
Langfuse
Helicone AI
LangSmith
LangChain
Openlayer
Braintrust.dev
Portkey
LastMile AI
massCode
GitHub Gist
Lepton
SnippetsLab
Quiver
Codespace
Pastebin.com
Cacher
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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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 / 14 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
To be honest, it didn't take off as I hoped. I struggled to attract enough users to make it sustainable. Eventually, I lost motivation and abandoned it to focus on my other open-source project, massCode. - Source: dev.to / 5 months ago
`cask "lepton"` [link][oss] + `cask "masscode"` [link][oss] for storing snippets as github gists or locally. Source: about 3 years ago
There are a plethora of snippet manager apps for developers, with syntax highlighting, etc, available for macOS, eg: - SnipperApp - Snip - massCode - SnippetsLab - Quiver. Source: over 3 years ago
I found out what it was; I went through the 'Download for Mac' button on masscode.io and it looked to default to the arm64 installer. I grabbed the Intel version from the repo and working now. Source: about 4 years ago
I use MassCode. Syntax is supported for several languages, and is selfhosted. Source: over 4 years ago
Helicone AI - Open-source LLM Observability for Developers
GitHub Gist - Gist is a simple way to share snippets and pastes with others.
LangSmith - Build and deploy LLM applications with confidence
Lepton - Lepton image compression: saving 22% losslessly from images at 15MB/s
LangChain - Framework for building applications with LLMs through composability
SnippetsLab - SnippetsLab is an easy-to-use snippets manager.