-
API Keys for embedding models, like:
- OpenAI Key
- Cohere Key
- etc,
-
Python 3.9 or newer
-
Docker Compose (Todo: update this in case we can do it all with WCS)
To run the project locally, it is best to setup python environment with venv.
First create a new venv configuration.
python3 -m venv .venv
Then switch to the new configuration:
source .venv/bin/activate
And install the required packages.
pip install -r requirements.txt
All together
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
If in the future, you need to switch to the venv setup, just call:
source .venv/bin/activate
To disconnect from the venv environment, call:
source deactivate
-
Go to the project https://github.com/weaviate-tutorials/weaviate-workshop.
-
Create a Codespace project
- Press the green
Code
button, then switch toCodespaces
tab. - Press
...
(next to the+
button) and selectNew with options...
- Change the
Machine type
to4-core
and press the greenCreate codespace
button
- After the codespace is ready – set up the evironment and install the required libraries. Run:
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
- For "lesson 5", start the
docker-compose-clip.yml
image (and give it a couple of minutes):
docker compose -f "5-multivec-named-vectors/docker-compose-clip.yml" up -d
- Install Jupyter notebook extension. You will be asked for it when you open any notebook. Then switch to the .venv image.