LLM Orchestration

@empiricalrun/llm

Package to connect and trace LLM calls for development and testing.

Status
UnmaintainedNo commits in 826 days.
Last checked
Checked · Oct 8, 2026
License
Open source
Pricing
Free tier · from $0
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What it is

Empirical provides a package that enables developers to easily integrate, test, and monitor Large Language Model (LLM) interactions within their applications. It is crucial for ensuring the reliability and performance of AI-driven features in software projects.

Empirical stands out by offering a comprehensive package for connecting and tracing LLM calls, providing developers with the tools they need to ensure their applications are reliable and performant.

When it fits — and when it doesn’t

A good fit for

  • Teams developing AI-powered applications who need to test and monitor LLM interactions.

  • Projects that require detailed tracing and debugging capabilities for LLM calls.

Look elsewhere if

  • Applications requiring real-time streaming of LLM responses (batch-only architecture).

  • Scenarios where a cloud-based service is preferred over local integration.

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

  1. 01

    Steep learning curve for non-JavaScript developers

    The package is primarily designed with JavaScript patterns, which might be unfamiliar to developers from other language backgrounds.

  2. 02

    Limited documentation and examples

    The official documentation lacks comprehensive guides and practical use cases, making it difficult for new users to get started quickly.

  3. 03

    Frequent breaking changes between versions

    Users have reported significant refactoring required when upgrading from v0.1 to v0.2 due to API changes.

  4. 04

    Small and less active community

    The GitHub repository has a limited number of contributors and low activity levels, which can delay issue resolution and feature requests.

What it does well

  • Easy integration with LLMs for testing and monitoring.

  • Detailed tracing of LLM calls to aid in debugging.

  • Support for various LLM providers through a unified interface.

Pricing

Free tier
YesOpen source — free to use
Paid from
$0
Model
Flat rate
Enterprise plan
No

Pricing not independently confirmed — check the vendor’s page.

Performance benchmarks

How Fast Is It?

Set up @empiricalrun/llm

Setup steps, common gotchas and what to check after 30 days.

Open the setup guide →