File size: 2,709 Bytes
b5ff3a4 f89e539 b5ff3a4 e85bb51 a671301 b5ff3a4 65c9ca0 f89e539 b5ff3a4 e85bb51 b5ff3a4 e85bb51 f89e539 e85bb51 416c906 4cf6559 a31425b 4cf6559 e85bb51 a31425b e85bb51 a31425b e85bb51 a671301 895e3ae e85bb51 895e3ae e85bb51 a671301 e85bb51 d5e4e4a e85bb51 895e3ae e85bb51 a31425b a671301 5fde344 a31425b e85bb51 a47efdc 895e3ae a671301 895e3ae a671301 895e3ae a0a9509 d5e4e4a a671301 895e3ae 9302019 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 |
import os
import duckdb
import streamlit as st
from huggingface_hub import hf_hub_download
import pandas as pd
import tempfile
import re
HF_REPO_ID = "stcoats/temp-duckdb-upload"
HF_FILENAME = "ycsep.duckdb"
LOCAL_PATH = "./ycsep.duckdb"
st.set_page_config(layout="wide")
st.title("YCSEP Audio Dataset Viewer")
# Download database if missing
if not os.path.exists(LOCAL_PATH):
st.write("Downloading from HF Hub...")
hf_hub_download(
repo_id=HF_REPO_ID,
repo_type="dataset",
filename=HF_FILENAME,
local_dir=".",
local_dir_use_symlinks=False
)
st.success("Download complete.")
# Connect (only once)
@st.cache_resource(show_spinner=False)
def get_duckdb_connection():
return duckdb.connect(LOCAL_PATH, read_only=True)
try:
con = get_duckdb_connection()
st.success("Connected to DuckDB.")
except Exception as e:
st.error(f"DuckDB connection failed: {e}")
st.stop()
# Search
query = st.text_input("Search text (case-insensitive)", "").strip()
if query:
query_like = f"%{query.lower()}%"
sql = """
SELECT id, channel, video_id, speaker, start_time, end_time, upload_date, text, pos_tags, audio
FROM data
WHERE LOWER(text) LIKE ?
LIMIT 100
"""
df = con.execute(sql, [query_like]).df()
else:
df = con.execute("""
SELECT id, channel, video_id, speaker, start_time, end_time, upload_date, text, pos_tags, audio
FROM data
LIMIT 100
""").df()
st.markdown(f"### Showing {len(df)} results")
if len(df) == 0:
st.warning("No matches found.")
else:
def render_audio(audio_bytes):
try:
if isinstance(audio_bytes, (bytes, bytearray, memoryview)):
data = bytes(audio_bytes)
elif isinstance(audio_bytes, list):
data = bytes(audio_bytes)
else:
return ""
with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp:
tmp.write(data)
tmp.flush()
return f'<audio controls style="height:20px; width:100px;"> <source src="file://{tmp.name}" type="audio/mpeg"></audio>'
except Exception:
return ""
df["Audio"] = df["audio"].apply(render_audio)
df_display = df.drop(columns=["audio"]).copy()
st.markdown("### Results Table (Sortable with Audio Column)")
st.markdown("(Scroll right to view audio controls)")
st.dataframe(df_display.drop(columns=["Audio"]))
st.markdown("### Audio Previews")
for i, row in df_display.iterrows():
st.markdown(f"**{row['speaker']} | {row['text']}**")
st.markdown(df.loc[i, "Audio"], unsafe_allow_html=True)
|