update app.py to use st.cache_resource (much faster/more responsive)

video_semantic_search/app.py

@@ -9,6 +9,7 @@ import pandas as pd
 import streamlit as st
 
 from pipeline import clip_wrapper
+from pipeline.process_videos import DATAFRAME_PATH
 
 NUM_FRAMES_TO_RETURN = 21
 
@@ -37,8 +38,9 @@ class SemanticSearcher:
  ]
 
 
-DATASET_PATH: Final[str] = os.environ.get("DATASET_PATH", "data/dataset.parquet")
-SEARCHER: Final[SemanticSearcher] = SemanticSearcher(pd.read_parquet(DATASET_PATH))
+@st.cache_resource
+def get_semantic_searcher():
+ return SemanticSearcher(pd.read_parquet(DATAFRAME_PATH))
 
 
 @dataclass
@@ -93,7 +95,7 @@ def display_search_results(results: list[SearchResult]) -> None:
  st.markdown(
  f"""
  <a href="{get_video_url(result.video_id, result.timestamp)}">
- <img src="data:image/jpeg;base64,{result.base64_image}" alt="frame {result.frame_idx} timestamp {int(result.timestamp)}" width="100%">
+ <img src="data:image/jpeg;base64,{result.base64_image.decode()}" alt="frame {result.frame_idx} timestamp {int(result.timestamp)}" width="100%">
  </a>
  """,
  unsafe_allow_html=True,
@@ -110,9 +112,10 @@ def main():
  st.markdown("_App by Ben Tenmann and Sidney Radcliffe_")
  st.text_input("What are you looking for?", key="query")
  query = st.session_state["query"]
+ searcher = get_semantic_searcher()
  if query:
  st.text("Click image to open video")
- display_search_results(SEARCHER.search(query))
+ display_search_results(searcher.search(query))
 
 
 if __name__ == "__main__":