William Caban Babilonia williamcaban

Kubernetes Gateway API implementation that covers the OpenAI Responses API endpoints based on the current documentation.

Core Response Operations:

POST /v1/responses - Create new responses with input, model, and tools
GET /v1/responses/{id} - Retrieve response by ID
GET /v1/responses/{id} (with Accept: text/event-stream) - Stream responses in real-time
POST /v1/responses/{id} - Continue/extend existing responses
DELETE /v1/responses/{id} - Delete responses

RAGAS Evaluation with Kubeflow Pipelines - Setup Guide

About

The ragas_pipeline.py is a Kubeflow Pipeline (KFP) definition on how to run RAGAS evaluations using KFP.

This pipeline is designed as an example pipeline with charactersitics expected for production environments like proper resource management, monitoring capabilities, and comprehensive documentation. You should adjust the components based on your specific RAG evaluation needs and infrastructure setup.

Key Components:

RHEL AI 1.1 as Inference Endpoint

Step 1. Update the host_port key serve section of the config.yaml to listen in all interfaces.

...
serve:
  backend: vllm
  chat_template: auto
 host_port: 0.0.0.0:8000

Installing the Redis Operator

# create namespace for operator
oc create ns redis-operator

# register Helm repo
helm repo add ot-helm https://ot-container-kit.github.io/helm-charts/

# install redis-operator using helm
helm upgrade redis-operator ot-helm/redis-operator \

Static routes in MacOS

Find the name of the network adapters

# List network interface name
networksetup -listallnetworkservices

An asterisk (*) denotes that a network service is disabled.
USB 10/100/1000 LAN

	import csv
	import os

	def convert_1password_to_apple(input_file, output_file):
	"""
	Convert a 1Password CSV export file to a format compatible with Apple Passwords.

	Apple Passwords import format requires the following columns:
	- Title
	- URL

	from datasets import load_dataset

	# Combine 'question' and 'answer' into a single 'text' field
	def combine_qa(local_dataset):
	local_dataset['text'] = f"User: {local_dataset['Question']}\nAssistant: {local_dataset['Answer']}"
	return local_dataset

	####################################################################################
	# main
	####################################################################################

	#
	import sys, json
	from pathlib import Path
	from datetime import datetime

	import pandas as pd

	TSTAMP = datetime.now().replace(microsecond=0).isoformat().replace(":", '_')
	ILABGEN = "granite-7b-lab-7b-Q4_K_M"+f"_{TSTAMP}"
	DEBUG = True

	---
	apiVersion: ingressnodefirewall.openshift.io/v1alpha1
	kind: IngressNodeFirewallConfig
	metadata:
	name: ingressnodefirewallconfig
	namespace: openshift-ingress-node-firewall
	spec:
	nodeSelector:
	node-role.kubernetes.io/control-plane: ""
	---