Chat with News: Interact with your articles

Demo

Website

Tools Used

1. 
   pgvector: I'm using pgvector to store the article embeddings that are generated through llama3.2 model.
   
   


2. 
   pgai: I use pgai to call llama3.2 model through SQL queries to get related articles and generate an answer.
   
   


3. 
   pgai Vectorizer: I set up a CLI command to run track changes on the articles table and vectorize all pending articles using llama3.2 model. You can set up a cron job to run every X minutes, to have your articles embeddings always ready. See code
   
   
   

   
   
   
   Final Thoughts
   

   
   
   

   This demo helped me establish some solid groundwork for a personal project involving news aggregation and AI. I believe the tools developed by the Timescale team truly empower developers, making them more efficient and simplifying tedious tasks in a consistent and user-friendly way.

   
   
   

   The pgai Vectorizer has been a game-changer for me. Keeping an embeddings store up to date can be repetitive and time-consuming. However, building a vectorizer worker is straightforward and highly effective for ensuring that your real data and embeddings store remain synchronized.

   
   
   

   
   
   
   Prize Categories
   

   
   
   

   This submission qualifies for:

   
   
   
   
   
   • Open-source Models from Ollama
   
   
   • Vectorizer Vibe
   
   
   • All the Extensions
   
   
   Vollständiger Original-Bericht

   Ausführliche Details, Code-Beispiele & Hersteller-Stellungnahme auf dev.to.

   ↗ Original-Artikel auf dev.to lesen