app.py

import gradio as gr
from huggingface_hub import login
import os

def load_healthcare_ner():
    login(token=os.environ["HF_TOKEN"])
    model = AutoModelForTokenClassification.from_pretrained(
        "TypicaAI/HealthcareNER-Fr",
        token=os.environ["HF_TOKEN"]
    )
    return model

def process_text(text):
    entities = model(text)
    # Format results with highlighting
    html_output = highlight_entities(text, entities)
    # Track usage for marketing insights
    log_demo_usage(text, len(entities))
    return html_output

demo = gr.Interface(
    fn=process_text,
    inputs=gr.Textbox(
        label="Paste French medical text",
        placeholder="Le patient présente une hypertension artérielle...",
        lines=5
    ),
    outputs=gr.HTML(label="Identified Medical Entities"),
    title="French Healthcare NER Demo | As featured in 'NLP on OCI'",
    description="""
    🔬 Live demo of the French Healthcare NER model built in Chapter 5 of 'NLP on OCI'
    
    📚 Follow along with the book to build this exact model step-by-step
    🏥 Perfect for medical text analysis, clinical studies, and healthcare compliance
    ⚡ Powered by Oracle Cloud Infrastructure
    
    By [Hicham Assoudi] - Oracle Consultant & AI Researcher
    """,
    examples=[
        ["Le patient souffre d'hypertension et diabète de type 2. Traitement: Metformine 500mg."],
        ["Antécédents: infarctus du myocarde en 2019. Allergie à la pénicilline."]
    ]
)

# Add conversion elements
with gr.Blocks() as marketing_elements:
    gr.Markdown("""
    ### 📖 Get the Complete Guide
    
    Learn how to build and deploy this exact model in 'NLP on OCI'
    - ✓ Step-by-step implementation
    - ✓ Performance optimization
    - ✓ Enterprise deployment patterns
    - ✓ Complete source code
    
    [Get the Book](your-book-link) | Use code `NERSPACE` for 15% off
    """)
    
    with gr.Row():
        email_input = gr.Textbox(
            label="Get the French Healthcare NER Dataset",
            placeholder="Enter your business email"
        )
        submit_btn = gr.Button("Access Dataset")