CLM - Coding-Academy Lecture Manager

CI codecov

Version: 1.28.0 | License: MIT | Python: 3.12, 3.13, 3.14

CLM is a course content processing system that converts educational materials (Jupyter notebooks, PlantUML diagrams, Draw.io diagrams) into multiple output formats.

Quick Start

Installation

# Install from PyPI
pip install coding-academy-lecture-manager

# Or with all optional dependencies (workers, TUI, web dashboard)
pip install "coding-academy-lecture-manager[all]"

For development, clone the repository and install in editable mode:

git clone https://github.com/hoelzl/clm.git
cd clm
pip install -e ".[all]"

Basic Usage

# Convert a course
clm build /path/to/course.xml

# Watch for changes and auto-rebuild
clm build /path/to/course.xml --watch

# Show help
clm --help

Features

  • Multiple Output Formats: HTML slides, Jupyter notebooks, extracted code
  • Multi-Language Notebooks: Python, C++, C#, Java, TypeScript, Markdown
  • Diagram Support: PlantUML and Draw.io conversion
  • Multiple Output Targets: Separate student/solution/instructor outputs
  • Shared-Source Includes: Declare <include source="…" as="…"/> on a <topic> or <section> to splice a canonical Python package (or any file/directory) into multiple topics at build time. clm course sync-includes materializes the same sources on disk so local notebook execution (VS Code, JupyterLab) finds them, with a .clm-include ledger for safe cleanup.
  • Output-Write Deduplication: When the same file is written to the same output path by multiple producers, CLM deduplicates the write and surfaces a output_dedup_count / output_conflicts summary so you can spot accidental cross-topic collisions.
  • Watch Mode: Auto-rebuild on file changes
  • Incremental Builds: Content-based caching
  • LLM Summaries: Generate course summaries with clm export summary using any OpenAI-compatible LLM API
  • Recording Management: Manage video recording workflows with pluggable backends — local ONNX pipeline, iZotope RX 11 external tool, or Auphonic cloud processing — plus assembly, job tracking, and per-course status (clm recordings)
  • MCP Server: Model Context Protocol server for AI-assisted slide authoring (clm mcp) with 16 tools for course navigation, validation, normalization, and bilingual editing
  • Slide Authoring Tools: Split-deck authoring sync (clm slides sync — the funnel that keeps both halves of a .de/.en pair consistent), topic resolution (clm course resolve-topic), fuzzy search (clm slides search), spec/slide validation (clm validate), normalization (clm slides normalize), bilingual language view (clm slides language-view), voiceover extraction (clm voiceover extract), LLM-driven voiceover coverage check (clm slides coverage), bilingual ↔ per-language file conversion (clm slides split / clm slides unify), and structured JSON outlines (clm export outline --format json). Lower-level plumbing (clm slides assign-ids, clm slides suggest-sync) stays available by name for scripts and agents.
  • Video Narration Harvest: Recover spoken narration from recorded videos into slide decks (clm harvest) — an agent-first report → task → accept loop over the deterministic transcribe/detect/match/align pipeline, with multi-part recordings, caching, and a legacy embedded-LLM one-shot (clm harvest autopilot)
  • LLM Polish: Clean up speaker notes with LLM-powered text polishing (clm polish)
  • Git Integration: Manage output repos with clm git init/sync/status, including --amend and --force-with-lease for iterative workflows
  • Flexible Remote URLs: Configurable git remote URL templates for SSH, custom hosts, etc.

Documentation

For Users:

For Developers:

Development Setup

# Install pre-commit hooks (recommended)
uv run pre-commit install

# This enables automatic linting (ruff) and type checking (mypy) on every commit

Testing

# Run unit tests
pytest

# Run all tests (unit, integration, e2e)
pytest -m ""

# Run with coverage
pytest --cov=src/clm

License

MIT License - see LICENSE for details.

Links

Project links

Data verified by PyPI on Sep 12, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

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  • Released:
Latest release

1 maintainer

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Avatar for mhoelzl from gravatar.com mhoelzl

Credits

PyPI data
Data sourced directly from PyPI's database.

Author: Dr. Matthias Hölzl

GitHub Statistics

Data verified by PyPI on Sep 12, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

MIT License (MIT)

Requires

Python >=3.12

Provides Extra

all all-workers dev docker drawio gcal mcp notebook plantuml recordings replay slides summarize tui voiceover voiceover-cohere voiceover-granite watch web

Tags

content course education jupyter notebooks

Classifiers

Report project as malware

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