File size: 1,017 Bytes
b89e85f |
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 |
import torch
import gradio as gr
from transformers import pipeline
# Initialize the sentiment-analysis pipeline
semantic_analysis = pipeline("sentiment-analysis", model="BAAI/bge-reranker-v2-m3")
# Define a function to analyze text semantics
def analyze_semantics(input_text):
# Get the result from the pipeline
result = semantic_analysis(input_text)
# Extract label (e.g., Positive/Negative) and confidence score
label = result[0]['label']
confidence = round(result[0]['score'] * 100, 2)
return f"Sentiment: {label} (Confidence: {confidence}%)"
# Set up the Gradio interface
gr.close_all()
Demo = gr.Interface(
fn=analyze_semantics,
inputs=[gr.Textbox(label="Enter Text for Semantic Analysis", lines=5)],
outputs=[gr.Textbox(label="Semantic Analysis Result", lines=2)],
title="Semantic Analysis App",
description="This application performs semantic analysis to determine the sentiment of the given text."
)
# Launch the app with a public link
Demo.launch(share=True)
|