Add __main__ entry and logging improvements #3
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Pull Request Overview
This PR adds a main module to allow execution via “python -m llmcontext”, swaps print statements for logging calls, and warns when generated context might exceed 1M tokens.
- Enable CLI invocation with a dedicated main module
- Replace direct print calls with logging in favor of verbosity control
- Update version and changelog accordingly
Reviewed Changes
Copilot reviewed 5 out of 5 changed files in this pull request and generated 1 comment.
Show a summary per file
| File | Description |
|---|---|
| tests/test_metadata.py | Updated CLI invocation to use the new main module interface |
| llmcontext/llmcontext.py | Replaced several print calls with logging improvements |
| llmcontext/main.py | Added entry point to support “python -m llmcontext” |
| llmcontext/init.py | Bumped version to 0.1.1 |
| CHANGELOG.md | Documented all new changes in this version update |
Comments suppressed due to low confidence (1)
llmcontext/llmcontext.py:440
- Consider using logger.warning instead of logger.info here (and similarly in subsequent exception handling blocks) to better reflect the severity of file access errors.
logger.info("Warning: Could not access/process file %s: %s", filepath_rel_posix, e)
| output_text = generate_project_context( | ||
| root_dir_abs, args.exclude, output_file_abs_path, args.verbose | ||
| ) | ||
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The current token estimate is based on splitting the output text by whitespace. Consider documenting that this is an approximation of token count for LLM context purposes.
Suggested change
| # Approximate token count based on splitting the text by whitespace. | |
| # Note: This does not reflect the actual tokenization process used by LLMs, | |
| # which may result in a different token count due to subword tokenization and special characters. |
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Summary
__main__module to allowpython -m llmcontextloggingTesting
pytest -qpython -m llmcontext --versionhttps://chatgpt.com/codex/tasks/task_e_68496b337ef0832b8c4bd6baa9a9b279