| > This is something that you can bootstrap into a proof-of-concept in a day and learn the tools you like and don't like along the way. Basically … Where do sloppyjoes get all of this unrestrained optimism? OP asked if such a solution exists. This documentation assistant is an oft requested tool in regards llms on this forum. If you can do it, you could start a business around it. OP could be your first customer! The only other comment in this thread at this time is from someone who is also a breathlessly vocal supporter of contemporary machine learning systems on this forum and yet they are saying “I have yet to see a convincing demo”, but here you are saying it’s easy; if only these damned margins were larger! I’ve checked your GitHub. I’m unable to find an implementation of this thing that you claim is so simple to implement. I checked your blog. Your most recent article is about you wasting 45 minutes hoping such an “ai agent” can fix a bug in your code. It proved unable to do so. You even call the experiment a failure in your post. So, where’s this optimism coming from?! But you do say you are having fun. Which is great! I’m glad you’re having fun. |
Here are a few of my own RAG implementations - getting a basic version working really is something that can be done in a few hours... but getting a GOOD version working takes a LOT longer than that.
- https://simonwillison.net/2023/Jan/13/semantic-search-answer... - my first attempt at RAG, before I knew it was called that, using custom SQLite SQL functions
- https://til.simonwillison.net/llms/embed-paragraphs#user-con... - a Bash script implementation of RAG
- https://simonwillison.net/2024/Jun/21/search-based-rag/ - an implementation of RAG using SQLite full-text search (as opposed to embedding vectors), built on https://www.val.town/