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Craft Generative AI for User Generated Content

Inspired by vision to include generative AI-powered user-generated content (UGC), this challenge tasks participants with building a sophisticated multi-agent system for creating, moderating, and personalizing short-form multimodal content. The system will employ Claude Opus 4.1 for its advanced creative generation and nuanced ethical reasoning capabilities, ensuring content aligns with user defined brand safety and creative guidelines. LangGraph will be used to orchestrate a dynamic, graph-based workflow for content generation, review, and iteration. This will include agents specializing in ideation, multimodal asset generation (text-to-video/image), and a crucial moderation agent that applies 'Guidance' for constrained generation, ensuring content adheres to specific brand safety and thematic rules. The challenge emphasizes balancing creative freedom with strict content policy enforcement.

Status
Always open
Difficulty
Advanced
Points
500
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Challenge at a glance
Host and timing
Vera

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Inspired by vision to include generative AI-powered user-generated content (UGC), this challenge tasks participants with building a sophisticated multi-agent system for creating, moderating, and personalizing short-form multimodal content. The system will employ Claude Opus 4.1 for its advanced creative generation and nuanced ethical reasoning capabilities, ensuring content aligns with user defined brand safety and creative guidelines. LangGraph will be used to orchestrate a dynamic, graph-based workflow for content generation, review, and iteration. This will include agents specializing in ideation, multimodal asset generation (text-to-video/image), and a crucial moderation agent that applies 'Guidance' for constrained generation, ensuring content adheres to specific brand safety and thematic rules. The challenge emphasizes balancing creative freedom with strict content policy enforcement.

Datasets

Shared data for this challenge

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Learning goals

What you should walk away with

Master LangGraph for building complex, stateful Directed Acyclic Graph (DAG) agent workflows with dynamic branching and human-in-the-loop steps.

Implement multimodal generation techniques with Claude Opus 4.1 for creative text, image, and short video content, ensuring brand alignment.

Utilize Llama 4 (or similar customizable open-source model) for fine-tuned creative variations and character generation within content.

Design and integrate a 'Guidance'-enabled agent for real-time constrained content generation and automated policy adherence checks.

Orchestrate agent-to-agent content review loops, where a generation agent submits content to a moderation agent, with feedback for iterative improvement.

Integrate Semantic Kernel plugins for connecting to external APIs (e.g., video synthesis, image processing) to enhance multimodal capabilities.

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Timeline and host

Operating window

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