use GH API to fetch up-to-date stargazers_count

add CHGNet to cv.projects

src/routes/cv/+page.svelte

@@ -1,6 +1,7 @@
 <script lang="ts">
   import Icon from '@iconify/svelte'
-  import cv from './cv-data.yml'
+
+  export let data
 
   const email = `janosh@lbl.gov`
   const links = { target: `_blank`, rel: `noreferrer` }
@@ -73,16 +74,17 @@
 <section class="body">
   <small>
     I joined the Materials Project in early 2023 where I build high-throughput workflows
-    for generating large DFT and ML potential datasets. I am a core maintainer of
+    for generating large DFT datasets. I am a core maintainer of
     <a href="https://github.com/materialsproject/pymatgen">pymatgen</a>
-    and enjoy building infrastructure around high-quality open source software that enables
-    new capabilities in computational materials to scale.
+    and enjoy building high-quality open source software that enables new capabilities in computational
+    materials to scale. In particular, my current interests are on further development, training
+    and benchmarking of universal interatomic potentials.
   </small>
   <h2>
     <Icon inline icon="zondicons:education" />&nbsp; Education
   </h2>
   <ul>
-    {#each cv.education as { title, thesis_title, date, href, uni }}
+    {#each data.cv.education as { title, thesis_title, date, href, uni }}
       <li>
         <h4>
           <a {href}>{title}</a>
@@ -97,7 +99,7 @@
     <Icon inline icon="iconoir:journal" />&nbsp; Selected Publications
   </h2>
   <ul>
-    {#each cv.publications as { title, authors, journal, date, url: href, arxiv }}
+    {#each data.cv.publications as { title, authors, journal, date, url: href, arxiv }}
       {@const year = new Date(date).getFullYear()}
       <li>
         <h4>{title}</h4>
@@ -121,7 +123,7 @@
     <!-- <small>only lead dev repos</small> -->
   </h2>
   <ul>
-    {#each cv.projects as { url, img_style, github, name, description, stars, logo }}
+    {#each data.cv.projects as { url, img_style, github, name, description, stars, logo }}
       {@const logo_url = logo ?? `${url}/favicon.svg`}
       <li>
         <h4>
@@ -147,7 +149,7 @@
     <Icon inline icon="mdi:trophy" />&nbsp; Awards
   </h2>
   <ul>
-    {#each cv.awards as { name, description, date, href }}
+    {#each data.cv.awards as { name, description, date, href }}
       <li>
         <h4><a {href}>{name}</a></h4>
         <p>{description} <small>{date}</small></p>
@@ -159,7 +161,7 @@
     <Icon inline icon="material-symbols:volunteer-activism" />&nbsp; Volunteer Work
   </h2>
   <ul>
-    {#each cv.volunteer as { name, description, href, logo, role }}
+    {#each data.cv.volunteer as { name, description, href, logo, role }}
       <li>
         <h4>
           <a {href}><img src={logo} alt={name} height="20" />{name}</a>
@@ -176,7 +178,7 @@
     <Icon inline icon="lucide:languages" />&nbsp; Languages
   </h3>
   <ul>
-    {#each cv.languages as { name, level }}
+    {#each data.cv.languages as { name, level }}
       <li>
         {name}
         <Icon inline icon="carbon:skill-level-{level}" />
@@ -187,7 +189,7 @@
   <h3>
     <Icon inline icon="mdi:earth" />&nbsp; Nationality
     <ul>
-      {#each cv.nationality as nat}
+      {#each data.cv.nationality as nat}
         <li>{nat}</li>
       {/each}
     </ul>
@@ -197,7 +199,7 @@
     <Icon inline icon="carbon:skill-level-advanced" />&nbsp; Skills
   </h3>
   <ul class="skills">
-    {#each cv.skills as { name, icon, score, href }}
+    {#each data.cv.skills as { name, icon, score, href }}
       <!-- color based on score style="color: hsl({score * 20}, 100%, 40%)" -->
       <li style:font-weight={(score - 3) * 100}>
         <a {href}>
@@ -213,7 +215,7 @@
     <Icon inline icon="material-symbols:interests" />&nbsp; Hobbies
   </h3>
   <ul>
-    {#each cv.hobbies as { name, icon, href }}
+    {#each data.cv.hobbies as { name, icon, href }}
       <li>
         <a {href}>
           <Icon inline {icon} />
@@ -228,7 +230,7 @@
     &nbsp; Memberships
   </h3>
   <ul>
-    {#each cv.memberships as { name, date, href }}
+    {#each data.cv.memberships as { name, date, href }}
       <li>
         <a {href}>{name}</a>&ensp;<small>{date}</small>
       </li>

