lucataco

name	description
replicate-mcp	Configure and validate Replicate MCP connectivity in Codex using REPLICATE_API_TOKEN and the official replicate-mcp server package. Use when setting up Replicate MCP for the first time, reconnecting after auth/config changes, or troubleshooting missing Replicate MCP tools.

Replicate MCP

Use this skill to set up and verify Replicate MCP access in Codex with minimal back-and-forth.

Workflow

lucataco

#!/bin/bash
# Update
sudo apt-get update

# Install tools
sudo apt install nvidia-cuda-toolkit

# Install cog
sudo curl -o /usr/local/bin/cog -L "https://github.com/replicate/cog/releases/latest/download/cog_$(uname -s)_$(uname -m)"
sudo chmod +x /usr/local/bin/cog

lucataco

palette = 0=#23272e
palette = 1=#f38020
palette = 2=#a8e6a3
palette = 3=#faae40
palette = 4=#4da6ff
palette = 5=#ff80ab
palette = 6=#66d9ef
palette = 7=#c0c5ce
palette = 8=#4f5b66
palette = 9=#f38020

lucataco

# Replace /etc/docker/daemon.json docker config in Brev.dev Crusoe GPUs
{
    "default-runtime": "nvidia",
    "mtu": 1500,
    "runtimes": {
        "nvidia": {
            "args": [],
            "path": "nvidia-container-runtime"
        }
    },

lucataco

#!/bin/bash

# This is local cli command that allows users to use kokoro on a Macbook Pro
# Requires you to first run the kokoro docker container:
docker run -p 8880:8880 ghcr.io/remsky/kokoro-fastapi-cpu:latest
# Then save this file to /usr/local/bin
# Finally you can test:
kokoro "The quick brown fox jumped over the lazy dog"
# Or even pipe from a stream like:
llm "tell me a joke" | kokoro

lucataco

# Setup:
# conda create -n wan python=3.10
# conda activate wan
# pip3 install torch torchvision torchaudio
# pip install git+https://github.com/huggingface/diffusers.git@3ee899fa0c0a443db371848a87582b2e2295852d 
# pip install accelerate==1.4.0
# pip install transformers==4.49.0
# pip install ftfy==6.3.1

lucataco

services:
  pihole-unbound:
    image: 'bigbeartechworld/big-bear-pihole-unbound:2024.07.0'
    environment:
      - SERVICE_FQDN_PIHOLE_8080
      - SERVICE_FQDN_PIHOLE_10443
      - 'DNS1=127.0.0.1#5353'
      - DNS2=no
      - TZ=America/Chicago
      - WEBPASSWORD=$SERVICE_PASSWORD_PIHOLE

lucataco

from optimum.quanto import freeze, qfloat8, quantize
from diffusers import FluxPipeline
import torch
import time

seed=1337
generator = torch.Generator("cuda").manual_seed(seed)

pipeline = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16).to("cuda")

lucataco

# conda create -n flux python=3.11
# conda activate flux
# pip install torch==2.3.1
# pip install diffusers==0.30.0 transformers==4.43.3
# pip install sentencepiece==0.2.0 accelerate==0.33.0 protobuf==5.27.3

import torch
from diffusers import  FluxPipeline
import diffusers

lucataco

import torch
import random

random.seed(42)
torch.manual_seed(42)


from transformers import LlamaTokenizer, LlamaForCausalLM
model_path = 'openlm-research/open_llama_3b_v2'
tokenizer = LlamaTokenizer.from_pretrained(model_path, legacy=True);