Lunary
Lunary is an open‑source platform that helps developers monitor, debug, and improve large language model applications.
About this tool
Lunary delivers a suite of tools for developers building applications that rely on large language models. It records interactions, surfaces errors, and lets teams label data for fine‑tuning, making it easier to trace problems and improve model performance over time.
The platform also includes cost monitoring and benchmarking capabilities. Users can segment usage by model or user, compare prompt variations, and identify the most efficient configurations, while self‑hosted deployments keep sensitive data under full control.
What you can do
Comprehensive Logging and Debugging
Lunary captures detailed logs of LLM agent activity, enabling developers to trace errors, label problematic outputs, and refine prompts based on real conversation data.
Cost Monitoring and Segmentation
The system tracks token usage and associated expenses, allowing teams to segment costs by user or model and optimise spending across multiple deployments.
Prompt Benchmarking and Experimentation
Users can run experiments on different prompts and models, compare results, and select the highest‑performing configurations for production use.
Who is it for?
- A chatbot development team records user conversations to spot knowledge gaps and iteratively improve the assistant’s responses.
- A SaaS provider monitors token consumption across customers, using the cost segmentation view to allocate budgets and prevent overruns.
- Data scientists run prompt experiments to benchmark model variants, selecting the version that yields the best accuracy for a specific task.
Before you choose
Investigate the level of compliance documentation provided for self‑hosted deployments to ensure it meets organisational security policies.
Determine whether the live‑tail feature and search functionality scale adequately for large volumes of logged interactions.
Frequently asked questions
Can non‑technical team members contribute to prompt design in Lunary?
Yes, Lunary includes template creation tools that let non‑technical collaborators build and edit prompts, which can then be shared with developers for testing and deployment.
How does Lunary help identify outlier results or errors in model output?
The platform generates alerts when logged interactions deviate from expected patterns, highlighting outlier responses so developers can investigate and correct underlying issues.
Is it possible to host Lunary on-premises for stricter data control?
Lunary offers self‑hosted deployment options, allowing organisations to keep all logs, cost data, and model interactions within their own infrastructure for maximum security.
Check the official website for current features, pricing, and terms.
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