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- content="Deformable Neural Radiance Fields creates free-viewpoint portraits (nerfies) from casually captured videos.">
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- <title>Nerfies: Deformable Neural Radiance Fields</title>
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  <div class="container is-max-desktop">
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- <h1 class="title is-1 publication-title">Nerfies: Deformable Neural Radiance Fields</h1>
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- <div class="is-size-5 publication-authors">
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- <span class="author-block">
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- <a href="https://keunhong.com" target="_blank">Keunhong Park</a><sup>1</sup>,</span>
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- <span class="author-block">
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- <a href="https://utkarshsinha.com" target="_blank">Utkarsh Sinha</a><sup>2</sup>,</span>
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- <a href="https://jonbarron.info" target="_blank">Jonathan T. Barron</a><sup>2</sup>,
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- <a href="http://sofienbouaziz.com" target="_blank">Sofien Bouaziz</a><sup>2</sup>,
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- <a href="https://www.danbgoldman.com" target="_blank">Dan B Goldman</a><sup>2</sup>,
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- <a href="https://homes.cs.washington.edu/~seitz/" target="_blank">Steven M. Seitz</a><sup>1,2</sup>,
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- </span>
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- <a href="http://www.ricardomartinbrualla.com" target="_blank">Ricardo Martin-Brualla</a><sup>2</sup>
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- </span>
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  <div class="is-size-5 publication-authors">
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- <span class="author-block"><sup>1</sup>University of Washington,</span>
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- <span class="author-block"><sup>2</sup>Google Research</span>
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- <a href="https://arxiv.org/pdf/2011.12948" target="_blank"
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- </span>
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- <span>Paper</span>
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  </a>
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- <a href="https://arxiv.org/abs/2011.12948" target="_blank"
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- <span>arXiv</span>
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  <h2 class="subtitle has-text-centered">
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- <span class="dnerf">Nerfies</span> turns selfie videos from your phone into
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- free-viewpoint
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- portraits.
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- <h2 class="title is-3">Abstract</h2>
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- We present the first method capable of photorealistically reconstructing a non-rigidly
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- deforming scene using photos/videos captured casually from mobile phones.
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- </p>
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- <p>
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- Our approach augments neural radiance fields
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- (NeRF) by optimizing an
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- additional continuous volumetric deformation field that warps each observed point into a
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- canonical 5D NeRF.
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- We observe that these NeRF-like deformation fields are prone to local minima, and
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- propose a coarse-to-fine optimization method for coordinate-based models that allows for
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- more robust optimization.
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- By adapting principles from geometry processing and physical simulation to NeRF-like
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- models, we propose an elastic regularization of the deformation field that further
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- improves robustness.
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- </p>
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- <p>
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- We show that <span class="dnerf">Nerfies</span> can turn casually captured selfie
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- photos/videos into deformable NeRF
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- models that allow for photorealistic renderings of the subject from arbitrary
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- viewpoints, which we dub <i>"nerfies"</i>. We evaluate our method by collecting data
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- using a
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- rig with two mobile phones that take time-synchronized photos, yielding train/validation
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- images of the same pose at different viewpoints. We show that our method faithfully
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- reconstructs non-rigidly deforming scenes and reproduces unseen views with high
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- fidelity.
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  </p>
 
 
 
 
 
 
 
 
 
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- <h2 class="title is-3">Video</h2>
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- <iframe src="https://www.youtube.com/embed/MrKrnHhk8IA?rel=0&amp;showinfo=0"
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- frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
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- <h2 class="title is-3">Visual Effects</h2>
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- Using <i>nerfies</i> you can create fun visual effects. This Dolly zoom effect
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- would be impossible without nerfies since it would require going through a wall.
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- <h2 class="title is-3">Matting</h2>
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- <p>
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- As a byproduct of our method, we can also solve the matting problem by ignoring
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- samples that fall outside of a bounding box during rendering.
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- <video id="matting-video" controls playsinline height="100%">
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- <!--/ Matting. -->
 
