AI-Enhanced Automated Learning Document Generation

This workflow is ideal for educators, content creators, and researchers who need to automate the generation of study materials or summaries from various document types. It is especially beneficial for those who frequently work with multiple file formats such as PDF, DOCX, and text files, and require a streamlined process to transform raw content into structured notes or guides.

This workflow addresses the challenge of efficiently converting newly added documents into useful study aids, such as study guides, timelines, and briefing documents. By automating the extraction, summarization, and generation of these materials, users can save significant time and effort, ensuring they can focus on content quality rather than manual processing.

1. Local File Trigger: Monitors a specified folder for new files and triggers the workflow upon detection.
2. File Import: Based on the file type (PDF, DOCX, or text), the workflow imports and extracts the content from the file.
3. Data Preparation: The extracted text is prepared for further processing, including summarization and vectorization.
4. Summarization: The content is summarized to create concise overviews, facilitating easier comprehension of the material.
5. Vectorization: Summarized content is stored in a vector database, enabling efficient retrieval for future queries.
6. Template Generation: For each document type, the workflow generates specific templates (e.g., study guides, timelines) using AI models to enhance the content's usability.
7. Export to Folder: Finally, the generated documents are saved back to the specified folder, ready for use by the end-user.