
Theme Forest
Creative Market
Elegant Themes
CodeCanyon
TemplateMonster
Themify
InkThemes
WPExplorer
Langfuse
Helicone AI
LangSmith
LangChain
Openlayer
Braintrust.dev
Portkey
LastMile AI
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.
Theme Forest
LangfuseBased on our record, Theme Forest should be more popular than Langfuse. It has been mentiond 65 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.
ThemeForest - Popular marketplace with buyer protection. - Source: dev.to / 7 months ago
You can probably find a ton of similar themes to purchase on ThemeForest (https://themeforest.net/). - Source: Hacker News / 12 months ago
Why not create reusable website templates with your favorite tech stack and sell them on platforms like Gumroad or Envato? I will start by selling website templates on Gumroad, I've read and seen it can be a highly profitable venture. - Source: dev.to / about 2 years ago
Check out themeforest.net for more themes. You can look at the blog-specific category, and add some search keywords (like "minimalistic") to narrow it down more. Source: over 2 years ago
Create and sell WordPress themes or plugins on platforms like ThemeForest, Elegant Themes, and CodeCanyon. Cater to the vast WordPress user base. - Source: dev.to / over 2 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 / 13 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
Creative Market - Buy and sell handcrafted, mousemade design content like vector patterns, icons, photoshop brushes, fonts and more at Creative Market.
Helicone AI - Open-source LLM Observability for Developers
Elegant Themes - Simple, yet beautiful WordPress themes with easy to use implementation and support.
LangSmith - Build and deploy LLM applications with confidence
CodeCanyon - Scripts and Snippets From $1 for PHP, JavaScript, ASP.NET, CSS, Plugins, HTML5, Mobile and more
LangChain - Framework for building applications with LLMs through composability