Dev tools · alternatives · 2026
24 alternatives to Using LLMs and Embeddings to classify application errors
Hi Hacker News! We’re Vadim and Chris from Highlight.io [1]. We do web app monitoring and are working on using LLMs/embeddings to add new functionality to our error monitoring product. Given that there’s a lot of founders/engineers using LLMs in their products, we figured we’d share how we built the new functionality, their impact on our workflows, and how you can try it out. Our goal was to build two features: (1) tagging errors (e.g. deeming an error as “authentication error” or a “database error”); and (2) grouping similar errors together (e.g. two errors that have a different…
Highlight.io is a web application monitoring platform that uses large language models and embeddings to automatically classify and organize application errors. It tags errors by type—such as authentication or database… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Using LLMs and Embeddings to classify application errors launched in 2023; newer entries below may have overtaken it.
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Hey HN! We’re open-sourcing highlight.io (https://github.com/highlight/highlight), a session replay and error monitoring tool. Highlight.io gives you a high-precision video-like replay of what users are doing when an error or exception occurs in your web app, along with a full-fledged error monitoring experience (similar to bugsnag, rollbar, etc..). The main value prop of highlight.io is that we help you understand the full context surrounding an error and allow you to drill down to the code path that a user invoked (i.e user clicked button X, sent network request Y, and…
2023 · github.com · its alternatives →
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Stop guessing why bugs happen
2023 · launchdarkly.com · its alternatives →
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Langfuse▲771Open source tracing and analytics for LLM applications
2023 · langfuse.com · its alternatives →
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Hey HN. We’re Jay and Vadim from Highlight.io (https://highlight.io). We’re building an open source [1] monitoring platform for web applications. Today we’re excited to be sharing a performance tool we’ve been working on, which helps you inspect the latency of code execution from the client to the server. As engineers at past startups, we often had to debug slow queries, poor load times, inconsistent errors, etc... While tools like Jaegar [2] helped us inspect server-side performance, we had no way to tie user events to the traces we were inspecting. In other words, although we had…
2024 · github.com · its alternatives →
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Outlines is a Python library that focuses on text generation with large language models. Brandon and I are not LLM experts and started the project a few months ago because we wanted to understand better how the generation process works. Our original background is probabilistic, relational and symbolic programming. Recently we came up with a fast way to generate text that matches a regex (https://blog.normalcomputing.ai/posts/2023-07-27-regex-guide...). The basic idea is simple: regular expressions have an equivalent Deterministic-Finite Automaton (DFA) representation. We…
2023 · github.com · its alternatives →
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Hey hn! I'm one of the co-founders of highlight.io, an open source monitoring tool. Today we're sharing a ClickHouse-based logging solution we've been working on. We wanted to showcase how we built it and share how you could try it out to give feedback. Since we started working on highlight.io, we've been hyper-focused on "cohesion", or ensuring that when you install your monitoring stack, all of the resources in that stack (user interactions, requests, traces, logs, etc.) are connected in a consumable way. We've written up more about our philosophy on this here [1]. We started building…
2023 · github.com · its alternatives →
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Highlight▲318See and act on your webapp's issues and interactions
2021 · launchdarkly.com · its alternatives →
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I spent a few hours last weekend testing whether AI can replace code by executing directly. Built a contact manager where every HTTP request goes to an LLM with three tools: database (SQLite), webResponse (HTML/JSON/JS), and updateMemory (feedback). No routes, no controllers, no business logic. The AI designs schemas on first request, generates UIs from paths alone, and evolves based on natural language feedback. It works—forms submit, data persists, APIs return JSON—but it's catastrophically slow (30-60s per request), absurdly expensive ($0.05/request), and has zero UI…
Nov 2025 · github.com · its alternatives →
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After working with LLMs for long enough, I found myself wanting a lightweight utility for doing various small tasks to prepare inputs, locate information and create evaluators. This library is two things: a very simple model and utilities that inference it (eg. fuzzy deduplication). The target platform is CPU, and it’s intended to be light, fast and pip installable — a library that lowers the barrier to working with strings semantically. You don’t need to install pytorch to use it, or any deep learning runtimes. How can this be accomplished? The model is simply token embeddings that are…
2024 · github.com · its alternatives →
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Highlight▲285Understand and debug customer issues with confidence
2022 · launchdarkly.com · its alternatives →
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A weekly summary of sessions and errors on your web app
2022 · launchdarkly.com · its alternatives →
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Hi HN! Langfuse is OSS observability and analytics for LLM applications (repo: https://github.com/langfuse/langfuse, 2 min demo: https://langfuse.com/video, try it yourself: https://langfuse.com/demo) Langfuse makes capturing and viewing LLM calls (execution traces) a breeze. On top of this data, you can analyze the quality, cost and latency of LLM apps. When GPT-4 dropped, we started building LLM apps – a lot of them! [1, 2] But they all suffered from the same issue: it’s hard to assure quality in 100% of cases and even to have a clear view…
2023 · github.com · its alternatives →
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Hey HN, I made Browser-Use, an open-source tool that lets (all Langchain supported) LLMs execute tasks directly in the browser just with function calling. It allows you to build agents that interact with web elements using natural language prompts. We created a layer that simplifies website interaction for LLMs by extracting xPaths and interactive elements like buttons and input fields (and other fancy things). This enables you to design custom web automation and scraping functions without manual inspection through DevTools. Hasn't this been done a lot of times? Good question, as a general…
2024 · github.com · its alternatives →
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I built this tool because I wanted a way to just take a bunch of URLs or domains, and query their content in RAG applications. It takes away the pain of crawling, extracting content, chunking, vectorizing, and updating periodically. I'm curious to see if it can be useful to others. I meant to launch this six months ago but life got in the way...
