The inspiration for Gemini-MAS (Multi-Agent System) came from several key insights:
- 🤖 Google Gemini's Capabilities: The remarkable multimodal abilities of Gemini API opened possibilities for sophisticated agent design
- 🔗 Distributed Systems Philosophy: Principles from distributed computing showed how independent agents could collaborate effectively
- 🧠 Cognitive Science: Understanding how human teams solve problems through specialization and communication
- 🎯 Real-World Complexity: Modern applications demand systems that can decompose problems, delegate tasks, and synthesize solutions
What I Built 🏗️
Gemini-MAS is a sophisticated multi-agent orchestration framework powered by Google Gemini API that enables:
- Task Decomposition: Breaking down complex problems into manageable subtasks
- Agent Specialization: Different agents with distinct roles and expertise
- Dynamic Collaboration: Real-time communication and coordination between agents
- Adaptive Execution: Self-optimizing workflows based on intermediate results
- Scalable Architecture: Support for horizontal scaling and distributed deployment
Core Architecture
$$\text{Input Task} \rightarrow \text{Orchestrator} \rightarrow \begin{cases} \text{Agent}_1 \ \text{Agent}_2 \ \vdots \ \text{Agent}_n \end{cases} \rightarrow \text{Aggregator} \rightarrow \text{Output}$$
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