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Google Cloud Vision PDF OCR to Markdown

A Python script that extracts text from PDF documents using Google Cloud Vision API and converts tables to Markdown format. Optimized for French documents with ~95% accuracy.

Features

✨ High Accuracy OCR: Leverages Google Cloud Vision API for superior text recognition
📊 Table Detection: Automatically detects and converts tables to Markdown format
🇫🇷 Language Optimized: Configured for French documents (easily customizable)
📄 Multi-page Support: Handles PDFs of any size

Prerequisites

Install required packages:

pip install google-cloud-vision google-cloud-storage

Set up Google Cloud:
- Create a Google Cloud project

Enable the Cloud Vision API

Ollama + Open WebUI = Local LLM Server

Motivation

This guide helps you deploy a local Large Language Model (LLM) server on your Apple MacBook (Intel CPU or Apple Silicon (M-series)) with a user-friendly chat interface. By running LLMs locally, you ensure data privacy, improve reliability with offline capabilities, and leverage cutting-edge tools for efficient AI workflows

Prerequisites

macOS 11.0 or later (Intel, Apple Silicon (M-series))
At least 8 GB of RAM (16 GB recommended for optimal performance)

	#!/usr/bin/env python3
	# -- coding: utf-8 --
	"""
	rename_files.py - Rename files by removing accents and special chars, safe for UTF-8

	Usage:
	python3 rename_files.py <directory> [--dry-run]

	Features:
	- Normalizes accents (NFKD)

	#!/bin/bash

	set -e

	# Vérification des arguments
	if [ $# -ne 2 ]; then
	echo "Usage: $0 <nom_utilisateur> <cluster_endpoint>"
	echo "Exemple: $0 user01 https://11.22.33.44"
	exit 1
	fi

	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8">
	<meta name="viewport" content="width=device-width, initial-scale=1.0">
	<title>Markdown to Google Docs Converter</title>
	<script src="https://cdnjs.cloudflare.com/ajax/libs/marked/4.3.0/marked.min.js"></script>
	<script src="https://cdnjs.cloudflare.com/ajax/libs/dompurify/3.0.5/purify.min.js"></script>
	<style>
	* {


	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8">
	<meta name="viewport" content="width=device-width, initial-scale=1.0">
	<title>QR Code Generator</title>
	<style>
	body {
	font-family: Arial, sans-serif;

	/target/
	!.mvn/wrapper/maven-wrapper.jar

	### STS ###
	.apt_generated
	.classpath
	.factorypath
	.project
	.settings
	.springBeans

	stage("docker_scan avec clair"){
	sh '''
	docker rm db
	docker rm clair

	docker run -p 5432:5432 -d --name db arminc/clair-db:2021-01-08
	docker run -p 6060:6060 -d --name clair arminc/clair-local-scan:arminc/clair-local-scan:v2.1.6_3bfb31ea61aa42eeb836354976065ccea308707e

	clair-scanner --clair="http://clair:6060" vulnerables/web-dvwa
	'''

	## Providers declaration
	terraform {
	required_providers {
	nexus = {
	source = "datadrivers/nexus"
	version = "1.10.5"
	}
	}
	}