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- <div class="column is-full-width">
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- <h2 class="title is-3">Animation</h2>
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-
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- <!-- Interpolating. -->
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- <h3 class="title is-4">Interpolating states</h3>
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- <div class="content has-text-justified">
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- <p>
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- We can also animate the scene by interpolating the deformation latent codes of two input
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- frames. Use the slider here to linearly interpolate between the left frame and the right
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- frame.
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- </p>
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- <div class="columns is-vcentered interpolation-panel">
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- <img src="./static/images/interpolate_start.jpg"
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- alt="Interpolate start reference image."/>
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- <p>Start Frame</p>
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- <div class="column interpolation-video-column">
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- <div id="interpolation-image-wrapper">
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- Loading...
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- step="1" min="0" max="100" value="0" type="range">
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- <img src="./static/images/interpolate_end.jpg"
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- class="interpolation-image"
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- alt="Interpolation end reference image."/>
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- <p class="is-bold">End Frame</p>
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- </div>
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- </div>
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- <br/>
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- <!--/ Interpolating. -->
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- <!-- Re-rendering. -->
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- <h3 class="title is-4">Re-rendering the input video</h3>
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  <div class="content has-text-justified">
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- <p>
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- Using <span class="dnerf">Nerfies</span>, you can re-render a video from a novel
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- viewpoint such as a stabilized camera by playing back the training deformations.
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- </p>
 
 
 
 
 
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- <div class="content has-text-centered">
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- <video id="replay-video"
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- controls
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- muted
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- preload
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- playsinline
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- width="75%">
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- <source src="./static/videos/replay.mp4"
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- type="video/mp4">
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- </video>
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- </div>
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- <!--/ Re-rendering. -->
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-
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  </div>
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  </div>
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- <!--/ Animation. -->
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-
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- <!-- Concurrent Work. -->
 
 
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- <div class="column is-full-width">
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- <h2 class="title is-3">Related Links</h2>
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-
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- <div class="content has-text-justified">
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- <p>
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- There's a lot of excellent work that was introduced around the same time as ours.
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- </p>
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- <p>
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- <a href="https://arxiv.org/abs/2104.09125" target="_blank">Progressive Encoding for Neural Optimization</a> introduces an idea similar to our windowed position encoding for coarse-to-fine optimization.
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- </p>
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- <p>
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- <a href="https://www.albertpumarola.com/research/D-NeRF/index.html" target="_blank">D-NeRF</a> and <a href="https://gvv.mpi-inf.mpg.de/projects/nonrigid_nerf/" target="_blank">NR-NeRF</a>
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- both use deformation fields to model non-rigid scenes.
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- </p>
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- <p>
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- Some works model videos with a NeRF by directly modulating the density, such as <a href="https://video-nerf.github.io/" target="_blank">Video-NeRF</a>, <a href="https://www.cs.cornell.edu/~zl548/NSFF/" target="_blank">NSFF</a>, and <a href="https://neural-3d-video.github.io/" target="_blank">DyNeRF</a>
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- </p>
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- <p>
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- There are probably many more by the time you are reading this. Check out <a href="https://dellaert.github.io/NeRF/" target="_blank">Frank Dellart's survey on recent NeRF papers</a>, and <a href="https://github.com/yenchenlin/awesome-NeRF" target="_blank">Yen-Chen Lin's curated list of NeRF papers</a>.
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- </p>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- <!--/ Concurrent Work. -->
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-
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  </section>
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  <section class="section" id="BibTeX">
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  <div class="container is-max-desktop content">
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  <h2 class="title">BibTeX</h2>
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- <pre><code>@article{park2021nerfies,
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- author = {Park, Keunhong and Sinha, Utkarsh and Barron, Jonathan T. and Bouaziz, Sofien and Goldman, Dan B and Seitz, Steven M. and Martin-Brualla, Ricardo},
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- title = {Nerfies: Deformable Neural Radiance Fields},
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- journal = {ICCV},
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- year = {2021},
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  }</code></pre>
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  </div>
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  </section>
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  <footer class="footer">
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+ <h1 class="title is-1 publication-title">LangGraph Agent Chat UI</h1>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ <span class="author-block">A React/Vite Interface for LangGraph Agents</span>
 
