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)