ManualTrigger Automate

This workflow is ideal for:

• Content Creators: Those who want to gather and summarize essays from Paul Graham for inspiration or reference.
• Researchers: Individuals needing quick access to summaries of essays without reading the entire content.
• Students: Learners looking for concise information from essays to aid in their studies.
• Developers: Programmers interested in automating the process of scraping and summarizing web content.
• Marketers: Professionals seeking insights from influential essays for content marketing strategies.

This workflow addresses the following issues:

• Time Consumption: It automates the process of fetching and summarizing essays, saving users from manually reading each one.
• Information Overload: By summarizing lengthy essays, it helps users quickly grasp key points and ideas.
• Accessibility: It makes valuable content from Paul Graham's essays easily accessible in summarized form, facilitating better understanding.

The workflow consists of the following steps:

1. Manual Trigger: The workflow is initiated by clicking the "Execute Workflow" button.
2. Fetch Essay List: It retrieves a list of essays from Paul Graham's website.
3. Extract Essay Names: The workflow extracts the titles and links of the essays from the fetched HTML content.
4. Split Out into Items: The extracted essay links are split into individual items for further processing.
5. Limit to First 3: It limits the workflow to process only the first three essays to avoid overload.
6. Fetch Essay Texts: For each essay, it fetches the complete text content from the respective URLs.
7. Extract Title: The title of each essay is extracted from the HTML content.
8. Extract Text Only: The main body of the essay text is extracted, skipping unnecessary elements like images and navigation.
9. Summarization Chain: The extracted text is summarized using an OpenAI language model.
10. Clean Up: The workflow organizes the output, assigning the title, summary, and URL for each essay.
11. Merge: The summarized data is merged into a single output format for easy review.