Remove UI component. It's now hosted in instructlab/ui repository

Signed-off-by: Anil Vishnoi <[email protected]>

.ansible-lint

@@ -1,4 +1,3 @@
 exclude_paths:
  - compose.yaml
  - .github/
- - ui/

.github/workflows/images.yml

@@ -48,88 +48,6 @@ jobs:
           cache-to: type=gha,mode=max
           file: gobot/Containerfile
 
-  push_to_registries_ui:
-    name: Push UI container image to GHCR
-    runs-on: ubuntu-latest
-    permissions:
-      packages: write
-      contents: read
-    steps:
-      - name: Check out the repo
-        uses: actions/checkout@v4
-
-      - name: Log in to the Container registry
-        uses: docker/login-action@v3
-        with:
-          registry: ghcr.io
-          username: ${{ github.actor }}
-          password: ${{ secrets.GITHUB_TOKEN }}
-
-      - uses: docker/setup-buildx-action@v3
-
-      - name: Extract metadata (tags, labels) for UI image
-        id: ui_meta
-        uses: docker/metadata-action@v5
-        with:
-          images: |
-            ghcr.io/${{ github.repository }}/bot-ui
-
-      - name: Build and push ui image
-        uses: docker/build-push-action@v6
-        with:
-          context: .
-          platforms: linux/amd64,linux/arm64
-          build-args: |
-            GITHUB_USER=instructlab-bot
-            GITHUB_TOKEN=${{ secrets.BOT_GITHUB_TOKEN }}
-          push: true
-          tags: ${{ steps.ui_meta.outputs.tags }}
-          labels: ${{ steps.ui_meta.outputs.labels }}
-          cache-from: type=gha
-          cache-to: type=gha,mode=max
-          file: ui/Containerfile
-
-  push_to_registries_apiserver:
-    name: Push apiserver container image to GHCR
-    runs-on: ubuntu-latest
-    permissions:
-      packages: write
-      contents: read
-    steps:
-      - name: Check out the repo
-        uses: actions/checkout@v4
-
-      - name: Log in to the Container registry
-        uses: docker/login-action@v3
-        with:
-          registry: ghcr.io
-          username: ${{ github.actor }}
-          password: ${{ secrets.GITHUB_TOKEN }}
-
-      - uses: docker/setup-buildx-action@v3
-
-      - name: Extract metadata (tags, labels) for apiserver image
-        id: apiserver_meta
-        uses: docker/metadata-action@v5
-        with:
-          images: |
-            ghcr.io/${{ github.repository }}/apiserver
-
-      - name: Build and push apiserver image
-        uses: docker/build-push-action@v6
-        with:
-          context: .
-          platforms: linux/amd64,linux/arm64
-          build-args: |
-            GITHUB_USER=instructlab-bot
-            GITHUB_TOKEN=${{ secrets.BOT_GITHUB_TOKEN }}
-          push: true
-          tags: ${{ steps.apiserver_meta.outputs.tags }}
-          labels: ${{ steps.apiserver_meta.outputs.labels }}
-          cache-from: type=gha
-          cache-to: type=gha,mode=max
-          file: ui/apiserver/Containerfile
-
   push_to_registries_serve:
     name: Push serve container image to GHCR
     runs-on: ubuntu-latest

.markdownlint-cli2.yaml

@@ -9,5 +9,3 @@ globs:
   - "**/*.md"
 ignores:
   - "pkg"
-  - "**/node_modules/*"
-  - "**/node_modules/**"

CONTRIBUTING.md

@@ -17,12 +17,10 @@ We'd also love PRs. If you're thinking of a large PR, we advise opening up an is
 ## Submitting a pull request
 
 1. [Fork][fork] and clone the repository.
-1. Configure and install the dependencies: `npm install`.
-1. Make sure the tests pass on your machine: `npm test`, note: these tests also apply the linter, so there's no need to lint separately.
-1. Create a new branch: `git checkout -b my-branch-name`.
-1. Make your change, add tests, and make sure the tests still pass.
-1. Push to your fork and [submit a pull request][pr].
-1. Pat your self on the back and wait for your pull request to be reviewed and merged.
+2. Create a new branch: `git checkout -b my-branch-name`.
+3. Make your change, add tests, and make sure the tests still pass.
+4. Push to your fork and [submit a pull request][pr].
+5. Pat your self on the back and wait for your pull request to be reviewed and merged.
 
 Here are a few things you can do that will increase the likelihood of your pull request being accepted:
 

Makefile

@@ -100,15 +100,7 @@ ilabserve-base-image: worker/Containerfile.servebase ## Build container image fo
 	$(ECHO_PREFIX) printf "  %-12s worker/Containerfile.servebase\n" "[PODMAN]"
 	$(CMD_PREFIX) podman build -f worker/Containerfile.servebase -t ghcr.io/instructlab/instructlab-bot/instructlab-serve-base:main .
 
