Hugging Face to Notion

For Notion, this automated workflow retrieves and analyzes Hugging Face research papers weekly, extracting key details and summaries. It efficiently stores the information in Notion, ensuring easy access to the latest academic insights and enhancing research productivity.

7/8/2025
11 nodes
Medium
schedulemediumschedule triggersplitinbatchessplitoutnotionlangchainautomationadvancedcronlogicconditionalapiintegration
Categories:
Schedule TriggeredMedium Workflow
Integrations:
Schedule TriggerSplitInBatchesSplitOutNotionLangChain

Target Audience

This workflow is ideal for:
- Researchers looking to automate the collection of recent academic papers from Hugging Face.
- Data Analysts who require structured data from academic resources for analysis or reporting.
- Content Managers needing to keep track of relevant literature and abstracts for content creation or updates.
- Developers interested in integrating academic research into their applications or services.
- Students who want to stay updated with the latest research in their fields of study.

Problem Solved

This workflow addresses the challenge of manually tracking and collecting recent academic papers from Hugging Face. By automating the process, users can:
- Save time and effort in searching for relevant papers.
- Ensure they do not miss important publications by running the workflow on a scheduled basis.
- Maintain an organized database of papers and their abstracts in Notion, making it easier to access and reference them later.

Workflow Steps

  • Schedule Trigger: The workflow begins by triggering automatically every week on specified days at 8 AM.
    2. Request Hugging Face Paper: It sends a request to the Hugging Face papers API to fetch papers published one day prior.
    3. Extract Hugging Face Paper: The HTML content of the response is parsed to extract the URLs of the papers.
    4. Split Out: The URLs are split into separate items for further processing.
    5. Loop Over Items: Each extracted URL is processed in a loop.
    6. Check Paper URL Existed: For each URL, the workflow checks if it already exists in the Notion database to avoid duplicates.
    7. Request Hugging Face Paper Detail: If the paper does not exist, it fetches detailed information about the paper using the URL.
    8. Extract Hugging Face Paper Abstract: The abstract and title of the paper are extracted from the detailed response.
    9. OpenAI Analysis Abstract: The abstract is sent to OpenAI for analysis, extracting key details such as core introduction, keywords, data and results, technical details, and classification.
    10. Store Abstract Notion: Finally, the extracted information is stored in a Notion database, creating a structured record of the paper.

    • Customization Guide

    To customize this workflow, users can:
    - Change the schedule in the Schedule Trigger node to run at different times or frequencies (e.g., daily, monthly).
    - Modify the query parameters in the Request Hugging Face Paper node to filter papers based on specific criteria (e.g., keywords, authors).
    - Adjust the extraction logic in the Extract Hugging Face Paper and Extract Hugging Face Paper Abstract nodes to capture additional or different data points.
    - Update the Notion database properties in the Store Abstract Notion node to match the user's specific database schema or to include additional fields as necessary.
    - Integrate additional nodes for further processing or notifications (e.g., sending an email when new papers are added).