DARK

DARK is an open-source movie curation platform built on Hexagonal architecture. Nyx OS routes Gemini tool calls to reactive web layouts and secure Slack adapters.

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Inspiration

We were inspired by the Decision Fatigue Crisis in modern streaming. Viewers spend an average of 18 18 minutes scrolling through repetitive catalogs before selecting a film—with nearly half of all sessions ending in choice paralysis. Existing recommendation engines operate as opaque, black-box algorithms that isolate viewers. We built DARK as a community-driven open-source solution to transform movie discovery into an interactive, explainable, and collaborative experience.

What it does

Conversational Discovery: The central AI assistant, Nyx, processes natural language requests, reasons about user preferences, and executes structured layout changes directly on the page. Dynamic Analytics: Tracks user behavioral telemetry across 8 statistical dimensions to display an interactive Movie DNA chart and assign taste personas. Collaborative Curation: Users can organize watchlists into custom Favorite folders, sync profiles with a partner using Co-Viewing sharing codes, or query recommendations inside team channels using our Slack Bolt adapter.

How we built it

We also built an automated prioritized model rotation queue backed by a stateful circuit breaker to handle API disruptions.

Challenges we ran into

Our primary technical hurdle was maintaining model latency and system availability under strict API rate limits. Sending raw user profiles consumed excessive quota. We solved this by developing a Dynamic Context Builder that compresses user context profile

Accomplishments that we're proud of

Developing the real-time Movie DNA Engine, which dynamically recalibrates telemetry metrics, donut charts, and unlocks progressive avatar styles based on live interaction scoring. Building a secure, production-ready Slack integration from scratch, utilizing Bolt event listeners, timing-safe HMAC-SHA256 signature verification, and dynamic Block Kit layouts.

What we learned

We learned that generative AI is most effective when integrated as a structured logic director rather than just a text generator. By training Gemini prompts to return deterministic JSON commands instead of conversational prose, we converted a standard chat bot into a dynamic visual curation system.

What's next for DARK

MCP Server Port: Expose Taste DNA profiles to native desktop clients via a Model Context Protocol tool server. Group Curation Blending: Implementing collaborative team taste DNA profiles to blend multiple members' interactions into a unified movie recommendation feed.

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