https://github.com/jivan052/supermind

Level Supermind Hackathon | Social Media Analytics Module | Langflow + Datastax Astra DB + GPT Model
https://github.com/jivan052/supermind

datastax-astra-db gpt-4o-mini langflow level-supermind-hackathon react

Last synced: about 2 months ago
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Level Supermind Hackathon | Social Media Analytics Module | Langflow + Datastax Astra DB + GPT Model

• Host: GitHub
• URL: https://github.com/jivan052/supermind
• Owner: Jivan052
• License: mit
• Created: 2025-01-07T15:59:40.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-01-08T17:49:19.000Z (over 1 year ago)
• Last Synced: 2025-07-03T14:09:01.473Z (12 months ago)
• Topics: datastax-astra-db, gpt-4o-mini, langflow, level-supermind-hackathon, react
• Language: JavaScript
• Homepage: https://supermind.vercel.app
• Size: 967 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

Awesome Lists containing this project

README

          
# 📊 Social Media Engagement Analytics Module

## 🌟 Overview

This project provides a **basic analytics module** to analyze social media engagement data, utilizing cutting-edge technologies for seamless workflow creation ( Langflow ), database operations ( Datastax Astra DB ), and insights generation( gpt ).

### ✨ Key Features

- **📥 Data Ingestion**: Store and manage mock social media engagement data in **DataStax Astra DB**.

- **🔍 Data Querying**: Query average engagement metrics (likes, comments, shares) based on post types.

- **📈 Insights Generation**: Leverage **Langflow** and GPT models for actionable insights.

- **📊 Visualization**: Display results using **React** and data visualization libraries like **Chart.js**.

- **💬 Chat Interface**: Enable users to ask questions and view insights via a chatbot interface.

---

## 🛠️ Technologies Used

- **☁️ DataStax Astra DB**: Cloud-based NoSQL database for scalable and efficient data storage.

- **🔗 Langflow**: Workflow tool for creating GPT-based automation and insights generation.

- **⚛️ React**: Frontend framework for user-friendly interfaces.

- **📊 Chart.js**: Library for creating data visualizations.

- **🤖 OpenAI GPT-4 API**: For advanced language understanding and insights generation.

---

## 🧩 Workflow Overview

 

### 🖧 Backend Workflow

1. **📥 Data Ingestion**:

   - Loading of mock engagement data (schema: `ID`, `Post Type`, `Likes`, `Comments`, `Shares`, etc.) into Astra DB.

2. **🔍 Data Querying**:

   - Querying of Astra DB for average engagement metrics based on post types.

   

3. **🤖 Insights Generation**:

   - Processing metrics using **Langflow** workflows integrated with GPT.

   - Generating text-based and graphical responses.

### 🎨 Frontend Workflow

- **📝 Input Form**:

  - Allows users to select post types or ask questions about engagement metrics.

  

- **📊 Results Display**:

  - Displays GPT-generated insights (text-based) to user.

  - Visualize engagement data using graphs (e.g., comparisons of likes, shares, comments).

- **💬 Chat Feature**:

  - Enable GPT-driven chat for user queries.

  - Dynamic responses to engagement-related questions.

---

## ⚙️ Implementation Steps

### 1️⃣ Mock Data Creation

- Created a schema: `ID`, `Post Type`, `Likes`, `Comments`, `Shares` for data.

- Uploaded this dataset to **DataStax Astra DB**.

### 2️⃣ Backend Development

- **🔗 Langflow Workflow**:

  - Takes input from users (e.g., Post Type).

  - Query the Astra DB for data.

  - Processes metrics via GPT.

  - Generates actionable insights as output.

### 3️⃣ Frontend Development

- Built the UI with **⚛️ React**:

  - Input form for queries.

  - Visualizations using **📊 Chart.js**.

  - Integration of GPT chat for engagement analysis.

---

## 📷 Screenshots and Diagrams

### 🖥️ User Interface

![Frontend](website.png)

### 🖥️ Langflow Workflow

![Langflow Workflow](WF_1.png)

![Langflow Workflow](WF_2.png)

![Langflow chat](chat.png)

### 🗄️ DataStax Astra DB Integration

![Astra DB Integration](DB_AS.png)

---

## 🎥 Demo and Resources

- **🌐 Web Application**: [[Link to the Web App](https://supermind.vercel.app/)](#) *(API integration pending)*  

- **🎬 YouTube Walkthrough**: [[YouTube Video](https://youtu.be/N7OWdsmktcg)](#)  

- **👨‍💻 FindCoder Project Link**: [[FindCoder Link](https://www.findcoder.io/projects/social-media-analytics-module/677ea2468015401a988d9768)](#)

---

## 🚀 Future Enhancements

- 🔗 Complete integration of API endpoints with the React frontend.

- 🤖 Enhance chatbot capabilities for more dynamic interactions.

- 📊 Add support for more visualization options (e.g., pie charts, heatmaps).

---

## 🔚 Conclusion

The **Social Media Engagement Analytics Module** demonstrates the power of integrating cutting-edge technologies like **DataStax Astra DB**, **Langflow**, and **OpenAI GPT-4** to analyze, process, and generate actionable insights from social media data. By combining data storage, querying, and advanced AI workflows, this project provides a scalable and efficient solution for understanding audience engagement.

### Key Takeaways:

- **Data-Driven Insights**: The module helps identify trends in social media performance, empowering users to make informed decisions.

- **Scalable Architecture**: Leveraging cloud-based solutions ensures reliability and scalability for large datasets.

- **User-Friendly Interaction**: The chatbot interface and visualization tools provide an intuitive way for users to engage with data.

This project lays the groundwork for future improvements, such as full frontend-backend integration, enhanced visualization, and more robust chatbot interactions. It showcases the potential of AI and cloud technologies in addressing real-world challenges, making it a valuable tool for businesses and individuals seeking to optimize their social media strategies.

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## 🤝 Contributors

Prepared by **Jivan Jamdar** & **Team CodeByte**




 




Happy coding...

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