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CodeForces
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Langfuse
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Openlayer
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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.
Interview Cake LangfuseBased on our record, Langfuse should be more popular than Interview Cake. 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.
Here's another site that helped me when I was starting out: interviewcake.com (I think I had a free trial or something). Source: over 4 years ago
Interviewcake.com has some great explanations and practice problems for leetcode style problems. I got the year subscription on sale. Source: almost 5 years ago
I also used to do the exact same thing during a technical interview. Seems like an obvious answer, but I've always noticed the more prior practice I have, the less nervous I get. I think a good part of the mental fatigue comes from nerves. And those nerves were amplified when I encountered a problem for which I didn't immediately have a general grasp of the solution. But as soon as I got more consistent with my... Source: almost 5 years ago
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 / 5 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 / 24 days 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
AlgoExpert.io - A better way to prep for tech interviews
Helicone AI - Open-source LLM Observability for Developers
interviewing.io - Free, anonymous technical interview practice
LangSmith - Build and deploy LLM applications with confidence
CodingInterview - CodingInterview offers essential information to help you conquer programming interviews.
LangChain - Framework for building applications with LLMs through composability