DocumentAI-Backend is an open-source FastAPI service providing REST endpoints for text extraction, form parsing, and data structuring. It integrates Google Document AI, OCR fallback (Tesseract/EasyOCR), and Docker deployment to deliver JSON results for PDF and image inputs.
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DocumentAI-Backend
DocumentAI-Backend is an open-source FastAPI service providing REST endpoints for text extraction, form parsing, and data structuring. It integrates Google Document AI, OCR fallback (Tesseract/EasyOCR), and Docker deployment to deliver JSON results for PDF and image inputs.
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What is DocumentAI-Backend?
DocumentAI-Backend is a lightweight backend framework that automates extraction of text, form fields, and structured data from documents. It offers REST API endpoints for uploading PDFs or images, processes them via Google Document AI with OCR fallback, and returns parsed results in JSON. Built with Python, FastAPI, and Docker, it enables quick integration into existing systems, scalable deployments, and customization through configurable pipelines and middleware.
Who will use DocumentAI-Backend?
- Developers building document processing pipelines
- Enterprises automating invoice and receipt extraction
- Startups digitizing paper forms
- Data engineers integrating OCR services
- Solution architects seeking modular AI backends
How to use the DocumentAI-Backend?
- Step1: Clone the repository: git clone https://github.com/sarthakpriyadarshi/DocumentAI-Backend
- Step2: Install dependencies with pip install -r requirements.txt
- Step3: Configure Google Document AI credentials and endpoint in .env
- Step4: Run the service locally with uvicorn main:app --reload or deploy via Docker
- Step5: Send POST requests to /extract_text or /extract_form with PDF/image files
- Step6: Receive structured JSON responses and integrate into your application
Platform
- Linux
- Mac
- Windows
DocumentAI-Backend's Core Features & Benefits
The Core Features
- REST API for text and form extraction
- Google Document AI integration
- OCR fallback support (Tesseract/EasyOCR)
- Multi-format input (PDF, JPEG, PNG)
- Configurable processing pipelines
- Docker container deployment
The Benefits
- Rapid integration with minimal setup
- Open-source and customizable
- Scalable via Docker orchestration
- Accurate extraction with OCR fallback
- JSON output for easy ingestion
DocumentAI-Backend's Main Use Cases & Applications
- Automated invoice and receipt data extraction
- Form field parsing for digital conversions
- Contract and legal document digitization
- Academic paper text extraction
- Bulk document processing pipelines
FAQs of DocumentAI-Backend
DocumentAI-Backend Company Information
DocumentAI-Backend Reviews
5/5
DocumentAI-Backend's Main Competitors and alternatives?
Google Cloud Document AI
AWS Textract
Azure Form Recognizer
Tesseract OCR
Nanonets Document AI
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