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.
Ollama is recommended for businesses and teams seeking an efficient project management solution. It is especially useful for remote teams, startups, and any organization looking to enhance collaboration and project tracking capabilities.
Based on our record, Ollama seems to be a lot more popular than Langfuse. While we know about 143 links to Ollama, we've tracked only 11 mentions of Langfuse. 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.
And then there’s evaluation and observability—two things you must consider when your AI app is live. You need to know if the model is doing its job, and why it failed when it didn’t. Tools like LangSmith and LangFuse can help with this, but you’ll need to spend time experimenting with what works best for your stack. - Source: dev.to / 1 day ago
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 / about 2 months ago
It is reportedly used on websites like Langfuse and Million.dev. - Source: dev.to / 3 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 / 4 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
Ollama: If you’re worried about running through OpenRouter’s quotas, you can always fall back to local setups. Ollama is plug-and-play and runs locally. The only trade-off? Heavy models are tough to handle on a local machine—but smaller models are often too limited. - Source: dev.to / 1 day ago
By default, it uses OpenAI's API with the gpt-3.5-turbo model, but it will work with any service that has an OpenAI-compatible API, as long as the model supports tool calling. This includes models you host yourself, Ollama if you're developing locally, or models hosted on other services such as Hugging Face. - Source: dev.to / 6 days ago
The application is powered by a Node.js + Express backend, a locally running LLM model via Ollama, and Postmark’s inbound email parsing feature to automate the extraction of useful promotional data from email content. - Source: dev.to / 11 days ago
> How does that work exactly? Do you have a link? https://ollama.com. - Source: Hacker News / 16 days ago
Go to https://ollama.com/ and download Ollama, then install it on your machine. - Source: dev.to / 22 days ago
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