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<!DOCTYPE html>
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<head>
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<title>AgentSquare: Automatic LLM Agent Search In Modular Design Space</title>
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<h1 id="title-text"><img src="static/img/icon/logo.jpg" id="title-icon" alt="AgentSquare">AgentSquare: Automatic LLM Agent Search In<br>
Modular Design Space<br>
(2024)
</h1>
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<a class="nav-button" href="https://arxiv.org/abs/2410.06153">
<img src="static/img/icon/paper_icon.png" alt="Paper">Paper
</a>
<a class="nav-button" href="https://github.com/tsinghua-fib-lab/AgentSquare" class="ext-link" target="_blank">
<img src="static/img/icon/code_icon.png" alt="Code">Code
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<div class="main-body">
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<h2>About AgentSquare</h2>
<p style="line-height: 150%">
<b>AgentSquare</b> is a novel LLM agent search framework that utilizes module evolution and recombination to efficiently optimize agent designs across
a modular design space consisting of Planning, Reasoning, Tool Use, and Memory modules.<br>
Main Performance of different Methods across various tasks and the modules that different agents contain are shown below, please check our <a
class="ext-link" href="module.html">New module</a> for more details about New Modules.
</p>
</div>
<div style="text-align: center; margin-top: 15px;">
<img src="demo.gif" alt="AgentSquare Module Overview" style="width: 100%; max-width: 1200px;">
</div>
<div style="text-align: left; margin-top: 10px;">
<p><b>Demo with ALFWorld:</b></p>
</div>
<div style="text-align: center;">
<video src="ALFWorld_demo.mp4" controls style="width: 100%; max-width: 1200px; margin-top: 10px;">
Your browser does not support the video tag.
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by:
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id="sort-by-reward-score">
Performance
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id="sort-by-grounding-acc">
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<canvas id="chart-success-reward-rate" width="520" height="500"></canvas>
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<script src="static/javascript/main_results_show.js" type="module"></script>
<div class="main-body">
<div class="section">
<!-- figure 1 -->
<h2>Overview of AgentSquare</h2>
<p style="line-height: 150%">
<b>AgentSquare</b> is a <b>modular framework</b> for designing and optimizing LLM agents.
We first propose a modular design space of LLM agents and extract 4 types of standardized modules
including <b>planning</b>, <b>reasoning</b>, <b>tooluse</b>, and <b>memory</b>. Based on this, we design a novel <b>LLM agent
search framework</b> to automatically discover good-performing agents.
You may check
our <a
class="ext-link" href="https://arxiv.org/abs/2410.06153" target="_blank">paper</a> for more details.
</p>
<div class="example-box">
<figure id="example-img" style="margin-left: 10px;">
<img src="static/img/f1.jpg" alt="figure1.jpg">
</figure>
</div>
<!-- figure 2 -->
<h2>Modular Design Space of LLM Agents</h2>
<p style="line-height: 150%; margin-top: 15px;">
Here is the illustration of the modular agent design space and <b>agentic workflow</b> (left) and the <b>standardized IO interface</b> of four types of modules (right).
</p>
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<figure id="example-img">
<img src="static/img/f2.jpg" alt="figure2.jpg" width="1000px">
</figure>
</div>
<!-- figure 3 -->
<h2>AgentSquare Search Framework</h2>
<p style="line-height: 150%; margin-top: 15px;">
The following figure is the overview of <b>AgentSquare search framework</b>. AgentSquare optimizes LLM agents through
the mechanisms of module <b>evolution</b> and <b>recombination</b>. We further introduce a <b>performance predictor</b> that implements
an in- context surrogate model for efficient evaluation of novel agents.
</p>
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<figure id="example-img">
<img src="static/img/f3.jpg" alt="figure3.jpg" width="1000px">
</figure>
</div>
</div>
<div class="section">
<div id="Contribute to AgentSquare" class="anchor"></div>
<h2>Contribute to AgentSquare</h2>
<p>
We invite you to contribute to AgentSquare by helping us standardize interfaces for additional agent modules.
By expanding our module pool, we can enhance the search process and discover even more optimized agents.
If you have ideas for new modules or interface improvements, we welcome your contributions to build a more robust framework.<br>
<br>
Here is the <a
class="ext-link" href="https://github.com/tsinghua-fib-lab/AgentSquare/blob/main/standard_module_interface.docx" target="_blank">guidance document</a> of standardizing human-designed agents,
and you can submit your standardized modules through this <a
class="ext-link" href="https://drive.google.com/drive/folders/1CrtW_s3n0-tCJRtUDzaKFWrBid7MuF9v" target="_blank">link</a>.
</p>
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<div id="citation" class="anchor"></div>
<h2>Citation</h2>
<!-- <p>-->
<!-- If the paper or codes inspires you, please cite us:-->
<!-- </p>-->
<pre class="bibtax">
@article{shang2024agentsquare,
title={AgentSquare: Automatic LLM Agent Search in Modular Design Space},
author={Shang, Yu and Li, Yu and Zhao, Keyu and Ma, Likai and Liu, Jiahe and Xu, Fengli and Li, Yong},
journal={arXiv preprint arXiv:2410.06153},
year={2024}
}
</pre>
</div>
<!-- Authors -->
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<h2>Contact Us</h2>
<p>If you have any questions about AgentSquare, Please contact us at <a href="mailto:[email protected]">[email protected]</a>
or create an issue on <a
href="https://github.com/tsinghua-fib-lab/AgentSquare" class="ext-link" target="_blank"> Github</a>.
For potential collaboration, please contact <a href="mailto:[email protected]">[email protected]</a>.
</p>
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© 2024
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