2024 · embedding.io · its alternatives →
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Author here. I just wanted a quick and easy way to easily submit strings to a REST API and get back the embedding vectors in JSON using Llama2 and other similar LLMs, so I put this together over the past couple days. It's very quick and easy to set up and totally self-contained and self-hosted. You can easily add new models to it by simply adding the HuggingFace URL to the GGML format model weights. Two models are included by default, and these are automatically downloaded the first time it's run. It lets you not only submit text strings and get back the embeddings, but also to compare two…
2023 · github.com · its alternatives →
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We've been building data pipelines that scrape websites and extract structured data for a while now. If you've done this, you know the drill: you write CSS selectors, the site changes its layout, everything breaks at 2am, and you spend your morning rewriting parsers. LLMs seemed like the obvious fix — just throw the HTML at GPT and ask for JSON. Except in practice, it's more painful than that: - Raw HTML is full of nav bars, footers, and tracking junk that eats your token budget. A typical product page is 80% noise. - LLMs return malformed JSON more often than you'd expect, especially with…
Mar 2026 · github.com · its alternatives →
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Hey HN, I’m Jay, a co-founder at Highlight and a YC alum; excited to share our replay-based debugging tool! TLDR; if you're using a tool like Fullstory for debugging, or you have trouble understanding the actual impact of your errors (e.g. in sentry), you should give us a try! We built Highlight because we constantly found ourselves flooded with errors and support tickets with very little context on why these issues occurred. To make matters worse, there was never an easy (and less annoying way) of reproducing these errors, other than by asking users to send screenshots, videos, etc.…
2022 · highlight.io · its alternatives →
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If you've built any web-based app in the last 15 years, you probably used something like Datadog, New Relic, Sentry, etc. to monitor and trace your app, right? Why should it be different when the app you're building happens to be using LLMs? So today we're open-sourcing OpenLLMetry-JS. It's an open protocol and SDK, based on OpenTelemetry, that provides traces and metrics for LLM JS/TS applications and can be connected to any of the 15+ tools that already support OpenTelemetry. Here's the repo: https://github.com/traceloop/openllmetry-js A few months ago we launched…
2024 · github.com · its alternatives →
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Hey HN, I just built an experimental VSCode extension called LLM Debugger. It’s a proof-of-concept that lets a large language model take charge of debugging. Instead of only looking at the static code, the LLM also gets to see the live runtime state—actual variable values, function calls, branch decisions, and more. The idea is to give it enough context to help diagnose issues faster and even generate synthetic data from running programs. Here’s what it does: * Active Debugging: It integrates with Node.js debug sessions to gather runtime info (like variable states and stack traces). *…
2025 · github.com · its alternatives →
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Embedding-based code duplication detector. Contribute to rafal-qa/slopo development by creating an account on GitHub.
Jul 2026 · github.com · its alternatives →
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Trails▲81Hey all, Justin here. I previously built Phind, the AI search engine for developers. One of the biggest problems we had there was figuring out what went wrong with bad searches. We had tons of searches per day, but less than 1% of users gave any explicit feedback. So we were either manually digging through searches or making general system improvements and hoping they helped. This problem gets harder with agents. Traces are longer and more complex. It takes more effort to review them, so I'm building a tool that lets you analyze LLM outputs directly to help developers of LLM apps and agents…
Jan 2026 · trails-red.vercel.app · its alternatives →
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[I'm the author] Spall is a web-accessible profiler that I made to help my web-dev friends load gigabyte+ JSON traces without lunch-break-long load times. Recently, Spall got experimental support for auto-tracing with binary traces (along with an in-progress native-port, to give it more memory headroom), which was used to help track down and fix some hard-to-spot lock contention issues in the Odin-language compiler. I demoed it at the Handmade Seattle conference in October, https://guide.handmade-seattle.com/c/2022/spall/, with a head-to-head against Perfetto,…
2023 · gravitymoth.com · its alternatives →
- 23VD
Discover, evaluate, and access relevant embeddings in your go-to framework. Skip all the infra for scraping, cleaning, indexing, and updating high-quality embeddings.
2023 · embedding.store · its alternatives →
- 24AT
I recently built a small open-source tool to benchmark different LLM API endpoints — including OpenAI, Claude, and self-hosted models (like llama.cpp). It runs a configurable number of test requests and reports two key metrics: • First-token latency (ms): How long it takes for the first token to appear • Output speed (tokens/sec): Overall output fluency Demo: https://llmapitest.com/ Code: https://github.com/qjr87/llm-api-test The goal is to provide a simple, visual, and reproducible way to evaluate performance across different LLM providers, including…
2025 · llmapitest.com · its alternatives →
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