Laminar

Laminar is an innovative, open-source platform designed to revolutionize the development of Large Language Model (LLM) products. It offers a comprehensive suite of tools for engineering best-in-class AI applications from first principles.

Key features and benefits:

1. Traces: Laminar provides powerful tracing capabilities, allowing developers to gain a clear picture of every step in their LLM application's execution. This feature simultaneously collects invaluable data that can be used for:

   • Setting up better evaluations
   • Creating dynamic few-shot examples
   • Fine-tuning models

2. Zero-overhead observability: All traces are sent in the background via gRPC, ensuring minimal impact on performance. The platform supports tracing for both text and image models, with audio model support coming soon.

3. Online evaluations: Laminar enables the setup of LLM-as-a-judge or Python script evaluators to run on each received span. This approach to evaluation is more scalable than human labeling and particularly beneficial for smaller teams.

4. Dataset creation: Users can build datasets from their traces, which can be utilized in evaluations, fine-tuning, and prompt engineering.

5. Prompt chain management: Laminar goes beyond single prompts, allowing users to build and host complex chains, including mixtures of agents or self-reflecting LLM pipelines.