Laminar
Open-source all-in-one platform for engineering AI products
Listed in categories:
Developer ToolsProductivityArtificial Intelligence
Description
Laminar is an open-source all-in-one platform designed for engineering best-in-class LLM (Large Language Model) products. It helps users collect, understand, and utilize data effectively to enhance the quality of their LLM applications.
How to use Laminar?
To get started with Laminar, clone the repository from GitHub and run the provided Docker commands to set up the environment. You can then initialize your project, set up tracing, and begin building your LLM applications.
Core features of Laminar:
1️⃣
Traces: Provides a clear picture of every step of execution in LLM applications, allowing for better evaluations and fine-tuning.
2️⃣
Online Evaluations: Set up LLM-as-a-judge or Python script evaluators for scalable labeling of spans, reducing reliance on human labeling.
3️⃣
Datasets: Build datasets from traces for use in evaluations, fine-tuning, and prompt engineering.
4️⃣
Prompt Chain Management: Create and manage complex chains of prompts, including mixtures of agents or self-reflecting LLM pipelines.
5️⃣
Fully Open Source: Laminar is completely open-source and can be easily self-hosted.
Why could be used Laminar?
| # | Use case | Status | |
|---|---|---|---|
| # 1 | Developing and fine-tuning LLM applications with enhanced data insights. | ✅ | |
| # 2 | Creating scalable evaluation systems for LLM outputs. | ✅ | |
| # 3 | Building complex prompt chains for advanced LLM functionalities. | ✅ | |
Who developed Laminar?
Laminar is developed by a community of open-source contributors dedicated to providing tools for LLM engineering and enhancing the capabilities of language models.