In simple English
When you build software that uses language models or AI agents, things often fail in strange ways. This tool records every step your AI takes and puts it into a searchable dashboard. You can watch what your code sends and receives in real time. It helps you find out why your bot got stuck or gave a wrong answer. You can run it on your own server using Docker or pay for their cloud version.
What it is
Laminar is an open-source observability platform purpose-built for tracing, evaluating, and debugging AI agents and large language model applications. It collects telemetry data from your code and provides a web interface to inspect traces, manage evaluation datasets, and query logs with SQL.
What it is good for
Solo developers building AI agents who need a clear way to see where their prompts fail, track token costs, and test changes before pushing them to users.
- Records traces automatically for major AI libraries with a single line of code.
- Includes a local evaluation tool to test prompt changes in your terminal or CI pipeline.
- Fast search and storage built with Rust and ClickHouse to handle large trace logs.
- Requires running external databases like ClickHouse and Postgres alongside the main service if you self-host.
- Needs an LLM provider key configured to power the built-in AI search and chat features.
- Self-hosted deployments collect anonymous usage telemetry by default unless you opt out.
Console.log debugging of prompt outputs and manual spreadsheet tracking of AI test cases.
Docker (a way to run a program inside its own sealed box, so it cannot break anything else on your server) and OpenAI.
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git clone https://github.com/lmnr-ai/lmnr cd lmnr docker compose up -d