Welcome! This tutorial will guide you through creating semantic search application using Upstash Vector and Sentence Transformers. We will create the embeddings using the dataset we’ve prepared for you that contains 100 questions. Then we’ll upsert these vectors to Upstash Vector, both to store the vectors, and to use basic vector operations such as query, fetch etc.

You can use this example as a template to build more advanced projects such as docs search, QA bot, similarity search over a content etc.

Outline:

1- Create Index and install dependencies

2- Generate embeddings

3- Insert vectors to index

4- Query the index

5- Outro

You can find the full tutorial and code in the notebook here.

Welcome! This tutorial will guide you through creating semantic search application using Upstash Vector and Sentence Transformers. We will create the embeddings using the dataset we’ve prepared for you that contains 100 questions. Then we’ll upsert these vectors to Upstash Vector, both to store the vectors, and to use basic vector operations such as query, fetch etc.

You can use this example as a template to build more advanced projects such as docs search, QA bot, similarity search over a content etc.

Outline:

1- Create Index and install dependencies

2- Generate embeddings

3- Insert vectors to index

4- Query the index

5- Outro

You can find the full tutorial and code in the notebook here.