Epokio
Watch, compare, queue and report machine learning training runs from a web page, a tray icon, a terminal or the macOS menu bar. Epokio reads the files your framework already writes, so there is no logging code to add, no account and no cloud.
What it does
- See every run on this machine or a remote GPU box: state, epoch, time left, best score, curves, plain-language notes ("recall is much higher than precision…") and the result images your framework saved.
- Get told when a run finishes, fails (NaN loss), stalls or reaches a target score: on the Mac, in the tray, or as a phone push (ntfy, Slack, Discord, Telegram).
- Compare runs: only the settings that differ, a settings table for a whole sweep next to each run's main score, CSV export and Markdown reports.
- Start and queue runs (Ultralytics YOLO) from the web page, one at a time, with a data check before
starting, a one-button Python setup (CUDA PyTorch on NVIDIA machines), resume from
weights/last.pt, and failure causes in plain words. - AI assistants can read and queue runs through the MCP server (
pip install "epokio[mcp]").
Reads Ultralytics (results.csv), Hugging Face Trainer (trainer_state.json), PyTorch Lightning
(metrics.csv), Keras (CSVLogger) and TensorBoard event files (read without TensorFlow). A hand-written
loop shows up with two lines:
import epokio
with epokio.start("runs/my-model", epochs=50, lr=1e-4) as run:
for epoch in range(50):
...
run.log(val_loss=vl, accuracy=acc)
Start
pip install epokio
epokio setup # finds your runs, starts the helper, opens the page
epokio setup --lan # also let your phone or another computer watch this machine
Other commands: epokio watch (terminal view, good over SSH), epokio tray (pip install "epokio[tray]"),
epokio doctor (what Epokio sees, for a bug report), epokio agent --stop.
Viewing is open on this machine; anything that starts, stops or changes something needs the machine's token
(epokio agent --show-token). The helper uses only the Python standard library.
MIT licence.
Release files for epokio 0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| epokio-0.3.0.tar.gz | 225.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| epokio-0.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 408.5 kB
Release files / epokio-0.3.0.tar.gz
| Download URL | epokio-0.3.0.tar.gz |
|---|---|
| Size | 225.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
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Transparency logRelease files / epokio-0.3.0-py3-none-any.whl
| Download URL | epokio-0.3.0-py3-none-any.whl |
|---|---|
| Size | 183.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
2ced2eaaa9bdb50db756269f609f29615858b38d413b6e5b8969d9a1b87903f9
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 26, 2026.
Transparency log