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  <p>
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+ The <strong>Agent Chat UI</strong> is a React/Vite application that provides a clean, chat-based interface for interacting with your LangGraph agents. It’s designed to work seamlessly with LangGraph’s core features, including checkpoints, thread management, and human-in-the-loop capabilities.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
82
  </p>
83
+ <p>Here’s why it’s a valuable tool:</p>
84
+ <ul>
85
+ <li><strong>Easy Connection:</strong> Connect to local or deployed LangGraph agents with a simple URL and graph ID.</li>
86
+ <li><strong>Intuitive Chat:</strong> Interact naturally with your agents in a familiar chat format.</li>
87
+ <li><strong>Visualize Agent Actions:</strong> See tool calls and their results rendered directly in the UI.</li>
88
+ <li><strong>Human-in-the-Loop Made Easy:</strong> Seamlessly integrate human input using LangGraph’s <code>interrupt</code> feature.</li>
89
+ <li><strong>Explore Execution Paths:</strong> Travel through time, inspect checkpoints, and fork conversations.</li>
90
+ <li><strong>Debug and Understand:</strong> Inspect the full state of your LangGraph thread at any point.</li>
91
+ </ul>
92
  </div>
93
  </div>
94
  </div>
 
 
 
 
 
 
 
 
 
 
 
 
 
95
  </div>
96
  </section>
97
 
 
98
  <section class="section">
99
  <div class="container is-max-desktop">
100
+ <h2 class="title is-3 has-text-centered">Get Started</h2>
101
  <div class="columns is-centered">
102
+ <div class="column is-four-fifths">
 
 
103
  <div class="content">
104
+ <h3 class="title is-4">1. Try the Deployed Version (No Setup Required!)</h3>
105
+ <ul>
106
+ <li><strong>Visit:</strong> <a href="https://agentchat.vercel.app/" target="_blank">agentchat.vercel.app</a></li>
107
+ <li><strong>Connect:</strong> Enter your LangGraph deployment URL and graph ID (the <code>path</code> set with <code>langserve.add_routes</code>). For production, include your LangSmith API key.</li>
108
+ <li><strong>Chat!</strong> Start interacting with your agent.</li>
109
+ </ul>
110
+
111
+ <h3 class="title is-4">2. Run Locally (Development & Customization)</h3>
112
+ <p><strong>Option A: Clone the Repository</strong></p>
113
+ <pre><code>git clone https://github.com/langchain-ai/agent-chat-ui.git
114
+ cd agent-chat-ui
115
+ pnpm install # Or npm install/yarn install
116
+ pnpm dev # Or npm run dev/yarn dev</code></pre>
117
+
118
+ <p><strong>Option B: Quickstart with <code>npx</code></strong></p>
119
+ <pre><code>npx create-agent-chat-app
120
+ cd agent-chat-app
121
+ pnpm install # Or npm install/yarn install
122
+ pnpm dev # Or npm run dev/yarn dev</code></pre>
123
+ <p>Open your browser to <code>http://localhost:5173</code>.</p>
 
 
 
 
 
 
 
 
124
  </div>
125
  </div>
126
  </div>
127
+ </div>
128
+ </section>
129
 
130
+ <section class="section">
131
+ <div class="container is-max-desktop">
132
+ <h2 class="title is-3 has-text-centered">Features</h2>
133
  <div class="columns is-centered">
134
+ <div class="column is-four-fifths">
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
135
  <div class="content has-text-justified">
136
+ <ul>
137
+ <li><strong>Easy Connection:</strong> Connect to local or production LangGraph deployments with a URL and graph ID.</li>
138
+ <li><strong>Chat Interface:</strong> Real-time messaging with automatic checkpoint persistence.</li>
139
+ <li><strong>Tool Call Rendering:</strong> Visualize tool calls and results, compatible with LangGraph’s <a href="https://python.langchain.com/docs/guides/tools/custom_tools" target="_blank">tool calling</a>.</li>
140
+ <li><strong>Human-in-the-Loop Support:</strong> Review, edit, and respond to interrupts using LangGraph’s <code>interrupt</code> function.</li>
141
+ <li><strong>Thread History:</strong> Navigate past interactions with checkpointing.</li>
142
+ <li><strong>Time Travel and Forking:</strong> Explore execution paths with LangGraph’s <a href="https://python.langchain.com/docs/modules/agents/concepts#checkpointing" target="_blank">checkpointing</a>.</li>
143
+ <li><strong>State Inspection:</strong> Debug by examining the full LangGraph thread state.</li>
144
+ </ul>
145
  </div>
 
 
 
 
 
 
 
 
 
 
 
 
 
