This AI Storyboard Generator represents one of the winning entries from the Mastra Templates Hackathon, showcasing sophisticated multi-agent orchestration for creative content generation.

Hackathon Recognition

Awarded “Best Use of Agent Network” for demonstrating:

• Complex Agent Interdependencies: Agents that build upon each other’s outputs rather than simple parallel processing
• End-to-End Automation: Complete pipeline from story concept to distributed final product
• Creative Domain Application: Sophisticated AI coordination for artistic content generation
• Production-Ready Integration: Full cloud infrastructure and distribution mechanisms

Architecture Overview

Multi-Agent Network Design

The system demonstrates advanced agent specialization with 5 coordinated agents:

Story Analysis Agent: Processes initial story concepts and extracts narrative elements Script Generation Agent: Creates detailed scripts with dialogue and scene descriptions
Image Generation Agent: Produces visual content with consistent character appearances Style Coordination Agent: Ensures visual consistency across multiple scenes Evaluation Agent: Measures output quality using comprehensive metrics

Workflow Pipeline

The complete storyboard generation follows this sophisticated pipeline:

1. Story Input → Story analysis and character extraction
2. Script Generation → Scene-by-scene script development with dialogue
3. Visual Generation → Image creation with character consistency constraints
4. Style Application → Multiple visual styles (anime, cinematic, graphic novel)
5. Quality Evaluation → Automated scoring and feedback metrics
6. Distribution → Cloud integration (Google Drive, AWS S3) and notifications

Technical Implementation

Agent Coordination Patterns

This project exemplifies advanced multi-agent coordination beyond simple parallel execution:

Sequential Dependencies: Story analysis informs script generation, which guides image creation Consistency Constraints: Character appearance data flows between agents to maintain visual coherence Style Propagation: Visual style decisions cascade through the image generation pipeline Quality Feedback: Evaluation results influence subsequent generation iterations

Cloud Integration Architecture

Storage Layer: AWS S3 for asset management and Google Drive for collaborative access Notification System: Automated updates through multiple channels Evaluation Pipeline: Comprehensive metrics covering visual consistency, narrative coherence, and technical quality

Architectural Insights

Advanced Orchestration Patterns

This project reveals several sophisticated patterns beyond basic multi-agent coordination:

Stateful Agent Communication: Agents maintain character and style state across generation steps Conditional Workflow Branching: Different generation paths based on story type and style preferences Quality-Driven Iteration: Feedback loops that enable agents to refine outputs based on evaluation metrics Multi-Modal Coordination: Text, image, and metadata agents working in concert

Creative AI Applications

The storyboard generator demonstrates how multi-agent systems can handle complex creative workflows requiring:

• Narrative Consistency: Maintaining story coherence across multiple scenes
• Visual Continuity: Ensuring character appearances remain consistent throughout
• Style Coherence: Applying unified visual aesthetics across generated content
• Quality Assurance: Automated evaluation to maintain professional standards

This project showcases the maturation of multi-agent systems from technical demonstrations to practical creative tools capable of producing professional-quality content through coordinated AI collaboration.