Here's an example of a real-time sentiment analysis tool for X posts, leveraging AI. This could be used to identify trends, moderate content, or enhance user engagement.

sentimentAnalyzer.ts

import express, { Request, Response } from 'express';
import { Pipeline, pipeline } from '@huggingface/hub';
import { Client } from 'twitter-api-sdk';

const app = express();
app.use(express.json());

// Set up Hugging Face sentiment analysis pipeline
const sentimentAnalyzer: Pipeline = pipeline('sentiment-analysis');

// Twitter API credentials (replace with your credentials)
const CONSUMER_KEY = "your_consumer_key";
const CONSUMER_SECRET = "your_consumer_secret";
const ACCESS_TOKEN = "your_access_token";
const ACCESS_SECRET = "your_access_secret";

// Set up Twitter API client
const twitterClient = new Client({
    appKey: CONSUMER_KEY,
    appSecret: CONSUMER_SECRET,
    accessToken: ACCESS_TOKEN,
    accessSecret: ACCESS_SECRET,
});

app.post('/analyze', async (req: Request, res: Response) => {
    const { text } = req.body;
    if (!text) {
        return res.status(400).json({ error: 'No text provided' });
    }

    try {
        const result = await sentimentAnalyzer(text);
        res.json({ text, sentiment: result });
    } catch (error) {
        res.status(500).json({ error: 'Error analyzing sentiment' });
    }
});

app.post('/stream', async (req: Request, res: Response) => {
    const { keywords } = req.body;
    if (!keywords || !Array.isArray(keywords)) {
        return res.status(400).json({ error: 'No keywords provided or invalid format' });
    }

    try {
        twitterClient.stream('tweets/search/stream', {
            expansions: 'author_id',
            query: keywords.join(' OR '),
        }).then(stream => {
            stream.on('data', (data: any) => {
                const text = data.data.text;
                sentimentAnalyzer(text).then(sentiment => {
                    console.log(`Tweet: ${text}\nSentiment: ${JSON.stringify(sentiment)}\n`);
                });
            });

            stream.on('error', (error: any) => {
                console.error('Stream error:', error);
            });
        });

        res.json({ message: 'Streaming started for keywords', keywords });
    } catch (error) {
        res.status(500).json({ error: 'Error starting stream' });
    }
});

const PORT = 3000;
app.listen(PORT, () => {
    console.log(`Server is running on port ${PORT}`);
});