initial commit

.github/workflows/automerge.yml

@@ -0,0 +1,21 @@
+name: Trigger PipelineRun on Push
+
+on:
+  workflow_dispatch:
+    inputs:
+      pr_url:
+        description: 'The PR URL that need to be merged to trigger the pipelinerun'
+        required: true
+jobs:
+  automerge:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: write
+      pull-requests: write
+      repository-projects: write
+    steps:
+      - name: Enable Automerge
+        run: gh pr merge --auto --squash "$PR_URL"
+        env:
+          PR_URL: ${{ github.event.inputs.pr_url }}
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.tekton/README.md

@@ -0,0 +1,22 @@
+# docker-build-ai-rhdh
+
+## Shared Git resolver model for shared pipeline and tasks
+
+This pipeline is used to create Containerfile based SSCS (Software Supply Chain Security) builds. The pipeline run by this runner clones the source, builds an image with SBOM (Software Bill of Materials), attests, and pushes these to the users image registry.  
+
+Tasks references come from this [repository](https://github.com/redhat-ai-dev/rhdh-pipelines) `pac/pipelines` and the tasks are defined in `pac/tasks`. The tasks are referenced by URL using the git resolver in tekton. 
+
+When the pipelines in this repository are updated, all future runs in existing pipelines are shared.
+
+A developer can override these tasks with a local copy and updated annotations. 
+
+Example 
+
+To override the git-clone task, you may simply copy the git reference into your .tekton directory and then reference it from the remote task annotation. 
+
+`pipelinesascode.tekton.dev/task-0: ".tekton/git-clone.yaml"` 
+
+## Templates 
+These pipelines are in template format. The references to this repository in the PaC template is `{{values.rawUrl}}` which is updated to point to this repo or the fork of this repo.
+
+The intent of the template is to fork this repository and update its use in the Developer Hub templates directory. 

.tekton/docker-pull-request.yaml

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+apiVersion: tekton.dev/v1
+kind: PipelineRun
+metadata:
+  name: 'test-2-resnet-on-pull-request'
+  annotations:
+    pipelinesascode.tekton.dev/on-event: "[pull_request]"
+    pipelinesascode.tekton.dev/on-target-branch: "[main]"
+    pipelinesascode.tekton.dev/max-keep-runs: "2"
+    pipelinesascode.tekton.dev/pipeline: "https://raw.githubusercontent.com/redhat-ai-dev/rhdh-pipelines/main/pac/pipelines/docker-build-ai-rhdh-pull-request.yaml"
+    pipelinesascode.tekton.dev/task-0: "https://raw.githubusercontent.com/redhat-ai-dev/rhdh-pipelines/main/pac/tasks/init.yaml"
+    pipelinesascode.tekton.dev/task-1: "https://raw.githubusercontent.com/redhat-ai-dev/rhdh-pipelines/main/pac/tasks/git-clone.yaml"
+    pipelinesascode.tekton.dev/task-2: "https://raw.githubusercontent.com/redhat-ai-dev/rhdh-pipelines/main/pac/tasks/buildah-ai-rhdh.yaml"
+    pipelinesascode.tekton.dev/task-3: "https://raw.githubusercontent.com/redhat-ai-dev/rhdh-pipelines/main/pac/tasks/show-sbom-rhdh.yaml"
+    pipelinesascode.tekton.dev/task-4: "https://raw.githubusercontent.com/redhat-ai-dev/rhdh-pipelines/main/pac/tasks/summary.yaml"
+  labels:
+    argocd/app-name: test-2-resnet
+    janus-idp.io/tekton: test-2-resnet
+    backstage.io/kubernetes-id: test-2-resnet
+    backstage.io/kubernetes-namespace: rhdh-app
+    app.kubernetes.io/part-of: test-2-resnet
+spec:
+  params:
+    - name: dockerfile
+      value: 'Containerfile'
+    - name: git-url
+      value: '{{repo_url}}'
+    - name: image-expires-after
+      value: 5d
+    - name: output-image
+      value: 'quay.io/jdubrick-ai/test-2-resnet:on-pr-{{revision}}'
+    - name: path-context
+      value: '.'
+    - name: revision
+      value: '{{revision}}'
+    - name: event-type
+      value: '{{event_type}}'
+    - name: gitops-auth-secret-name
+      value: 'gitops-auth-secret'
+  pipelineRef:
+    name: docker-build-ai-rhdh-pull-request
+  workspaces:
+    - name: git-auth
+      secret:
+        secretName: "{{ git_auth_secret }}"
+    - name: workspace
+      volumeClaimTemplate:
+        spec:
+          accessModes:
+            - ReadWriteOnce
+          resources:
+            requests:
+              storage: 1Gi

