fertiscan-backend

FertiScan helps inspectors analyze and process fertilizer labels by extracting text and generating structured forms.

Overview

This repository contains the backend for FertiScan, a Flask-based server designed to work with the frontend. It handles image uploads, document analysis using OCR, and form generation using an LLM.

Setup for Development

Prerequisites

• Python 3.8+
• pip
• virtualenv
• Azure Document Intelligence and OpenAI API keys

Running Locally

1. Clone the repository:

   git clone https://github.com/ai-cfia/fertiscan-backend.git
   cd fertiscan-backend

2. Install dependencies:

   pip install -r requirements.txt

3. Start the server:

   python ./app.py

Running with Docker

1. Build the Docker image:

   docker build -t fertiscan-backend \
   --build-arg ARG_AZURE_API_ENDPOINT=your_azure_form_recognizer_endpoint \
   --build-arg ARG_AZURE_API_KEY=your_azure_form_recognizer_key \
   --build-arg ARG_AZURE_OPENAI_API_ENDPOINT=your_azure_openai_endpoint \
   --build-arg ARG_AZURE_OPENAI_API_KEY=your_azure_openai_key \
   --build-arg ARG_PROMPT_PATH=path/to/prompt_file \
   --build-arg ARG_UPLOAD_PATH=path/to/upload_file \
   --build-arg ARG_FRONTEND_URL=http://url.to_frontend/ \
   .

2. Run the Docker container:

   docker run -p 5000:5000 fertiscan-backend

Environment Variables

Create a .env file from .env.template.

AZURE_API_ENDPOINT=your_azure_form_recognizer_endpoint
AZURE_API_KEY=your_azure_form_recognizer_key
AZURE_OPENAI_API_ENDPOINT=your_azure_openai_endpoint
AZURE_OPENAI_API_KEY=your_azure_openai_key
AZURE_OPENAI_DEPLOYMENT=your_azure_openai_deployment

PROMPT_PATH=path/to/file
UPLOAD_PATH=path/to/file
FRONTEND_URL=http://url.to_frontend/

API Endpoints

• POST /analyze: Upload images for analysis and get the results as a JSON form.