AI-Assisted-Smart-Data-Entry-PoC/README.md

AI-Assisted Smart Data Entry Backend

This project provides a FastAPI-based backend for extracting structured data from medical receipts using OpenAI's GPT-4o model with structured outputs.

Features

• FastAPI: Modern, fast web framework for building APIs.
• Structured Extraction: Uses OpenAI's beta.chat.completions.parse to ensure extracted data adheres to a Pydantic schema.
• CORS Enabled: Configured to allow access from frontend applications (e.g., Angular).
• Health Check: Simple endpoint to verify server status.

Setup

1. Install Dependencies:

   pip install -r requirements.txt
   

   1. Configure Environment: Create a .env file in the root directory and add your OpenAI API key: env OPENAI_API_KEY=your_api_key_here

2. Run the Server:

   python main.py
   

   Or using uvicorn:

   uvicorn main:app --reload
   

API Endpoints

GET /health

Returns the status of the server.

POST /api/v1/extract

Extracts data from a medical receipt image.

Request Body:

• file: Multipart image file.
• user_name (optional): Name of the employee.
• department (optional): Department of the employee.

Response: Returns a structured JSON matching the ExtractionResponse schema.

Project Structure

• main.py: Entry point and API endpoints.
• schemas.py: Pydantic models for data validation and structured output.
• services/:
  • openai_service.py: Logic for interacting with OpenAI API.
• requirements.txt: Python dependencies.
• .env: Environment variables (not tracked by git).