I'm wondering if any glass plates were recovered? I'm not sure they were all salvaged at the time, but I don't know how they would fare in the saltwater.
How do you weight results between vector search and bm25? Do you fall back to bm25 when vector similarity is below a threshold, or maybe you tweak the weights by hand for each data set?
I must have missed that feature. I don't see it under Data Source or Integrations. Can you point me to it? Use case is mostly call an API and show one or more property values from the JSON object that comes back, or use it as a tabular data source.
Edit: Maybe I'm misunderstanding the UI and this is something you would do directly through Python?
That’s correct - it’s something you should do in Python.
To pull data from the API you can use the requests package which is already within your Python environment.
If you have sensitive API keys you can add them to your environment variables list and then read them with Python too so they’re not apparent in the code.
While your original comment might be taken as funny, this one quickly devolved into a strawman argument ending in a personal attack. Was that your intention?
I like the idea! A few things I noted: 1) despite the paged UI, the API call /rest/v1/arxiv_papers?select=*&order=published.desc is downloading all 708 articles. You will find the UI more snappy if you do server-side paging. b) most of the javascript is cached, but not all of it, e.g., page-script.js
* An Introduction to the Delia Derbyshire Archive [video](https://www.youtube.com/watch?v=pPIqq7_RjnA)