Pavel Diatchenko diatche

## ollama-langchain.py
# Ask questions about a document using Ollama and Langchain.
# This leverages a local LLM to provide insights into any document.
# It's far from perfect, as it's power is limited by the LLM size.

# It leverages the langchain library to perform tasks like document loading,
# text splitting, embedding generation, and using the Ollama client for generating answers.

# You need to have Ollama installed (with model llama2:13b available). See https://github.com/jmorganca/ollama

# Usage:

## transcribe.py
import argparse
import subprocess
import os
import math
from openai import OpenAI

MAX_SIZE = 26214400  # Maximum file size (in bytes)

# Parse command line arguments
parser = argparse.ArgumentParser(

## revolut-csv.py
#!/bin/python3

# Converts Revolut CSV format into a CSV table
# format which is easier for automated processing.
#
# Removes the following categories automatically:
# general, transfers
#
# Usage:
#

## swedbank-csv.py
#!/bin/python3

# Converts Swedbank CSV format into a CSV table
# format which is easier for automated processing.
#
# Usage:
#
# 1. Save file as swedbank-csv.py and open terminal in folder location.
# 2. In termial: python3 swedbank-csv.py -i <path to source CSV>
# 3. For more info, run: python3 swedbank-csv.py --help

## recall-test.html
<script src="https://cdn.jsdelivr.net/gh/amark/gun@master/gun.js"></script>
<script src="https://cdn.jsdelivr.net/gh/amark/gun@master/sea.js"></script>
<!-- <script src="https://cdn.jsdelivr.net/npm/gun/gun.js"></script>
<script src="https://cdn.jsdelivr.net/npm/gun/sea.js"></script> -->
<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.15/lodash.min.js"></script>
<script>
;(() => {
    // Reset by uncommenting the next line, run once and comment out again.
    // sessionStorage.clear();
    localStorage.clear();

## slack_cleaner.py
# Deletes old bot Slack messages using slack_cleaner2
# https://github.com/sgratzl/slack-cleaner
# Usage:
# 1. Install slack_cleaner2 and Arrow
# 2. Run with token as CLI arg. E.g. `python slack_cleaner.py <token xoxp-...>`

import arrow
import time
import sys
from slack_cleaner2 import *

## li.html
<html><body>
<style>
  html, body {
    background: rgb(245, 245, 245);
    margin: 0;
    padding: 0;
  }
  div {
    position: relative;
    overflow: hidden;
	# Ask questions about a document using Ollama and Langchain.
	# This leverages a local LLM to provide insights into any document.
	# It's far from perfect, as it's power is limited by the LLM size.

	# It leverages the langchain library to perform tasks like document loading,
	# text splitting, embedding generation, and using the Ollama client for generating answers.

	# You need to have Ollama installed (with model llama2:13b available). See https://github.com/jmorganca/ollama

	# Usage:
	import argparse
	import subprocess
	import os
	import math
	from openai import OpenAI

	MAX_SIZE = 26214400 # Maximum file size (in bytes)

	# Parse command line arguments
	parser = argparse.ArgumentParser(
	#!/bin/python3

	# Converts Revolut CSV format into a CSV table
	# format which is easier for automated processing.
	#
	# Removes the following categories automatically:
	# general, transfers
	#
	# Usage:
	#
	#!/bin/python3

	# Converts Swedbank CSV format into a CSV table
	# format which is easier for automated processing.
	#
	# Usage:
	#
	# 1. Save file as swedbank-csv.py and open terminal in folder location.
	# 2. In termial: python3 swedbank-csv.py -i <path to source CSV>
	# 3. For more info, run: python3 swedbank-csv.py --help
	<script src="https://cdn.jsdelivr.net/gh/amark/gun@master/gun.js"></script>
	<script src="https://cdn.jsdelivr.net/gh/amark/gun@master/sea.js"></script>
	<!-- <script src="https://cdn.jsdelivr.net/npm/gun/gun.js"></script>
	<script src="https://cdn.jsdelivr.net/npm/gun/sea.js"></script> -->
	<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.15/lodash.min.js"></script>
	<script>
	;(() => {
	// Reset by uncommenting the next line, run once and comment out again.
	// sessionStorage.clear();
	localStorage.clear();
	# Deletes old bot Slack messages using slack_cleaner2
	# https://github.com/sgratzl/slack-cleaner
	# Usage:
	# 1. Install slack_cleaner2 and Arrow
	# 2. Run with token as CLI arg. E.g. `python slack_cleaner.py <token xoxp-...>`

	import arrow
	import time
	import sys
	from slack_cleaner2 import *
	<html><body>
	<style>
	html, body {
	background: rgb(245, 245, 245);
	margin: 0;
	padding: 0;
	}
	div {
	position: relative;
	overflow: hidden;