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 MALT (Multi-Agent Learning Task) is a sophisticated orchestration framework that coordinates multiple specialized AI agents to tackle complex tasks through structured conversations. Inspired by the principles outlined in the [MALT research paper](https://arxiv.org/pdf/2412.01928), this implementation provides a reliable, extensible system for multi-agent collaboration.
 
 The framework is designed around a three-agent architecture:
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 1. **Creator Agent**: Generates initial content or solutions
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 2. **Verifier Agent**: Critically evaluates the creator's output
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 3. **Refiner Agent**: Improves the solution based on verifier feedback
 
 This collaborative approach enables high-quality outputs for complex tasks by combining the strengths of multiple specialized agents, each focused on a different aspect of the problem-solving process.