.tekton/docker-push.yaml

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+apiVersion: tekton.dev/v1
+kind: PipelineRun
+metadata:
+  name: 'test-2-resnet-on-push'
+  annotations:
+    pipelinesascode.tekton.dev/on-event: "[push]"
+    pipelinesascode.tekton.dev/on-target-branch: "[main]"
+    pipelinesascode.tekton.dev/max-keep-runs: "2"
+    pipelinesascode.tekton.dev/pipeline: "https://raw.githubusercontent.com/redhat-ai-dev/rhdh-pipelines/main/pac/pipelines/docker-build-ai-rhdh-push-gitops.yaml"
+    pipelinesascode.tekton.dev/task-0: "https://raw.githubusercontent.com/redhat-ai-dev/rhdh-pipelines/main/pac/tasks/init.yaml"
+    pipelinesascode.tekton.dev/task-1: "https://raw.githubusercontent.com/redhat-ai-dev/rhdh-pipelines/main/pac/tasks/git-clone.yaml"
+    pipelinesascode.tekton.dev/task-2: "https://raw.githubusercontent.com/redhat-ai-dev/rhdh-pipelines/main/pac/tasks/buildah-ai-rhdh.yaml"
+    pipelinesascode.tekton.dev/task-3: "https://raw.githubusercontent.com/redhat-ai-dev/rhdh-pipelines/main/pac/tasks/update-deployment-gitops.yaml"
+    pipelinesascode.tekton.dev/task-4: "https://raw.githubusercontent.com/redhat-ai-dev/rhdh-pipelines/main/pac/tasks/show-sbom-rhdh.yaml"
+    pipelinesascode.tekton.dev/task-5: "https://raw.githubusercontent.com/redhat-ai-dev/rhdh-pipelines/main/pac/tasks/summary.yaml"
+  labels:
+    argocd/app-name: test-2-resnet
+    janus-idp.io/tekton: test-2-resnet
+    backstage.io/kubernetes-id: test-2-resnet
+    backstage.io/kubernetes-namespace: rhdh-app
+    app.kubernetes.io/part-of: test-2-resnet
+spec:
+  params:
+    - name: dockerfile
+      value: 'Containerfile'
+    - name: git-url
+      value: '{{repo_url}}'
+    - name: image-expires-after
+      value: 5d
+    - name: output-image
+      value: 'quay.io/jdubrick-ai/test-2-resnet:{{revision}}'
+    - name: path-context
+      value: '.'
+    - name: revision
+      value: '{{revision}}'
+    - name: gitops-auth-secret-name
+      value: 'gitops-auth-secret'
+  pipelineRef:
+    name: docker-build-ai-rhdh-push-gitops
+  workspaces:
+    - name: git-auth
+      secret:
+        secretName: "{{ git_auth_secret }}"
+    - name: gitops-auth
+      secret:
+        secretName: $(params.gitops-auth-secret-name)
+    - name: workspace
+      volumeClaimTemplate:
+        spec:
+          accessModes:
+            - ReadWriteOnce
+          resources:
+            requests:
+              storage: 1Gi

