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🦑 Welcome to TruLens!

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, retrievers, knowledge sources and more, TruLens 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, 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 pip package from PyPI.

    pip install trulens

Quick Usage

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

Open In Colab

💡 Contributing & Community

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

The best way to support TruLens is to give us a ⭐ on GitHub and join our discourse community!

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (2.15.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for Truera from gravatar.com Truera

Credits

Author: Snowflake Inc.

License

MIT License (MIT)

Requires

Python !=2.7.*, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*, !=3.7.*, !=3.8.*, >=3.9

Classifiers

Report project as malware

Metadata

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (2.15.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for Truera from gravatar.com Truera

Credits

Author: Snowflake Inc.

License

MIT License (MIT)

Requires

Python !=2.7.*, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*, !=3.7.*, !=3.8.*, >=3.9

Classifiers

Report project as malware

Release files for trulens 1.4.9

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for trulens 1.4.9
File Size Uploaded
trulens-1.4.9.tar.gz 4.1 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for trulens 1.4.9
File Interpreter ABI Platform
trulens-1.4.9-py3-none-any.whl 3.7 kB Python 3 none any Details

Total release size: 7.8 kB

Release files / trulens-1.4.9.tar.gz

Download URL trulens-1.4.9.tar.gz
Size 4.1 kB
Tags Source
SHA-256 checksum
How to use checksums 		c17af32396c3ce83c7f489be231de9ad885298af49164b77b54c376b2e17df49
BLAKE2b-256 checksum
How to use checksums 		45e0e49b7c492c3435873ff7ed13d7fb9163516016d9113b2798d4a365943e71
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing? 		No
Uploaded via twine/5.1.1 CPython/3.11.9

Release files / trulens-1.4.9-py3-none-any.whl

Download URL trulens-1.4.9-py3-none-any.whl
Size 3.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums 		0c820738dbac19e51fcf2be1818488e979ad268458d3f9f8dc59ab17131f9470
BLAKE2b-256 checksum
How to use checksums 		7671622d84ef05936ae686c779c991d4e3b6ccdc2f7a691fcc4ee36ddd9a8f77
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing? 		No
Uploaded via twine/5.1.1 CPython/3.11.9

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2.15.0

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