Develops and operates large-language-models with tools for evaluation, observability, and metrics.
Automations like: when a new customer signs up, add them to a database and send a welcome message.
langfuse provides a platform for efficient LLM operations, streamlining tasks and saving time.
"A founder uses langfuse to monitor LLM performance and optimize it for better results. First, they install langfuse and set up OpenTelemetry for metrics and observability. Next, they create a prompt management system and configure it to integrate with the LLM. Finally, they run a series of tests to fine-tune the model's performance. With langfuse, they're able to scale their LLM operations efficiently and make data-driven decisions."
If you're new to AI engineering, start with langfuse when you need to set up and manage a simple LLM system.
Senior engineers use langfuse for custom LLM deployments and complex operations, leveraging its integration capabilities.
langfuse is not just a development tool, but also a platform for operation and optimization.
Langfuse is an open-source platform for large language model (LLM) engineering, providing observability, metrics, and management tools for LLM development and deployment.
git clone https://github.com/langfuse/langfuse.git && cd langfuse && npm installRun 'npm run eval -- --model <your-llm-model> --prompt <your-prompt-text>' to evaluate your LLM's performance on a specific prompt
Read the entire source before you build — unlike paid marketplaces that hide it behind a buy button.
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