
Langfuse
Helicone AI
LangSmith
LangChain
Openlayer
Braintrust.dev
Portkey
LastMile AI
PurifyCSS
Unused CSS
Babel
Purgecss
Etsy Hound
Google Lighthouse
jQuery
React Native
Langfuse is an open-source LLM engineering platform designed to empower developers by providing insights into user interactions with their LLM applications. We offer tools that help developers understand usage patterns, diagnose issues, and improve application performance based on real user data. By integrating seamlessly into existing workflows, Langfuse streamlines the process of monitoring, debugging, and optimizing LLM applications. Our platform's robust documentation and active community support make it easy for developers to leverage Langfuse for enhancing their LLM projects efficiently. Whether you're troubleshooting interactions or iterating on new features, Langfuse is committed to simplifying your LLM development journey.
Langfuse
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Based on our record, Langfuse should be more popular than PurifyCSS. It has been mentiond 28 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
In this project we will build a Python banking assistant agent using Strands Agents and make it observable and continuously evaluated using Langfuse โ step by step. - Source: dev.to / 12 days ago
Langfuse is the open-source standard for LLM observability. It traces every LLM interaction โ prompts, completions, latency, token usage, cost โ and provides the tooling to debug, evaluate, and optimize LLM applications in production. Think of it as "Datadog for LLM calls" with a focus on prompt engineering workflows. - Source: dev.to / about 1 month ago
You're monitoring production traffic. You need Langfuse / Phoenix / Helicone / Braintrust for that. Online eval is a different problem class: implicit feedback, drift detection, hallucination rates on your data, not on HellaSwag. - Source: dev.to / about 1 month ago
Gateway or proxy attribution. A reverse proxy in front of the model-provider API records the request, computes the cost, and exposes per-customer breakdowns. Open-source options include Helicone, LiteLLM, Langfuse, and OpenLLMetry. Hosted equivalents serve as the AI cost observability layer for teams that want centralized visibility: LangSmith, Datadog LLM Observability, Arize Phoenix. Adds a network hop.... - Source: dev.to / about 1 month ago
Same approach works with Langfuse, Phoenix, Braintrust, or your existing OTel pipeline โ the metadata.userId pattern is the universal part. - Source: dev.to / about 2 months ago
PurgeCSS analyzes your HTML and internally keeps track of which selectors are being used or not. PurgeCSS actually analyzes other types of files besides HTML for selectors, such as template files and JavaScript. This feature is what makes PurgeCSS different from a similar solution, UnCSS, and related to a 'predecessor' solution called PurifyCSS. More on both of those later on. - Source: dev.to / about 4 years ago
> Isn't there a process of reducing it to only what one needs? Yes there is: https://github.com/purifycss/purifycss. - Source: Hacker News / over 4 years ago
Check out purifycss, Iโm not sure if it works with scss though. Source: over 5 years ago
Helicone AI - Open-source LLM Observability for Developers
Unused CSS - Easily find and remove unused CSS rules
LangSmith - Build and deploy LLM applications with confidence
Babel - Babel is a compiler for writing next generation JavaScript.
LangChain - Framework for building applications with LLMs through composability
Purgecss - Easily remove unused CSS