# fossasia/visdom

Tool for real-time visualization, monitoring and collaborative analysis of AI/ML experiments and live data. Supports Python, PyTorch/Torch, NumPy, TensorFlow/Keras https://visdom.dev

Repository: https://github.com/fossasia/visdom
Canonical: https://ross.abutalabs.com/products/visdom
Homepage: https://visdom.dev
Language: Python
License: Apache-2.0
License Family: permissive
Last push: 2026-08-26T16:43:06+00:00

## Health v2 (maintenance only)
Score: 67/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 8, longevity 100
- inputs: {"age_days": 3507, "days_push": 7, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 10282, forks 1248 (observed 2026-08-28T04:10:41.474661+00:00)

## What it is
Visdom is a Python tool for real-time visualization, monitoring, and collaborative analysis of live data and ML experiments. It provides a web-based UI with draggable windows for plots, images, and text, organized into persistent environments for building dashboards and debugging experiments.

## Use cases
- visualize training curves of pytorch experiments in real time
- monitor live data plots from a remote server
- share experiment dashboards with collaborators
- debug machine learning code by inspecting intermediate results
- plot images and text during model training
- build dashboards for live scientific data

## When to choose
- you train models with PyTorch, TensorFlow, or NumPy and want lightweight live plotting
- you need to monitor experiments running on remote machines
- you want a shareable web UI for collaborative experiment inspection

## When to avoid
- you need full experiment-tracking with metrics versioning and model registries like MLflow or W&B
- you only need static publication-quality plots
- your project is not Python-based

## Facets
- artifact type: library
- maturity: active
- function: data-visualization, monitoring, analytics
- domain: data-visualization, machine-learning, data-science, developer-tools
- platform: python, cross-platform
- tags: pytorch, tensorflow, experiment-tracking, dashboards, live-data, plotting, web-server

## Member repositories
- fossasia/visdom (main) score 67

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:41.474661+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:19:20.964081+00:00, confidence not recorded.
  - readme: https://github.com/fossasia/visdom (fetched 2026-08-28T04:10:41.474661+00:00, sha f33b4257490d)
  - homepage: https://visdom.dev (fetched 2026-08-29T08:18:39.742295+00:00, sha 44136fa355b3)
- Data as of 2026-08-30T08:39:29.467469+00:00.