|
|
|
import gradio as gr |
|
import numpy as np |
|
import pandas as pd |
|
import pickle |
|
import transformers |
|
from transformers import AutoTokenizer, AutoConfig,AutoModelForSequenceClassification,TFAutoModelForSequenceClassification |
|
from scipy.special import softmax |
|
|
|
model_path = "Kaludi/Reviews-Sentiment-Analysis" |
|
tokenizer = AutoTokenizer.from_pretrained(model_path) |
|
config = AutoConfig.from_pretrained(model_path) |
|
model = AutoModelForSequenceClassification.from_pretrained(model_path) |
|
|
|
|
|
def preprocess(text): |
|
new_text = [] |
|
for t in text.split(" "): |
|
t = "@user" if t.startswith("@") and len(t) > 1 else t |
|
t = "http" if t.startswith("http") else t |
|
new_text.append(t) |
|
return " ".join(new_text) |
|
|
|
|
|
def sentiment_analysis(text): |
|
text = preprocess(text) |
|
|
|
encoded_input = tokenizer(text, return_tensors = "pt") |
|
output = model(**encoded_input) |
|
scores_ = output[0][0].detach().numpy() |
|
scores_ = softmax(scores_) |
|
|
|
|
|
labels = ["Negative", "Positive"] |
|
scores = {l:float(s) for (l,s) in zip(labels, scores_) } |
|
|
|
return scores |
|
|
|
|
|
|
|
app = gr.Interface(fn = sentiment_analysis, |
|
inputs = gr.Textbox("Write your text or review here..."), |
|
outputs = "label", |
|
title = "Sentiment Analysis of Customer Reviews", |
|
description = "A tool that analyzes the overall sentiment of customer reviews for a specific product or service, whether it's positive or negative. This analysis is performed by using natural language processing algorithms and machine learning from the model 'Reviews-Sentiment-Analysis' trained by Kaludi, allowing businesses to gain valuable insights into customer satisfaction and improve their products and services accordingly.", |
|
article = "<p style='text-align: center'><a href='https://github.com/Kaludii'>Github</a> | <a href='https://huggingface.co/Kaludi'>HuggingFace</a></p>", |
|
interpretation = "default", |
|
examples = [["I was extremely disappointed with this product. The quality was terrible and it broke after only a few days of use. Customer service was unhelpful and unresponsive. I would not recommend this product to anyone."],[ "I am so impressed with this product! The quality is outstanding and it has exceeded all of my expectations. The customer service team was also incredibly helpful and responsive to any questions I had. I highly recommend this product to anyone in need of a top-notch, reliable solution."],["I don't feel like you trust me to do my job."],["This service was honestly one of the best I've experienced, I'll definitely come back!"]] |
|
) |
|
|
|
app.launch() |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|