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import gradio as gr
import openai
import base64
import io
from PIL import Image
import fitz # PyMuPDF
import os
# Load API key
openai.api_key = os.getenv("OPENAI_API_KEY")
# Prompt for extraction
prompt = """
You are analyzing a medical document or an application form from a 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_pdf(pdf_file):
# pdf_file is already bytes when using gr.File(type="binary")
doc = fitz.open(stream=pdf_file, filetype="pdf")
results = []
for page_num in range(len(doc)):
page = doc.load_page(page_num)
pix = page.get_pixmap(dpi=200) # Use 150-200 DPI for balance
# Convert to PIL Image
image = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
# Convert to base64 JPEG
buffered = io.BytesIO()
image.save(buffered, format="JPEG")
base64_image = base64.b64encode(buffered.getvalue()).decode()
# Send to GPT-4o
response = openai.chat.completions.create(
model="gpt-4o",
messages=[
{"role": "user", "content": [
{"type": "text", "text": prompt},
{"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"}}
]}
],
max_tokens=1000
)
results.append(response.choices[0].message.content.strip())
return "\n\n---\n\n".join(results)
# Gradio UI
demo = gr.Interface(
fn=process_pdf,
inputs=gr.File(type="binary", label="Upload PDF Form"),
outputs="textbox",
title="Healthelic Form Data Extractor (PDF Scanner) - OpenAI GPT-4o",
description="Upload a scanned medical form in PDF format to extract key fields using GPT-4o vision model."
)
if __name__ == "__main__":
demo.launch()
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