File size: 1,255 Bytes
1dd91b0
 
d8f59b2
 
 
 
 
1dd91b0
 
 
 
 
 
 
 
 
d8f59b2
1dd91b0
 
 
d8f59b2
 
 
1dd91b0
 
d8f59b2
 
 
1dd91b0
 
 
 
 
 
 
 
 
 
 
 
d8f59b2
94404f3
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
31
32
33
34
35
36
37
38
39
40
41
42
import gradio as gr
from textblob import TextBlob
import logging

# Set up basic logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

def sentiment_analysis(text: str) -> dict:
    """
    Analyze the sentiment of the given text.
    Args:
        text (str): The text to analyze
    Returns:
        dict: A dictionary containing polarity, subjectivity, and assessment
    """
    logger.info(f"Received input: {text}")
    blob = TextBlob(text)
    sentiment = blob.sentiment
    
    result = {
        "polarity": round(sentiment.polarity, 2),
        "subjectivity": round(sentiment.subjectivity, 2),
        "assessment": "positive" if sentiment.polarity > 0 else "negative" if sentiment.polarity < 0 else "neutral"
    }
    
    logger.info(f"Returning result: {result}")
    return result

# Create the Gradio interface
demo = gr.Interface(
    fn=sentiment_analysis,
    inputs=gr.Textbox(placeholder="Enter text to analyze..."),
    outputs=gr.JSON(),
    title="Text Sentiment Analysis",
    description="Analyze the sentiment of text using TextBlob"
)

# Launch the interface and MCP server
if __name__ == "__main__":
    logger.info("Starting Gradio app...")
    demo.launch(mcp_server=True, show_error=True)