doc-scan-gemini / app.py
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import gradio as gr
import google.generativeai as genai
import base64
import io
from PIL import Image
import os
import json
# Configure Google Cloud credentials (replace with your actual API key or setup)
genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
# Select the Gemini Pro Vision model
model = genai.GenerativeModel('gemini-pro-vision')
# Prompt definition
prompt = """
You are analyzing a medical document or an application form from patient.
Extract the following fields as JSON:
- Position applied for
- Office/Ministry
- Duty station
- First name(s)
- Surname
- Date of birth
- Gender
- Citizenship
- Postal Address
- Residential Address
- Email
- Phone number (mobile)
"""
def process_image(image: Image.Image):
buffered = io.BytesIO()
image.save(buffered, format="JPEG")
base64_image = base64.b64encode(buffered.getvalue()).decode()
contents = [
genai.Content.create(role="user", parts=[genai.Part.from_text(prompt)]),
genai.Content.create(role="user", parts=[genai.Part.from_data(base64.b64decode(base64_image), mime_type="image/jpeg")])
]
response = model.generate_content(contents)
return response.text
# Gradio interface
demo = gr.Interface(
fn=process_image,
inputs=gr.Image(type="pil"),
outputs="textbox",
title="Healthelic Form Data Extractor (Doc Scaner)",
description="Upload a scanned medical form to extract key fields."
)
if __name__ == "__main__":
demo.launch()