From Commands to Prompts: LLM-based Semantic File System for AIOS
Large language models (LLMs) have demonstrated significant potential in the
development of intelligent applications and systems such as LLM-based agents
and agent operating systems (AIOS). However, when these applications and
systems interact with the underlying file system, the file system still remains
the traditional paradigm: reliant on manual navigation through precise
commands. This paradigm poses a bottleneck to the usability of these systems as
users are required to navigate complex folder hierarchies and remember cryptic
file names. To address this limitation, we propose an LLM-based semantic file
system ( LSFS ) for prompt-driven file management. Unlike conventional
approaches, LSFS incorporates LLMs to enable users or agents to interact with
files through natural language prompts, facilitating semantic file management.
At the macro-level, we develop a comprehensive API set to achieve semantic file
management functionalities, such as semantic file retrieval, file update
monitoring and summarization, and semantic file rollback). At the micro-level,
we store files by constructing semantic indexes for them, design and implement
syscalls of different semantic operations (e.g., CRUD, group by, join) powered
by vector database. Our experiments show that LSFS offers significant
improvements over traditional file systems in terms of user convenience, the
diversity of supported functions, and the accuracy and efficiency of file
operations. Additionally, with the integration of LLM, our system enables more
intelligent file management tasks, such as content summarization and version
comparison, further enhancing its capabilities.
6711adca41ad206aabacc032
Zeru Shi
6711adca41ad206aabacc033
Kai Mei
6711adca41ad206aabacc034
Mingyu Jin
6711adca41ad206aabacc035
Yongye Su
6711adca41ad206aabacc036
Chaoji Zuo
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Wenyue Hua
claimed_verified
2025-08-06T19:45:09.266Z
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https://cdn-avatars.huggingface.co/v1/production/uploads/639a25aba2b0b1c9d85a51e8/pphz-MK62hPNbBkMHAkeR.jpeg
Wenyue Hua
user
wenyueH
6711adca41ad206aabacc038
Wujiang Xu
6711adca41ad206aabacc039
Yujie Ren
6711adca41ad206aabacc03a
Zirui Liu
6711adca41ad206aabacc03b
Mengnan Du
6711adca41ad206aabacc03c
Dong Deng
6711adca41ad206aabacc03d
Yongfeng Zhang
From Commands to Prompts: LLM-based Semantic File System for AIOS
Large language models (LLMs) have demonstrated significant potential in the
development of intelligent applications and systems such as LLM-based agents
and agent operating systems (AIOS). However, when these applications and
systems interact with the underlying file system, the file system still remains
the traditional paradigm: reliant on manual navigation through precise
commands. This paradigm poses a bottleneck to the usability of these systems as
users are required to navigate complex folder hierarchies and remember cryptic
file names. To address this limitation, we propose an LLM-based semantic file
system ( LSFS ) for prompt-driven file management. Unlike conventional
approaches, LSFS incorporates LLMs to enable users or agents to interact with
files through natural language prompts, facilitating semantic file management.
At the macro-level, we develop a comprehensive API set to achieve semantic file
management functionalities, such as semantic file retrieval, file update
monitoring and summarization, and semantic file rollback). At the micro-level,
we store files by constructing semantic indexes for them, design and implement
syscalls of different semantic operations (e.g., CRUD, group by, join) powered
by vector database. Our experiments show that LSFS offers significant
improvements over traditional file systems in terms of user convenience, the
diversity of supported functions, and the accuracy and efficiency of file
operations. Additionally, with the integration of LLM, our system enables more
intelligent file management tasks, such as content summarization and version
comparison, further enhancing its capabilities.
An LLM-based semantic file system enhances file management through natural language prompts and semantic operations, improving user convenience and system capabilities.
LLMs LLM-based agents agent operating systems AIOS semantic file system LSFS semantic file management API set semantic file retrieval file update monitoring summarization semantic file rollback semantic indexes vector database CRUD group by join content summarization version comparison