Ivan Fioravanti ivanfioravanti

Using Claude Code with various AI providers

Create various settings file I have one file for each provider, all in ~/.claude

KIMI K2.5: kimi_settings.json

{
  "env": {
    "ANTHROPIC_BASE_URL": "https://api.moonshot.ai/anthropic",

Create a single-page website for "PHANTOM PROTOCOL" — a fictional upcoming AAA tactical shooter video game set in a near-future cyberpunk world where elite hackers and mercenaries fight for control of a fractured megacity. Requirements:

Bold, immersive, cinematic design that feels like a AAA game landing page A full-screen hero section with a dramatic background image/video and the game logo/title A "Story" or "The World" section with atmospheric imagery and a brief narrative hook A "Characters" or "Operatives" section showcasing 3-4 playable characters with images and short bios A "Features" section highlighting 3 key gameplay elements (e.g., tactical combat, online multiplayer, dynamic environments) A "Pre-order" or "Wishlist" call-to-action section A footer with platform icons (PC, PlayStation, Xbox), social links, and age rating

Create a production-ready, visually stunning website with a futuristic luxury travel theme.

GOAL Build a single-page (plus optional “Destination” detail route) website for a fictional brand: “AURORA LUXE TRAVEL” — ultra-premium, concierge-level trips.

TECH STACK (use exactly this unless something breaks)

Next.js (latest stable) + TypeScript
Tailwind CSS
Framer Motion (for scroll/entrance animations)

Here the full prompt used:

Create a stunning, modern sports-car showcase website as a SINGLE self-contained HTML file (one page) with embedded CSS and JavaScript. Output ONLY the final HTML.

HARD REQUIREMENTS

Single file: index.html only. No external files.

Benchmarks for mlx-lm

The command for evaluating on MMLU Pro:

mlx_lm.evaluate --model model/repo --task mmlu_pro

The command for efficiency benchmarks:


	Benchmark started on 2025-10-19 22:52:10

	** Command line:
	/Users/ifioravanti/github/consumer-tflop-database/.venv/bin/python mamf-finder.py --m_range 0 16384 1024 --n_range 0 16384 1024 --k_range 0 16384 1024 --dtype bfloat16 --output_file=2025-10-19-22:52:09.txt

	** Dtype: torch.bfloat16

	** Platform/Device info:
	- Darwin MacStudioIvan 25.1.0 Darwin Kernel Version 25.1.0: Sun Oct 5 21:09:25 PDT 2025; root:xnu-12377.40.120~10/RELEASE_ARM64_T6031 arm64 arm

	"""Run four batched generations with varying sampling settings."""

	import argparse

	import mlx.core as mx

	from mlx_lm import batch_generate, load
	from mlx_lm.sample_utils import make_sampler

	#!/usr/bin/env python3
	"""
	MLX benchmark script that replicates llama-bench behavior exactly.
	Uses random tokens for both prompt and generation, no sampling.
	"""

	import mlx.core as mx
	import mlx_lm
	from mlx_lm.models.cache import make_prompt_cache
	import time

	import pygame
	import math
	import random

	# Initialize pygame
	pygame.init()

	# Screen dimensions
	WIDTH, HEIGHT = 800, 800
	screen = pygame.display.set_mode((WIDTH, HEIGHT))

	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8">
	<meta name="viewport" content="width=device-width, initial-scale=1.0">
	<title>P5.js Particle Animation</title>
	<script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.4.0/p5.min.js"></script>
	<style>
	body {
	margin: 0;