Apr 13 · 3 min read · What you'll learn How to evaluate monitoring solutions beyond the mainstream options Key architectural differences between Langfuse alternatives for your specific use case A step-by-step approach to migrating from traditional tracing platforms to mo...
Join discussionNov 24, 2025 · 11 min read · The rise of Retrieval-augmented Generation (RAG) has changed how we build large language model (LLM) applications. Instead of relying solely on a model's internal knowledge, RAG allows you to plug in your own data source, such as knowledge bases, PDF...
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Nov 22, 2025 · 3 min read · Background LLM applications are harder to debug and optimize than traditional software. Prompts are non-deterministic, outputs vary, and performance depends on token usage, latency, and cost. Without visibility into these dimensions, it is commercial...
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Aug 29, 2025 · 4 min read · Introduction LangGraph is an open-source framework for building stateful, multi-step, agentic workflows on top of LLMs. It is part of the LangChain ecosystem and is designed to help developers orchestrate complex reasoning, tool use, and memory in LL...
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Aug 10, 2025 · 6 min read · I've recently completed a thorough testing of Langfuse (v3.95.2 OSS), and I wanted to share my observations on its capabilities and overall suitability for AI model observability. My overall impression is that Langfuse is a robust and beneficial tool...
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Jul 23, 2025 · 7 min read · Introduction LangChain is an open-source framework designed to simplify the development of applications powered by large language models (LLMs). It provides a modular, extensible toolkit for building, orchestrating, and deploying LLM-driven workflows...
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Jul 3, 2025 · 4 min read · INTRODUCTION In traditional web applications, engineers rely on tools like Loki for logging, Prometheus for monitoring server utilization, and Grafana for visualization in order to bring observability into their application to get more metrics. Howev...
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May 2, 2025 · 5 min read · LangFuse is awesome. If you're working with Large Language Models (LLMs), you probably know how useful it is for seeing what your AI is actually doing. It helps us track everything, keep an eye on costs, get feedback, and manage the prompts we feed o...
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