146
  </div>
147
  </div>
148
+ </div>
149
+ </section>
150
 
151
+ <section class="section">
152
+ <div class="container is-max-desktop">
153
+ <h2 class="title is-3 has-text-centered">LangGraph Setup Examples</h2>
154
  <div class="columns is-centered">
155
+ <div class="column is-four-fifths">
156
+ <div class="content">
157
+ <h3 class="title is-4">Basic LangGraph Agent</h3>
158
+ <pre><code class="language-python"># agent.py
159
+ from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
160
+ from langchain_openai import ChatOpenAI
161
+ from langgraph.prebuilt import create_agent_executor
162
+ from langserve import add_routes
163
+ from fastapi import FastAPI
164
+
165
+ prompt = ChatPromptTemplate.from_messages([
166
+ ("system", "You are a helpful assistant"),
167
+ MessagesPlaceholder(variable_name="messages"),
168
+ MessagesPlaceholder(variable_name="agent_scratchpad"),
169
+ ])
170
+ model = ChatOpenAI(temperature=0)
171
+ agent = {"messages": lambda x: x["messages"], "agent_scratchpad": lambda x: []} | prompt | model
172
+ app = create_agent_executor(agent, [])
173
+ fastapi_app = FastAPI(title="LangGraph Agent")
174
+ add_routes(fastapi_app, app, path="/chat")
175
+
176
+ if __name__ == "__main__":
177
+ import uvicorn
178
+ uvicorn.run(fastapi_app, host="localhost", port=2024)
179
+ </code></pre>
180
+ <p>Run at <code>http://localhost:2024/chat</code> with graph ID <code>chat</code>.</p>
181
+
182
+ <h3 class="title is-4">Human-in-the-Loop Example</h3>
183
+ <pre><code class="language-python"># agent.py
184
+ from langgraph.prebuilt import create_agent_executor, interrupt
185
+ from langchain_core.tools import tool
186
+
187
+ @tool
188
+ def write_email(subject: str, body: str, to: str):
189
+ return f"Draft email to {to} with subject {subject} sent."
190
+
191
+ tools = [write_email]
192
+ model = ChatOpenAI(model="gpt-4-turbo-preview").bind_tools(tools)
193
+
194
+ def handle_interrupt(state):
195
+ messages = state["messages"]
196
+ if isinstance(messages[-1].content, list):
197
+ for msg in messages[-1].content:
198
+ if isinstance(msg, ToolInvocation) and msg.name == "write_email":
199
+ return interrupt(messages, {"type": "interrupt", "args": {"type": "response", "studio": msg.args}})
200
+ return {"messages": messages}
201
+
202
+ agent = {"messages": lambda x: x["messages"], "agent_scratchpad": lambda x: []} | prompt | model | handle_interrupt
203
+ app = create_agent_executor(agent, tools)
204
+ fastapi_app = FastAPI(title="LangGraph Agent")
205
+ add_routes(fastapi_app, app, path="/email_agent")
206
+
207
+ if __name__ == "__main__":
208
+ import uvicorn
209
+ uvicorn.run(fastapi_app, host="localhost", port=2024)
210
+ </code></pre>
211
+ <p>Run at <code>http://localhost:2024/email_agent</code> with graph ID <code>email_agent</code>.</p>
212
  </div>
213
  </div>
214
  </div>
 
 
215
  </div>
216
  </section>
217
 
 
218
  <section class="section" id="BibTeX">
219
  <div class="container is-max-desktop content">
220
  <h2 class="title">BibTeX</h2>
221
+ <pre><code>@misc{langgraph2023agentchat,
222
+ title = {LangGraph Agent Chat UI},
223
+ author = {LangChain Team},
224
+ year = {2023},
225
+ url = {https://github.com/langchain-ai/agent-chat-ui}
226
  }</code></pre>
227
  </div>
228
  </section>
229
 
 
230
  <footer class="footer">
231
  <div class="container">
232
  <div class="content has-text-centered">
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+ <a class="icon-link" href="https://github.com/langchain-ai/agent-chat-ui" target="_blank">
 
 
 
 
234
  <i class="fab fa-github"></i>
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  </a>
236
  </div>
 
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  <div class="column is-8">
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  <div class="content">
240
  <p>
241
+ This website is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/" target="_blank">Creative Commons Attribution-ShareAlike 4.0 International License</a>.
 
 
 
 
 
 
 
 
 
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