made streamlit ui for base search ui

pyproject.toml

@@ -14,6 +14,7 @@ dependencies = [
     "pyarrow>=18.1.0",
     "sentence-transformers>=3.3.1",
     "sentencepiece>=0.2.0",
+    "streamlit>=1.41.1",
     "torch>=2.5.1",
     "tqdm>=4.67.1",
     "unidic-lite>=1.0.8",

requirements.txt

@@ -9,4 +9,5 @@ pandas
 numpy
 polars
 pyarrow
-duckdb
+duckdb
+streamlit

src/app.py

@@ -0,0 +1,51 @@
+import streamlit as st
+import duckdb
+from embedding import get_embeddings
+from config import DUCKDB_FILE
+
+
+@st.cache_resource
+def get_conn():
+    return duckdb.connect(DUCKDB_FILE)
+
+
+query = """WITH ordered_embeddings AS (
+    SELECT embeddings.id, embeddings.part FROM embeddings
+        ORDER BY array_distance(embedding, ?::FLOAT[1024])
+    LIMIT 10
+)
+SELECT
+    p.title,
+    p.date,
+    e.start,
+    e.text
+  FROM
+      ordered_embeddings oe
+  JOIN
+      episodes e
+    ON
+      oe.id = e.id AND oe.part = e.part
+  JOIN
+      podcasts p
+    ON
+      oe.id = p.id;
+"""
+
+st.title("terapyon cannel search")
+
+word = st.text_input("Search word")
+if word:
+    st.write(f"Search word: {word}")
+    embeddings = get_embeddings([word], query=True)
+    word_embedding = embeddings[0, :]
+
+    conn = get_conn()
+    result = conn.execute(query, (word_embedding,)).df()
+    selected = st.dataframe(result, 
+                            on_select="rerun",
+                            selection_mode="single-row")
+    if selected:
+        rows = selected["selection"].get("rows")
+        if rows:
+            row = rows[0]
+            st.text(result.iloc[row, 3])