Link to Folder with Everything
https://drive.google.com/drive/folders/1-B0R2kDebOQE9nprQh-trEKX05NRK9td
Recording of Video
[https://drive.google.com/file/d/1b4KNTvf0hfoDQK2BmvbS_Oka_lpjZlho/view?usp=drive_link](https://drive.google.com/file/d/1b4KNTvf0hfoDQK2BmvbS_Oka_lpjZlho/view?usp=drive_link)
Summary ( by Gemini )
Summary Notes:
- Rahul Singh discussed a project focused on knowledge organization, involving data curation from various sources into a database and publishing websites around specific topics (e.g., Cassandra.link).
- The project's next iteration involves using curated content to create vector databases and catalogs for AI experts on subjects like Cassandra, NoCode, and AI technologies.
- The goal is to develop a self-learning expert system that continuously integrates human curations, summarizes information, categorizes it, and indexes it for chatbot interaction and content review.
- Rahul explored various UI systems (v0.dev, Bolt, Bubble, Weebly) and backend/API tools (Xano, Airtable) for building applications and managing data.
- Airtable was chosen for its quick data model building and interface capabilities, despite cost concerns for long-term use.
- Rahul aimed to automate data entry into Airtable by creating an AI-driven system that, given a URL, could extract and categorize information (source, description, type, category, topic, researcher) in JSON format.
- He used ChatGPT to refine a prompt for extracting structured information from URLs and explored Build Ship, a low-code tool, to implement this automation.
- The session involved setting up a Build Ship flow to scrape website content, use the ChatGPT prompt for information extraction, and format the output as JSON.
- Rahul also attempted to add a screenshot feature to the flow but encountered some issues that required further troubleshooting.
- The next steps involve integrating this automated system with Airtable triggers to streamline data entry and potentially exposing the functionality as an API endpoint.
- The session concluded with a brief discussion of potential triggers and API usage within Build Ship.
Key Takeaways:
- The focus is on building an AI-powered knowledge management system.
- Various NoCode/low-code tools are being evaluated and utilized.