Augplot 0.3.0

Added

• ChatGPT sign-in with secure credential storage, account switching, model discovery,
  and per-account model selection, alongside existing API-provider configuration.
• Full-input category counts and saved rejected-generation diagnostics, with an optional
  second repair attempt through max_repairs=2.
• Reusable count-weighted empirical smoothing and renderer-aware direct curve labels,
  with SciPy-backed helpers bundled into standalone Python exports.
• Bounded grouped relationship profiles, numeric quantiles, and explicit coverage,
  sampling, log-transform, and truncation metadata.
• Optional max_model_calls budget shared across generation, repairs, and clarification,
  and inspectable attempted-call counts on charts and Augplot failures.
• An opt-in H–R visual-evaluation harness and unrelated complex-plot regressions.

Changed

• Accept single-binding pyplot colormap calls and bounded literal numeric formatting,
  including Unicode-aware format-width limits.
• Guide generation toward statistical smoothing and consistent external-colorbar layout.
• Version helper/profile changes in history identity while preserving existing workflow,
  live Figures, provider setup, and execution guardrails.
• Add SciPy 1.11.4 or newer as a runtime dependency for shared smoothing.
• Refresh the H–R notebook with a short appearance-focused request and strict fresh
  one-call generation. Document sparse and contaminated class-label limits.

Fixed

• Allow library-internal date-formatting imports and NumPy dtype=object annotations
  while retaining generated-code import and reflection restrictions.
• Report undefined generated names in repair diagnostics without exposing raw data or
  library-internal names, and mask account identity in ChatGPT plotting progress.
• Avoid duplicate inline figures in the H–R notebook's standalone-export example.

Augplot 0.2.0

What’s new in Augplot 0.2.0

• A simpler generated-code validator supports more common Pandas and NumPy plotting patterns while retaining checks for unsafe operations and excessive resource use.
• Plotting now shows generation and repair progress, including a status message when a model request takes longer than 20 seconds.
• Updated chart guidance improves title sizing, legend placement, labels, and spacing.
• The refreshed quickstart and new anonymized cross-validation notebook include saved chart examples.
  Saved visualizations may be regenerated because the validator and prompt versions changed.

Full Changelog: v0.1.1...v0.2.0

Augplot 0.1.1

What's Changed

• Broaden guarded plotting compatibility by @egpand in #6
• Prepare 0.1.1 release by @egpand in #7

Full Changelog: v0.1.0...v0.1.1

Augplot 0.1.0 — first PyPI beta

First PyPI beta

Augplot 0.1.0 is the first public beta release on PyPI. It turns plain-language
visualization requests into inspectable, reusable Matplotlib or Seaborn code directly
from a notebook.

Highlights

• Generate a plot from in-memory pandas, NumPy, and common Python data structures.
• Refine an existing visualization with follow-up instructions.
• Re-render saved code against compatible data without another model request.
• Export generated visualizations as standalone Python functions.
• Cache and replay matching visualization history locally.
• Use bounded data profiles and conservative generated-code validation.
• Support Python 3.11 through 3.14 and LiteLLM-compatible providers with strict JSON
  Schema responses.

Install

pip install augplot

This is a beta release, so APIs and saved-history formats may change before 1.0.
Generated Python is validated before local execution, but execution is not an OS
sandbox. Review generated code before using it with sensitive data or in
security-critical environments.

See the README for configuration and the
quick-start workflow.