AdminMart Reviews

1. sanjayjoshi

   · Working at wrappixel · over 1 year ago
   Peace of mind knowing Admin Templates is regularly updated with the latest security patches.

   Wish I discovered Admin Template sooner! It's become an essential part of our development team.

   🏁 Competitors: Wrappixel, Creative Tim, AdminLTE
2. mayuri_parmar4

   · search engine optimization at wrappixel · over 1 year ago

   The site features both free and premium templates, built on various frameworks like Next.js, Nuxt.js, React, Angular, Vue.js, and Bootstrap, along with utility-first designs using Tailwind CSS.

   🏁 Competitors: Creative Tim, Wrappixel, ThemeSelection

Langfuse Reviews

AdminMart mentions (2)

• Why I Built This Open Source Shadcn Tool After 15 Years of Building Templates

  For the past 15 years, I’ve built web templates, dashboards, components, and figma ui kits. Through products like Wrappixel, AdminMart, Tailwindadmin, and Get Nextjs Templates, we’ve worked on hundreds of layouts across famous frameworks and UI libraries. - Source: dev.to / 5 months ago

• Flowbite React vs. Shadcn: Which UI Library Should You Choose for Your React Project?

  And remember, you don’t have to choose between them entirely. With AdminMart’s Flowbite React Templates & Wrappixel’s Shadcn Templates, you can enjoy the benefits of both worlds. These Admin templates are designed to help you kickstart your project, save time, and ensure you deliver a top-notch user experience. - Source: dev.to / over 1 year ago

Langfuse mentions (28)

• Strands Agents + Langfuse Evaluations

  In this project we will build a Python banking assistant agent using Strands Agents and make it observable and continuously evaluated using Langfuse — step by step. - Source: dev.to / 13 days ago

• Best AI Monitoring Tools in 2026: LLM, Agent, and MCP Observability Compared

  Langfuse is the open-source standard for LLM observability. It traces every LLM interaction — prompts, completions, latency, token usage, cost — 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

• What is an LLM evaluation harness? A deep dive into lm-eval-harness

  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

• How to track LLM costs per customer in production

  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

• Per-user cost attribution for your AI APP

  Same approach works with Langfuse, Phoenix, Braintrust, or your existing OTel pipeline — the metadata.userId pattern is the universal part. - Source: dev.to / about 2 months ago