Inspiration
We wanted to create a way for users to see their “year in TikTok” in a wrapped format—analyzing their viewing patterns, behaviors, and engagement, while also generating a fun personality type based on what they watch.
What it does
Our service takes in user watch history and behavior data, sends it to a trained DigitalOcean Gradient AI agent for analysis, and returns insights, statistics, and a personality profile presented in a fun, engaging way.
How we built it
Backend: Flask app handles file uploads, data formatting, and AI agent integration.
AI Analysis: DigitalOcean Gradient agents process the metrics and generate insights, personas, and humorous commentary.
Frontend: Simple and interactive interface displaying statistics, top categories, emotional patterns, and AI-generated personality summaries.
Challenges we ran into
- Connecting to DigitalOcean Gradient agents: Setting up private endpoints and handling access keys for secure communication was tricky.
- Parsing and normalizing CSV data from various sources to feed into the AI agents reliably.
- Ensuring fast response times while orchestrating multiple agents for metrics, persona, and humor generation.
Accomplishments that we're proud of
- Successfully integrated multiple AI agents to generate detailed, personalized insights.
- Created an engaging and visually satisfying “wrapped” experience with meaningful metrics.
- Developed a flexible backend that can be extended to handle multi-agent orchestration and future personalization features.
What we learned
- How to securely connect and authenticate with private AI agents on DigitalOcean.
- Effective techniques for transforming raw user data into actionable metrics.
- Orchestrating multiple AI agents to produce a coherent, entertaining, and informative output.
What's next for Deepfeed Wrapped
- Add features that allow judges or users to input preferences and generate custom analyses.
- Expand multi-platform support, especially mobile, for better accessibility.
- Automate data generation from scraping or other sources to simulate user activity without relying solely on uploads.
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