Skip to main content

Library to systematically track and evaluate LLM based applications.

Project description

Welcome to TruLens-Eval!

TruLens

Don't just vibe-check your llm app! Systematically evaluate and track your LLM experiments with TruLens. As you develop your app including prompts, models, retreivers, knowledge sources and more, TruLens-Eval is the tool you need to understand its performance.

Fine-grained, stack-agnostic instrumentation and comprehensive evaluations help you to identify failure modes & systematically iterate to improve your application.

Read more about the core concepts behind TruLens including [Feedback Functions](https://www.trulens.org/trulens_eval/getting_started/core_concepts/ The RAG Triad, and Honest, Harmless and Helpful Evals.

TruLens in the development workflow

Build your first prototype then connect instrumentation and logging with TruLens. Decide what feedbacks you need, and specify them with TruLens to run alongside your app. Then iterate and compare versions of your app in an easy-to-use user interface 👇

Architecture Diagram

Installation and Setup

Install the trulens-eval pip package from PyPI.

    pip install trulens-eval

Quick Usage

Walk through how to instrument and evaluate a RAG built from scratch with TruLens.

Open In Colab

💡 Contributing

Interested in contributing? See our contributing guide for more details.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

trulens_eval-0.30.1-py3-none-any.whl (751.0 kB view details)

Uploaded Python 3

File details

Details for the file trulens_eval-0.30.1-py3-none-any.whl.

File metadata

  • Download URL: trulens_eval-0.30.1-py3-none-any.whl
  • Upload date:
  • Size: 751.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.11.9

File hashes

Hashes for trulens_eval-0.30.1-py3-none-any.whl
Algorithm Hash digest
SHA256 f3f7f2ff7928d5d19e635f7e79f865dd81797224acf945b87acb424be70b6262
MD5 c5c68288a9752bba13ca54921d70b497
BLAKE2b-256 352602b6b80b21debcf96b6c19843041976b1ae27249eadcbaac5738de5bdf26

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page