Skip to content

Open-source platform for extracting structured data from documents using AI.

License

Notifications You must be signed in to change notification settings

DocumindHQ/documind

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

15 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Documind

Featured on Hacker News

Documind is an advanced document processing tool that leverages AI to extract structured data from PDFs. It is built to handle PDF conversions, extract relevant information, and format results as specified by customizable schemas.

This repo was built on top of Zerox - https://github.com/getomni-ai/zerox. The MIT license from Zerox is included in the core folder and is also mentioned in the root license file.

Features

  • Converts PDFs to images for detailed AI processing.
  • Uses OpenAI’s API to extract and structure information.
  • Allows users to specify extraction schemas for various document formats.
  • Designed for flexible deployment on local or cloud environments.

Try the Hosted Version 🚀

A demo of the documind hosted version will be available soon for you to try out! The hosted version provides a seamless experience with fully managed APIs, so you can skip the setup and start extracting data right away.

For full access to the hosted service, please request access and we’ll get you set up.

Requirements

Before using documind, ensure the following software dependencies are installed:

System Dependencies

  • Ghostscriptdocumind relies on Ghostscript for handling certain PDF operations.
  • GraphicsMagick: Required for image processing within document conversions.

Install both on your system before proceeding:

# On macOS
brew install ghostscript graphicsmagick

# On Debian/Ubuntu
sudo apt-get update
sudo apt-get install -y ghostscript graphicsmagick

Node.js & NPM

Ensure Node.js (v18+) and NPM are installed on your system.

Installation

You can install documind via npm:

npm install documind

Environment Setup

documind requires an .env file to store sensitive information like your OpenAI API key.

Create an .env file in your project directory and add the following:

OPENAI_API_KEY=your_openai_api_key

Usage

Basic Example

First, import documind and define your schema. The schema outline what information documind should look for in each document. Here’s a quick setup to get started.

1. Define a Schema

The schema is an array of objects where each object defines:

  • name: Field name to extract.
  • type: Data type (e.g., "string""number""array""object").
  • description: Description of the field.
  • children (optional): For arrays and objects, define nested fields.

Example schema for a bank statement:

const schema = [
  {
    name: "accountNumber",
    type: "string",
    description: "The account number of the bank statement."
  },
  {
    name: "openingBalance",
    type: "number",
    description: "The opening balance of the account."
  },
  {
    name: "transactions",
    type: "array",
    description: "List of transactions in the account.",
    children: [
      {
        name: "date",
        type: "string",
        description: "Transaction date."
      },
      {
        name: "creditAmount",
        type: "number",
        description: "Credit Amount of the transaction."
      },
      {
        name: "debitAmount",
        type: "number",
        description: "Debit Amount of the transaction."
      },
      {
        name: "description",
        type: "string",
        description: "Transaction description."
      }
    ]
  },
  {
    name: "closingBalance",
    type: "number",
    description: "The closing balance of the account."
  }
];

2. Run documind

Use documind to process a PDF by passing the file URL and the schema.

import { extract } from 'documind';

const runExtraction = async () => {
  const result = await extract({
    file: 'https://bank_statement.pdf',
    schema
  });

  console.log("Extracted Data:", result);
};

runExtraction();

Example Output

Here’s an example of what the extracted result might look like:

 {
  "success": true,
  "pages": 1,
  "data": {
    "accountNumber": "100002345",
    "openingBalance": 3200,
    "transactions": [
        {
        "date": "2021-05-12",
        "creditAmount": null,
        "debitAmount": 100,
        "description": "transfer to Tom" 
      },
      {
        "date": "2021-05-12",
        "creditAmount": 50,
        "debitAmount": null,
        "description": "For lunch the other day"
      },
      {
        "date": "2021-05-13",
        "creditAmount": 20,
        "debitAmount": null,
        "description": "Refund for voucher"
      },
      {
        "date": "2021-05-13",
        "creditAmount": null,
        "debitAmount": 750,
        "description": "May's rent"
      }
    ],
    "closingBalance": 2420
  },
  "fileName": "bank_statement.pdf"
}

Contributing

Contributions are welcome! Please submit a pull request with any improvements or features.

License

This project is licensed under the AGPL v3.0 License.