Show HN: I built a RAG APIs that works like Stripe Checkout
liquidindex.devI'm building LiquidIndex, an RAG API service that makes it easy to add personalized context to AI apps. Instead of building a whole system to upload, process, and search through a user’s files or notes, you just call a few APIs. It handles the hard parts - like connecting to Notion or Google Drive, breaking the data into usable pieces, and making it searchable. Then, when you want to answer a question using that data, you just query it, and it gives you the most relevant results - optionally with an LLM-generated answer. No pipelines, no infrastructure, no headaches.
Here are the core APIs:
1. Create a customer (This is a space to put data)
2. Create an upload session (This is where users upload their data)
3. Query
Current connectors: File Upload, Google Drive, Notion, Dropbox
Supported File Types: PDF, text files, Markdown, CSVs, and XLSX (these include google docs and sheets)
Website: https://liquidindex.dev/
Check out the playground to get a feel of how it works!
Hi HN! I'm building this as a solo dev. I wanted to make it dead simple for devs to add user context to AI apps without building pipelines. Would really appreciate any feedback, especially from folks who've wrangled RAG systems before.
Very impressive.-
Thank you so much! I really appreciate that! Would love to hear what stood out to you, or if anything felt confusing or rough.
You are bitting a very tough nut to crack - the general idea itself is great ...
... but it you really manage to achieve what you set out to do, that'd be great. A game changer.-
Appreciate the thoughtful comment. Just to clarify, this is already working, not a concept. If you have a minute, I’d love to hear your take after trying it: https://liquidindex.dev/playground
Congratulations.-
I meant "achieve" as in "become widely used" - enough to change SOTA.-