Langfuse
LangSmith
Datumo Eval
Braintrust
Braintrust.dev
LangChain
Athina AI
PromptHub
Microsoft Azure
Amazon AWS
DigitalOcean
Linode
Google Cloud Platform
Heroku
Vultr
Ethereum
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 Microsoft AzureBased on our record, Microsoft Azure should be more popular than Langfuse. It has been mentiond 66 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.
Langfuse is another open-source platform for debugging, analyzing, and iterating on language model applications. It offers tracing, evaluation, and prompt management. While Langfuse offers many capabilities, some (like the Prompt Playground and automated evaluation) are only available in the paid tier for self-hosted users. - Source: dev.to / 22 days ago
It is reportedly used on websites like Langfuse and Million.dev. - Source: dev.to / 2 months ago
LangFuse is a monitoring and debugging platform for LLM-powered applications. It provides insights into token usage and costs. It can also analyze latency, and the performance of AI interactions. The platform allows debug prompts, and analyzes how they behave in production. - Source: dev.to / 3 months ago
You'll notice there's a lot of prompts in these examples. As you develop your prompts, you'll likely want to iterate and refine them over time. I recommend using tools like Langfuse or Langsmith for prompt management and metrics, making it easier to track performance and make improvements. - Source: dev.to / 4 months ago
Langfuse (https://langfuse.com). We started with observability and have branched out into more workflows over time (evals, prompt mgmt, playground, testing...). We have a bunch of traction and are looking for our fourth to sixth hire in scaling and building feature depth. We're hiring in person (4-5 days/week) in Berlin, Germany (salary ranges for each job 70k-130k, up to 0.35% equity). We value quality in... - Source: Hacker News / 4 months ago
Microsoft Azure offers a Bot Framework with built-in support for voice interactions via the Speech SDK. - Source: dev.to / 9 months ago
The first step in creating a virtual machine is getting a Microsoft account. Once you have a Microsoft account click this link to create an Azure free trial account. Click on the "Try Azure for free" button. This takes you to the page below. - Source: dev.to / about 1 year ago
Before you start, ensure you have an active Azure subscription, if you don't have one, Click here to create a free account. - Source: dev.to / about 1 year ago
A VM is the original “hosting” product of the cloud era. Over the last 20 years, VM providers have come and gone, as have enterprise virtualization solutions such as VMware. Today you can do this somewhere like OVHcloud, Hetzner or DigitalOcean, which took over the “server” market from the early 2000’s. Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft's Azure also offer VMs, at a less... - Source: dev.to / over 1 year ago
Before deploying the application with Kubernetes, you need to containerize the application using docker. This article shows how to deploy a Flask application on Ubuntu 22.04 using Minikube; a Kubernetes tool for local deployment for testing and free offering. Alternatively, you can deploy your container apps using Cloud providers such as GCP(Google Cloud), Azure(Microsoft) or AWS(Amazon). - Source: dev.to / over 1 year ago
LangSmith - Build and deploy LLM applications with confidence
Amazon AWS - Amazon Web Services offers reliable, scalable, and inexpensive cloud computing services. Free to join, pay only for what you use.
Datumo Eval - Discover Datumo Eval, the cutting-edge LLM evaluation platform from Datumo, designed to optimize AI model accuracy, reliability, and performance through advanced evaluation methodologies.
DigitalOcean - Simplifying cloud hosting. Deploy an SSD cloud server in 55 seconds.
Braintrust - Braintrust connects companies with top technical talent to complete strategic projects and drive innovation. Our AI Recruiter can 100x your recruiting power.
Linode - We make it simple to develop, deploy, and scale cloud infrastructure at the best price-to-performance ratio in the market.
