PAR AI OCR

PAR AI OCR is a command-line tool that uses artificial intelligence to perform Optical Character Recognition (OCR) on PDF files and images. It extracts text from the input files and generates markdown output.

Screenshots

Features

• Extracts text for PDFs and images to Markdown while preserving as much formatting as possible.
• Works with most providers and vision models (quality will vary depending on provider and model used)
• Uses my PAR AI Core

Known Issues

• Providers other than OpenAI and Anthropic are hit-and-miss depending on provider / model / data being extracted.

Prerequisites

Install poppler (Used for PDF processing)

Linux

apt install poppler-utils

Mac

brew install poppler

Windows

scoop install poppler

uv is recommended

Linux and Mac

curl -LsSf https://astral.sh/uv/install.sh | sh

Windows

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Installation

Installation From Source

Clone the repository and install the package:

git clone https://github.com/paulrobello/par_ocr.git
cd par_ocr
uv sync

From PiPy

uv tool install par_ocr

Usage

Basic usage from source:

uv run par_ocr

Basic usage if installed:

par_ocr

Command Line Parameters

• --ai-provider, -a: AI provider to use for processing [Ollama|LlamaCpp|OpenAI|Groq|XAI|Anthropic|Google|Bedrock|Github|Mistral] (default: OpenAI)
• --model, -m: AI model to use for processing (default: provider-specific)
• --ai-base-url, -b: Override the base URL for the AI provider
• --system-prompt-file, -p: File containing custom system prompt, if you want to use one other than the default
• --input-file, -i: File to process, supported extensions: .pdf, .png, .jpg
• --pricing, -p: Configure pricing summary display [none|price|details] (default: price)
• --pages: Comma-separated page numbers or hyphen-separated range (e.g., '1,3,5-7')
• --output, -o: Output directory for markdown files (default same folder as input file)
• --debug, -D: Output extra debug info (Default: false)
• --version, -v: Show version information and exit

Examples

Note: If running from source prepend "uv run" to the beginning of the example commands.

1. Process a PDF file using the default settings:

   par_ocr --input-file path/to/your/file.pdf
   

2. Use a specific AI provider and model:

   par_ocr --ai-provider ANTHROPIC --model claude-3-5-sonnet-20241022 --input-file path/to/your/file.pdf
   

3. Process specific pages of a PDF:

   par_ocr --input-file path/to/your/file.pdf --pages 1,3,5-7
   

4. Specify an output directory:

   par_ocr --input-file path/to/your/file.pdf --output path/to/output/directory
   

5. Enable pricing details:

   par_ocr --pricing details --input-file path/to/your/file.pdf 
   

Note

Make sure to set the appropriate environment variables for the AI provider you're using (e.g., OPENAI_API_KEY for OpenAI). you may also create a file ~/.par_ocr_config with your API Keys such as:

# AI API KEYS
OPENAI_API_KEY=
ANTHROPIC_API_KEY=
GROQ_API_KEY=
XAI_API_KEY=
GOOGLE_API_KEY=
MISTRAL_API_KEY=
GITHUB_TOKEN=
OPENROUTER_API_KEY=
# Used by Bedrock
AWS_PROFILE=
AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=


### Tracing (optional)
LANGCHAIN_TRACING_V2=false
LANGCHAIN_ENDPOINT=https://api.smith.langchain.com
LANGCHAIN_API_KEY=
LANGCHAIN_PROJECT=par_ocr

AI API KEYS

• ANTHROPIC_API_KEY is required for Anthropic. Get a key from https://console.anthropic.com/
• OPENAI_API_KEY is required for OpenAI. Get a key from https://platform.openai.com/account/api-keys
• GITHUB_TOKEN is required for GitHub Models. Get a free key from https://github.com/marketplace/models
• GOOGLE_API_KEY is required for Google Models. Get a free key from https://console.cloud.google.com
• XAI_API_KEY is required for XAI. Get a free key from https://x.ai/api
• GROQ_API_KEY is required for Groq. Get a free key from https://console.groq.com/
• MISTRAL_API_KEY is required for Mistral. Get a free key from https://console.mistral.ai/
• OPENROUTER_KEY is required for OpenRouter. Get a key from https://openrouter.ai/
• AWS_PROFILE or AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY are used for Bedrock authentication. The environment must already be authenticated with AWS.
• No key required to use with Ollama or LlamaCpp.

Open AI Compatible Providers

If a specify provider is not listed but has an OpenAI compatible endpoint you can use the following combo of vars:

• PARAI_AI_PROVIDER=OpenAI
• PARAI_MODEL=Your selected model
• PARAI_AI_BASE_URL=The providers OpenAI endpoint URL

Whats New

• Version 0.2.0:
  • Updated ai lib and other dependencies
  • Added debug flag
• Version 0.1.1:
  • Updated ai lib
  • Fixed markdown fences
• Version 0.1.0:
  • Initial release

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Author

Paul Robello - probello@gmail.com