Neeko

by weiyifan1023 · indexed from github

Code and Data for EMNLP 2024 Paper "Neeko: Leveraging Dynamic LoRA for Efficient Multi-Character Role-Playing Agent"

Large Language Models (LLMs) have revolutionized open-domain dialogue agents but encounter challenges in multi-character role-playing (MCRP) scenarios. To address the issue, we present Neeko, an innovative framework designed for efficient multiple characters imitation. Unlike existing methods, Neeko employs a dynamic low-rank adapter (LoRA) strategy, enabling it to adapt seamlessly to diverse characters. Our framework breaks down the role-playing process into agent pre-training, multiple characters playing, and character incremental learning, effectively handling both seen and unseen roles.

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# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/weiyifan1023-neeko/.well-known/agent.json

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#      is the id from the card's skills[], verbatim (standard §26).
#     We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }'

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ragcodedata

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