Mental Health Analysis Application

Overview

This application analyzes social media posts to detect signs of mental health issues and provides insights. It uses LlamaIndex for semantic analysis and can integrate with social media platforms' APIs for data collection.

Features

• Collects social media data from platforms like Twitter, Reddit, and others.
• Preprocesses and embeds the data using LlamaIndex.
• Analyzes the data for signs of mental health issues.
• Provides insights and recommendations based on the analysis.

Prerequisites

• Python 3.8+
• Node.js (for deploying with Vercel)
• Social media API keys (Twitter, Reddit, Facebook, Instagram, YouTube)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/mental-health-app.git
   cd mental-health-app

2. Install Python dependencies:

   pip install -r requirements.txt

3. Set up environment variables:

   Create a .env file in the root directory and add your API keys:

   TWITTER_CONSUMER_KEY=your_consumer_key
   TWITTER_CONSUMER_SECRET=your_consumer_secret
   TWITTER_ACCESS_TOKEN=your_access_token
   TWITTER_ACCESS_TOKEN_SECRET=your_access_token_secret
   
   REDDIT_CLIENT_ID=your_client_id
   REDDIT_CLIENT_SECRET=your_client_secret
   REDDIT_USER_AGENT=your_user_agent
   
   FACEBOOK_ACCESS_TOKEN=your_access_token
   
   INSTAGRAM_ACCESS_TOKEN=your_access_token
   INSTAGRAM_USER_ID=your_user_id
   
   YOUTUBE_API_KEY=your_api_key

4. Set up the backend server:

   python app.py

5. Initialize a new Next.js project:

   npx create-next-app frontend
   cd frontend

6. Create API endpoints in Next.js:

   Add the following files:

   • pages/api/fetch_data.js

   import fetch from 'node-fetch';
   
   export default async function handler(req, res) {
       const data = [
           { content: "I am feeling very stressed and anxious lately." },
           { content: "Life has been really hard these days." },
           // Add more posts as needed
       ];
       res.status(200).json(data);
   }

   • pages/api/analyze_mental_health.js

   import { preprocess_data, generate_embeddings, analyze_mental_health } from '../../path_to_your_scripts';
   
   export default async function handler(req, res) {
       const data = req.body;
       const preprocessed_data = preprocess_data(data);
       const index = generate_embeddings(preprocessed_data);
       const analysis_results = analyze_mental_health(index, "signs of mental health issues");
       res.status(200).json(analysis_results);
   }

7. Create frontend pages:

   • pages/index.js

   import Link from 'next/link';
   
   export default function Home() {
       return (
           <div className="container">
               <h1>Welcome to the Mental Health App</h1>
               <p>Your well-being is our priority.</p>
               <Link href="/data-input"><button>Get Started</button></Link>
               <style jsx>{`
                   .container {
                       display: flex;
                       flex-direction: column;
                       align-items: center;
                       justify-content: center;
                       height: 100vh;
                       text-align: center;
                       background-color: #f0f4f8;
                   }
                   h1 {
                       color: #333;
                   }
                   button {
                       padding: 10px 20px;
                       background-color: #0070f3;
                       color: #fff;
                       border: none;
                       border-radius: 5px;
                       cursor: pointer;
                   }
               `}</style>
           </div>
       );
   }

   • pages/data-input.js

   import { useState } from 'react';
   import Router from 'next/router';
   
   export default function DataInput() {
       const [data, setData] = useState('');
   
       const handleSubmit = async () => {
           const response = await fetch('/api/analyze_mental_health', {
               method: 'POST',
               headers: {
                   'Content-Type': 'application/json',
               },
               body: JSON.stringify({ content: data }),
           });
           const result = await response.json();
           Router.push({
               pathname: '/results',
               query: { analysis: JSON.stringify(result) },
           });
       };
   
       return (
           <div className="container">
               <h1>Input Your Data</h1>
               <textarea
                   value={data}
                   onChange={(e) => setData(e.target.value)}
                   placeholder="Enter your recent social media posts or thoughts here..."
               ></textarea>
               <button onClick={handleSubmit}>Analyze</button>
               <style jsx>{`
                   .container {
                       display: flex;
                       flex-direction: column;
                       align-items: center;
                       justify-content: center;
                       height: 100vh;
                       text-align: center;
                       background-color: #f0f4f8;
                   }
                   textarea {
                       width: 80%;
                       height: 200px;
                       padding: 10px;
                       border: 1px solid #ccc;
                       border-radius: 5px;
                       margin-bottom: 20px;
                   }
                   button {
                       padding: 10px 20px;
                       background-color: #0070f3;
                       color: #fff;
                       border: none;
                       border-radius: 5px;
                       cursor: pointer;
                   }
               `}</style>
           </div>
       );
   }

   • pages/results.js

   import { useRouter } from 'next/router';
   
   export default function Results() {
       const router = useRouter();
       const { analysis } = router.query;
       const parsedAnalysis = analysis ? JSON.parse(analysis) : {};
   
       return (
           <div className="container">
               <h1>Analysis Results</h1>
               <pre>{JSON.stringify(parsedAnalysis, null, 2)}</pre>
               <button onClick={() => router.push('/')}>Go Back</button>
               <style jsx>{`
                   .container {
                       display: flex;
                       flex-direction: column;
                       align-items: center;
                       justify-content: center;
                       height: 100vh;
                       text-align: center;
                       background-color: #f0f4f8;
                   }
                   pre {
                       text-align: left;
                       background: #fff;
                       padding: 20px;
                       border-radius: 5px;
                       box-shadow: 0 0 10px rgba(0, 0, 0, 0.1);
                   }
                   button {
                       padding: 10px 20px;
                       background-color: #0070f3;
                       color: #fff;
                       border: none;
                       border-radius: 5px;
                       cursor: pointer;
                       margin-top: 20px;
                   }
               `}</style>
           </div>
       );
   }

Deployment

1. Deploy the Backend:

   You can use any cloud provider like AWS, Google Cloud, or Azure. For simplicity, here's an example using AWS Elastic Beanstalk:

   eb init -p python-3.8 mental-health-app
   eb create mental-health-app-env

2. Deploy the Frontend with Vercel:

   vercel deploy

Usage

1. Start the backend server:

   python app.py

2. Navigate to your Vercel deployment URL to use the frontend interface.

Security and Privacy

• Ensure HTTPS is used for secure communication.
• Implement authentication and authorization.
• Comply with data protection regulations (e.g., GDPR).

Contributing

Contributions are welcome! Please submit a pull request or open an issue to discuss any changes.

License

This project is licensed under the MIT License.