Setup
Configure credentials, dependencies, and workspace for Look Tongji Notes.
When to Use
- User says
/setupor asks to configure the skill. - First-time setup before transcribing lectures.
- User wants to change or migrate the course knowledge-base path.
Workflow
- Run setup:
bashpython "<SKILL_DIR>/../../scripts/look_tongji.py" setup
- Non-interactive workspace options:
bashpython "<SKILL_DIR>/../../scripts/look_tongji.py" setup \ --workspace-root "<COURSE_WIKI_ROOT>" \ --owner-name "<OWNER_NAME>" \ --site-name "<OWNER_NAME>的课程知识库"
-
The CLI checks: Python deps (requests, playwright, python-dotenv, markdown, markitdown), ffmpeg, Node.js, vision-support config, and optionally XeLaTeX.
-
Vision Support setup: If
vision-support/config.jsondoes not exist, the CLI prints the init command. The embedded vision-support is at<SKILL_DIR>/../../vision-support/. Help the user configure a vision provider (OpenAI, Google, Anthropic, deepseek, dashscope, zhipuai, ollama, or custom). -
Verify vision-support: After configuration, test with:
bashnode "<SKILL_DIR>/../../vision-support/scripts/vision.mjs" "<SKILL_DIR>/../../komari.jpg"The agent should correctly identify image content (should mention "red-haired girl" or equivalent).
-
Never ask for passwords in chat. Use interactive terminal input or environment variables.
Where <SKILL_DIR> Points
<SKILL_DIR> is the directory containing this SKILL.md. Shared scripts (look_tongji.py, timeline_tools.py, tongji_backend/) and references live two levels up in the repository root (<SKILL_DIR>/../../scripts/ and <SKILL_DIR>/../../references/).


