
GitHub Sponsors
Open Collective
Google Open Source
Patreon
Liberapay
The Tidelift Subscription
Kubernetes
GitHub
Langfuse
Helicone AI
LangSmith
LangChain
Openlayer
Braintrust.dev
Portkey
PromptLayer
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.
GitHub Sponsors
LangfuseBased on our record, GitHub Sponsors should be more popular than Langfuse. It has been mentiond 143 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.
This... exists? Did they even search for it? https://github.com/open-source/sponsors. - Source: Hacker News / 6 months ago
Community-Driven Upgrades: Increased integration of real-time community feedback via platforms such as GitHub Sponsors and social media channels (e.g., Twitter (@fsf)) could drive iterative improvements in the license. - Source: dev.to / about 1 year ago
Chad has been leading the Open Source Pledge, a simple framework to get companies to fund the projects they rely on. The idea is straightforward: for every developer your company employs, allocate $2,000 per year to open source. Distribute those funds however you wantโGitHub Sponsors, Open Collective, Thanks.dev, direct payments, etc. The only other ask is to publish a blog post showing what you did. - Source: dev.to / about 1 year ago
Abstract: This post dives into the evolution and global expansion of GitHub Sponsors and its impact on funding open-source projects. We examine its inception, supported countries, technical challenges, and how blockchain innovations and alternative funding models are shaping the future of open source development. From core benefits and practical use cases to potential hurdles and forward-looking trends, this... - Source: dev.to / about 1 year ago
This post explores the critical issue of sustainable funding for open source projects. We dive into historical challenges, innovative funding strategies, and future trends that aim to support the collaborative spirit of open source development. Using examples from corporate sponsorships, non-profit foundations, crowdfunding methods, subscription models, government grants, and commercialization, the article... - Source: dev.to / about 1 year 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 / 9 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 / 27 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
Open Collective - Recurring funding for groups.
Helicone AI - Open-source LLM Observability for Developers
Google Open Source - All of Googles open source projects under a single umbrella
LangSmith - Build and deploy LLM applications with confidence
Patreon - Patreon enables fans to give ongoing support to their favorite creators.
LangChain - Framework for building applications with LLMs through composability