https://github.com/tinybirdco/demo_vector_search_recommendation
https://github.com/tinybirdco/demo_vector_search_recommendation
Last synced: 9 months ago
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- Host: GitHub
- URL: https://github.com/tinybirdco/demo_vector_search_recommendation
- Owner: tinybirdco
- Created: 2024-09-26T17:41:17.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-09-30T16:49:21.000Z (over 1 year ago)
- Last Synced: 2025-09-17T01:39:29.071Z (9 months ago)
- Language: Python
- Size: 17.6 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Use Case Demo: Build a content recommendation system using vector search
This repository contains code for an example content recommendation system using vector search in Tinybird.
Vector search is a great way to approach content matching and recommendations. You can calculate embeddings based on multi-modal analysis of text, images, and other media, then calculate vector distances between embeddings to recommend matching content.
Read more about [vector search use cases here](https://www.tinybird.co/docs/use-cases/vector-search).
## Deploy it yourself
This repository mirrors work that Tinybird has done to recommend related blog posts on the official [Tinybird Blog](https://www.tinybird.co/blog).
[Read the guide](https://www.tinybird.co/docs/guides/tutorials/vector-search-recommendation) to deploy this demo application yourself.
## License
This code is available under the MIT license. See the [LICENSE](./LICENSE.txt) file for more details.
## Need help?
- [Tinybird Slack Community](https://www.tinybird.co/community)
- [Tinybird Docs](https://www.tinybird.co/docs)
## Authors
- [Jordi Villar](https://github.com/jrdi)
- [Cameron Archer](https://github.com/tb-peregrine)