Download dashboard/logs.py from mgbam/AICEO: direct link, hf CLI and curl.
- Browser
- Download file 793 Bytes
-
https://huggingface.co/spaces/mgbam/AICEO/resolve/309404e1401bf41ba6104877bc7bfaeb2bec3196/dashboard/logs.py
- Command line
-
hf download hf://spaces/mgbam/AICEO@309404e1401bf41ba6104877bc7bfaeb2bec3196/dashboard/logs.py
-
curl -L -o logs.py https://huggingface.co/spaces/mgbam/AICEO/resolve/309404e1401bf41ba6104877bc7bfaeb2bec3196/dashboard/logs.py
793 Bytes
| import sqlite3 | |
| import pandas as pd | |
| import streamlit as st | |
| import os | |
| DB_PATH = os.path.join("/mnt/data", "memory.db") | |
| def show_logs(): | |
| # Ensure DB exists | |
| if not os.path.exists(DB_PATH): | |
| st.info("No logs yet β run your first pipeline!") | |
| return | |
| conn = sqlite3.connect(DB_PATH) | |
| df = pd.read_sql("SELECT * FROM memory_logs ORDER BY id DESC", conn) | |
| conn.close() | |
| if df.empty: | |
| st.info("No logs yet β run your first pipeline!") | |
| else: | |
| st.dataframe(df, use_container_width=True) | |
| # Offer download | |
| csv = df.to_csv(index=False).encode("utf-8") | |
| st.download_button( | |
| label="π₯ Download Logs CSV", | |
| data=csv, | |
| file_name="agent_memory_logs.csv", | |
| mime="text/csv" | |
| ) | |