Languages
chevron-right
Python
chevron-right

How to Build an App with Semantic Search: Django, MongoDB Atlas & Voyage AI Tutorial

18 min • Published Jun 23, 2025
AIMongoDBVector SearchPython
Facebook Icontwitter iconlinkedin icon
Rate this video
star-empty
star-empty
star-empty
star-empty
star-empty
Read the written tutorial: https://dev.to/mongodb/grab-a-pint-with-django-mongodb-backend-voyage-ai-and-langchain-170n Watch the Django MongoDB Backend Quickstart tutorial: https://youtu.be/laXann1O0cg Sign-up for a free cluster → https://mdb.link/5s5ngllTB8E-register Access the Kaggle dataset here: https://www.kaggle.com/datasets/anaiya/guinnesswinebarsdublin Subscribe to MongoDB YouTube→ https://mdb.link/subscribe Looking for the best places to grab a drink in Dublin? Stop searching and start building! With the power of the Django-MongoDB-Backend Python package and AI, you can find the exact drink you're looking for. Build your own intelligent Dublin pub finder! This tutorial shows you how to combine Django, MongoDB, Voyage AI, and LangChain to create an AI-powered app with semantic search. Learn to set up your backend, embed data, and implement smart search functionality to help anyone discover the perfect pub in Dublin. Dive into the exciting world where Python, databases, and AI converge! Chapters: 0:00 Introduction to the Dublin Pub Finder 0:28 What is Django MongoDB Backend? 1:07 Understanding LangChain & MongoDB Integration 1:58 Why Voyage AI for Embeddings? 2:30 Project Prerequisites 3:25 Demo: Our Intelligent Pub Finder in Action 4:18 Data Collection & Preparation (Google Places API) 5:39 Setting up Django MongoDB Backend 7:24 Defining Django Models (models.py) 8:55 Generating Embeddings with Voyage AI 10:19 Importing Data to MongoDB Atlas 11:46 Creating Your Atlas Vector Search Index 13:10 Integrating LangChain for Semantic Search 14:48 Building the Django Application (views.py & URLs) 16:00 Crafting the User Interface (HTML/CSS) 17:15 Running the Application 17:35 Conclusion & Key Takeaways This video is not affiliated with, endorsed by, or sponsored by Python. The use of any trademark is solely for informational and identification purposes, so that we may provide clear and accurate descriptions. All opinions and critiques provided in this video are those of the creator and do not reflect the views of Python or its affiliates. Visit Mongodb.com → https://mdb.link/MongoDB Read the MongoDB Blog → https://mdb.link/Blog Read the Developer Blog → https://mdb.link/developerblogAll MongoDB Videos

Facebook Icontwitter iconlinkedin icon
Rate this video
star-empty
star-empty
star-empty
star-empty
star-empty
Related
Quickstart

Getting Started With MongoDB and Sanic


Jul 12, 2024 | 5 min read
Tutorial

Efficiently Managing and Querying Visual Data With MongoDB Atlas Vector Search and FiftyOne


Aug 28, 2024 | 5 min read
Tutorial

Building Generative AI Applications Using MongoDB: Harnessing the Power of Atlas Vector Search and Open Source Models


Mar 12, 2025 | 10 min read
Article

3 Underused MongoDB Features


Sep 11, 2024 | 6 min read