Langfuse Has a Free LLM Observability Platform — Debug Your AI Apps Like a Pro

Your AI App Is a Black Box Your LLM app works in testing. In production, users complain about hallucinations, slow responses, and wrong answers. But you cannot see what happened because LLM calls are opaque — input goes in, output comes out. Langfuse: Observability for LLM Applications Langfuse is an open-source LLM engineering platform. Trace every LLM call, measure quality, manage prompts, and debug issues — all in one dashboard. Free Options Self-hosted : 100% free, unlimited traces Cloud : Free tier with 50K observations/month What You See For every LLM call, Langfuse captures: Input prompt (full) Output response (full) Token usage and cost Latency (time to first token, total) Model used User feedback scores Custom metadata Add Tracing in 3 Lines Python (OpenAI) from langfuse.openai import openai # That is it. Every OpenAI call is now traced. client = openai . OpenAI () response = client . chat . completions . create ( model = " gpt-4 " , messages = [{ " role " : " user " , " conte