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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