# Module 1: Project setup · Semantic search on Chromia using Vector DB · Learn Chromia

> This module covers the environment setup for the Vector DB Movie Demo.

Source: https://chromia.com/learn/vector-db-movie-demo/setup/

Semantic search on Chromia using Vector DBLesson 2 of 15

1. [01Searching movies semantically on Chromia](https://chromia.com/learn/vector-db-movie-demo/introduction/)

Module 1: Project setup

1. [02Overview](https://chromia.com/learn/vector-db-movie-demo/setup/)
2. [03Choose an embedding model](https://chromia.com/learn/vector-db-movie-demo/setup/embedding-model/)
3. [04Configure your Rell module](https://chromia.com/learn/vector-db-movie-demo/setup/configure.rell/)
4. [05Deploy your Rell module](https://chromia.com/learn/vector-db-movie-demo/setup/deploy-rell-module/)
5. [06Finalize your Python environment](https://chromia.com/learn/vector-db-movie-demo/setup/finalize-python-env/)

Module 2: Running the data pipeline

1. [07Overview](https://chromia.com/learn/vector-db-movie-demo/data-pipeline/)
2. [08Preprocess movie data](https://chromia.com/learn/vector-db-movie-demo/data-pipeline/preprocess/)
3. [09Generate sentence embeddings](https://chromia.com/learn/vector-db-movie-demo/data-pipeline/generate-embeddings/)
4. [10Store vectors on the blockchain](https://chromia.com/learn/vector-db-movie-demo/data-pipeline/upload-vectors/)

1. [11Search the vector database](https://chromia.com/learn/vector-db-movie-demo/search/)

Module 4: A deep dive into the code

1. [12Overview](https://chromia.com/learn/vector-db-movie-demo/code-deep-dive/)
2. [13Link your data to the Vector DB with Rell](https://chromia.com/learn/vector-db-movie-demo/code-deep-dive/rell-interface/)
3. [14Work with Chromia through the Python client](https://chromia.com/learn/vector-db-movie-demo/code-deep-dive/python-client/)

1. [15Use cases and extensions](https://chromia.com/learn/vector-db-movie-demo/use-cases/)

[Learn](https://chromia.com/learn/)[Semantic search on Chromia using Vector DB](https://chromia.com/learn/vector-db-movie-demo/)

02 / 15Module 1: Project setupAdvanced

# Module 1: Project setup

This module covers the environment setup for the Vector DB Movie Demo.

You pick a sentence embedding model and match the `vector_db_extension` dimensionality to it. Then you configure the Rell backend, deploy it to the Chromia testnet, and prepare your Python environment.

When you finish, your backend runs on testnet and your Python scripts are configured, so you can move on to working with data in the next module.

## In this lesson

1. [Choose an embedding model](https://chromia.com/learn/vector-db-movie-demo/setup/embedding-model/)
2. [Configure your Rell module](https://chromia.com/learn/vector-db-movie-demo/setup/configure.rell/)
3. [Deploy your Rell module](https://chromia.com/learn/vector-db-movie-demo/setup/deploy-rell-module/)
4. [Finalize your Python environment](https://chromia.com/learn/vector-db-movie-demo/setup/finalize-python-env/)

[Begin lesson →](https://chromia.com/learn/vector-db-movie-demo/setup/embedding-model/)

Written for this site from Chromia’s public course. Code samples are the course’s own.

[← Previous**Searching movies semantically on Chromia**](https://chromia.com/learn/vector-db-movie-demo/introduction/)[Next →**Choose an embedding model**](https://chromia.com/learn/vector-db-movie-demo/setup/embedding-model/)