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import json
from textblob import TextBlob
from fastapi import FastAPI, HTTPException
import uvicorn
import gradio as gr
import mcp
app = FastAPI()
def analyze_sentiment(text: str) -> dict:
"""Core sentiment analysis logic"""
blob = TextBlob(text)
sentiment = blob.sentiment
return {
"polarity": round(sentiment.polarity, 2),
"subjectivity": round(sentiment.subjectivity, 2),
"assessment": "positive" if sentiment.polarity > 0
else "negative" if sentiment.polarity < 0
else "neutral"
}
@app.post("/mcp/sentiment")
async def handle_mcp_request(data: dict):
"""
MCP-compatible endpoint
Format: {"parameters": {"text": "your text"}}
"""
try:
text = data.get("parameters", {}).get("text", "")
if not text:
raise HTTPException(status_code=400, detail="Missing 'text' parameter")
return {
"jsonrpc": "2.0",
"result": analyze_sentiment(text),
"id": "sentiment-response"
}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.get("/")
async def health_check():
"""Required for Hugging Face health checks"""
return {"status": "OK"}
demo = gr.Interface(
fn=analyze_sentiment,
inputs=gr.Textbox(placeholder="Enter text to analyze..."),
outputs=gr.Textbox(),
title="Text Sentiment Analysis",
description="Analyze the sentiment of text using TextBlob"
)
# Launch the interface and MCP server
if __name__ == "__main__":
demo.launch(mcp_server=True)
uvicorn.run(app, host="0.0.0.0", port=7860) # HF uses 7860 |