File size: 810 Bytes
522d644 0b01c5c 522d644 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 |
# app.py
import gradio as gr
import spacy
from transformers import pipeline
# Load the spaCy model for POS tagging
nlp = spacy.load("en_core_web_sm")
def identify_nouns_verbs(text):
# Process the text with spaCy
doc = nlp(text)
# Extract nouns and verbs
nouns = [token.text for token in doc if token.pos_ == "NOUN"]
verbs = [token.text for token in doc if token.pos_ == "VERB"]
return {"Nouns": nouns, "Verbs": verbs}
# Create the Gradio interface
iface = gr.Interface(
fn=identify_nouns_verbs,
inputs=gr.inputs.Textbox(lines=10, placeholder="Enter your text here..."),
outputs=gr.outputs.JSON(),
title="Noun and Verb Identifier",
description="Enter a document or text to identify the nouns and verbs."
)
if __name__ == "__main__":
iface.launch()
|