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| 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") |