Langfuse is the #1 open source LLM engineering platform. It helps teams iterate on and improve their LLM applications: LLM tracing, metrics, llm-as-a-judge, evaluations, prompt management, datasets testing and more. Create a free account or self-host Langfuse.
Hi Product Hunt 👋👋👋
I’m Clemens, co-founder of Langfuse. We are so excited to be live on Product Hunt again today, launching the biggest feature yet: Langfuse Prompt Experiments!
This new feature is designed to close the loop of developing and improving LLM applications.
With Prompt Experiments, you can test and evaluate different prompt versions and LLMs on hundreds of examples simultaneously; Perform live LLM-as-a-judge evaluations and compare results in our new Dataset Comparison View to optimize prompts for your specific use case.
You can quickly make prompt changes, see whether they improve metrics without causing new issues, and then deploy to production with confidence. Move faster on your LLM Application development than ever before.
A few things you should know about Langfuse:
👣 Tracing: TS & Python & API + OpenAI, Llama Index, LangChain, LiteLLM + many more
✏️ Prompt Management: Collaboratively manage and deploy prompts from within Langfuse
⚖️ Evaluation: Automatically run evals to control for hallucinations or other criteria you care about
💾 Datasets: Collaboratively manage fine-tuning, testing and golden datasets
🧪 Dataset Experiments: Test different prompts and models on hundreds of traces simultaneously
📊 Metrics: Dashboards and analytics on cost, latency and quality
🕹️ LLM Playground: Engineer your prompts and directly see results
🏎️ Export & Fine Tune: Open GET API and csv/JSON exports to build downstream use cases
🚄 Scale: We’ve invested significantly in scaling and resilience as we’ve scaled to thousands of users and handle many many millions of events a day
🧑🤝🧑Community: Join our thousands of users on GitHub Discussions and Discord
See for yourself:
⭐ GitHub: https://github.com/langfuse/lang...
⏯️ Interactive Demo: https://langfuse.com/demo
📒 Docs: https://langfuse.com/docs
💬 Discord: https://langfuse.com/discord
Thanks again, PH community. This is where we started, and we are incredibly grateful for all of the community feedback which led to the development of this major new feature.
We’re excited and will be in the comments the whole day to hear your thoughts & feedback!
About Langfuse Prompt Experiments on Product Hunt
“Open Source LLM Engineering Platform”
Langfuse Prompt Experiments launched on Product Hunt on November 22nd, 2024 and earned 469 upvotes and 44 comments, placing #5 on the daily leaderboard. Langfuse is the #1 open source LLM engineering platform. It helps teams iterate on and improve their LLM applications: LLM tracing, metrics, llm-as-a-judge, evaluations, prompt management, datasets testing and more. Create a free account or self-host Langfuse.
On the analytics side, Langfuse Prompt Experiments competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Langfuse Prompt Experiments performed against the three products that launched closest to it on the same day.
Who hunted Langfuse Prompt Experiments?
Langfuse Prompt Experiments was hunted by Clemens Rawert. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Reviews
Langfuse Prompt Experiments has received 42 reviews on Product Hunt with an average rating of 5.00/5. Read all reviews on Product Hunt.
For a complete overview of Langfuse Prompt Experiments including community comment highlights and product details, visit the product overview.
Clemens Rawert