@router.get("/think/k8s")
def think_k8s():
    """
    Fetch Kubernetes data, send it to the AI API, and return the AI-generated summary.
    """
    config.load_incluster_config()
    v1 = client.CoreV1Api()

    cluster_name = "k8s-cluster"

    # Format node data
    nodes = []
    for node in v1.list_node().items:
        # Fetch ephemeral-storage and instance type
        ephemeral_storage = node.status.capacity.get("ephemeral-storage", "0")
        instance_type = node.metadata.labels.get("beta.kubernetes.io/instance-type", "N/A")

        nodes.append({
            "name": node.metadata.name,
            "cpu": f"{node.status.capacity.get('cpu')} cores",
            "memory": f"{round(int(node.status.capacity.get('memory').replace('Ki', '')) / 1024 / 1024, 2)} GB",
            "storage": f"{round(int(ephemeral_storage.replace('Ki', '')) / (1024 ** 2), 2)} GB",
            "type": instance_type,
            "namespaces": [ns.metadata.name for ns in v1.list_namespace().items]
        })

    # Fetch environment variables
    api_url = os.getenv("AI_API_URL")
    auth_token = os.getenv("AI_API_TOKEN")

    if not api_url or not auth_token:
        raise HTTPException(status_code=500, detail="AI API URL or token is not set. Please set AI_API_URL and AI_API_TOKEN environment variables.")

    # Call AI API
    summary = fetch_ai_summary(cluster_name, nodes, api_url, auth_token)

    return {"summary": summary}