app.py

import gradio as gr
from transformers import pipeline

# تحميل نموذج NER الإنجليزي
ner_pipeline = pipeline(
    "token-classification",
    model="dslim/bert-base-NER",
    aggregation_strategy="simple"
)

def extract_entities(text):
    if not text.strip():
        return "Please enter some text."

    entities = ner_pipeline(text)
    result = ""
    for ent in entities:
        result += f"Word: {ent['word']} | Entity: {ent['entity_group']}\n"

    return result

interface = gr.Interface(
    fn=extract_entities,
    inputs=gr.Textbox(
        lines=5,
        placeholder="Enter an English text (e.g. My name is John and I live in London)"
    ),
    outputs=gr.Textbox(lines=12),
    title="English NER Detector",
    description="Testing dslim/bert-base-NER model for Named Entity Recognition"
)

interface.launch()