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Set up 101 tutorial from bash

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Mike Jang
2023-11-25 18:52:03 -08:00
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qdrant-landing/content/documentation/tutorials/search-beginners.md
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If you are new to vector databases, this tutorial is for you. In 5 minutes you will build a semantic search engine for science fiction books. After you set it up, you will ask the engine about an impending alien threat. Your creation will recommend books as preparation for a potential space attack.
Before you begin, you need to have a [recent version of Python](https://www.python.org/downloads/) installed. If you don't know how to run this code in a virtual environment, follow [this tutorial](https://towardsdatascience.com/creating-and-using-virtual-environment-on-jupyter-notebook-with-python-db3f5afdd56a) first.
Before you begin, you need to have a [recent version of Python](https://www.python.org/downloads/) installed. If you don't know how to run this code in a virtual environment, follow Python documentation for [Creating Virtual Environments](https://docs.python.org/3/tutorial/venv.html#creating-virtual-environments) first.
This tutorial assumes you're in the bash shell. Use the Python documentation to activate a virtual environment.
## 1. Installation
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### Import the models
Once the two main frameworks are defined, you need to specify the exact models this engine will use.
Once the two main frameworks are defined, you need to specify the exact models this engine will use. Before you do, activate the Python prompt (`>>>`) with the `python` command.
```python
from qdrant_client import models, QdrantClient
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## Next Steps
Congratulations, you have just created your very first search engine! Trust us, the rest of Qdrant is not that complicated, either. For your next tutorial you should try building an actual [Neural Search Service with a complete API and a dataset](../../tutorials/neural-search/).
## Return to the bash shell
To return to the bash prompt:
1. Press Ctrl+D to exit the Python prompt (`>>>`).
1. Enter the `deactivate` command to deactivate the virtual environment.