add streamlit frontend stuff

frontend/styles.css

@@ -0,0 +1,44 @@
+/* White mode CSS */
+
+body {
+    background-color: #FFFFFF; /* Light background */
+    color: #212529; /* Dark text */
+}
+
+.stApp {
+    background-color: #FFFFFF; /* Light background */
+}
+
+h1, h2, h3, h4, h5, h6 {
+    color: #212529; /* Dark headings */
+}
+
+a {
+    color: #007BFF; /* Bootstrap primary link color */
+}
+
+.css-18e3th9 {
+    background-color: #F8F9FA; /* Light gray for input fields */
+    border-color: #CED4DA; /* Gray border for input fields */
+}
+
+.dark-mode-btn {
+    position: absolute;
+    top: 10px;
+    right: 10px;
+    background-color: transparent;
+    border: none;
+    font-size: 20px;
+    cursor: pointer;
+    color: #212529; /* Dark button text */
+}
+
+/* Change the text color of the input field */
+input {
+    color: #212529; /* Dark input text */
+}
+
+/* Change the placeholder text color */
+input::placeholder {
+    color: #6C757D; /* Placeholder color */
+}

streamlit.py

@@ -0,0 +1,37 @@
+import streamlit as st
+
+from core.recommender import EmbeddingProcessor, Recommender
+
+st.title("U.S. ML PhD Faculty Advisor Recommender")
+
+# Define CSS for light and dark mode toggle
+def load_css(css_file):
+    with open(css_file, "r") as f:
+        st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)
+
+load_css("frontend/styles.css")
+
+
+# Set up
+embedding_processor = EmbeddingProcessor()
+recommender = Recommender(embedding_processor)
+
+# Query input field
+query = st.text_input("Name an ML research area you are interested in (e.g. low-rank adaptation)")
+
+# Search and display professors
+if query:
+    top_k_indices = recommender.get_top_k(query, top_k=10)
+    professors_data = recommender.get_recommended_data(top_k_indices)
+
+    if professors_data:
+        for professor_data in professors_data:
+            st.subheader(professor_data["name"])
+            st.write(f"{professor_data['title']} of {professor_data['department']}, {professor_data['university']}")
+
+            # List of papers
+            st.write("Most Relevant Papers:")
+            for paper in professor_data["papers"]:
+                st.markdown(f"- [{paper[1]}](https://arxiv.org/abs/{paper[0]})")
+    else:
+        st.write("No results found for your query.")