src/routes/cv/+page.ts

@@ -0,0 +1,21 @@
+import cv from './cv.yml'
+
+export const load = async ({ fetch }) => {
+  // fetch the number of GitHub stars for each repo the projects array in cv.yml
+
+  const token = import.meta.env.VITE_GITHUB_TOKEN
+
+  for (const project of cv.projects) {
+    const handle = project.github.replace(`https://github.com/`, ``)
+
+    const response = await fetch(`https://api.github.com/repos/${handle}`, {
+      headers: {
+        Authorization: `token ${token}`,
+      },
+    })
+    const json = await response.json()
+    project.stars = json.stargazers_count
+  }
+
+  return { cv }
+}

src/routes/cv/cv-data.yml → src/routes/cv/cv.yml

@@ -61,38 +61,36 @@ projects:
     img_style: 'filter: invert(1);'
     github: https://github.com/janosh/matbench-discovery
     description: Benchmark for machine learning energy models simulating a real-world materials discovery campaign. Interactive leader board and Python package make new model submissions easy.
+  - name: CHGNet
+    url: https://chgnet.lbl.gov
+    github: https://github.com/CederGroupHub/chgnet
+    description: Pretrained universal neural network potential for charge-informed atomistic modeling. Published on the cover of Nature Machine Intelligence.
   - name: Elementari
     url: https://elementari.janosh.dev
     github: https://github.com/janosh/elementari
     description: A library of Svelte components for building interactive web apps with performant chemistry visualizations like periodic tables, Bohr atoms, nuclei, heatmaps, scatter plots.
-    stars: 49
   - name: pymatviz
     url: https://pymatviz.janosh.dev
     img_style: 'filter: invert(1);'
     github: https://github.com/janosh/pymatviz
     description: A toolkit for visualizations in materials informatics to complement pymatgen.
-    stars: 48
   - name: Tensorboard Reducer
     github: https://github.com/janosh/tensorboard-reducer
     logo: https://raw.githubusercontent.com/janosh/tensorboard-reducer/main/assets/tensorboard-reducer-square.svg
     description: Reduce multiple PyTorch TensorBoard runs to new events/CSV/JSON. Good for model ensembles.
-    stars: 51
     pypi: https://pypi.org/project/tensorboard-reducer
   - name: Aviary
     github: https://github.com/CompRhys/aviary
     logo: https://raw.githubusercontent.com/janosh/tikz/main/assets/aviary/aviary.svg
     description: Multiple ML energy model implementations (Roost, Wren, CGCNN, Wrenformer) with a consistent API.
-    stars: 21
     pypi: https://pypi.org/project/tensorboard-reducer
   - name: Normalizing Flows
     github: https://github.com/janosh/awesome-normalizing-flows
-    stars: 983
     logo: https://api.iconify.design/logos:awesome.svg?color=%23888888
     description: Curated list of resources for learning and using normalizing flows, a powerful tool in ML for modeling probability distributions.
   - name: MultiSelect
     url: https://multiselect.janosh.dev
     github: https://github.com/janosh/svelte-multiselect
-    stars: 146
     description: Keyboard-friendly, accessible and customizable multi-select web component.
 
 skills: