docs: Drop docs older than 0.21

1 files changed, 0 insertions, 71 deletions

diff --git a/docs/versioned_docs/version-v0.16.0/02-Installation/04-kubernetes.md b/docs/versioned_docs/version-v0.16.0/02-Installation/04-kubernetes.md
deleted file mode 100644
index 524f6e61..00000000
--- a/docs/versioned_docs/version-v0.16.0/02-Installation/04-kubernetes.md
+++ /dev/null
@@ -1,71 +0,0 @@
-# Kubernetes
-
-### Requirements
-
-- A kubernetes cluster
-- kubectl
-- kustomize
-
-### 1. Get the deployment manifests
-
-You can clone the repository and copy the `/kubernetes` directory into another directory of your choice.
-
-### 2. Populate the environment variables
-
-To configure the app, edit the configuration in `.env`.
-
-
-You **should** change the random strings. You can use `openssl rand -base64 36` to generate the random strings. You should also change the `NEXTAUTH_URL` variable to point to your server address.
-
-Using `HOARDER_VERSION=release` will pull the latest stable version. You might want to pin the version instead to control the upgrades (e.g. `HOARDER_VERSION=0.10.0`). Check the latest versions [here](https://github.com/hoarder-app/hoarder/pkgs/container/hoarder-web).
-
-### 3. Setup OpenAI
-
-To enable automatic tagging, you'll need to configure OpenAI. This is optional though but highly recommended.
-
-- Follow [OpenAI's help](https://help.openai.com/en/articles/4936850-where-do-i-find-my-openai-api-key) to get an API key.
-- Add the OpenAI API key to the `.env` file:
-
-```
-OPENAI_API_KEY=<key>
-```
-
-Learn more about the costs of using openai [here](/openai).
-
-<details>
-    <summary>[EXPERIMENTAL] If you want to use Ollama (https://ollama.com/) instead for local inference.</summary>
-
-    **Note:** The quality of the tags you'll get will depend on the quality of the model you choose. Running local models is a recent addition and not as battle tested as using openai, so proceed with care (and potentially expect a bunch of inference failures).
-
-    - Make sure ollama is running.
-    - Set the `OLLAMA_BASE_URL` env variable to the address of the ollama API.
-    - Set `INFERENCE_TEXT_MODEL` to the model you want to use for text inference in ollama (for example: `mistral`)
-    - Set `INFERENCE_IMAGE_MODEL` to the model you want to use for image inference in ollama (for example: `llava`)
-    - Make sure that you `ollama pull`-ed the models that you want to use.
-
-
-</details>
-
-### 4. Deploy the service
-
-Deploy the service by running:
-
-```
-make deploy
-```
-
-### 5. Access the service
-
-By default, these manifests expose the application as a LoadBalancer Service. You can run `kubectl get services` to identify the IP of the loadbalancer for your service.
-
-Then visit `http://<loadbalancer-ip>:3000` and you should be greated with the Sign In page.
-
-> Note: Depending on your setup you might want to expose the service via an Ingress, or have a different means to access it.
-
-### [Optional] 6. Setup quick sharing extensions
-
-Go to the [quick sharing page](/quick-sharing) to install the mobile apps and the browser extensions. Those will help you hoard things faster!
-
-## Updating
-
-Edit the `HOARDER_VERSION` variable in the `kustomization.yaml` file and run `make clean deploy`.