Create app.py

app.py

@@ -0,0 +1,68 @@
+import gradio as gr
+from transformers import pipeline
+from huggingface_hub import login
+import os
+
+# Initialize global pipeline
+ner_pipeline = None
+    
+def load_healthcare_ner_pipeline():
+    """Load the Hugging Face pipeline for Healthcare NER."""
+    global ner_pipeline
+    if ner_pipeline is None:        
+
+        ner_pipeline = pipeline(
+            "token-classification",
+            model="TypicaAI/magbert-ner",
+            aggregation_strategy="first"  # Groups B- and I- tokens into entities
+        )
+    return ner_pipeline
+
+
+def process_text(text):
+    """Process input text and return highlighted entities."""
+    pipeline = load_healthcare_ner_pipeline()
+    entities = pipeline(text)
+    return {"text": text, "entities": entities}
+
+
+def log_demo_usage(text, num_entities):
+    """Log demo usage for analytics."""
+    print(f"Processed text: {text[:50]}... | Entities found: {num_entities}")
+
+# Define the main demo interface
+demo = gr.Interface(
+    fn=process_text,
+    inputs=gr.Textbox(
+        label="Paste French text",
+        placeholder="La Coupe du monde de football 2030 se déroulera au Maroc, en Espagne et au Portugal.",
+        lines=5
+    ),
+    outputs=gr.HighlightedText(label="Identified Entities"),
+    title="🌟 MagBERT-NER: High-Performing French NER",
+    description="""
+    _By **[Hicham Assoudi](https://huggingface.co/hassoudi)** – AI Researcher (Ph.D.), Oracle Consultant, and Author._ 🔗 [Follow me on LinkedIn](https://www.linkedin.com/in/assoudi)
+    
+    MagBERT-NER is a robust **Named Entity Recognition (NER)** model for the **French language**, trained on a **manually curated dataset** from diverse Moroccan sources. It’s designed to handle **names, places, currencies**, and other entities with exceptional precision, especially in **Moroccan contexts**.  
+    ## 🚀 Highlights:  
+    - **20,000+ Downloads**: Trusted by developers and researchers for French NER tasks.  
+    - **🌐 Recognized by John Snow Labs**: Adapted for scalability and enterprise-grade applications like **healthcare**.
+    """,
+    article="""
+    ## ⚠️ Disclaimer
+    This is a **free demo model** provided without support. While it showcases high precision and is ideal for educational and exploratory purposes, it is not intended for production or commercial use.  
+
+    For production-grade or commercial models, please contact us at **assoudi@typica.ai**.
+    """,
+    examples=[
+        ["Fatima Zahra a acheté une babouche artisanale au souk de Fès pour 250 dirhams."],
+        ["Youssef a participé à une réunion importante à Tétouan pendant Ramadan."],
+        ["Amina a vendu des tapis au marché local pour 1 200 dirhams."],
+        ["Le projet Al Massira, situé près d'Oujda, sera lancé en septembre."],
+        ["Khadija a reçu un prix pour ses recherches sur l'arganier lors d'une cérémonie à Agadir."],
+        ["L'association Amal prévoit une collecte de fonds à Tanger pour soutenir les artisans locaux."],    ]
+)
+
+# Launch the Gradio demo
+if __name__ == "__main__":
+    demo.launch()