It's a lightweight tool that summarizes Hacker News articles. For example, here’s what it outputs for this very post, "Ask HN: Is anyone doing anything cool with tiny language models?":
"A user inquires about the use of tiny language models for interesting applications, such as spam filtering and cookie notice detection. A developer shares their experience with using Ollama to respond to SMS spam with unique personas, like a millennial gymbro or a 19th-century British gentleman. Another user highlights the effectiveness of 3B and 7B language models for cookie notice detection, with decent performance achieved through prompt engineering."
I originally used LLaMA 3:Instruct for the backend, which performs much better, but recently started experimenting with the smaller LLaMA 3.2:1B model.
It’s been cool seeing other people’s ideas too. Curious—does anyone have suggestions for small models that are good for summaries?
That's cool, I really like it. One piece of feedback: I am usually more interested in the HN comments than in the original article. If you'd include a link to the comments then I might switch to GopherSignal as a replacement for the HN frontpage.
My flow is generally: Look at the title and the amount of upvotes to decide if I'm interested in the article. Then view the comments to see if there's interesting discussion going on or if there's already someone adding essential context. Only then I'll decide if I want to read the article or not.
Of course no big deal if you're not interested in my patronage, just wanted to let you know your page already looks good enough for me to consider switching my most visited page to it if it weren't for this small detail. And maybe the upvote count.
Hey, thanks a ton for the feedback! That was super helpful to hear about your flow—makes a lot of sense and it's pretty similar to how I browse HN too. I usually only dive into the article after checking out the upvotes and seeing what context the comments add.
I'll definitely add a link to the comments and the upvote count—gotta keep my tiny but mighty userbase (my mom, me, and hopefully you soon) happy, right? lol
And if there's even a chance you'd use GopherSignal as your daily driver, that's a no-brainer for me. Really appreciate you taking the time to share your ideas and help me improve.
EDIT: Apologies for breaking things earlier while trying to fix it! I’ve been working on updating it and got the upvote count and comment link in there. Wondering what you think about these updates—appreciate any feedback! Thanks again for helping me improve it!
Hey thanks a ton for checking out GopherSignal! From the feedback I’m getting, it seems like comments and upvotes are the secret sauce I’ve been missing—appreciate you helping me get that through my thick skull lol. The pressure’s on now—I’ll do my best to deliver.
Great call! That’s a really solid idea—using the LLMs to rate posts based on comment activity could totally work and would be fun.
Were you thinking something like a “DramaLlama,” deciding if it’s a slow day or a meltdown-worthy soap opera in the comments? Or maybe something more valuable, like an “Insight Index” that uses the LLM to analyze comments for links, explanations, or phrases that add context or insight—basically gauging how constructive or meaningful the discussion is?
I also saw an idea in another post on this thread about an LLM that constantly listens to conversations and declares a winner. That could be fun to adapt for spicier posts—like the LLM picking a “winner” in the comments. Make the argument GopherSignal official lol. If it helps bring in another user, I’m all in!
Hey, thanks for reaching out! The idea of integrating GopherSignal with Discord as a bot or feature is super cool, and I’d love to make that happen. I haven’t worked with Discord bots or automation before, so I’d definitely take you up on your offer to help out with that. If you want to connect, my email is kjzehnder3 [at] gmail [dot] com. Thank u!
It's a lightweight tool that summarizes Hacker News articles. For example, here’s what it outputs for this very post, "Ask HN: Is anyone doing anything cool with tiny language models?":
"A user inquires about the use of tiny language models for interesting applications, such as spam filtering and cookie notice detection. A developer shares their experience with using Ollama to respond to SMS spam with unique personas, like a millennial gymbro or a 19th-century British gentleman. Another user highlights the effectiveness of 3B and 7B language models for cookie notice detection, with decent performance achieved through prompt engineering."
I originally used LLaMA 3:Instruct for the backend, which performs much better, but recently started experimenting with the smaller LLaMA 3.2:1B model.
It’s been cool seeing other people’s ideas too. Curious—does anyone have suggestions for small models that are good for summaries?
Feel free to check it out or make changes: https://github.com/k-zehnder/gophersignal