Alternatives
Products that do what Onuion does
session security
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Hello! This is Jeane and Samuel and we’re building RecipeUI. RecipeUI is an open source Postman alternative that uses TypeScript to statically type and autocomplete requests. We built this because current API tools don’t deal with the fact that some APIs are just painful to work with. For us, it’s usually error after error as we try to figure out how to properly form the first request. We recorded a demo to show you how TypeScript helps us autocomplete a request correctly. https://youtu.be/O_Mly_p-g5s How does our platform improve the developer experience? The analogy is…
2023 · recipeui.com
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Hey HN, I am building an open source platform to make on-call better and less stressful for engineers. We are building a tool that can silence alerts and help with debugging and root cause analysis. We also want to automate tedious parts of being on-call (running runbooks manually, answering questions on Slack, dealing with Pagerduty). Here is a quick video of how it works: https://youtu.be/m_K9Dq1kZDw I hated being on-call for a couple of reasons: * Alert volume: The number of alerts kept increasing over time. It was hard to maintain existing alerts. This would lead to a lot…
2024 · github.com
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2024 · github.com
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Check out this impressive project that enables running LLMs entirely in the browser using WebGPU. Key features: - Zero token costs, no cloud infrastructure required - Complete data privacy through local processing - Simple 3-line code integration - Built on MLC and Transformer.js The benchmarks show smaller models can effectively handle many common tasks. Currently the project roadmap includes: - No-code AI pipeline builder - Browser-based RAG for document chat - Analytics/logging - Model fine-tuning interface
2025 · github.com
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We've open-sourced Klarity - a tool for analyzing uncertainty and decision-making in LLM token generation. It provides structured insights into how models choose tokens and where they show uncertainty. What Klarity does: - Real-time analysis of model uncertainty during generation - Dual analysis combining log probabilities and semantic understanding - Structured JSON output with actionable insights - Fully self-hostable with customizable analysis models The tool works by analyzing each step of text generation and returns a structured JSON: - uncertainty_points: array of {step, entropy,…
2025 · github.com
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Hello HN! Pierre and Paul here. We are building an open source text analytics tool for user inputs and LLM app outputs The repo is https://github.com/phospho-app/phospho and landing is https://phospho.ai Most people building with LLMs today don’t have quantified evaluation and usage metrics on the interactions between users and their product. The only solution is to read every message (or a sample) to get a sense of what is going on. You can't improve your product without understanding who your users are and how they are using it. Nobody would launch a website…
2024 · github.com
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Hi Hacker News! Shahar and Tal from Keep here. We're thrilled to announce that we're open-sourcing our alerting CLI tool, Keep (https://github.com/keephq/keep). Designed by developers for developers, Keep streamlines and simplifies alerting, making it a first-class citizen within the development process. Think of Keep as Prometheus Alertmanager but for all observability tools, with a simple and intuitive (GitHub actions-like) syntax. We believe that alerting has historically been neglected in existing monitoring platforms, leading to subpar alerting practices. With Keep,…
2023 · github.com
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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
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2018 · github.com
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Our team worked for 1,000 days to create and open-source a web user analytics platform. It is a lightweight (~5 dependencies), “low-tech” PHP/PostgreSQL software that answers the question of what logged-in users are doing on your web application and helps mitigate some risks. Online demo: https://play.tirreno.com Source code: https://github.com/TirrenoTechnologies/tirreno If that's not of interest, there's also a game by @KilledByAPixel: https://play.tirreno.com/game, which has some sentimental flavour. Happy New 20¼ everyone! Dedication:…
2024 · github.com
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May 2026 · github.com
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Hi HN! I'm Inacio, the author of REASON. I've been tinkering with LLMs since the GPT-3 API's release May 2020. Seeing the emergence of many frameworks in the last 15 months has been exciting. While many understandably focused on launching quick, I found myself intrigued by a different question: what would a thoughtful, first-principles approach look like? This curiosity led to a personal project, RΞASON, a minimalistic open-source TypeScript framework. It's been a couple of months of digging deep and learning a ton, and I'm eager to share it and grow it with insights from all of you. In the…
2023 · tryreason.dev
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Hi HN, I’m the founder of Pangea. We’ve built a developer platform where you can easily add security to your code through a simple set of APIs - features like authentication, secrets management, audit logging, redaction of PII, restricting embargoed countries, known threat actor intelligence, etc. With the ChatGPT and LLM explosion, we thought of ways to reduce the risk of both the inputs and outputs from these services. Our NextJS sample app adds a security layer on top of ChatGPT with various security services that you can implement quickly. It’s basically a front end to the OpenAI API…
2023 · github.com
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2017 · calctopia.com
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