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Laminar - open-source all-in-one platform for engineering AI products. Crate data flywheel for you AI app. Traces, Evals, Datasets, Labels. YC S24.

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Overview of lmnr: The Open-Source AI Engineering Platform

lmnr, also known as Laminar, is a powerful open-source platform designed specifically for engineering Large Language Model (LLM) products. It streamlines the processes of tracing, evaluating, labeling, and analyzing LLM applications, making it an essential tool for AI developers and data scientists.

Key Features

Tracing LLM Applications

With just two lines of code, users can trace their LLM applications, gaining visibility into every execution step. This feature collects valuable data for evaluations, few-shot examples, and fine-tuning, enhancing the overall performance of LLM products.

LLM Observability

Laminar provides seamless observability by sending traces in the background via gRPC, ensuring minimal performance and latency overhead. This allows developers to focus on building without compromising efficiency.

Automated Evaluation and Labeling

Set up Python online evaluators to process received spans automatically. This scalable solution reduces the need for manual labeling, enabling users to create datasets for evaluations, fine-tuning, and prompt engineering effortlessly.

How to Use

Getting started with lmnr is straightforward. Simply execute a few commands to self-host the platform and begin integrating tracing into your LLM applications.

Benefits for Users

  • Enhanced Efficiency: Automates the evaluation process, saving time and resources.
  • Flexibility: Easily build and iterate on prompts and LLM chains using the intuitive pipeline builder.
  • Community Support: Being open-source, users can contribute and benefit from a collaborative community.

Alternatives

While lmnr stands out for its comprehensive features, alternatives like Hugging Face’s Transformers and OpenAI’s API also provide valuable functionalities for LLM development.

Conclusion

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