-apiserver-image: ui/apiserver/Containerfile ## Build continaer image for the Apiserver
-	$(ECHO_PREFIX) printf "  %-12s ui/apiserver/Containerfile\n" "[PODMAN]"
-	$(CMD_PREFIX) podman build -f ui/apiserver/Containerfile -t ghcr.io/instructlab/instructlab-bot/apiserver:main .
-
-ui-image: ui/Containerfile ## Build continaer image for the bot ui
-	$(ECHO_PREFIX) printf "  %-12s ui/Containerfile\n" "[PODMAN]"
-	$(CMD_PREFIX) podman build -f ui/Containerfile -t ghcr.io/instructlab/instructlab-bot/bot-ui:main .
-
-all-images: gobot-image worker-test-image apiserver-image ui-image ## Build all container images
+all-images: gobot-image worker-test-image ## Build all container images
 	$(ECHO_PREFIX) printf "  %-12s BUILD ALL CONTAINER IMAGES\n"
 
 .PHONY: gobot
@@ -154,28 +146,12 @@ run-dev: ## Deploy the bot development stack.
 	$(ECHO_PREFIX) printf "Deploy the development stack\n"
 	$(CMD_PREFIX) podman compose -f ./deploy/compose/dev-single-worker-compose.yaml up -d
 
-.PHONY: run-dev-ui
-run-dev-ui: ## Deploy the bot development stack with the UI components.
-	$(ECHO_PREFIX) printf "  %-12s \n" "[RUN DEV UI STACK]"
-	$(CMD_PREFIX) if [ ! -f .env ]; then \
-		echo ".env not found. Copy .env.example to .env and configure it." ; \
-		exit 1 ; \
-	fi
-	$(ECHO_PREFIX) printf "Deploy the development stack with UI components\n"
-	$(CMD_PREFIX) podman compose -f ./deploy/compose/dev-single-worker-with-ui.yaml up -d
-
 .PHONY: stop-dev
 stop-dev: ## Stop the bot development stack.
 	$(ECHO_PREFIX) printf "  %-12s \n" "[STOP DEV STACK]"
 	$(ECHO_PREFIX) printf "Stop the development stack\n"
 	$(CMD_PREFIX) podman compose -f ./deploy/compose/dev-single-worker-compose.yaml down
 
-.PHONY: stop-dev-ui
-stop-dev-ui: ## Stop the bot development stack with the UI components.
-	$(ECHO_PREFIX) printf "  %-12s \n" "[STOP DEV UI STACK]"
-	$(ECHO_PREFIX) printf "Stop the development stack with UI components\n"
-	$(CMD_PREFIX) podman compose -f ./deploy/compose/dev-single-worker-with-ui.yaml down
-
 .PHONY: redis-stack
 redis-stack: ## Run a redis-stack container
 	$(ECHO_PREFIX) printf "  %-12s redis/redis-stack:latest\n" "[PODMAN]"

deploy/ansible/README.md

@@ -117,14 +117,6 @@ This playbook installs all the components in the containers.
 ansible-playbook -i inventory.txt  -e @secrets.enc --ask-vault-pass deploy-bot-stack.yml
 ```
 
-## Install the UI stack that works with the Bot stack
-
-This playbook installs all the required UI components in the containers.
-
-```console
-ansible-playbook -i inventory.txt  -e @secrets.enc --ask-vault-pass deploy-ui-stack.yml
-```
-
 ## Install the Worker stack (first time installation)
 
 This playbook installs all the required component on the host itself

docs/dev-env.md

@@ -85,38 +85,6 @@ To destroy the stack:
 make stop-dev
 ```
 
-## Setup local development deployment with UI components
-
-If you want to deploy the bot with the UI components, you need to do the following steps:
-
-1) Build the ui and apiserver images and set the `/ui/.env`. That .env file will be copied into the container at build time, it needs to be edited before building the image.
-
-    ```text
-    IL_UI_ADMIN_USERNAME=<ui-login-username>
-    IL_UI_ADMIN_PASSWORD=<ui-login-password>
-    IL_UI_API_SERVER_USERNAME=<api-server-username>
-    IL_UI_API_SERVER_PASSWORD=<api-server-password>
-    IL_UI_API_SERVER_URL=http://localhost:3000/jobs  # Keep this as is.
-    ```
-
-2) Build the images
-
-    ```bash
-    make all-images
-    ```
-
-3) Run the stack
-
-    ```bash
-    make run-dev-ui
-    ```
-
-To destroy the stack:
-
-```bash
-make stop-dev-ui
-```
-
 ## Setup testing deployment
 
 We use ansible for deploying this setup on the AWS cloud. To deploy this setup, you will need the following to be present on your local machine: