369 karma · joined September 4, 2018
To this day I think it remains the only landing page with extensive use of SVG metaballs as a splitter between sections
Overwork culture is also present here and exploited by a lot of companies.
It opens up absolutely bonkers capabilities.
There's always a market for things that people are too lazy to do on their own.
Here's it in plain text to be more visible:
``` textclip.sh→URL gen: #t=<txt>→copy page | ?ask=<preset>#t=→svc redirect | ?redirect=<url>#t=→custom(use __TEXT__ placeholder). presets∈{claude,chatgpt,perplexity,gemini,google,bing,kagi,duckduckgo,brave,ecosia,wolfram}. len>500→auto deflate-raw #c= base64url encoded, efficient≤16k tokens. custom redirect→local LLM|any ?param svc. view mode: txt display+copy btn+new clip btn; copy→clipboard API→"Copied!" feedback 2s. create mode: textarea+live counters{chars,~tokens(len/4),url len}; color warn: tokens≥8k→yellow,≥16k→red; url≥7k→yellow,≥10k→red. badge gen: shields.io md [!alt](target_url); ```
It uses math notation to heavily compress the representation while keeping information content relatively preserved (similarly to GlyphLang. Later, LLM can comfortably use it to describe service in detail and answer user's questions about it. Same is applicable to arbitrary information, including source code/logic.
For example see this prompt describing an app: https://textclip.sh/?ask=chatgpt#c=XZTNbts4EMfvfYqpc0kQWpsEc...
Edit: yeah, Intel GPUs only.
I have settled on a combination of log(stars) and half-life penalty for days since last commit. It works surprisingly OK, highlighting large active repos and demoting ones that aren't actively maintained.
I'm sure there are many other approaches to the same thing, curious to learn how you solved it.
I've been rocking my LLM setup for more than two years now and it grew quite extensive enough to warrant an "awesome" list.
You may read in detail about my experience with all the services here on r/LocalLLaMa: https://www.reddit.com/r/LocalLLaMA/comments/1oclug7/getting...
So, I'm building a toolkit that allows to keep things simple for the end user. Run Ollama and Open WebUI configured to work together: `harbor up ollama webui`. Don't like Ollama? Then `harbor up llamacpp webui`. There are 17 backends, 14 frontends and 50+ different satellite projects, config profiles that can be imported from a URL, tunnels, and a helper desktop app.
https://github.com/av/harbor?tab=readme-ov-file#what-can-har...
You can watch a live recording here: https://www.youtube.com/watch?v=Of3Nx9b71Mg
You can see how it slowly picks up more and more coherence over 5000 training steps.