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## llm-hackathon.md

      
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                mseri
                / llm-hackathon.md
            
            
              Created
              July 8, 2025 15:31
                — forked from chriscarrollsmith/llm-hackathon.md
            
              
                Coders' Colaboratory mini-hackathon on `llm` by simonw
              
          
    Let's hack on llm!

If you have uv installed (and you should!), you can install llm globally in a uv-managed tool environment with:
uv tool install llm
If you want to use models other than OpenAI models, you'll need some extensions:

  
## TextRecognizer.swift
#!/usr/bin/swift
// Started from the code in https://terminalbytes.com/iphone-8-solar-powered-vision-ocr-server/
// Edited from Mistral generated code: https://chat.mistral.ai/chat/563cacdf-6def-49e4-9df6-ee8e263978c5
import AppKit
import CoreGraphics
import Foundation
import SwiftUI
import Vision

func processImageSync(imagePath: String) -> String? {

## lms_to_llm.py
import requests
import subprocess
import yaml

def get_data_from_api():
    base_url = "http://localhost:1234/v1"
    response = requests.get(base_url + "/models")

    if response.status_code == 200:
        json_data = response.json()

## code_completion_ide.py
import sys
from io import StringIO

import streamlit as st              # pip install streamlit
from code_editor import code_editor # pip install streamlit_code_editor
import ollama as ol                 # pip install ollama

st.set_page_config(layout='wide')
st.title('`Offline code completion`')

## l3min.py
"""
A minimal, fast example generating text with Llama 3.1 in MLX.

To run, install the requirements:

    pip install -U mlx transformers fire

Then generate text with:

    python l3min.py "How tall is K2?"

## chat-interface.html
<!doctype html>
<html lang="en">
    <head>
        <meta charset="UTF-8" />
        <meta name="viewport" content="width=device-width, initial-scale=1.0" />
        <title>LM Studio Chat Interface</title>
        <style>
            body {
                font-family: -apple-system, BlinkMacSystemFont, "Segoe UI",
                    Roboto, sans-serif;

## ollama-export.go
package main

import (
	"encoding/json"
	"fmt"
	"io/ioutil"
	"os"
	"os/user"
	"path/filepath"
	"strings"

## ollama-export.sh
#!/bin/bash
# Ollama Model Export Script
# Usage: bash ollama-export.sh vicuna:7b
# License: MIT (https://ncurl.xyz/s/o_o6DVqIR)
# https://gist.github.com/supersonictw/f6cf5e599377132fe5e180b3d495c553

# Interrupt if any error occurred
set -e

# Declare

## htm_to_md.sh
# Faster but not private way to achive the above
# is to define a bash function and source it at startup
function html_to_md () {
  if [[ $# -eq 2 ]]; then
    curl "https://r.jina.ai/$1" > "$2".md
    echo "Content saved to \"$2\".md"
  else
    curl "https://r.jina.ai/$@"
  fi
}

## lwarp-tips.md

      
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                mseri
                / lwarp-tips.md
            
            
              Created
              August 3, 2024 21:41
                — forked from DominikPeters/lwarp-tips.md
            
              
                Some tips for using lwarp for Latex to HTML conversion
              
          
    Replace natbib by biblatex to get citation links
\usepackage[backend=bibtex, style=authoryear-comp, natbib=true, sortcites=false]{biblatex}
\addbibresource{main.bib}

% optional if you want (Smith 1776) instead of (Smith, 1776)
\renewcommand*{\nameyeardelim}{\addspace}

\begin{document}
	#!/usr/bin/swift
	// Started from the code in https://terminalbytes.com/iphone-8-solar-powered-vision-ocr-server/
	// Edited from Mistral generated code: https://chat.mistral.ai/chat/563cacdf-6def-49e4-9df6-ee8e263978c5
	import AppKit
	import CoreGraphics
	import Foundation
	import SwiftUI
	import Vision

	func processImageSync(imagePath: String) -> String? {
	import requests
	import subprocess
	import yaml

	def get_data_from_api():
	base_url = "http://localhost:1234/v1"
	response = requests.get(base_url + "/models")

	if response.status_code == 200:
	json_data = response.json()
	import sys
	from io import StringIO

	import streamlit as st # pip install streamlit
	from code_editor import code_editor # pip install streamlit_code_editor
	import ollama as ol # pip install ollama

	st.set_page_config(layout='wide')
	st.title('`Offline code completion`')
	"""
	A minimal, fast example generating text with Llama 3.1 in MLX.

	To run, install the requirements:

	pip install -U mlx transformers fire

	Then generate text with:

	python l3min.py "How tall is K2?"
	<!doctype html>
	<html lang="en">
	<head>
	<meta charset="UTF-8" />
	<meta name="viewport" content="width=device-width, initial-scale=1.0" />
	<title>LM Studio Chat Interface</title>
	<style>
	body {
	font-family: -apple-system, BlinkMacSystemFont, "Segoe UI",
	Roboto, sans-serif;
	package main

	import (
	"encoding/json"
	"fmt"
	"io/ioutil"
	"os"
	"os/user"
	"path/filepath"
	"strings"
	#!/bin/bash
	# Ollama Model Export Script
	# Usage: bash ollama-export.sh vicuna:7b
	# License: MIT (https://ncurl.xyz/s/o_o6DVqIR)
	# https://gist.github.com/supersonictw/f6cf5e599377132fe5e180b3d495c553

	# Interrupt if any error occurred
	set -e

	# Declare
	# Faster but not private way to achive the above
	# is to define a bash function and source it at startup
	function html_to_md () {
	if [[ $# -eq 2 ]]; then
	curl "https://r.jina.ai/$1" > "$2".md
	echo "Content saved to \"$2\".md"
	else
	curl "https://r.jina.ai/$@"
	fi
	}