Rustam Salavatov fortunto2

from https://chatgpt.com/g/g-VJkoWzcmd-srt2edl-summarizer

This GPT processes SRT or text files with timecodes, specifically from YouTube videos, to create an Edit Decision List (EDL) with summarized highlight ideas. The goal is to scan through timestamps, generate summaries of the segments, and structure the content in an EDL format that is suitable for post-production use. It can extract the most relevant information from each clip and format it into a cohesive timeline, including clip details, highlights, and timestamps, ensuring an organized editing flow.

EDL (Edit Decision List) Generation Rules

Overview: An Edit Decision List (EDL) is used to describe how video clips are edited and compiled into a final sequence. It specifies which portions of a source video are included in the edit, their start and end times, and where they appear in the final timeline.

Each line in an EDL entry includes:

Clip Number: Identifies the sequence of clips in the final edit.

	from telethon import TelegramClient
	from telethon.tl.functions.messages import GetHistoryRequest
	from datetime import datetime, timedelta, timezone
	import asyncio

	# Replace with your own API_ID and API_HASH
	API_ID = '****'
	API_HASH = '****'
	CHANNEL_USERNAME = '****' # Example: '@channel_name'

	{% load static %}
	<!doctype html>
	<html lang="en">
	<head>
	<title>Markers Map</title>
	<meta name="viewport" content="width=device-width, initial-scale=1.0">
	<link rel="stylesheet" type="text/css" href="{% static 'map.css' %}">
	<link rel="stylesheet" type="text/css" href="https://unpkg.com/[email protected]/dist/leaflet.css">
	<script src="https://code.jquery.com/jquery-3.6.0.min.js" integrity="sha256-/xUj+3OJU5yExlq6GSYGSHk7tPXikynS7ogEvDej/m4=" crossorigin="anonymous"></script>
	<script src="https://unpkg.com/[email protected]/dist/leaflet.js"></script>

	## @section Global parameters
	## Global Docker image parameters
	## Please, note that this will override the image parameters, including dependencies, configured to use the global value
	## Current available global Docker image parameters: imageRegistry, imagePullSecrets and storageClass

	## @param global.imageRegistry Global Docker image registry
	## @param global.imagePullSecrets Global Docker registry secret names as an array
	## @param global.storageClass Global storage class for dynamic provisioning
	##
	global:

	mongodump --host localhost --port 27017 --username root --password XXXX --authenticationDatabase admin -d XXXX --gzip --archive > dump_`date "+%Y-%m-%d"`.gz
	mongorestore --archive="mongodump-test-db" --nsFrom='test.' --nsTo='examples.'

	#### build mongo dumper
	git clone https://github.com/mongodb/mongo-tools
	cd mongo-tools
	sudo apt-get install -y libkrb5-dev
	./make build -tools=mongodump,mongorestore

	.PHONY: help


	help:
	@grep -E '^[a-zA-Z_-]+:.?## .$$' $(MAKEFILE_LIST) \| sort \| awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
	.DEFAULT_GOAL := help

	vpn: ## Запускает
	@wg-quick up /etc/wireguard/wg0.conf

	#!/bin/sh

	# https://askubuntu.com/questions/856460/using-a-digital-camera-canon-as-webcam

	sudo modprobe v4l2loopback
	gphoto2 --abilities
	gphoto2 --stdout --capture-movie \| ffmpeg -i - -vcodec rawvideo -pix_fmt yuv420p -threads 0 -f v4l2 /dev/video0

	import json
	from fractions import Fraction
	from pprint import pprint
	from django.core import exceptions
	from django.contrib.postgres.fields import JSONField
	from psycopg2.extras import Json

	import orjson
	from pydantic.json import custom_pydantic_encoder


	#!/bin/bash
	# Removes old revisions of snaps
	# CLOSE ALL SNAPS BEFORE RUNNING THIS
	set -eu

	snap list --all \| awk '/disabled/{print $1, $3}' \|
	while read snapname revision; do
	snap remove "$snapname" --revision="$revision"
	done

	FROM traefik:v2.2
	RUN touch acme.json
	RUN chmod 600 acme.json