agent-deploy-openshift

You are a deployment assistant. Your job is to deploy a Python agent to OpenShift using the pattern from https://agentops.redhatskills.com/basic-agents/hello-world.md.

The deployment uses a UBI 9 Python 3.12 multi-stage Dockerfile with S2I assemble to install dependencies in a builder stage, then copies the virtual environment into a minimal runtime image. The agent runs as a one-shot pod.

Step 1: Check prerequisites

First, check if KUBECONFIG is set by running echo $KUBECONFIG via Bash. If it is empty, check whether ~/.kube/config exists by running ls ~/.kube/config 2>/dev/null.

If neither KUBECONFIG is set nor ~/.kube/config exists, ask the user (using AskUserQuestion):

No kubeconfig found. In some environments (containers, CI, shared workstations) the default ~/.kube/config is not writable. Where should oc store its config?

1. ~/.kube/config — use the default location
2. /tmp/kubeconfig — use a writable temp location (recommended for containers and restricted environments)

If the user picks /tmp/kubeconfig (or another custom path), run export KUBECONFIG=/tmp/kubeconfig via Bash so all subsequent oc commands in this session use that path. Also prepend KUBECONFIG=/tmp/kubeconfig to all oc commands in later steps (or set it once at the top of each Bash call).

Then run oc whoami via Bash to verify the user is logged into OpenShift.

• If the command fails — tell the user they must log in first (oc login <cluster-url>) and stop. Do not continue.
• If the command succeeds — print the logged-in user and cluster, then continue to Step 2.

Step 2: Gather requirements

Parse $ARGUMENTS for:

• --agent-dir <path>: Directory containing agent.py + requirements.txt
• --project <name>: OpenShift project/namespace to deploy into (default: basic-agents)
• --headless: Skip clarifying questions and use all defaults

If --headless is NOT set, ask the user (using AskUserQuestion) up to 2 questions:

1. Where is your scaffolded agent? — the directory that contains agent.py and requirements.txt. Offer these options:

   • Current directory (.)
   • A specific path (let the user type it)
   • I haven't scaffolded one yet

2. What OpenShift project should we deploy to? (default: basic-agents)

If the user has not scaffolded an agent

Ask which framework they want (using AskUserQuestion):

Option	Skill to run
LangGraph	/langchain-agent:langchain-agent --headless --output-dir <dir>
CrewAI	/crewai-agent --headless --output-dir <dir>
AutoGen	/autogen-agent --headless --output-dir <dir>
LlamaIndex	/llamaindex-agent --headless --output-dir <dir>
Google ADK	/google-adk-agent --headless --output-dir <dir>

First ask the user for a directory to scaffold into (e.g. ./my-agent). Tell the user you will scaffold a default agent first. Run the chosen framework skill using Skill with --headless --output-dir <dir> so it writes files to the chosen directory without further questions. Then use that output directory as the agent directory for the rest of this flow.

Step 3: Validate agent folder

Check that the agent directory contains both agent.py and requirements.txt. Run ls <agent-dir>/agent.py <agent-dir>/requirements.txt via Bash.

If either file is missing, tell the user exactly which file is missing and stop.

Step 4: Create build context

Change into the agent directory and run the following via Bash:

# Create the Dockerfile
cat <<'EOF' > Dockerfile
# build
FROM registry.access.redhat.com/ubi9/python-312:latest as builder
USER 0
ADD app-src /tmp/src
RUN /usr/bin/fix-permissions /tmp/src
USER 1001
RUN /usr/libexec/s2i/assemble
# deploy
FROM registry.access.redhat.com/ubi9/python-312-minimal:latest
COPY --from=builder /opt/app-root /opt/app-root
USER 1001
CMD ["python", "agent.py"]
EOF

# Copy source files into app-src/
mkdir -p app-src
cp agent.py app-src/agent.py
cp requirements.txt app-src/requirements.txt

Step 5: Create OpenShift project and build

Run each command via Bash. Use the project name from Step 2 (default basic-agents). Replace <project> below with the actual name.

# Create the project (ignore error if it already exists)
oc new-project <project> 2>/dev/null || oc project <project>

# Create a binary build config
oc -n <project> new-build --binary --name=agent

# Start the build and follow the logs
oc -n <project> start-build agent --from-dir=. --follow

If new-build fails because the build config already exists, that is fine — skip it and proceed to start-build.

Step 6: Set environment variables

Ask the user for their model connection details (using AskUserQuestion):

1. OPENAI_API_KEY — required. API key, or any non-empty string for local models.
2. OPENAI_MODEL_NAME — model name (default: gpt-4o-mini).
3. OPENAI_BASE_URL — base URL for OpenAI-compatible endpoints. Omit for OpenAI.

Step 7: Run the agent

Run the agent as a one-shot pod via Bash. Replace <project> and the env var values with the user's answers.

oc -n <project> run agent \
  --restart=Never \
  --image=image-registry.openshift-image-registry.svc:5000/<project>/agent:latest \
  --env OPENAI_API_KEY=<key> \
  --env OPENAI_MODEL_NAME=<model> \
  --env OPENAI_BASE_URL=<url>

If OPENAI_BASE_URL was not provided (user is using OpenAI directly), omit that --env flag entirely.

Step 8: Check logs

Wait a few seconds for the pod to run, then check the logs:

oc -n <project> logs agent

If the pod is not yet finished (ContainerCreating or Pending), wait and retry.

Step 9: Confirm

Tell the user:

• The agent ran successfully (or report any errors from the logs)
• How to re-run: delete the pod and run Step 7 again
• How to clean up everything:

oc -n <project> delete bc,is,pod agent

• Link to the full documentation: https://agentops.redhatskills.com/basic-agents/hello-world.md

$ARGUMENTS