bioshazard

git config --global alias.nb '!f() { git fetch origin && git checkout -b "$1" origin/${2:-master} --no-track; }; f'
git config --global --type bool push.autoSetupRemote true

bioshazard

#!/bin/bash

# MCPO CLI - Efficient MCP OpenAPI Proxy Client
# Usage: ./mcpo.sh <command> [args...]

set -e

# Configuration
MCPO_HOST="${MCPO_HOST:-http://localhost:8000}"
MCPO_TOKEN="${MCPO_TOKEN:-supersecret}"

bioshazard

import os
import re
from typing import Callable, Any
from youtube_transcript_api import YouTubeTranscriptApi
from youtube_transcript_api.formatters import TextFormatter

class EventEmitter:
    def __init__(self, event_emitter: Callable[[dict], Any] = None):
        self.event_emitter = event_emitter

bioshazard

INPUT=$1

# TY https://github.com/paulpaul999/vr-video-notes/blob/main/vr-to-flat/README.md
ffmpeg -i $INPUT -filter_complex "
[0:v]crop=iw/2:ih:0:0[left];
[0:v]crop=iw/2:ih:iw/2:0[right];
[left]v360=input=hequirect:output=flat:d_fov=125:w=1920:h=1080:pitch=0[flattened_left];
[right]v360=input=hequirect:output=flat:d_fov=125:w=1920:h=1080:pitch=0[flattened_right]
" \
-map "[flattened_left]" -c:v libx265 -crf 18 -pix_fmt yuv420p flattened_left.mp4 \

bioshazard

# BOOK_SRC=mp3s/what-govt-has-done-to-our-money  BOOK_DEST=What-Government-Has-Done-To-Our-Money.m4b bash m4b-tool.sh
docker run -it --rm -u $(id -u):$(id -g) -v "$(pwd)":/mnt sandreas/m4b-tool:latest \
  merge -vv --jobs=3 --ffmpeg-threads=3 "/mnt/$BOOK_SRC" --output-file="/mnt/$BOOK_DEST"

bioshazard

import https from 'https';
import request from 'request';
import fs from 'fs';
import bodyParser from 'body-parser';

var jsonParser = bodyParser()

const backend = {
  'proto': 'https',
  'host': 'your-instance-name.openai.azure.com'

bioshazard

This paste.txt is a transcript of a podcast episode. Generate a concise descriptive non-click-baity podcast title. Also generate a concise descriptive non-click-baity episode description using "we" language like "we cover ...". Finally, provide a concise representative bullet list of topics along with when those topics start based on timestamp in format "- HH:MM:SS ".

bioshazard

Use custom upstream DNS with CoreDNS

In my use case, I run a K3D cluster in my home and wanted to resolved my local .home.arpa domain hosts (eg ponics.home.arpa) via my router DNS from the pods rather than setting static IPs in DHCP and manifests.

The solution was pretty simple: update in kubectl edit cm/coredns -n kube-system to replace in forward . 192.168.0.1 so domains not handled by CoreDNS used my router as the upstream.

bioshazard

const markdownComponents = {
  code: CodeBlock, // look up how to use Syntax Highlighter etc, this gist is really just for the rest of the elements
  p: ({ children }) => <p className='py-2'>{children}</p>,
  // li: ({ children }) => <li className='list-disc ml-6'>{children}</li>,
  h1: ({ children }) => <h1 className='text-2xl font-bold py-2'>{children}</h1>,
  h2: ({ children }) => <h2 className='text-xl font-bold py-2'>{children}</h2>,
  h3: ({ children }) => <h3 className='text-lg font-bold py-2'>{children}</h3>,
  h4: ({ children }) => <h4 className='text-base font-bold py-2'>{children}</h4>,
  h5: ({ children }) => <h5 className='text-sm font-bold py-2'>{children}</h5>,
  em: ({ children }) => <em className='italic'>{children}</em>,

bioshazard

# WIP attempt at summarizing a podcast given a timestamped transcript
# https://python.langchain.com/en/latest/modules/chains/index_examples/summarize.html
import os
from langchain import OpenAI, PromptTemplate, LLMChain
from langchain.text_splitter import CharacterTextSplitter
from langchain.chains.mapreduce import MapReduceChain
from langchain.prompts import PromptTemplate
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.docstore.document import Document
from langchain.chains.summarize import load_summarize_chain