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import json
import gradio as gr
from textblob import TextBlob
from snownlp import SnowNLP
def sentiment_analysis(text: str) -> str:
'''
Analyse the sentiment of the given text
Args:
text (str): The text to analyse
Returns:
str: A JSON string containing polarity, subjectivity, and assessment
'''
blob = TextBlob(text)
sentiment = blob.sentiment
result = {
'polarity': round(sentiment.polarity, 2), # -1 (negative) to 1 (positive)
'subjectivity': round(sentiment.subjectivity, 2), # 0 (objective) to 1 (subjective)
'assessment': 'positive' if sentiment.polarity > 0 else 'negative' if sentiment.polarity < 0 else 'neutral'
}
return json.dumps(result)
def chinese_sentiment_analysis(text: str) -> str:
'''
Analyse the sentiment of the given Chinese text
Args:
text (str): The text to analyse
Returns:
str: A JSON string containing polarity, subjectivity, and assessment
'''
s = SnowNLP(text)
# SnowNLP 的情感分析返回值範圍是 0 到 1，0 表示負面，1 表示正面
polarity = s.sentiments
subjectivity = None # SnowNLP 不提供主觀性評估，可設為 None 或其他值
result = {
'polarity': round(polarity, 2), # 0 (negative) to 1 (positive)
'subjectivity': subjectivity, # SnowNLP 不提供主觀性評估
'assessment': 'positive' if polarity > 0.5 else 'negative' if polarity < 0.5 else 'neutral'
}
return json.dumps(result)
# gradio interface
demo = gr.TabbedInterface(
[
gr.Interface(
fn = sentiment_analysis,
inputs = gr.Textbox(placeholder = 'Enter text to analyse...'),
outputs = gr.Textbox(),
title = 'Text Sentiment Analysis',
description = 'Analyse the sentiment of text using TextBlob',
api_name = 'sentiment_analysis'
),
gr.Interface(
fn = chinese_sentiment_analysis,
inputs = gr.Textbox(placeholder = '要分析的中文...'),
outputs = gr.Textbox(),
title = 'Chinese Sentiment Analysis',
description = 'Analyse the sentiment of Chinese text using SnowNLP',
api_name = 'chinese_sentiment_analysis'),
],
[
'sentiment analysis',
'chinese sentiment analysis',
]
)
# Launch the interface and MCP server
if __name__ == '__main__':
demo.launch(mcp_server = True) |