The project uses ruff for lint+format, and pyright was redundant and
slow. The previous pyright run surfaced ~30 false positives from running
outside the venv plus 5 real-but-minor typing issues that don't justify
the extra CI minutes on a 0.2.x CLI.
CI now runs only ruff check, ruff format --check, and the import/CLI
smoke matrix on 3.10/3.11/3.12/3.13.
The previous config required branch protection with required status checks,
but main has no protection rules configured, so auto-merge never fired and
PRs had to be merged manually.
Switch to direct squash merge in the action itself, which works regardless
of branch protection settings.
Abstract out generate validation and error handling into BaseProvider, eliminating duplicated logic across Anthropic, OpenRouter, and OpenAI providers.
Enhancements:
- Replaced verbose scanning of many manifest files with targeted parsing of key project manifests (pyproject.toml, package.json, requirements.txt).
- Generated a compact one‑line‑per‑file summary, reducing token usage.
- Improved clarity and readability of the AI‑provided context.
Clarify output format and remove redundant guidance.
New Features:
- Added explicit format and type list
Enhancements:
- Simplified instructions, removed unnecessary guidance
Bug Fixes:
- None
Add limits to prevent token‑limit errors during commit generation.
- New `--max-groups` option to cap the number of commit groups.
- New `--max-diff-size` option to set maximum diff size per group (default 8000 chars).
Update logging to reflect the new options and pass them to the engine.
Add token limit error detection and formatting across all provider modules to surface clear diagnostics when context windows are exceeded, improving error messages and preventing silent failures.
New Features
- Introduce `is_token_limit_error` checks in Anthropic, Gemini, Hugging Face, Ollama, OpenAI, and OpenRouter providers.
- Use `format_token_limit_error` to generate user‑friendly error messages for token limit overs.
Enhancements
- Centralize token limit error handling for consistent diagnostics across providers.
- Explicitly re‑raise `RuntimeError` in Hugging Face to preserve original behavior.
Bug Fixes
- None
- Add "ollama" to AI provider choices in config prompts
- Prompt user for Ollama server URL when selecting the Ollama provider
- Store the configured Ollama host in the config under the "ollama_host" key
- Update config saving logic in both edit_config and setup_config functions
- New Features
- Added Ollama as a supported AI model source.
- Updated README and project manifests to include Ollama.
- Enhancements
- Expanded AI model selection to handle local Ollama endpoints.
- Improved dependency resolution for Ollama packages.
- Bug Fixes
- None
Add a new provider that wraps the local Ollama server using an OpenAI‑compatible client, enabling generation via `ollama_host` configuration. This introduces the first provider for local LLM inference.
New Features
- Implement OllamaProvider with a `generate()` method, supporting custom host, model selection, and robust error handling.
Add support for the Ollama provider in the AI generation pipeline and expose a configurable host address.
New Features:
- Introduce `ollama` as a selectable provider.
- Add `ollama_host` configuration option with default `http://localhost:11434`.
Enhancements:
- Extend provider list in error message to include Ollama.
- Enhanced error messages when version cannot be determined, providing clearer guidance.
- Added explicit handling for missing pyproject.toml and TOML parsing errors.
- Improved user feedback for installation corruption issues.
Enhancements:
- Split ModuleNotFoundError and AttributeError handling to deliver clearer diagnostics
- Explicitly list available providers and flag missing provider classes as packaging bugs
Bug Fixes:
- Provide specific guidance when a provider module is not a built‑in module
- Clarify that a missing provider class indicates a packaging issue rather than user error
- New Features - Introduced distinct sections for Performance, Refactor, Tests, Style, and Chore in changelog generation.
- Added dedicated emojis for each new category.
- Updated section ordering to reflect the new categories.
- Enhancements
- Enhanced push logic to fetch upstream before push, avoiding non‑fast‑forward rejections.
- Refactored `is_ahead_of_remote` with a fetch flag to reduce network calls and TOCTOU windows.
- Improved error logging with full traceback for group processing failures.
- Bug Fixes
- Fixed emoji mappings for "Style" and "Other Changes".
- Corrected handling of empty upstream ref to prevent errors.
- Ensured proper exception handling when remote branch is missing.
Added a concise AI‑focused description and a centered badge section to the README, improving the project overview.
New Features- Introduced an AI‑centric tagline that highlights automation of commits, changelogs, and project management tasks.
Enhancements
- Centered and styled the title block for consistent visual presentation.
- Integrated project badges for PyPI version, Python compatibility, license, build status, and pre‑commit.
Bug Fixes
- None.
sankalp
dependabot[bot]