Resonance Engine: Hackathon Story

Inspiration

We were inspired by the idea that culture drives connection—between brands, artists, and audiences. Qloo’s Taste AI unlocks deep, cross-domain insights, and we wanted to build a tool that could instantly analyze cultural compatibility and spark creative collaborations using the latest in AI.

What We Learned

  • How to integrate external APIs (Qloo) with LLMs for richer, actionable insights.
  • The power of open-source LLMs like Llama 3 for privacy, cost, and flexibility.
  • Building real-time streaming UIs in Next.js for a smooth user experience.
  • Handling API errors gracefully and providing fallback logic.

How We Built It

  • Frontend: Next.js with React, streaming markdown output, PDF download, and copy/share features.
  • Backend: LangChain agents, Qloo API integration, and Llama 3 via Ollama for local LLM reasoning.
  • Features: Creative mode for campaign ideas, intermediate steps display, actionable recommendations, and robust error handling.
  • Expandability: Architecture supports OpenAI, Anthropic, and future creative tools like Stable Diffusion.

Challenges

  • Qloo API Authorization: Our biggest challenge was getting a valid Qloo API key before the deadline. We built robust fallback logic so the app remains useful even if Qloo is unavailable.
  • Streaming Output: Implementing real-time streaming from local LLMs required careful handling of chunked responses.
  • Time Constraints: Building a polished, feature-rich demo in a short timeframe pushed us to prioritize and iterate quickly.

Math & Reasoning

We explored compatibility scoring using cosine similarity and set intersections, e.g.:

$$ \text{Compatibility} = \frac{|A_{\text{values}} \cap B_{\text{values}}|}{|A_{\text{values}} \cup B_{\text{values}}|} $$

This approach can be extended for more advanced cultural graph analysis.


Resonance Engine is ready for real-world use and further development.
We’re excited to see how AI and cultural intelligence can shape the future of collaboration!

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