Multi-Agent-LLMs/mallm

Framework: Multi-Agent LLMs For Conversational Task-Solving (MALLM)

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/ 100
Emerging

MALLM (Multi-Agent LLMs For Conversational Task-Solving) helps you automate complex conversational tasks using large language models. You provide a dataset of texts or questions and a specific instruction, and the system simulates multiple AI 'agents' debating or collaborating to produce a refined answer or paraphrase. This is ideal for researchers or developers experimenting with advanced LLM behaviors and collective intelligence.

Use this if you need to simulate multi-agent discussions to solve tasks, explore different conversational dynamics, or enhance LLM output quality through simulated debate.

Not ideal if you're looking for a simple, out-of-the-box chatbot or a direct-to-consumer application without a focus on agent-based task resolution.

LLM experimentation conversational AI research agent-based systems natural language processing AI workflow automation
No Package No Dependents
Maintenance 10 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 7 / 25

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Stars

52

Forks

3

Language

Python

License

Apache-2.0

Category

multi-agent-debate-systems

Last pushed

Jan 22, 2026

Commits (30d)

0

GitHub
Multi Agent Debate Systems · 2 models

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