Containerfile

@@ -0,0 +1,8 @@
+FROM registry.access.redhat.com/ubi9/python-311:1-77.1726664316
+WORKDIR /locallm
+COPY requirements.txt /locallm/requirements.txt
+RUN pip install --upgrade pip && \
+    pip install --no-cache-dir --upgrade -r requirements.txt
+COPY object_detection_client.py object_detection_client.py
+EXPOSE 8501
+ENTRYPOINT [ "streamlit", "run", "object_detection_client.py" ]

catalog-info.yaml

@@ -0,0 +1,23 @@
+apiVersion: backstage.io/v1alpha1
+kind: Component
+metadata:
+  name: test-2-resnet 
+  description: Secure Supply Chain Example for Object Detection Application   
+  links:
+    - url: https://www.redhat.com/en/solutions/trusted-software-supply-chain
+      title: Trusted Secure Supply Chain 
+      icon: dashboard
+      type: admin-dashboard
+  annotations:
+    # ArgoCD apps from this template used rhtap-gitops as the grouping
+    argocd/app-selector: rhtap/gitops=test-2-resnet  
+    janus-idp.io/tekton: test-2-resnet 
+    backstage.io/kubernetes-id: test-2-resnet 
+    backstage.io/techdocs-ref: dir:. 
+    quay.io/repository-slug: jdubrick-ai/test-2-resnet
+  tags: ["ai", "detr", "python"] 
+spec:
+  type: service
+  owner: user:guest 
+  lifecycle: experimental
+

docs/gitops-application.md

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+# ai-lab-template-gitops
+
+# Gitops Repo Patterns
+
+This repository contains an HTTP Gitops repository format component for use as the AI-Lab Gitops template.
+
+## HTTP
+
+This contains a deployment with the following characteristics:
+
+**Model service image** `quay.io/redhat-ai-dev/object_detection_python:latest` **listening on port** `8000`.
+
+**App interface image** `quay.io/redhat-ai-dev/ai-template-bootstrap-app:latest` **listening on port** `8501` for service and routing.
+
+This matches the current AI-Lab software template default deployment.

docs/index.md

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+# AI Software Template
+
+This application, test-2-resnet, is created from an AI Software Template. These software templates create a new source code repository as well as a new GitOps deployment repository.
+
+The chosen sample source applicable is included in the source code repository.
+
+## Sample Source Application
+
+A DEtection TRansformer (DETR) model streamlit application. Upload an image to identify and locate objects in the image.
+
+## Repositories
+
+The source code for your application can be found in [https://github.com/jdubrick-ai/test-2-resnet ](https://github.com/jdubrick-ai/test-2-resnet ).
+
+The GitOps repository, which contains the Kubernetes manifests for the application can be found in 
+[https://github.com/jdubrick-ai/test-2-resnet-gitops ](https://github.com/jdubrick-ai/test-2-resnet-gitops ). 
+
+## Application namespaces 
+
+The default application is found in the namespace: **`rhdh-app`**. Applications can be deployed into their own unique namespace or multiple software templates can generate numerous applications into the same namespace.

docs/pipelines.md

@@ -0,0 +1,22 @@
+# docker-build-ai-rhdh
+
+## Shared Git resolver model for shared pipeline and tasks
+
+This pipeline is used to create Containerfile based SSCS (Software Supply Chain Security) builds. The pipeline run by this runner clones the source, builds an image with SBOM (Software Bill of Materials), attests, and pushes these to the users image registry.  
+
+Tasks references come from this [repository](https://github.com/redhat-ai-dev/rhdh-pipelines) `pac/pipelines` and the tasks are defined in `pac/tasks`. The tasks are referenced by URL using the git resolver in tekton. 
+
+When the pipelines in this repository are updated, all future runs in existing pipelines are shared.
+
+A developer can override these tasks with a local copy and updated annotations. 
+
+Example 
+
+To override the git-clone task, you may simply copy the git reference into your .tekton directory and then reference it from the remote task annotation. 
+
+`pipelinesascode.tekton.dev/task-0: ".tekton/git-clone.yaml"` 
+
+## Templates 
+These pipelines are in template format. The references to this repository in the PaC template is `{{values.rawUrl}}` which is updated to point to this repo or the fork of this repo.
+
+The intent of the template is to fork this repository and update its use in the Developer Hub templates directory. 

