import gradio as gr
from transformers import pipeline
import os
HF_TOKEN = os.getenv('HF_TOKEN')
hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN, "crowdsourced-sentiment")
def sentiment_analysis_generate_text(text):
# Define the model
model_name = "gsar78/HellenicSentimentAI"
# Create the pipeline
nlp = pipeline("sentiment-analysis", model=model_name)
# Split the input text into individual sentences
sentences = text.split('|')
# Run the pipeline on each sentence and collect the results
results = nlp(sentences)
output = []
for sentence, result in zip(sentences, results):
output.append(f"Text: {sentence.strip()}\nSentiment: {result['label']}, Score: {result['score']:.4f}\n")
# Join the results into a single string to return
return "\n".join(output)
def sentiment_analysis_generate_table(text):
# Define the model
model_name = "gsar78/HellenicSentimentAI"
# Create the pipeline
nlp = pipeline("sentiment-analysis", model=model_name)
# Split the input text into individual sentences
sentences = text.split('|')
# Generate the HTML table with enhanced colors and bold headers
html = """
Text
Score
Sentiment
"""
for sentence in sentences:
result = nlp(sentence.strip())[0]
text = sentence.strip()
score = f"{result['score']:.4f}"
sentiment = result['label']
# Determine the sentiment class
if sentiment.lower() == "positive":
sentiment_class = "positive"
elif sentiment.lower() == "negative":
sentiment_class = "negative"
else:
sentiment_class = "neutral"
# Generate table rows
html += f'
{text}
{score}
{sentiment}
'
html += """
"""
return html
if __name__ == "__main__":
iface = gr.Interface(
fn=sentiment_analysis_generate_table,
inputs=gr.Textbox(placeholder="Enter sentence here..."),
outputs=gr.HTML(),
title="Hellenic Sentiment AI",
description="A sentiment analysis model, primarily for the Greek language. "
"Type in some text to see its sentiment classification: positive, neutral, or negative. "
"Multiple sentences can be classified when separated by the | character. "
"For Emotion & Sentiment Classification visit Version 2.0: Hellenic Sentiment AI v2 "
"Version 1.1 - Developed by GeoSar",
examples=[
["Η πικάντικη γεύση αυτής της σούπας λαχανικών ήταν ακριβώς αυτό που χρειαζόμουν σήμερα. Είχε μια ωραία γαργαλιστική αίσθηση χωρίς να είναι πολύ καυτερή."],
["Η πίτσα ήταν καμένη και τα υλικά φθηνής ποιότητας. Σίγουρα δεν θα ξαναπαραγγείλω από εκεί."]
],
allow_flagging="manual",
flagging_options=["Incorrect", "Ambiguous"],
flagging_callback=hf_writer,
examples_per_page=2,
allow_duplication=False,
concurrency_limit="default"
)
iface.launch(share=True)