Level SuperMind Pre-Hackathon

TEAM SIZE:

3-4

ENTRY:

Via Qualifiers

LOCATION:

Mumbai (Offline)

Pre-Hackathon Assignment:

Social Media Performance Analysis

Objective:

Build a basic analytics module using Langflow and DataStax to analyze engagement data from mock social media accounts.

Tools to Use:

• DataStax Astra DB for database operations.
• Langflow for workflow creation and GPT integration.

Task Details:

1. Fetch Engagement Data:
   • Create a small dataset simulating social media engagement (e.g., likes, shares, comments, post types).
   • Store this data in DataStax Astra DB.


2. Analyze Post Performance: Using Langflow, build a simple flow that
   • Accepts post types (e.g., carousel, reels, static images) as input.
   • Queries the dataset in Astra DB to calculate average engagement metrics for each post type.


3. Provide Insights: Use GPT integration in Langflow to generate simple insights based on the data
   • Example outputs:
   • Carousel posts have 20% higher engagement than static posts.
   • Reels drive 2x more comments compared to other formats.

Submission requirement:

• -Create your project, link it to level supermind hackathon
• -Record a video describing:
  • --Langflow workflow
  • --How DataStax was used to store and query data
  • --How GPT was leveraged to generate insights
• -Add the link to your Github repository or Google Drive link of the ZIP file containing your code.
• -Add the YouTube video link.
• -Demo videos are a must.
• -The video shouldn't be private.
• -A well-written description is a plus.
• -The project repository must be public.