mistral-ai-ocr 1.5

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Mistral AI OCR

This is a simple script that uses the Mistral AI OCR API to get the Markdown text from a PDF or image file

Usage

Install the Requirements

To install the necessary requirements, run the following command:

pip install mistral-ai-ocr

Typical Usage

mistral-ai-ocr paper.pdf
mistral-ai-ocr paper.pdf --dpi 200
mistral-ai-ocr paper.pdf --api-key jrWjJE5lFketfB2sA6vvhQK2SoHQ6R39
mistral-ai-ocr paper.pdf -o revision
mistral-ai-ocr paper.pdf -e
mistral-ai-ocr paper.pdf -m FULL
mistral-ai-ocr page74.jpg -e
mistral-ai-ocr -j paper.json
mistral-ai-ocr -j paper.json -m TEXT_NO_PAGES -n

Arguments

Argument		Description
		input PDF or image file
-d DPI	--dpi DPI	DPI (dots per inch) setting for the PDF to image conversion. Defaults to 600
-k API_KEY	--api-key API_KEY	Mistral API key, can be set via the MISTRAL_API_KEY environment variable
-o OUTPUT	--output OUTPUT	output directory path. If not set, a directory will be created in the current working directory using the same stem (filename without extension) as the input file
-j JSON_OCR_RESPONSE	--json-ocr-response JSON_OCR_RESPONSE	path from which to load a pre-existing JSON OCR response (any input file will be ignored)
-m MODE	--mode MODE	mode of operation: either the name or numerical value of the mode. Defaults to FULL_NO_PAGES
-s PAGE_SEPARATOR	--page-separator PAGE_SEPARATOR	page separator to use when writing the Markdown file. Defaults to \n
-n	--no-json	do not write the JSON OCR response to a file. By default, the response is written
-e	--load-dot-env	load the .env file from the current directory using python-dotenv, to retrieve the Mistral API key
-E	--load-path-dot-env	load the .env file from the specified path using python-dotenv, to retrieve the Mistral API key. Defaults to ~/.mistral_ai_ocr.env

Modes

Value	Name
0	FULL
1	FULL_ALT
2	FULL_NO_DIR
3	FULL_NO_PAGES
4	TEXT
5	TEXT_NO_PAGES

Given the input file paper.pdf, the directory structure for each mode is shown below:

0 - FULL

Structure

paper
├── full
│   ├── image1.png
│   ├── image2.png
│   ├── image3.png
│   └── paper.md
├── page_0
│   ├── image1.png
│   └── paper.md
├── page_1
│   ├── image2.png
│   └── paper.md
└── page_2
    ├── image3.png
    └── paper.md

1 - FULL_ALT

Structure

paper
├── image1.png
├── image2.png
├── image3.png
├── paper.md
├── page_0
│   ├── image1.png
│   └── paper.md
├── page_1
│   ├── image2.png
│   └── paper.md
└── page_2
    ├── image3.png
    └── paper.md

2 - FULL_NO_DIR

Structure

paper
├── image1.png
├── image2.png
├── image3.png
├── paper.md
├── paper0.md
├── paper1.md
└── paper2.md

3 - FULL_NO_PAGES default

Structure

paper
├── image1.png
├── image2.png
├── image3.png
└── paper.md

4 - TEXT

Structure

paper
├── paper.md
├── paper0.md
├── paper1.md
└── paper2.md

5 - TEXT_NO_PAGES

Structure

paper
└── paper.md

By default, the JSON response from the Mistral AI OCR API is saved in the output directory. To disable JSON output, use the -n or --no-json argument. To experiment with a different mode without using additional API calls, reuse an existing JSON response instead of the original input file

Mistral AI API Key

To obtain an API key, you need a Mistral AI account. Then visit https://admin.mistral.ai/organization/api-keys and click the Create new key button

To avoid using -e to load the .env file, you can create one at $HOME/.mistral_ai_ocr.env (where $HOME is your home directory). It will then be automatically loaded at the start of the script

For example, for an user called vavilov, the path would look like this:

• Linux

  /home/vavilov/.mistral_ai_ocr.env  
  

• macOS

  /Users/vavilov/.mistral_ai_ocr.env  
  

• Windows

  C:\Users\vavilov\.mistral_ai_ocr.env  
  

and the content will be something like this:

MISTRAL_API_KEY=jrWjJE5lFketfB2sA6vvhQK2SoHQ6R39