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d7efa84 | 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 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 | """Admin panel for tracking labeler progress and activity."""
import csv
import logging
import os
from pathlib import Path
import streamlit as st
from config import load_config
logger = logging.getLogger(__name__)
def render_admin_panel():
"""Render the admin dashboard."""
config = load_config()
# Header with logout
col_title, col_logout = st.columns([4, 1])
with col_title:
st.title("Admin Panel")
with col_logout:
from auth import logout
if st.button("Logout"):
logout()
st.rerun()
# Tabs for different views
tab_progress, tab_metadata, tab_skipped, tab_activity, tab_downloads = st.tabs(
["Progress", "Metadata CSVs", "Skipped Audios", "Activity Log", "Downloads"]
)
with tab_progress:
_render_progress(config)
with tab_metadata:
_render_metadata_viewer(config)
with tab_skipped:
_render_skipped_viewer(config)
with tab_activity:
_render_activity_log(config)
with tab_downloads:
_render_downloads(config)
def _read_csv_rows(csv_path: str) -> list[dict]:
"""Read all rows from a CSV file."""
path = Path(csv_path)
if not path.exists():
return []
try:
with open(path, "r", encoding="utf-8", newline="") as f:
reader = csv.DictReader(f)
return [row for row in reader]
except Exception as e:
logger.warning(f"Could not read CSV {csv_path}: {e}")
return []
def _count_audio_files(audio_folder: str) -> int:
"""Count WAV files in a folder."""
folder = Path(audio_folder)
if not folder.exists():
return 0
return sum(1 for f in folder.iterdir() if f.suffix.lower() == ".wav" and f.is_file())
def _render_progress(config: dict):
"""Render progress tracking for each labeler."""
st.subheader("Labeler Progress")
shared_output_dir = config["shared_output_dir"]
skip_csv_path = os.path.join(shared_output_dir, "skipped_audios.csv")
skip_rows = _read_csv_rows(skip_csv_path)
for labeler_name, labeler_cfg in config["labelers"].items():
st.markdown(f"### {labeler_name}")
total_files = _count_audio_files(labeler_cfg["audio_folder"])
csv_path = os.path.join(labeler_cfg["output_dir"], f"{labeler_name}_metadata.csv")
labeled_rows = _read_csv_rows(csv_path)
labeled_count = len(labeled_rows)
# Count skips for this labeler
skipped_count = sum(1 for r in skip_rows if r.get("labeler") == labeler_name)
remaining = max(0, total_files - labeled_count - skipped_count)
col1, col2, col3, col4 = st.columns(4)
col1.metric("Total", total_files)
col2.metric("Labeled", labeled_count)
col3.metric("Skipped", skipped_count)
col4.metric("Remaining", remaining)
if total_files > 0:
progress = (labeled_count + skipped_count) / total_files
st.progress(min(progress, 1.0))
else:
st.progress(0.0)
st.divider()
def _render_metadata_viewer(config: dict):
"""Render metadata CSV viewer for each labeler."""
st.subheader("Metadata CSVs")
for labeler_name, labeler_cfg in config["labelers"].items():
csv_path = os.path.join(labeler_cfg["output_dir"], f"{labeler_name}_metadata.csv")
rows = _read_csv_rows(csv_path)
with st.expander(f"{labeler_name} β {len(rows)} entries", expanded=False):
if rows:
st.dataframe(rows, use_container_width=True)
else:
st.info("No labels recorded yet.")
def _render_skipped_viewer(config: dict):
"""Render skipped audios CSV viewer."""
st.subheader("Skipped Audios")
shared_output_dir = config["shared_output_dir"]
skip_csv_path = os.path.join(shared_output_dir, "skipped_audios.csv")
rows = _read_csv_rows(skip_csv_path)
if rows:
# Filter by labeler
labelers = list(config["labelers"].keys())
selected_labeler = st.selectbox(
"Filter by labeler", options=["All"] + labelers, key="skip_filter"
)
if selected_labeler != "All":
rows = [r for r in rows if r.get("labeler") == selected_labeler]
st.dataframe(rows, use_container_width=True)
st.caption(f"Total skipped: {len(rows)}")
else:
st.info("No skipped audios recorded yet.")
def _render_activity_log(config: dict):
"""Render recent activity from both metadata and skip CSVs."""
st.subheader("Activity Log")
# Collect all activity with timestamps
activities = []
# From metadata CSVs (no timestamp column, so we just show them)
for labeler_name, labeler_cfg in config["labelers"].items():
csv_path = os.path.join(labeler_cfg["output_dir"], f"{labeler_name}_metadata.csv")
rows = _read_csv_rows(csv_path)
for row in rows:
activities.append({
"labeler": row.get("labeler", labeler_name),
"action": "labeled",
"source": row.get("source", ""),
"details": f"gender={row.get('gender', '')}, pii={row.get('pii', '')}",
"timestamp": "",
})
# From skip CSV (has timestamps)
shared_output_dir = config["shared_output_dir"]
skip_csv_path = os.path.join(shared_output_dir, "skipped_audios.csv")
skip_rows = _read_csv_rows(skip_csv_path)
for row in skip_rows:
activities.append({
"labeler": row.get("labeler", ""),
"action": "skipped",
"source": row.get("source", ""),
"details": row.get("reason", ""),
"timestamp": row.get("timestamp", ""),
})
# Sort by timestamp (skips have timestamps, labels don't β labels go to end)
activities.sort(key=lambda x: x["timestamp"] or "0", reverse=True)
if activities:
# Show last 50
st.dataframe(activities[:50], use_container_width=True)
st.caption(f"Showing latest {min(50, len(activities))} of {len(activities)} total actions.")
else:
st.info("No activity recorded yet.")
def _render_downloads(config: dict):
"""Render download buttons for CSV files."""
st.subheader("Download Reports")
# Metadata CSVs
for labeler_name, labeler_cfg in config["labelers"].items():
csv_path = os.path.join(labeler_cfg["output_dir"], f"{labeler_name}_metadata.csv")
path = Path(csv_path)
if path.exists():
data = path.read_bytes()
st.download_button(
label=f"π₯ {labeler_name}_metadata.csv",
data=data,
file_name=f"{labeler_name}_metadata.csv",
mime="text/csv",
key=f"dl_metadata_{labeler_name}",
)
else:
st.caption(f"{labeler_name}_metadata.csv β not yet created")
st.divider()
# Skipped CSV
shared_output_dir = config["shared_output_dir"]
skip_csv_path = os.path.join(shared_output_dir, "skipped_audios.csv")
skip_path = Path(skip_csv_path)
if skip_path.exists():
data = skip_path.read_bytes()
st.download_button(
label="π₯ skipped_audios.csv",
data=data,
file_name="skipped_audios.csv",
mime="text/csv",
key="dl_skipped",
)
else:
st.caption("skipped_audios.csv β not yet created")
st.divider()
# App log file
log_dir = os.environ.get("LOG_DIR", "/var/log/audio_labeling_tool")
log_path = Path(log_dir) / "app.log"
if log_path.exists():
data = log_path.read_bytes()
st.download_button(
label="π₯ app.log",
data=data,
file_name="app.log",
mime="text/plain",
key="dl_log",
)
else:
st.caption("app.log β not yet created")
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