totalhack

5 ms·

31.
by totalhack 3y ago
Thanks! I did notice the queue count showing up occasionally but not every time. Maybe someone could repeat the test who has access without the queue so we can get an understanding of the potential latency once scaled and geo-distributed. W
32.
by totalhack 3y ago
Where is the data center located? The fastest response time I could get from some quick testing from the northeast US, having it output just one letter, was 670ms. Just wondering if that's an expected result, as it's on a par or s
33.
by totalhack 3y ago
What are the performance implications, if any? I assume it's just translating queries as needed into the database engine language, in which case I wouldn't expect much of a performance issue.
34.
by totalhack 3y ago
Thanks! I'm not sure if I'll have the bandwidth to help yet, but interested to hear about the problem you are facing. I'll reach out this week.
35.
by totalhack 3y ago
I've also been frustrated when testing out tools that kinda keep you locked into one predetermined view, table, or set of tables at a time. I made a semantic data modeling library that puts together queries (and of course joins) for yo
36.
by totalhack 3y ago
Sure, AI will assist more and more in the cases where people must write SQL or manage a database, perhaps to the point you suggest. But my point was actually that more people think they need to know SQL today than is actually the case. Excl
37.
by totalhack 3y ago
Have you considered a semantic layer instead, or does it have to be a natural language interface?
38.
by totalhack 3y ago
Maybe you could utilize views to make your EAV schema more friendly for the LLM? Whether that's realistic depends on the specifics of your situation of course.
39.
by totalhack 3y ago
Sounds like you are describing a semantic layer. You don't need AI to achieve that, though it is fun when it works. Example of a semantic layer I made below, but there are others out there with more support behind them. https:/&#
40.
by totalhack 3y ago
This somewhat already exists in the form of semantic layers, which if done well can handle many of the queries necessary in the course of business without business users needing to know any SQL. There will still be cases where you need dire
41.
by totalhack 3y ago
I think AI to direct SQL will have use cases, but I personally have found it more of a fun toy than anything close to the main way I would interact with my data, at least in the course of running a business. I am a fan of a semantic layer (
42.
by totalhack 3y ago
My best use case so far has been to make GPTs for a particular tech stack specific to a project I might be working on for a couple months. Saves a lot of re-prompting to build context. Seems like they understand this type of use case as val
43.
by totalhack 3y ago
Twilio is great and super frustrating at the same time. I've run into outdated or missing documentation, and plenty of low hanging fruit UI improvements that get ignored. They seem to be asleep at the wheel at this point.
44.
by totalhack 3y ago
A friend and I recently created an app to track realtime scores for a high school reunion fantasy draft (we drafted teams with a few friends and you get points if the person shows up). With AI helping it really lowers the barrier to persona
45.
by totalhack 3y ago
I use org mode which was great in emacs but the plugin kinda sucks for VS code. The main feature there is the ability to fold and nest sections. I see you have a "blocks" concept which seems roughly equivalent to a top level folda
46.
by totalhack 3y ago
+1 for using a semantic layer. I built (and open-sourced) one for use in my own business but Cube looks well done. https://github.com/totalhack/zillion
47.
by totalhack 3y ago
Have you ever looked at adding a semantic layer on top of a db for those that prefer to avoid direct SQL?
48.
by totalhack 3y ago
Mind providing more details about the hardware in your setup, cameras etc?
49.
by totalhack 3y ago
Would this be embeddable in something like a custom chatgpt-style app? Say I wanted any tabular data that I'm interacting with to be a grist spreadsheet, for example. How many rows can it handle before the browser starts to feel sluggi
50.
by totalhack 3y ago
https://github.com/totalhack/zillion Semantic data warehousing and analytics tool written in python. It has experimental/half-baked NLP features to query your warehouse by interacting with the semantic layer with
51.
by totalhack 3y ago
It was a while ago now so the details have faded, but for one all of the docker services it had to spin up vs the single container that qdrant runs. I'm sure there is a reason for this, but I haven't needed it.
52.
by totalhack 3y ago
I'll just add that there are use cases where the extra layer actually adds a nice element of control and visibility. Adjusting a prompt to a black box LLM can sometimes lead to unpredictable results, though that can be mitigated with a
53.
by totalhack 3y ago
I'm interested to try some of these others next time around, but I've used qdrant self-hosted in two projects and been pleased. Milvus was recommended so I gave that a try but found it over complicated. Pgvector seems like an obvi
54.
by totalhack 3y ago
Looks pretty neat. Having not fully investigated it yet, I will say the one thing I usually run into with this and other BI tools is a lack of flexibility in the UI for forming queries. It's sometimes limited to one table or view at a
55.
by totalhack 3y ago
I must like to live dangerously. In all seriousness though there are low cost alternatives to those mega BI tools that suit many use cases. If I wasn't rolling my own I'd probably start with Metabase or Superset. What I use: http
56.
by totalhack 3y ago
How about an LLM talking to a semantic layer that then writes the SQL? I added experimental support for that in a project of mine, but using a semantic layer makes most querying so simple that natural language based approaches just seem kin
57.
by totalhack 3y ago
IMO a semantic layer is a nice UX/DX improvement over plain SQL in a business/analytics setting. I use a semantic layer* for >95% of use cases and fall back to SQL when needed. This balance will be different for each business o
58.
by totalhack 3y ago
There are also ways to add some flexibility into a "fixed" schema when you need it. Entity-attribute-value tables, views, JSON columns (as a last resort), or a semantic layer like https://github.com/totalhack/
59.
by totalhack 3y ago
I think there are probably a million posts and papers talking about text to SQL as it's a problem that's been tackled for a long time now...just with more vigor recently now that LLMs provide an improved/shiny approach. I thi
60.
by totalhack 3y ago
From our good friend GPT-4 who can summarize it better than I can... A semantic data layer is an abstraction layer that sits between the raw data stored in databases and the applications or analytics tools that use this data. The purpose of

More ›