Update app.py

app.py

@@ -1,32 +1,64 @@
 import gradio as gr
+from huggingface_hub import login
+import os
 
-def load_disclaimer():
-    return """
-    ⚠️ EDUCATIONAL VERSION
-    This demo implements the exact model you'll build in Chapter [6] 
-    of the book "Natural Language Processing on Oracle Cloud Infrastructure: Building Transformer-Based NLP Solutions Using Oracle AI and Hugging Face". 
-    For production solutions, contact us.
-    """
+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="Try French Healthcare NER (Educational Version)",
-        placeholder="En cas d'infection bactérienne, le médecin recommande une antibiothérapie."
+        label="Paste French medical text",
+        placeholder="Le patient présente une hypertension artérielle...",
+        lines=5
     ),
-    outputs=gr.HTML(label="Entities Found"),
-    title="Educational French Healthcare NER | From the book 'Natural Language Processing on Oracle Cloud Infrastructure: Building Transformer-Based NLP Solutions Using Oracle AI and Hugging Face'",
+    outputs=gr.HTML(label="Identified Medical Entities"),
+    title="French Healthcare NER Demo | As featured in 'NLP on OCI'",
     description="""
-    🎓 Educational Implementation
-    - Follows Chapters 4, 5 and 6 of the book"
-    - Perfect for learning NLP concepts
-    - Not for production use
+    🔬 Live demo of the French Healthcare NER model built in Chapter 5 of 'NLP on OCI'
     
-    Want to build this yourself? 
-    Get the book: https://a.co/d/2soeB3b
+    📚 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
     
-    Need a production solution?
-    Schedule a call: https://typica.ai/
+    By [Hicham Assoudi] - Oracle Consultant & AI Researcher
     """,
-    article=load_disclaimer()
-)
+    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")