docs/rhoai.md

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+# Running Samples in OpenShift AI
+
+This document outlines how you can build and run your sample applications within an OpenShift AI workbench.
+
+## Prerequisites
+
+- Red Hat OpenShift AI installed, and `Create workbench for OpenShift AI` selected during component creation.
+- `oc` cli installed
+   - `oc` can be downloaded from https://mirror.openshift.com/pub/openshift-v4/clients/ocp/stable/
+- Permissions to run `oc port-forward` on the cluster, specifically an account with the following roles:
+   - `get`, `create`, and `list` for the `pods/portforward` subresource
+
+## Running the Sample
+
+1) On the Console, click the square "apps" icon on the upper-right corner (next to the notifications icon). `Openshift AI` is listed in the drop-down list.
+
+![image](./images/access-openshift-ai.png)
+
+2) Go to the `Data Science Projects` section and access your application's project named `rhdh-app`.
+
+![image](./images/data-science-projects.png)
+
+3) Access the `workbench` named `test-2-resnet-notebook`.
+
+![image](./images/access-workbench.png)
+
+4) Go to `File->Open` and select `Terminal`.
+
+![image](./images/open-terminal.png)
+
+5) In the terminal, run `cd test-2-resnet` to navigate to your sample app's directory.
+
+6) Run `pip install --upgrade -r requirements.txt` to install the dependencies for your application.
+
+7) Run `streamlit run object_detection_client.py` to run the sample in the workbench.
+
+## Accessing the Sample
+
+With the sample app now running, complete the following steps to access the sample app in your browser:
+
+1) Go to the OpenShift AI dashboard, and find the name of your workbench.
+![image](./images/workbench-name.png)
+
+2) In a terminal window on your machine, run `oc get pods -l app=<workbench-name>`. This retrieves the name of the pod where the workbench is running.
+
+3) Run `oc port-forward <pod-name> 8501` to port forward the sample application's port to your local machine.
+
+4) Finally, visit `http://localhost:8501` in your browser to access the application.

docs/source-component.md

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+#  AI-lab samples
+
+## Usage in AI-lab templates
+
+This repository is being used in [ai-lab-template](https://github.com/redhat-ai-dev/ai-lab-template) as component source code for users to start with.
+
+This is a copy of the ai lab sample apps source code. The master copy of those apps are under [ai-lab-recipes](https://github.com/containers/ai-lab-recipes)
+
+To pull in the latest changes, run `./pull-sample-app.sh`, and commit the changes.

mkdocs.yml

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+site_name: 'Documentation'
+
+nav:
+  - Home: index.md
+  - Source Component: source-component.md
+  - Pipelines: pipelines.md
+  - GitOps Application: gitops-application.md
+  - OpenShift AI: rhoai.md
+
+plugins:
+  - techdocs-core

object_detection_client.py

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+import streamlit as st
+import base64
+import requests
+from PIL import Image
+import os
+import io
+
+st.title("🕵️‍♀️ Object Detection")
+endpoint =os.getenv("MODEL_ENDPOINT", default = "http://0.0.0.0:8000")
+endpoint_bearer = os.getenv("MODEL_ENDPOINT_BEARER")
+headers = {"accept": "application/json",
+           "Content-Type": "application/json"}
+if endpoint_bearer:
+    headers["Authorization"] = f"Bearer {endpoint_bearer}"
+image = st.file_uploader("Upload Image")
+window = st.empty()
+
+if image:            
+    #Ensure image dimensions are appropriate
+    img = Image.open(io.BytesIO(image.read()))
+    scale_factor = (500 * 500)/(img.height * img.width)
+    if scale_factor < 0.20:
+        scale_factor = 0.20
+    img = img.resize((int(img.width * scale_factor) , 
+                int(img.height * scale_factor)))
+    window.image(img, use_column_width=True)  
+    # convert PIL image into bytes for post request 
+    bytes_io = io.BytesIO() 
+    if img.mode in ("RGBA", "P"): 
+        img = img.convert("RGB")
+    img.save(bytes_io, "JPEG")
+    img_bytes = bytes_io.getvalue()
+    b64_image = base64.b64encode(img_bytes).decode('utf-8')
+    data = {'image': b64_image}
+    response = requests.post(f'{endpoint}/detection', headers=headers,json=data, verify=False)
+    # parse response and display outputs
+    response_json = response.json()
+    image = response_json["image"]
+    window.image(base64.b64decode(image), use_column_width=True)
+    for box in response_json["boxes"]:
+        st.markdown(box)