Open Issues Need Help
View All on GitHubAI Summary: This issue requests the creation of a GitHub Actions CI workflow (`ci.yml`) that triggers on pull requests and pushes to the `main` branch. The workflow should automate the project's development lifecycle by running `npm install`, linting, testing, and attempting a headless build using the project's build script or `electron-builder`. A passing CI status badge must also be added to the project's README.
A desktop application built with Electron and Node.js that converts documents (PDF, DOCX, DOC, RTF, TXT, MD, HTML) into AI training data using Ollama-run models to summarize and output the data.
AI Summary: This issue requests the creation of a 20-60 second demo GIF showcasing the app's core features: launch, document drag & drop, auto-summarization, and JSON export. The GIF should be saved as `assets/demo.gif` and embedded in the `README.md` with a short caption. A placeholder GIF is acceptable if a real one cannot be recorded immediately, provided the README is updated accordingly.
A desktop application built with Electron and Node.js that converts documents (PDF, DOCX, DOC, RTF, TXT, MD, HTML) into AI training data using Ollama-run models to summarize and output the data.
AI Summary: This issue requests the addition of two new markdown files: `CONTRIBUTING.md` and `CODE_OF_CONDUCT.md`. The `CONTRIBUTING.md` should detail local development setup, testing, PR workflow, and guidelines for commits and labels. The `CODE_OF_CONDUCT.md` will use the Contributor Covenant, and both files need to be linked in the project's `README`.
A desktop application built with Electron and Node.js that converts documents (PDF, DOCX, DOC, RTF, TXT, MD, HTML) into AI training data using Ollama-run models to summarize and output the data.
A desktop application built with Electron and Node.js that converts documents (PDF, DOCX, DOC, RTF, TXT, MD, HTML) into AI training data using Ollama-run models to summarize and output the data.
A desktop application built with Electron and Node.js that converts documents (PDF, DOCX, DOC, RTF, TXT, MD, HTML) into AI training data using Ollama-run models to summarize and output the data.